WorldWideScience

Sample records for modis algorithm maiac

  1. Multiangle Implementation of Atmospheric Correction (MAIAC): 2. Aerosol Algorithm

    Science.gov (United States)

    Lyapustin, A.; Wang, Y.; Laszlo, I.; Kahn, R.; Korkin, S.; Remer, L.; Levy, R.; Reid, J. S.

    2011-01-01

    An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 micron) and shortwave infrared (2.1 micron) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.

  2. Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

    Science.gov (United States)

    Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.

    2012-01-01

    The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

  3. Analysis of MAIAC Dust Aerosol Retrievals from MODIS Over North Africa

    Science.gov (United States)

    Lyapustin, A.; Wang, Y.; Hsu, C.; Torres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.

    2011-01-01

    An initial comparison of aerosol optical thickness over North Africa for year 2007 was performed between the Deep Blue and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms complimented with MISR and OMI data. The new MAIAC algorithm has a better sensitivity to the small dust storms than the DB algorithm, but it also has biases in the brightest desert regions indicating the need for improvement. The quarterly averaged AOT values in the Bodele depression and western downwind transport region show a good agreement among MAIAC, MISR and OMI data, while the DB algorithm shows a somewhat different seasonality.

  4. Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

    Science.gov (United States)

    Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

    2017-12-01

    The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance

  5. The satellite-based remote sensing of particulate matter (PM) in support to urban air quality: PM variability and hot spots within the Cordoba city (Argentina) as revealed by the high-resolution MAIAC-algorithm retrievals applied to a ten-years dataset (2

    Science.gov (United States)

    Della Ceca, Lara Sofia; Carreras, Hebe A.; Lyapustin, Alexei I.; Barnaba, Francesca

    2016-04-01

    Particulate matter (PM) is one of the major harmful pollutants to public health and the environment [1]. In developed countries, specific air-quality legislation establishes limit values for PM metrics (e.g., PM10, PM2.5) to protect the citizens health (e.g., European Commission Directive 2008/50, US Clean Air Act). Extensive PM measuring networks therefore exist in these countries to comply with the legislation. In less developed countries air quality monitoring networks are still lacking and satellite-based datasets could represent a valid alternative to fill observational gaps. The main PM (or aerosol) parameter retrieved from satellite is the 'aerosol optical depth' (AOD), an optical parameter quantifying the aerosol load in the whole atmospheric column. Datasets from the MODIS sensors on board of the NASA spacecrafts TERRA and AQUA are among the longest records of AOD from space. However, although extremely useful in regional and global studies, the standard 10 km-resolution MODIS AOD product is not suitable to be employed at the urban scale. Recently, a new algorithm called Multi-Angle Implementation of Atmospheric Correction (MAIAC) was developed for MODIS, providing AOD at 1 km resolution [2]. In this work, the MAIAC AOD retrievals over the decade 2003-2013 were employed to investigate the spatiotemporal variation of atmospheric aerosols over the Argentinean city of Cordoba and its surroundings, an area where a very scarce dataset of in situ PM data is available. The MAIAC retrievals over the city were firstly validated using a 'ground truth' AOD dataset from the Cordoba sunphotometer operating within the global AERONET network [3]. This validation showed the good performances of the MAIAC algorithm in the area. The satellite MAIAC AOD dataset was therefore employed to investigate the 10-years trend as well as seasonal and monthly patterns of particulate matter in the Cordoba city. The first showed a marked increase of AOD over time, particularly evident in

  6. Seasonal monitoring and estimation of regional aerosol distribution over Po valley, northern Italy, using a high-resolution MAIAC product

    Science.gov (United States)

    Arvani, Barbara; Pierce, R. Bradley; Lyapustin, Alexei I.; Wang, Yujie; Ghermandi, Grazia; Teggi, Sergio

    2016-09-01

    In this work, the new 1 km-resolved Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is employed to characterize seasonal PM10 - AOD correlations over northern Italy. The accuracy of the new dataset is assessed compared to the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data, retrieved at 0.55 μm with spatial resolution of 10 km (MYD04_L2). We focused on evaluating the ability of these two products to characterize both temporal and spatial distributions of aerosols within urban and suburban areas. Ground PM10 measurements were obtained from 73 of the Italian Regional Agency for Environmental Protection (ARPA) monitoring stations, spread across northern Italy, during a three-year period from 2010 to 2012. The Po Valley area (northern Italy) was chosen as the study domain because of its severe urban air pollution, resulting from it having the highest population and industrial manufacturing density in the country, being located in a valley where two surrounding mountain chains favor the stagnation of pollutants. We found that the global correlations between the bin-averaged PM10 and AOD are R2 = 0.83 and R2 = 0.44 for MYD04_L2 and for MAIAC, respectively, suggesting a greater sensitivity of the high-resolution product to small-scale deviations. However, the introduction of Relative Humidity (RH) and Planetary Boundary Layer (PBL) depth corrections allowed for a significant improvement to the bin-averaged PM - AOD correlation, which led to a similar performance: R2 = 0.96 for MODIS and R2 = 0.95 for MAIAC. Furthermore, the introduction of the PBL information in the corrected AOD values was found to be crucial in order to capture the clear seasonal cycle shown by measured PM10 values. The study allowed us to define four seasonal linear correlations that estimate PM10 concentrations satisfactorily from the remotely sensed MAIAC AOD retrieval. Overall, the results show that the high

  7. MODIS Science Algorithms and Data Systems Lessons Learned

    Science.gov (United States)

    Wolfe, Robert E.; Ridgway, Bill L.; Patt, Fred S.; Masuoka, Edward J.

    2009-01-01

    For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.

  8. Enhancement of the Daytime MODIS Based Aircraft Icing Potential Algorithm Using Mesoscale Model Data

    National Research Council Canada - National Science Library

    Sherman, Zoe B

    2006-01-01

    .... The algorithm by Alexander (2005) was used to process MODIS imagery on four separate storms in January 2006, and his algorithm was validated using 133 positive and negative pilot reports (PIREPs...

  9. An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

    Science.gov (United States)

    Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

    2012-01-01

    An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

  10. Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

    Science.gov (United States)

    Lipponen, Antti; Mielonen, Tero; Pitkänen, Mikko R. A.; Levy, Robert C.; Sawyer, Virginia R.; Romakkaniemi, Sami; Kolehmainen, Ville; Arola, Antti

    2018-03-01

    We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15 %) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

  11. Amazon Forests Response to Droughts: A Perspective from the MAIAC Product

    Science.gov (United States)

    Bi, Jian; Myneni, Ranga; Lyapustin, Alexei; Wang, Yujie; Park, Taejin; Chi, Chen; Yan, Kai; Knyazikhin, Yuri

    2016-01-01

    Amazon forests experienced two severe droughts at the beginning of the 21st century: one in 2005 and the other in 2010. How Amazon forests responded to these droughts is critical for the future of the Earth's climate system. It is only possible to assess Amazon forests' response to the droughts in large areal extent through satellite remote sensing. Here, we used the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) data to assess Amazon forests' response to droughts, and compared the results with those from the standard (Collection 5 and Collection 6) MODIS VI data. Overall, the MAIAC data reveal more realistic Amazon forests inter-annual greenness dynamics than the standard MODIS data. Our results from the MAIAC data suggest that: (1) the droughts decreased the greenness (i.e., photosynthetic activity) of Amazon forests; (2) the Amazon wet season precipitation reduction induced by El Niño events could also lead to reduced photosynthetic activity of Amazon forests; and (3) in the subsequent year after the water stresses, the greenness of Amazon forests recovered from the preceding decreases. However, as previous research shows droughts cause Amazon forests to reduce investment in tissue maintenance and defense, it is not clear whether the photosynthesis of Amazon forests will continue to recover after future water stresses, because of the accumulated damages caused by the droughts.

  12. Amazon Forests’ Response to Droughts: A Perspective from the MAIAC Product

    Directory of Open Access Journals (Sweden)

    Jian Bi

    2016-04-01

    Full Text Available Amazon forests experienced two severe droughts at the beginning of the 21st century: one in 2005 and the other in 2010. How Amazon forests responded to these droughts is critical for the future of the Earth’s climate system. It is only possible to assess Amazon forests’ response to the droughts in large areal extent through satellite remote sensing. Here, we used the Multi-Angle Implementation of Atmospheric Correction (MAIAC Moderate Resolution Imaging Spectroradiometer (MODIS vegetation index (VI data to assess Amazon forests’ response to droughts, and compared the results with those from the standard (Collection 5 and Collection 6 MODIS VI data. Overall, the MAIAC data reveal more realistic Amazon forests inter-annual greenness dynamics than the standard MODIS data. Our results from the MAIAC data suggest that: (1 the droughts decreased the greenness (i.e., photosynthetic activity of Amazon forests; (2 the Amazon wet season precipitation reduction induced by El Niño events could also lead to reduced photosynthetic activity of Amazon forests; and (3 in the subsequent year after the water stresses, the greenness of Amazon forests recovered from the preceding decreases. However, as previous research shows droughts cause Amazon forests to reduce investment in tissue maintenance and defense, it is not clear whether the photosynthesis of Amazon forests will continue to recover after future water stresses, because of the accumulated damages caused by the droughts.

  13. MODIS 3km Aerosol Product: Algorithm and Global Perspective

    Science.gov (United States)

    Remer, L. A.; Mattoo, S.; Levy, R. C.; Munchak, L.

    2013-01-01

    After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

  14. High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

    Science.gov (United States)

    Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment

  15. Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

    Science.gov (United States)

    Wang, Jiao; Deng, Zhiqiang

    2017-06-01

    A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

  16. Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

    Science.gov (United States)

    Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; hide

    2014-01-01

    The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra- Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on

  17. Combined Dust Detection Algorithm by Using MODIS Infrared Channels over East Asia

    Science.gov (United States)

    Park, Sang Seo; Kim, Jhoon; Lee, Jaehwa; Lee, Sukjo; Kim, Jeong Soo; Chang, Lim Seok; Ou, Steve

    2014-01-01

    A new dust detection algorithm is developed by combining the results of multiple dust detectionmethods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTDmethods have limitations in identifying the offset values of the BTDto discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10 × 10 pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia.

  18. Evaluating the accuracy of a MODIS direct broadcast algorithm for mapping burned areas over Russia

    Science.gov (United States)

    Petkov, A.; Hao, W. M.; Nordgren, B.; Corley, R.; Urbanski, S. P.; Ponomarev, E. I.

    2012-12-01

    Emission inventories for open area biomass burning rely on burned area estimates as a key component. We have developed an automated algorithm based on MODerate resolution Imaging Spectroradiometer (MODIS) satellite instrument data for estimating burned area from biomass fires. The algorithm is based on active fire detections, burn scars from MODIS calibrated radiances (MOD02HKM), and MODIS land cover classification (MOD12Q1). Our burned area product combines active fires and burn scar detections using spatio-temporal criteria, and has a resolution of 500 x 500 meters. The algorithm has been used for smoke emission estimates over the western United States. We will present the assessed accuracy of our algorithm in different regions of Russia with intense wildfire activity by comparing our results with the burned area product from the Sukachev Institute of Forest (SIF) of the Russian Academy of Sciences in Krasnoyarsk, Russia, as well as burn scars extracted from Landsat imagery. Landsat burned area extraction was based on threshold classification using the Jenks Natural Breaks algorithm to the histogram for each singe scene Normalized Burn Ratio (NBR) image. The final evaluation consisted of a grid-based approach, where the burned area in each 3 km x 3 km grid cell was calculated and compared with the other two sources. A comparison between our burned area estimates and those from SIF showed strong correlation (R2=0.978), although our estimate is approximately 40% lower than the SIF burned areas. The linear fit between the burned area from Landsat scenes and our MODIS algorithm over 18,754 grid cells resulted with a slope of 0.998 and R2=0.7, indicating that our algorithm is suitable for mapping burned areas for fires in boreal forests and other ecosystems. The results of our burned area algorithm will be used for estimating emissions of trace gasses and aerosol particles (including black carbon) from biomass burning in Northern Eurasia for the period of 2002-2011.

  19. Adapting MODIS Dust Mask Algorithm to Suomi NPP VIIRS for Air Quality Applications

    Science.gov (United States)

    Ciren, P.; Liu, H.; Kondragunta, S.; Laszlo, I.

    2012-12-01

    Despite pollution reduction control strategies enforced by the Environmental Protection Agency (EPA), large regions of the United States are often under exceptional events such as biomass burning and dust outbreaks that lead to non-attainment of particulate matter standards. This has warranted the National Weather Service (NWS) to provide smoke and dust forecast guidance to the general public. The monitoring and forecasting of dust outbreaks relies on satellite data. Currently, Aqua/MODIS (MODerate resolution Imaging Spectrometer) and Terra/MODIS provide measurements needed to derive dust mask and Aerosol Optical Thickness (AOT) products. The newly launched Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer Suite) instrument has a Suspended Matter (SM) product that indicates the presence of dust, smoke, volcanic ash, sea salt, and unknown aerosol types in a given pixel. The algorithm to identify dust is different over land and ocean but for both, the information comes from AOT retrieval algorithm. Over land, the selection of dust aerosol model in the AOT retrieval algorithm indicates the presence of dust and over ocean a fine mode fraction smaller than 20% indicates dust. Preliminary comparisons of VIIRS SM to CALIPSO Vertical Feature Mask (VFM) aerosol type product indicate that the Probability of Detection (POD) is at ~10% and the product is not mature for operational use. As an alternate approach, NESDIS dust mask algorithm developed for NWS dust forecast verification that uses MODIS deep blue, visible, and mid-IR channels using spectral differencing techniques and spatial variability tests was applied to VIIRS radiances. This algorithm relies on the spectral contrast of dust absorption at 412 and 440 nm and an increase in reflectivity at 2.13 μm when dust is present in the atmosphere compared to a clear sky. To avoid detecting bright desert surface as airborne dust, the algorithm uses the reflectances at 1.24 μm and 2.25 μm to flag bright pixels. The

  20. Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

    Science.gov (United States)

    Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; hide

    2015-01-01

    Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

  1. Seasonal nitrate algorithms for nitrate retrieval using OCEANSAT-2 and MODIS-AQUA satellite data.

    Science.gov (United States)

    Durairaj, Poornima; Sarangi, Ranjit Kumar; Ramalingam, Shanthi; Thirunavukarassu, Thangaradjou; Chauhan, Prakash

    2015-04-01

    In situ datasets of nitrate, sea surface temperature (SST), and chlorophyll a (chl a) collected during the monthly coastal samplings and organized cruises along the Tamilnadu and Andhra Pradesh coast between 2009 and 2013 were used to develop seasonal nitrate algorithms. The nitrate algorithms have been built up based on the three-dimensional regressions between SST, chl a, and nitrate in situ data using linear, Gaussian, Lorentzian, and paraboloid function fittings. Among these four functions, paraboloid was found to be better with the highest co-efficient of determination (postmonsoon: R2=0.711, n=357; summer: R2=0.635, n=302; premonsoon: R2=0.829, n=249; and monsoon: R2=0.692, n=272) for all seasons. Based on these fittings, seasonal nitrate images were generated using the concurrent satellite data of SST from Moderate Resolution Imaging Spectroradiometer (MODIS) and chlorophyll (chl) from Ocean Color Monitor (OCM-2) and MODIS. The best retrieval of modeled nitrate (R2=0.527, root mean square error (RMSE)=3.72, and mean normalized bias (MNB)=0.821) was observed for the postmonsoon season due to the better retrieval of both SST MODIS (28 February 2012, R2=0.651, RMSE=2.037, and MNB=0.068) and chl OCM-2 (R2=0.534, RMSE=0.317, and MNB=0.27). Present results confirm that the chl OCM-2 and SST MODIS retrieve nitrate well than the MODIS-derived chl and SST largely due to the better retrieval of chl by OCM-2 than MODIS.

  2. Aerosol retrieval algorithm for the characterization of local aerosol using MODIS L1B data

    International Nuclear Information System (INIS)

    Wahab, A M; Sarker, M L R

    2014-01-01

    Atmospheric aerosol plays an important role in radiation budget, climate change, hydrology and visibility. However, it has immense effect on the air quality, especially in densely populated areas where high concentration of aerosol is associated with premature death and the decrease of life expectancy. Therefore, an accurate estimation of aerosol with spatial distribution is essential, and satellite data has increasingly been used to estimate aerosol optical depth (AOD). Aerosol product (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) data is available at global scale but problems arise due to low spatial resolution, time-lag availability of AOD product as well as the use of generalized aerosol models in retrieval algorithm instead of local aerosol models. This study focuses on the aerosol retrieval algorithm for the characterization of local aerosol in Hong Kong for a long period of time (2006-2011) using high spatial resolution MODIS level 1B data (500 m resolution) and taking into account the local aerosol models. Two methods (dark dense vegetation and MODIS land surface reflectance product) were used for the estimation of the surface reflectance over land and Santa Barbara DISORT Radiative Transfer (SBDART) code was used to construct LUTs for calculating the aerosol reflectance as a function of AOD. Results indicate that AOD can be estimated at the local scale from high resolution MODIS data, and the obtained accuracy (ca. 87%) is very much comparable with the accuracy obtained from other studies (80%-95%) for AOD estimation

  3. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  4. An improved MODIS standard chlorophyll-a algorithm for Malacca Straits Water

    International Nuclear Information System (INIS)

    Lah, N Z Ab; Reba, M N M; Siswanto, Eko

    2014-01-01

    The Malacca Straits has high productivity of nutrients as a result to potential primary production. Yet, the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua has shown an overestimation of Chl-a retrieval in the case-2 water of Malacca Straits. In an update to the previous study, this paper presents the second validation exercise of MODIS OC3M algorithm using the reprocessed MODIS data (R2013) and locally tuned the algorithm with respect to two in-sit stations located at northern and southern part of Malacca Straits. The result shows the OC3M retrieved in the case-2 (south station) water remarkably overestimated in-situ Chl-a, but it is underestimated in the case-1 (north station). Local tuning was employed by iterative regression at the fourth-order polynomial to improve the accuracy of Chl-a retrieval. As a result, locally tuned OC3M algorithm give robust statistical performance and can be applied best for both case-1 and case-2 water in Malacca Straits

  5. Evaluation of Operational Albedo Algorithms For AVHRR, MODIS and VIIRS: Case Studies in Southern Africa

    Science.gov (United States)

    Privette, J. L.; Schaaf, C. B.; Saleous, N.; Liang, S.

    2004-12-01

    Shortwave broadband albedo is the fundamental surface variable that partitions solar irradiance into energy available to the land biophysical system and energy reflected back into the atmosphere. Albedo varies with land cover, vegetation phenological stage, surface wetness, solar angle, and atmospheric condition, among other variables. For these reasons, a consistent and normalized albedo time series is needed to accurately model weather, climate and ecological trends. Although an empirically-derived coarse-scale albedo from the 20-year NOAA AVHRR record (Sellers et al., 1996) is available, an operational moderate resolution global product first became available from NASA's MODIS sensor. The validated MODIS product now provides the benchmark upon which to compare albedo generated through 1) reprocessing of the historic AVHRR record and 2) operational processing of data from the future National Polar-Orbiting Environmental Satellite System's (NPOESS) Visible/Infrared Imager Radiometer Suite (VIIRS). Unfortunately, different instrument characteristics (e.g., spectral bands, spatial resolution), processing approaches (e.g., latency requirements, ancillary data availability) and even product definitions (black sky albedo, white sky albedo, actual or blue sky albedo) complicate the development of the desired multi-mission (AVHRR to MODIS to VIIRS) albedo time series -- a so-called Climate Data Record. This presentation will describe the different albedo algorithms used with AVHRR, MODIS and VIIRS, and compare their results against field measurements collected over two semi-arid sites in southern Africa. We also describe the MODIS-derived VIIRS proxy data we developed to predict NPOESS albedo characteristics. We conclude with a strategy to develop a seamless Climate Data Record from 1982- to 2020.

  6. Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

    Directory of Open Access Journals (Sweden)

    Patrick H. Freeborn

    2014-02-01

    Full Text Available Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI Fire Thermal Anomaly (FTA detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS across the Central African Republic (CAR. Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI’s omission rate can be attributed to a coupling between SEVIRI’s low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI’s commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i future improvements to the SEVIRI FTA detection algorithm; (ii the assimilation of the SEVIRI and MODIS active fire products; and (iii the potential inclusion of SEVIRI into a network of geostationary

  7. Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

    Science.gov (United States)

    Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent

    2012-01-01

    The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

  8. Assessment of two aerosol optical thickness retrieval algorithms applied to MODIS Aqua and Terra measurements in Europe

    Directory of Open Access Journals (Sweden)

    P. Glantz

    2012-07-01

    Full Text Available The aim of the present study is to validate AOT (aerosol optical thickness and Ångström exponent (α, obtained from MODIS (MODerate resolution Imaging Spectroradiometer Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground with the SAER (Satellite AErosol Retrieval algorithm and with MODIS Collection 5 (c005 standard product retrievals (10 km horizontal resolution, against AERONET (AErosol RObotic NETwork sun photometer observations over land surfaces in Europe. An inter-comparison of AOT at 0.469 nm obtained with the two algorithms has also been performed. The time periods investigated were chosen to enable a validation of the findings of the two algorithms for a maximal possible variation in sun elevation. The satellite retrievals were also performed with a significant variation in the satellite-viewing geometry, since Aqua and Terra passed the investigation area twice a day for several of the cases analyzed. The validation with AERONET shows that the AOT at 0.469 and 0.555 nm obtained with MODIS c005 is within the expected uncertainty of one standard deviation of the MODIS c005 retrievals (ΔAOT = ± 0.05 ± 0.15 · AOT. The AOT at 0.443 nm retrieved with SAER, but with a much finer spatial resolution, also agreed reasonably well with AERONET measurements. The majority of the SAER AOT values are within the MODIS c005 expected uncertainty range, although somewhat larger average absolute deviation occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between AOT from SAER and AERONET is, however, substantially larger for the wavelength 488 nm. This means that the values are, to a larger extent, outside of the expected MODIS uncertainty range. In addition, both satellite retrieval algorithms are unable to estimate α accurately, although the MODIS c005 algorithm performs better. Based on the inter-comparison of the SAER and MODIS c005 algorithms, it was found that SAER on the whole is

  9. An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States

    Science.gov (United States)

    Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu; William T. Sommers

    2006-01-01

    Traditional fire detection algorithms mainly rely on hot spot detection using thermal infrared (TIR) channels with fixed or contextual thresholds. Three solar reflectance channels (0.65 μm, 0.86 μm, and 2.1 μm) were recently adopted into the MODIS version 4 contextual algorithm to improve the active fire detection. In the southeastern United...

  10. Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

    Science.gov (United States)

    Oreopoulos, Lazaros; Wilson, Michael J.; Varnai, Tamas

    2010-01-01

    This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

  11. Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

    Science.gov (United States)

    Wilson, Michael J.; Oreopoulos, Lazarous

    2011-01-01

    The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

  12. Developing a Random Forest Algorithm for MODIS Global Burned Area Classification

    Directory of Open Access Journals (Sweden)

    Rubén Ramo

    2017-11-01

    Full Text Available This paper aims to develop a global burned area (BA algorithm for MODIS BRDF-corrected images based on the Random Forest (RF classifier. Two RF models were generated, including: (1 all MODIS reflective bands; and (2 only the red (R and near infrared (NIR bands. Active fire information, vegetation indices and auxiliary variables were taken into account as well. Both RF models were trained using a statistically designed sample of 130 reference sites, which took into account the global diversity of fire conditions. For each site, fire perimeters were obtained from multitemporal pairs of Landsat TM/ETM+ images acquired in 2008. Those fire perimeters were used to extract burned and unburned areas to train the RF models. Using the standard MD43A4 resolution (500 × 500 m, the training dataset included 48,365 burned pixels and 6,293,205 unburned pixels. Different combinations of number of trees and number of parameters were tested. The final RF models included 600 trees and 5 attributes. The RF full model (considering all bands provided a balanced accuracy of 0.94, while the RF RNIR model had 0.93. As a first assessment of these RF models, they were used to classify daily MCD43A4 images in three test sites for three consecutive years (2006–2008. The selected sites included different ecosystems: Australia (Tropical, Boreal (Canada and Temperate (California, and extended coverage (totaling more than 2,500,000 km2. Results from both RF models for those sites were compared with national fire perimeters, as well as with two existing BA MODIS products; the MCD45 and MCD64. Considering all three years and three sites, commission error for the RF Full model was 0.16, with an omission error of 0.23. For the RF RNIR model, these errors were 0.19 and 0.21, respectively. The existing MODIS BA products had lower commission errors, but higher omission errors (0.09 and 0.33 for the MCD45 and 0.10 and 0.29 for the MCD64 than those obtained with the RF models, and

  13. Assessment of MODIS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea

    Digital Repository Service at National Institute of Oceanography (India)

    Tilstone, G.H.; Lotliker, A.A; Miller, P.I.; Ashraf, P.M.; SrinivasaKumar, T.; Suresh, T.; Ragavan, B.R.; Menon, H.B.

    applied to Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-Aqua) data against in situ measurements. Ocean Colour 3 band ratio (OC3M), Garver-Siegel-Maritorena Model (GSM) and Generalized Inherent Optical Property (GIOP) Chl-a algorithms were...

  14. Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

    Science.gov (United States)

    Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip T.; Cronk, Heather Q.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert Y.; Fisher, Brenden; Osterman, Gregory B.; Pollock, Randy H.; Crisp, David; Eldering, Annmarie; Gunson, Michael R.

    2016-03-01

    The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20-25 % of all OCO-2 soundings

  15. Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated MODIS and CALIOP data

    Science.gov (United States)

    Taylor, T. E.; O'Dell, C. W.; Frankenberg, C.; Partain, P.; Cronk, H. Q.; Savtchenko, A.; Nelson, R. R.; Rosenthal, E. J.; Chang, A. Y.; Fisher, B.; Osterman, G.; Pollock, R. H.; Crisp, D.; Eldering, A.; Gunson, M. R.

    2015-12-01

    The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of ≃ 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be

  16. The Operational MODIS Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results

    Science.gov (United States)

    Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas

    2012-01-01

    Operational Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for MODIS Terra and Aqua, respectively) are currently being reprocessed along with other MODIS Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar reflectance techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud reflectance and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from MODIS Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the MODIS L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.

  17. A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data

    International Nuclear Information System (INIS)

    Wan, Z.; Li, Z.L.

    1997-01-01

    The authors have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NEΔT) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4--0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10--12.5 microm IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2--3 K

  18. MODIS-Based Estimation of Terrestrial Latent Heat Flux over North America Using Three Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Xuanyu Wang

    2017-12-01

    Full Text Available Terrestrial latent heat flux (LE is a key component of the global terrestrial water, energy, and carbon exchanges. Accurate estimation of LE from moderate resolution imaging spectroradiometer (MODIS data remains a major challenge. In this study, we estimated the daily LE for different plant functional types (PFTs across North America using three machine learning algorithms: artificial neural network (ANN; support vector machines (SVM; and, multivariate adaptive regression spline (MARS driven by MODIS and Modern Era Retrospective Analysis for Research and Applications (MERRA meteorology data. These three predictive algorithms, which were trained and validated using observed LE over the period 2000–2007, all proved to be accurate. However, ANN outperformed the other two algorithms for the majority of the tested configurations for most PFTs and was the only method that arrived at 80% precision for LE estimation. We also applied three machine learning algorithms for MODIS data and MERRA meteorology to map the average annual terrestrial LE of North America during 2002–2004 using a spatial resolution of 0.05°, which proved to be useful for estimating the long-term LE over North America.

  19. Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

    Science.gov (United States)

    Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

    2017-12-01

    Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

  20. MODIS 250m burned area mapping based on an algorithm using change point detection and Markov random fields.

    Science.gov (United States)

    Mota, Bernardo; Pereira, Jose; Campagnolo, Manuel; Killick, Rebeca

    2013-04-01

    Area burned in tropical savannas of Brazil was mapped using MODIS-AQUA daily 250m resolution imagery by adapting one of the European Space Agency fire_CCI project burned area algorithms, based on change point detection and Markov random fields. The study area covers 1,44 Mkm2 and was performed with data from 2005. The daily 1000 m image quality layer was used for cloud and cloud shadow screening. The algorithm addresses each pixel as a time series and detects changes in the statistical properties of NIR reflectance values, to identify potential burning dates. The first step of the algorithm is robust filtering, to exclude outlier observations, followed by application of the Pruned Exact Linear Time (PELT) change point detection technique. Near-infrared (NIR) spectral reflectance changes between time segments, and post change NIR reflectance values are combined into a fire likelihood score. Change points corresponding to an increase in reflectance are dismissed as potential burn events, as are those occurring outside of a pre-defined fire season. In the last step of the algorithm, monthly burned area probability maps and detection date maps are converted to dichotomous (burned-unburned maps) using Markov random fields, which take into account both spatial and temporal relations in the potential burned area maps. A preliminary assessment of our results is performed by comparison with data from the MODIS 1km active fires and the 500m burned area products, taking into account differences in spatial resolution between the two sensors.

  1. An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by combining Landsat, MODIS, and secondary data

    Science.gov (United States)

    Thenkabail, Prasad S.; Wu, Zhuoting

    2012-01-01

    The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated vs. rainfed) over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan using mega file data cubes (MFDCs) involving data from Landsat Global Land Survey (GLS), Landsat Enhanced Thematic Mapper Plus (ETM+) 30 m, Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series, a suite of secondary data (e.g., elevation, slope, precipitation, temperature), and in situ data. First, the process involved producing an accurate reference (or truth) cropland layer (TCL), consisting of cropland extent, areas, and irrigated vs. rainfed cropland areas, for the entire country of Tajikistan based on MFDC of year 2005 (MFDC2005). The methods involved in producing TCL included using ISOCLASS clustering, Tasseled Cap bi-spectral plots, spectro-temporal characteristics from MODIS 250 m monthly normalized difference vegetation index (NDVI) maximum value composites (MVC) time-series, and textural characteristics of higher resolution imagery. The TCL statistics accurately matched with the national statistics of Tajikistan for irrigated and rainfed croplands, where about 70% of croplands were irrigated and the rest rainfed. Second, a rule-based ACCA was developed to replicate the TCL accurately (~80% producer’s and user’s accuracies or within 20% quantity disagreement involving about 10 million Landsat 30 m sized cropland pixels of Tajikistan). Development of ACCA was an iterative process involving series of rules that are coded, refined, tweaked, and re-coded till ACCA derived croplands (ACLs) match accurately with TCLs. Third, the ACCA derived cropland

  2. An Automated Cropland Classification Algorithm (ACCA for Tajikistan by Combining Landsat, MODIS, and Secondary Data

    Directory of Open Access Journals (Sweden)

    Prasad S. Thenkabail

    2012-09-01

    Full Text Available The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated vs. rainfed over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan using mega file data cubes (MFDCs involving data from Landsat Global Land Survey (GLS, Landsat Enhanced Thematic Mapper Plus (ETM+ 30 m, Moderate Resolution Imaging Spectroradiometer (MODIS 250 m time-series, a suite of secondary data (e.g., elevation, slope, precipitation, temperature, and in situ data. First, the process involved producing an accurate reference (or truth cropland layer (TCL, consisting of cropland extent, areas, and irrigated vs. rainfed cropland areas, for the entire country of Tajikistan based on MFDC of year 2005 (MFDC2005. The methods involved in producing TCL included using ISOCLASS clustering, Tasseled Cap bi-spectral plots, spectro-temporal characteristics from MODIS 250 m monthly normalized difference vegetation index (NDVI maximum value composites (MVC time-series, and textural characteristics of higher resolution imagery. The TCL statistics accurately matched with the national statistics of Tajikistan for irrigated and rainfed croplands, where about 70% of croplands were irrigated and the rest rainfed. Second, a rule-based ACCA was developed to replicate the TCL accurately (~80% producer’s and user’s accuracies or within 20% quantity disagreement involving about 10 million Landsat 30 m sized cropland pixels of Tajikistan. Development of ACCA was an iterative process involving series of rules that are coded, refined, tweaked, and re-coded till ACCA derived croplands (ACLs match accurately with TCLs. Third, the ACCA derived

  3. Terrestrial remote sensing science and algorithms planned for EOS/MODIS

    Science.gov (United States)

    Running, S. W.; Justice, C.O.; Salomonson, V.V.; Hall, D.; Barker, J.; Kaufmann, Y. J.; Strahler, Alan H.; Huete, A.R.; Muller, Jan-Peter; Vanderbilt, V.; Wan, Z.; Teillet, P.; Carneggie, David M. Geological Survey (U.S.) Ohlen

    1994-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) will be the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch on the EOS-AM platform in June 1998 and the EOS-PM platform in December 2000. MODIS is a 36 channel radiometer covering 0·415-14·235 μm wavelengths, with spatial resolution from 250 m to 1 km at nadir. MODIS will be the primary EOS sensor for providing data on terrestrial biospheric dynamics and process activity. This paper presents the suite of global land products currently planned for EOSDIS implementation, to be developed by the authors of this paper, the MODIS land team (MODLAND). These include spectral albedo, land cover, spectral vegetation indices, snow and ice cover, surface temperature and fire, and a number of biophysical variables that will allow computation of global carbon cycles, hydrologic balances and biogeochemistry of critical greenhouse gases. Additionally, the regular global coverage of these variables will allow accurate surface change detection, a fundamental determinant of global change.

  4. Incremental cost-effectiveness of algorithm-driven genetic testing versus no testing for Maturity Onset Diabetes of the Young (MODY) in Singapore.

    Science.gov (United States)

    Nguyen, Hai Van; Finkelstein, Eric Andrew; Mital, Shweta; Gardner, Daphne Su-Lyn

    2017-11-01

    Offering genetic testing for Maturity Onset Diabetes of the Young (MODY) to all young patients with type 2 diabetes has been shown to be not cost-effective. This study tests whether a novel algorithm-driven genetic testing strategy for MODY is incrementally cost-effective relative to the setting of no testing. A decision tree was constructed to estimate the costs and effectiveness of the algorithm-driven MODY testing strategy and a strategy of no genetic testing over a 30-year time horizon from a payer's perspective. The algorithm uses glutamic acid decarboxylase (GAD) antibody testing (negative antibodies), age of onset of diabetes (30 years) to stratify the population of patients with diabetes into three subgroups, and testing for MODY only among the subgroup most likely to have the mutation. Singapore-specific costs and prevalence of MODY obtained from local studies and utility values sourced from the literature are used to populate the model. The algorithm-driven MODY testing strategy has an incremental cost-effectiveness ratio of US$93 663 per quality-adjusted life year relative to the no testing strategy. If the price of genetic testing falls from US$1050 to US$530 (a 50% decrease), it will become cost-effective. Our proposed algorithm-driven testing strategy for MODY is not yet cost-effective based on established benchmarks. However, as genetic testing prices continue to fall, this strategy is likely to become cost-effective in the near future. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  5. Updates on the development of Deep Blue aerosol algorithm for constructing consistent long-term data records from MODIS to VIIRS

    Science.gov (United States)

    Hsu, N. Y. C.; Sayer, A. M.; Lee, J.; Kim, W. V.

    2017-12-01

    The impacts of natural and anthropogenic sources of air pollution on climate and human health have continued to gain attention from the scientific community. In order to facilitate these effects, high quality consistent long-term global aerosol data records from satellites are essential. Several EOS-era instruments (e.g., SeaWiFS, MODIS, and MISR) are able to provide such information with a high degree of fidelity. However, with the aging MODIS sensors and the launch of the VIIRS instrument on Suomi NPP in late 2011, the continuation of long-term aerosol data records suitable for climate studies from MODIS to VIIRS is needed urgently. Recently, we have successfully modified our MODIS Deep Blue algorithm to process the VIIRS data. Extensive works were performed in refining the surface reflectance determination scheme to account for the wavelength differences between MODIS and VIIRS. Better aerosol models (including non-spherical dust) are also now implemented in our VIIRS algorithm compared to the MODIS C6 algorithm. We will show the global (land and ocean) distributions of various aerosol products from Version 1 of the VIIRS Deep Blue data set. The preliminary validation results of these new VIIRS Deep Blue aerosol products using data from AERONET sunphotometers over land and ocean will be discussed. We will also compare the monthly averaged Deep Blue aerosol optical depth (AOD) from VIIRS with the MODIS C6 products to investigate if any systematic biases may exist between MODIS C6 and VIIRS AOD. The Version 1 VIIRS Deep Blue aerosol products are currently scheduled to be released to the public in 2018.

  6. Land Surface Temperature Retrieval from MODIS Data by Integrating Regression Models and the Genetic Algorithm in an Arid Region

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2014-06-01

    Full Text Available The land surface temperature (LST is one of the most important parameters of surface-atmosphere interactions. Methods for retrieving LSTs from satellite remote sensing data are beneficial for modeling hydrological, ecological, agricultural and meteorological processes on Earth’s surface. Many split-window (SW algorithms, which can be applied to satellite sensors with two adjacent thermal channels located in the atmospheric window between 10 μm and 12 μm, require auxiliary atmospheric parameters (e.g., water vapor content. In this research, the Heihe River basin, which is one of the most arid regions in China, is selected as the study area. The Moderate-resolution Imaging Spectroradiometer (MODIS is selected as a test case. The Global Data Assimilation System (GDAS atmospheric profiles of the study area are used to generate the training dataset through radiative transfer simulation. Significant correlations between the atmospheric upwelling radiance in MODIS channel 31 and the other three atmospheric parameters, including the transmittance in channel 31 and the transmittance and upwelling radiance in channel 32, are trained based on the simulation dataset and formulated with three regression models. Next, the genetic algorithm is used to estimate the LST. Validations of the RM-GA method are based on the simulation dataset generated from in situ measured radiosonde profiles and GDAS atmospheric profiles, the in situ measured LSTs, and a pair of daytime and nighttime MOD11A1 products in the study area. The results demonstrate that RM-GA has a good ability to estimate the LSTs directly from the MODIS data without any auxiliary atmospheric parameters. Although this research is for local application in the Heihe River basin, the findings and proposed method can easily be extended to other satellite sensors and regions with arid climates and high elevations.

  7. Assessing the MODIS crop detection algorithm for soybean crop area mapping and expansion in the Mato Grosso state, Brazil.

    Science.gov (United States)

    Gusso, Anibal; Arvor, Damien; Ducati, Jorge Ricardo; Veronez, Mauricio Roberto; da Silveira, Luiz Gonzaga

    2014-01-01

    Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, with R (2) = 0.97 and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.

  8. Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

    Science.gov (United States)

    Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

    2018-01-01

    An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

  9. Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

    Science.gov (United States)

    Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

    2016-01-01

    An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

  10. Assessment of MODIS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea

    Science.gov (United States)

    Tilstone, Gavin H.; Lotliker, Aneesh A.; Miller, Peter I.; Ashraf, P. Muhamed; Kumar, T. Srinivasa; Suresh, T.; Ragavan, B. R.; Menon, Harilal B.

    2013-08-01

    The use of ocean colour remote sensing to facilitate the monitoring of phytoplankton biomass in coastal waters is hampered by the high variability in absorption and scattering from substances other than phytoplankton. The eastern Arabian Sea coastal shelf is influenced by river run-off, winter convection and monsoon upwelling. Bio-optical parameters were measured along this coast from March 2009 to June 2011, to characterise the optical water type and validate three Chlorophyll-a (Chla) algorithms applied to Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-Aqua) data against in situ measurements. Ocean Colour 3 band ratio (OC3M), Garver-Siegel-Maritorena Model (GSM) and Generalized Inherent Optical Property (GIOP) Chla algorithms were evaluated. OC3M performed better than GSM and GIOP in all regions and overall, was within 11% of in situ Chla. GSM was within 24% of in situ Chla and GIOP on average was 55% lower. OC3M was less affected by errors in remote sensing reflectance Rrs(λ) and by spectral variations in absorption coefficient (aCDOM(λ)) of coloured dissolved organic material (CDOM) and total suspended matter (TSM) compared to the other algorithms. A nine year Chla time series from 2002 to 2011 was generated to assess regional differences between OC3M and GSM. This showed that in the north eastern shelf, maximum Chla occurred during the winter monsoon from December to February, where GSM consistently gave higher Chla compared to OC3M. In the south eastern shelf, maximum Chla occurred in June to July during the summer monsoon upwelling, and OC3M yielded higher Chla compared to GSM. OC3M currently provides the most accurate Chla estimates for the eastern Arabian Sea coastal waters.

  11. An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by Combining Landsat, MODIS, and Secondary Data

    OpenAIRE

    Thenkabail, Prasad S.; Wu, Zhuoting

    2012-01-01

    The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated vs. rainfed) over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan u...

  12. Improvement of Alternative Crop Phenology Detection Algorithms using MODIS NDVI Time Series Data in US Corn Belt Region

    Science.gov (United States)

    Lee, J.; Kang, S.; Seo, B.; Lee, K.

    2017-12-01

    Predicting crop phenology is important for understanding of crop development and growth processes and improving the accuracy of crop model. Remote sensing offers a feasible tool for monitoring spatio-temporal patterns of crop phenology in region and continental scales. Various methods have been developed to determine the timing of crop phenological stages using spectral vegetation indices (i.e. NDVI and EVI) derived from satellite data. In our study, it was compared four alternative detection methods to identify crop phenological stages (i.e. the emergence and harvesting date) using high quality NDVI time series data derived from MODIS. Also we investigated factors associated with crop development rate. Temperature and photoperiod are the two main factors which would influence the crop's growth pattern expressed in the VI data. Only the effect of temperature on crop development rate was considered. The temperature response function in the Wang-Engel (WE) model was used, which simulates crop development using nonlinear models with response functions that range from zero to one. It has attempted at the state level over 14 years (2003-2016) in Iowa and Illinois state of USA, where the estimated phenology date by using four methods for both corn and soybean. Weekly crop progress reports produced by the USDA NASS were used to validate phenology detection algorithms effected by temperature. All methods showed substantial uncertainty but the threshold method showed relatively better agreement with the State-level data for soybean phenology.

  13. Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm

    Science.gov (United States)

    Wu, Zhuoting; Thenkabail, Prasad S.; Mueller, Rick; Zakzeski, Audra; Melton, Forrest; Johnson, Lee; Rosevelt, Carolyn; Dwyer, John; Jones, Jeanine; Verdin, James P.

    2014-01-01

    Increasing drought occurrences and growing populations demand accurate, routine, and consistent cultivated and fallow cropland products to enable water and food security analysis. The overarching goal of this research was to develop and test automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow cropland extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Seasonal ACCA development process involves writing series of iterative decision tree codes to separate cultivated and fallow croplands from noncroplands, aiming to accurately mirror reliable reference data sources. A pixel-by-pixel accuracy assessment when compared with the U.S. Department of Agriculture (USDA) cropland data showed, on average, a producer’s accuracy of 93% and a user’s accuracy of 85% across all months. Further, ACCA-derived cropland maps agreed well with the USDA Farm Service Agency crop acreage-reported data for both cultivated and fallow croplands with R-square values over 0.7 and field surveys with an accuracy of ≥95% for cultivated croplands and ≥76% for fallow croplands. Our results demonstrated the ability of ACCA to generate cropland products, such as cultivated and fallow cropland extents and areas, accurately, automatically, and repeatedly throughout the growing season.

  14. Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm

    Science.gov (United States)

    Wu, Zhuoting; Thenkabail, Prasad S.; Mueller, Rick; Zakzeski, Audra; Melton, Forrest; Johnson, Lee; Rosevelt, Carolyn; Dwyer, John; Jones, Jeanine; Verdin, James P.

    2014-01-01

    Increasing drought occurrences and growing populations demand accurate, routine, and consistent cultivated and fallow cropland products to enable water and food security analysis. The overarching goal of this research was to develop and test automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow cropland extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Seasonal ACCA development process involves writing series of iterative decision tree codes to separate cultivated and fallow croplands from noncroplands, aiming to accurately mirror reliable reference data sources. A pixel-by-pixel accuracy assessment when compared with the U.S. Department of Agriculture (USDA) cropland data showed, on average, a producer's accuracy of 93% and a user's accuracy of 85% across all months. Further, ACCA-derived cropland maps agreed well with the USDA Farm Service Agency crop acreage-reported data for both cultivated and fallow croplands with R-square values over 0.7 and field surveys with an accuracy of ≥95% for cultivated croplands and ≥76% for fallow croplands. Our results demonstrated the ability of ACCA to generate cropland products, such as cultivated and fallow cropland extents and areas, accurately, automatically, and repeatedly throughout the growing season.

  15. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; hide

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  16. Aerosol Retrievals Over Land and Water using Deep Blue Algorithm from SeaWiFS and MODIS during UAE2 Field Campaign

    Science.gov (United States)

    Hsu, N.

    2005-12-01

    The environment in Southwest Asia exhibits one of the most complex situations for aerosol remote sensing from space. Several air masses with different aerosol characteristics commonly converge in this region. In particular, there are often fine mode pollution particles generated from oil industry activities in the Persian Gulf colliding with coarse mode dust particles lifted from desert sources in the surrounding areas. During the course of the UAE field campaign (August-October, 2004), we provided near-real time information, calculated using the Deep Blue algorithm, of satellite aerosol optical thickness and Angstrom exponent over the Southwest Asia region, including the Arabian Peninsula, Iran, Afghanistan, Pakistan, and part of north Africa. In this paper, we will present results of aerosol characteristics retrieved from SeaWiFS and MODIS over the Arabian Peninsula, Persian Gulf, and the Arabian Sea during the UAE experiment. The spectral surface reflectance data base constructed using satellite reflectance from MODIS and SeaWiFS employed in our algorithm will be discussed. We will also compare the resulting satellite retrieved aerosol optical thickness and Angstrom exponent with those obtained from the ground based sun photometers from AERONET in the region. Finally, we will discuss the changes in shortwave and longwave fluxes at the top of atmosphere in response to changes in aerosol optical thickness (i.e. aerosol forcing).

  17. An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface Reflectance and MODIS BRDF

    Science.gov (United States)

    Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.

    2011-01-01

    We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.

  18. A data fusion Kalman filter algorithm to estimate leaf area index evolution by using Modis LAI and PROBA-V top of canopy synthesis data

    Science.gov (United States)

    Novelli, Antonio

    2016-08-01

    Leaf Area Index (LAI) is essential in ecosystem and agronomic studies, since it measures energy and gas exchanges between vegetation and atmosphere. In the last decades, LAI values have widely been estimated from passive remotely sensed data. Common approaches are based on semi-empirical/statistic techniques or on radiative transfer model inversion. Although the scientific community has been providing several LAI retrieval methods, the estimated results are often affected by noise and measurement uncertainties. The sequential data assimilation theory provides a theoretical framework to combine an imperfect model with incomplete observation data. In this document a data fusion Kalman filter algorithm is proposed in order to estimate the time evolution of LAI by combining MODIS LAI data and PROBA-V surface reflectance data. The reflectance data were linked to LAI by using the Reduced Simple Ratio index. The main working hypotheses were lacking input data necessary for climatic models and canopy reflectance models.

  19. Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

    Science.gov (United States)

    Teluguntla, Pardhasaradhi G.; Thenkabail, Prasad S.; Xiong, Jun N.; Gumma, Murali Krishna; Congalton, Russell G.; Oliphant, Adam; Poehnelt, Justin; Yadav, Kamini; Rao, Mahesh N.; Massey, Richard

    2017-01-01

    Mapping croplands, including fallow areas, are an important measure to determine the quantity of food that is produced, where they are produced, and when they are produced (e.g. seasonality). Furthermore, croplands are known as water guzzlers by consuming anywhere between 70% and 90% of all human water use globally. Given these facts and the increase in global population to nearly 10 billion by the year 2050, the need for routine, rapid, and automated cropland mapping year-after-year and/or season-after-season is of great importance. The overarching goal of this study was to generate standard and routine cropland products, year-after-year, over very large areas through the use of two novel methods: (a) quantitative spectral matching techniques (QSMTs) applied at continental level and (b) rule-based Automated Cropland Classification Algorithm (ACCA) with the ability to hind-cast, now-cast, and future-cast. Australia was chosen for the study given its extensive croplands, rich history of agriculture, and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing. This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m normalized difference vegetation index 16-day composite time-series data for 16 years: 2000 through 2015. The products consisted of: (1) cropland extent/areas versus cropland fallow areas, (2) irrigated versus rainfed croplands, and (3) cropping intensities: single, double, and continuous cropping. An accurate reference cropland product (RCP) for the year 2014 (RCP2014) produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015. A comparison between the ACCA-derived cropland products (ACPs) for the year 2014 (ACP2014) versus RCP2014 provided an overall agreement of 89.4% (kappa = 0.814) with six classes: (a) producer’s accuracies varying

  20. Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

    Directory of Open Access Journals (Sweden)

    Laura Ulsig

    2017-01-01

    Full Text Available Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI. This study investigates the potential of a Photochemical Reflectance Index (PRI, which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R2 = 0.36–0.8, which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R2 > 0.6 in all cases. The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

  1. An EOF-Based Algorithm to Estimate Chlorophyll a Concentrations in Taihu Lake from MODIS Land-Band Measurements: Implications for Near Real-Time Applications and Forecasting Models

    Directory of Open Access Journals (Sweden)

    Lin Qi

    2014-11-01

    Full Text Available For near real-time water applications, the Moderate Resolution Imaging Spectroradiometers (MODIS on Terra and Aqua are currently the only satellite instruments that can provide well-calibrated top-of-atmosphere (TOA radiance data over the global aquatic environments. However, TOA radiance data in the MODIS ocean bands over turbid atmosphere in east China often saturate, leaving only four land bands to use. In this study, an approach based on Empirical Orthogonal Function (EOF analysis has been developed and validated to estimate chlorophyll a concentrations (Chla, μg/L in surface waters of Taihu Lake, the third largest freshwater lake in China. The EOF approach analyzed the spectral variance of normalized Rayleigh-corrected reflectance (Rrc data at 469, 555, 645, and 859 nm, and subsequently related that variance to Chla using 28 concurrent MODIS and field measurements. This empirical algorithm was then validated using another 30 independent concurrent MODIS and field measurements. Image analysis and radiative transfer simulations indicated that the algorithm appeared to be tolerant to aerosol perturbations, with unbiased RMS uncertainties of <80% for Chla ranging between 3 and 100 μg/L. Application of the algorithm to a total of 853 MODIS images between 2000 and 2013 under cloud-free conditions revealed spatial distribution patterns and seasonal changes that are consistent to previous findings based on floating algae mats. The current study can provide additional quantitative estimates of Chla that can be assimilated in an existing forecast model, which showed improved performance over the use of a previous Chla algorithm. However, the empirical nature, relatively large uncertainties, and limited number of spectral bands all point to the need of further improvement in data availability and accuracy with future satellite sensors.

  2. Remote Sensing of Fires and Smoke from the Earth Observing System MODIS Instrument

    Science.gov (United States)

    Kaufman, Y. J.; Hao, W. M.; Justice, C.; Giglio, L.; Herring, D.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The talk will include review of the MODIS (Moderate Resolution Imaging Spectrometer) algorithms and performance e.g. the MODIS algorithm and the changes in the algorithm since launch. Comparison of MODIS and ASTER fire observations. Summary of the fall activity with the Forest Service in use of MODIS data for the fires in the North-West. Validation on the ground of the MODIS fire product.

  3. Mossin, Mody

    DEFF Research Database (Denmark)

    2005-01-01

    Katalog til udstillingen på KA d. 12. - 30. oktober 2005. Kataloget til udstillingen Mossin: Mody, til udstillingens fotografier og til det arkitektoniske udviklingsarbejde, som fotografierne dokumenterer igennem deres formidling af et særligt og kritisk syn på by og bygning.......Katalog til udstillingen på KA d. 12. - 30. oktober 2005. Kataloget til udstillingen Mossin: Mody, til udstillingens fotografier og til det arkitektoniske udviklingsarbejde, som fotografierne dokumenterer igennem deres formidling af et særligt og kritisk syn på by og bygning....

  4. Evaluation of Multilayer Cloud Detection Using a MODIS CO2-Slicing Algorithm With CALIPSO-CloudSat Measurements

    Science.gov (United States)

    Viudez-Mora, Antonio; Kato, Seiji

    2015-01-01

    This work evaluates the multilayer cloud (MCF) algorithm based on CO2-slicing techniques against CALISPO-CloudSat (CLCS) measurement. This evaluation showed that the MCF underestimates the presence of multilayered clouds compared with CLCS and are retrained to cloud emissivities below 0.8 and cloud optical septs no larger than 0.3.

  5. Mapping Changes in Area and the Cropping Season of Irrigated Rice in Senegal and Mauritania between 2003 and 2014 Using the PhenoRice Algorithm and MODIS Imagery

    Science.gov (United States)

    Zwart, S.; Busetto, L.; Diagne, M.; Boschetti, M.; Nelson, A.

    2017-12-01

    Government policies have resulted in rapid expansion of irrigated rice area in Mauritania and Senegal through private and public investments. Farmers switch rice cultivation from the wet to the dry season to achieve higher production while rice double cropping is increasingly practiced. As a result Senegal is close to attaining self-sufficiency in the coming years. However, tools to monitor those changes are absent and this inhibits assessments on for example its impact on wetlands located in the delta area, increased water demands and climate induced risks to farmers. In this study we aimed to map changes in irrigated rice area in the wet and dry seasons. We applied the PhenoRice algorithm on a combined time-series of MODIS Aqua and Terra images obtained between 2003 and 2016 to map pixels dominated by rice and determine the start, end and length of the growing season from sowing/transplanting to maturity. Between 2002 and 2010 researchers from the Africa Rice Center interviewed annually around 100 rice farmers located in two irrigation schemes in Senegal. We extracted the reported sowing/transplanting and harvest dates from the data base and used these to validate the estimates obtained by PhenoRice. We also compared the obtained rice areas with official statistics provided by the Senegalese Ministry of Agriculture. Analysis of PhenoRice results highlighted that starting 2008, rice farmers cultivate also during the dry season; the area is steadily increasing from 2008 onwards and in the recent years approximately almost equals that of the wet season. This was confirmed by official statistics, though the total area estimated by PhenoRice is smaller than reported, most likely due to the mismatch between pixel size and the small cultivated areas. However, the algorithm was able to detect the overall trends and inter-annual variations observed in the wet (r2=0.57) and dry season rice cultivated area (r2=0.91). The start of the season, that varied maximally 4 weeks

  6. Evaluation of Different MODIS AOD Retrieval Algorithms for PM (sub 2.5) Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

    Science.gov (United States)

    Al-Hamdan, Mohammad; Crosson, William; Burrows, Erica; Coffield, Shane; Crane, Breanna

    2016-01-01

    This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP (Minority University Research and Education Project) Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns PM (sub 2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM (sub 2.5) varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target versus Deep Blue), Collections (5.1 versus 6) and spatial resolutions (10-kilometers versus 3-kilometers) for cities in the Western, Midwestern and Southeastern U.S. We developed and validated PM (sub 2.5) prediction models using remotely-sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM (sub 2.5) models, especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Our study re-establishes the connection between PM (sub 2.5) and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM (sub 2.5) data and health data from the Centers for

  7. Physically-based Canopy Reflectance Model Inversion of Vegetation Biophysical-Structural Information from Terra-MODIS Imagery in Boreal and Mountainous Terrain for Ecosystem, Climate and Carbon Models using the BIOPHYS-MFM Algorithm

    Science.gov (United States)

    Peddle, D. R.; Hall, F.

    2009-12-01

    The BIOPHYS algorithm provides innovative and flexible methods for the inversion of canopy reflectance models (CRM) to derive essential biophysical structural information (BSI) for quantifying vegetation state and disturbance, and for input to ecosystem, climate and carbon models. Based on spectral, angular, temporal and scene geometry inputs that can be provided or automatically derived, the BIOPHYS Multiple-Forward Mode (MFM) approach generates look-up tables (LUTs) that comprise reflectance data, structural inputs over specified or computed ranges, and the associated CRM output from forward mode runs. Image pixel and model LUT spectral values are then matched. The corresponding BSI retrieved from the LUT matches is output as the BSI results. BIOPHYS-MFM has been extensively used with agencies in Canada and the USA over the past decade (Peddle et al 2000-09; Soenen et al 2005-09; Gamon et al 2004; Cihlar et al 2003), such as CCRS, CFS, AICWR, NASA LEDAPS, BOREAS and MODIS Science Teams, and for the North American Carbon Program. The algorithm generates BSI products such as land cover, biomass, stand volume, stem density, height, crown closure, leaf area index (LAI) and branch area, crown dimension, productivity, topographic correction, structural change from harvest, forest fires and mountain pine beetle damage, and water / hydrology applications. BIOPHYS-MFM has been applied in different locations in Canada (six provinces from Newfoundland to British Columbia) and USA (NASA COVER, MODIS and LEDAPS sites) using 7 different CRM models and a variety of imagery (e.g. MODIS, Landsat, SPOT, IKONOS, airborne MSV, MMR, casi, Probe-1, AISA). In this paper we summarise the BIOPHYS-MFM algorithm and results from Terra-MODIS imagery from MODIS validation sites at Kananaskis Alberta in the Canadian Rocky Mountains, and from the Boreal Ecosystem Atmosphere Study (BOREAS) in Saskatchewan Canada. At the montane Rocky Mountain site, BIOPHYS-MFM density estimates were within

  8. Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

    Science.gov (United States)

    Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rozenhaimer, Michal; Spurr, Rob

    2016-01-01

    We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

  9. Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

    Science.gov (United States)

    de Moura, Yhasmin Mendes; Galvão, Lênio Soares; Hilker, Thomas; Wu, Jin; Saleska, Scott; do Amaral, Cibele Hummel; Nelson, Bruce Walker; Lopes, Aline Pontes; Wiedeman, Kenia K.; Prohaska, Neill; de Oliveira, Raimundo Cosme; Machado, Carolyne Bueno; Aragão, Luiz E. O. C.

    2017-09-01

    September with new foliage. Variations in red-edge position were not statistically significant between the species and across dates at the 95% confidence level. The camera data were affected by view-illumination effects, which reduced the SMA shade fraction over time. When MODIS data were corrected for these effects using the Multi-Angle Implementation of Atmospheric Correction Algorithm (MAIAC), we observed an EVI increase toward September that closely tracked the modeled LAI of mature leaves (3-5 months). Compared to the EVI, the GRND was a better indicator of leaf flushing because the modeled production of new leaves peaked in August and then declined in September following the GRND closely. While the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing.

  10. Accuracy assessment of Terra-MODIS aerosol optical depth retrievals

    International Nuclear Information System (INIS)

    Safarpour, Sahabeh; Abdullah, Khiruddin; Lim, Hwee San; Dadras, Mohsen

    2014-01-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been widely used to address environment and climate change subjects with daily global coverage. Aerosol optical depth (AOD) is retrieved by different algorithms based on the pixel surface, determining between land and ocean. MODIS-Terra and Global Aerosol Robotic Network (AERONET) products can be obtained from the Multi-sensor Aerosol Products Sampling System (MAPSS) for coastal regions during 2000-2010. Using data collected from 83 coastal stations worldwide from AERONET from 2000-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard the Terra satellite. AOD retrieved from MODIS at 0.55μm wavelength has been compared With the AERONET derived AOD, because it is reliable with the major wavelength used by many chemistry transport and climate models as well as previous MODIS validation studies. After removing retrievals with quality flags below1 for Ocean algorithm and below 3 for Land algorithm, The accuracy of AOD retrieved from MODIS Dark Target Ocean algorithms (correlation coefficient R 2 is 0.844 and a regression equation of τ M = 0.91·τ A + 0.02 (where subscripts M and A represent MODIS and AERONET respectively), is the greater than the MODIS Dark Target Land algorithms (correlation coefficient R 2 is 0.764 and τ M = 0.95·τ A + 0.03) and the Deep Blue algorithm (correlation coefficient R 2 is 0.652 and τ M = 0.81·τ A + 0.04). The reasons of the retrieval error in AOD are found to be the various underlying surface reflectance. Therefore, the aerosol models and underlying surface reflectance are the dominant factors which influence the accuracy of MODIS retrieval performance. Generally the MODIS Land algorithm implements better than the Ocean algorithm for coastal sites

  11. The use of a MODIS band-ratio algorithm versus a new hybrid approach for estimating colored dissolved organic matter (CDOM)

    Science.gov (United States)

    Satellite remote sensing offers synoptic and frequent monitoring of optical water quality parameters, such as chlorophyll-a, turbidity, and colored dissolved organic matter (CDOM). While traditional satellite algorithms were developed for the open ocean, these algorithms often do...

  12. Genetika MODY diabetu

    OpenAIRE

    Dušátková, Petra

    2012-01-01

    The most common form of monogenic diabetes is MODY (Maturity-Onset Diabetes of the Young). It ranks among genetic defects of the β cell. It is clinically heterogenous group of disorders characterised with non insulin-dependent diabetes mellitus with autosomal dominant inheritance and age at diagnosis up to 40 years. We specified the diagnosis of MODY in more than 240 Czech families using molecular-genetic approach. The most common subtype of MODY is GCK-MODY which was proved in 376 subjects f...

  13. The 2015 Indonesian biomass-burning season with extensive peat fires: Remote sensing measurements of biomass burning aerosol optical properties from AERONET and MODIS satellite data

    Science.gov (United States)

    Eck, T. F.; Holben, B. N.; Giles, D. M.; Smirnov, A.; Slutsker, I.; Sinyuk, A.; Schafer, J.; Sorokin, M. G.; Reid, J. S.; Sayer, A. M.; Hsu, N. Y. C.; Levy, R. C.; Lyapustin, A.; Wang, Y.; Rahman, M. A.; Liew, S. C.; Salinas Cortijo, S. V.; Li, T.; Kalbermatter, D.; Keong, K. L.; Elifant, M.; Aditya, F.; Mohamad, M.; Mahmud, M.; Chong, T. K.; Lim, H. S.; Choon, Y. E.; Deranadyan, G.; Kusumaningtyas, S. D. A.

    2016-12-01

    The strong El Nino event in 2015 resulted in below normal rainfall throughout Indonesia, which in turn allowed for exceptionally large numbers of biomass burning fires (including much peat burning) from Aug though Oct 2015. Over the island of Borneo, three AERONET sites measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in Sep and Oct ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain significant signal at mid-visible, therefore a newly developed algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the longer wavelengths as possible. The AOD at longer wavelengths were then utilized to provide estimates of AOD at 550 nm with maximum values of 9 to 11. Additionally, satellite retrievals of AOD at 550 nm from MODIS data and the Dark Target, Deep Blue, and MAIAC algorithms were analyzed and compared to AERONET measured AOD. The AOD was sometimes too high for the satellite algorithms to make retrievals in the densest smoke regions. Since the AOD was often extremely high there was often insufficient AERONET direct sun signal at 440 nm for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, new hybrid sky radiance scans can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for more retrievals and at higher AOD levels. The retrieved volume median radius of the fine mode increased from 0.18 to 0.25 micron as AOD increased from 1 to 3 (at 440 nm). These are very large size particles for biomass burning aerosol and are similar in size to smoke particles measured in Alaska during the very dry years of 2004 and 2005 (Eck et al. 2009) when peat soil burning also contributed to the fuel burned. The average single scattering albedo over the wavelength range of 440 to 1020 nm

  14. GHRSST Level 2P USA NASA MODIS Terra SST:1

    Data.gov (United States)

    National Aeronautics and Space Administration — The production of the MODIS L2P data is a joint collaboration between JPL, OBPG and RSMAS. RSMAS is responsible for sea surface temperature algorithm development,...

  15. GHRSST Level 2P USA NASA MODIS Aqua SST:1

    Data.gov (United States)

    National Aeronautics and Space Administration — The production of the MODIS L2P data is a joint collaboration between JPL, OBPG and RSMAS. RSMAS is responsible for sea surface temperature algorithm development,...

  16. Algorithms

    Indian Academy of Sciences (India)

    polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.

  17. Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity

    Science.gov (United States)

    Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.

    2017-12-01

    The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for

  18. Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

    Science.gov (United States)

    Rodriguez-Galiano, Victor; Aragones, David; Caparros-Santiago, Jose A.; Navarro-Cerrillo, Rafael M.

    2017-10-01

    Land surface phenology (LSP) can improve the characterisation of forest areas and their change processes. The aim of this work was: i) to characterise the temporal dynamics in Mediterranean Pinus forests, and ii) to evaluate the potential of LSP for species discrimination. The different experiments were based on 679 mono-specific plots for the 5 native species on the Iberian Peninsula: P. sylvestris, P. pinea, P. halepensis, P. nigra and P. pinaster. The entire MODIS NDVI time series (2000-2016) of the MOD13Q1 product was used to characterise phenology. The following phenological parameters were extracted: the start, end and median days of the season, and the length of the season in days, as well as the base value, maximum value, amplitude and integrated value. Multi-temporal metrics were calculated to synthesise the inter-annual variability of the phenological parameters. The species were discriminated by the application of Random Forest (RF) classifiers from different subsets of variables: model 1) NDVI-smoothed time series, model 2) multi-temporal metrics of the phenological parameters, and model 3) multi-temporal metrics and the auxiliary physical variables (altitude, slope, aspect and distance to the coastline). Model 3 was the best, with an overall accuracy of 82%, a kappa coefficient of 0.77 and whose most important variables were: elevation, coast distance, and the end and start days of the growing season. The species that presented the largest errors was P. nigra, (kappa= 0.45), having locations with a similar behaviour to P. sylvestris or P. pinaster.

  19. Algorithms

    Indian Academy of Sciences (India)

    to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...

  20. GADEP Continuous PM2.5 mass concentration data, VIIRS Day Night Band SDR (SVDNB), MODIS Terra Level 2 water vapor profiles (infrared algorithm for atmospheric profiles for both day and night, NWS surface meteorological data

    Science.gov (United States)

    Data descriptions are provided at the following urls:GADEP Continuous PM2.5 mass concentration data - https://aqs.epa.gov/aqsweb/documents/data_mart_welcome.htmlhttps://www3.epa.gov/ttn/amtic/files/ambient/pm25/qa/QA-Handbook-Vol-II.pdfVIIRS Day Night Band SDR (SVDNB) http://www.class.ngdc.noaa.gov/saa/products/search?datatype_family=VIIRS_SDRMODIS Terra Level 2 water vapor profiles (infrared algorithm for atmospheric profiles for both day and night -MOD0&_L2; http://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html NWS surface meteorological data - https://www.ncdc.noaa.gov/isdThis dataset is associated with the following publication:Wang, J., C. Aegerter, and J. Szykman. Potential Application of VIIRS Day/Night Band for Monitoring Nighttime Surface PM2.5 Air Quality From Space. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 124(0): 55-63, (2016).

  1. Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

    Science.gov (United States)

    Sun, Junqiang; Xiong, Xiaoxiong; Madhavan, Sriharsha; Wenny, Brian

    2012-01-01

    The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the NASA Earth Observing System (EOS). The first MODIS instrument was launched in December, 1999 on-board the Terra spacecraft. MODIS has 36 bands, covering a wavelength range from 0.4 micron to 14.4 micron. MODIS band 27 (6.72 micron) is a water vapor band, which is designed to be insensitive to Earth surface features. In recent Earth View (EV) images of Terra band 27, surface feature contamination is clearly seen and striping has become very pronounced. In this paper, it is shown that band 27 is impacted by electronic crosstalk from bands 28-30. An algorithm using a linear approximation is developed to correct the crosstalk effect. The crosstalk coefficients are derived from Terra MODIS lunar observations. They show that the crosstalk is strongly detector dependent and the crosstalk pattern has changed dramatically since launch. The crosstalk contributions are positive to the instrument response of band 27 early in the mission but became negative and much larger in magnitude at later stages of the mission for most detectors of the band. The algorithm is applied to both Black Body (BB) calibration and MODIS L1B products. With the crosstalk effect removed, the calibration coefficients of Terra MODIS band 27 derived from the BB show that the detector differences become smaller. With the algorithm applied to MODIS L1B products, the Earth surface features are significantly removed and the striping is substantially reduced in the images of the band. The approach developed in this report for removal of the electronic crosstalk effect can be applied to other MODIS bands if similar crosstalk behaviors occur.

  2. Algorithms

    Indian Academy of Sciences (India)

    ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...

  3. MODY diabetes - diagnostika a terapie

    OpenAIRE

    Verner, Miroslav

    2010-01-01

    This work summarized basic informations about different types of MODY diabetes. The keypoint is diagnostic, based on family history, followed by analysis of MODY diabetes types with suggestion of optimal therapy. In conclusion I suggest a possible solution of the underestimated diagnostic in MODY diabetes with an information poster in diabetological consulting rooms.

  4. Estimativa do fluxo do calor sensível utilizando o algoritmo SEBAL e imagens MODIS para a região Norte Fluminense, RJ Estimative of sensible heat flux (H in North Fluminense region, RJ, using MODIS products and SEBAL algorithm

    Directory of Open Access Journals (Sweden)

    José Carlos Mendonça

    2012-03-01

    Full Text Available Neste estudo foram utilizadas imagens do sensor MODIS e o SEBAL na avaliação de duas proposições para a estimação do fluxo de calor sensível (H, baseadas na seleção dos pixels âncoras utilizados na determinação da diferença da temperatura à superfície (dT. Denominou-se H-CLÁSSICO, a proposição que utilizou pixels com temperaturas extremas, e H-PESAGRO, aquela que adotou o pixel frio para a menor temperatura e o pixel quente para o valor de H obtido como resíduo da equação de Penman-Monteith (FAO56, estimado com dados observados em uma estação agrometeorológica. Os resultados de H estimados pelas duas proposições foram comparados com valores de H obtidos pelo Balanço de Energia (Razão de Bowen sobre uma área cultivada com cana-de-açúcar. Com os resultados obtidos pode-se concluir que a proposição H-PESAGRO necessitou de um menor número de interações para a estabilização dos valores da resistência aerodinâmica (r ah e que os resultados, estimados com a proposição H-CLÁSSICA, apresentaram valores 58,35 % mais elevados do que os estimados pela H-PESAGRO. Quando comparados com os valores de H estimados pelo método da razão de Bowen sobre o pixel da cana-de-açúcar, os coeficientes de correlação foram r = 0,54 e r = 0,71, respectivamente, para as proposições H-CLÁSSICA e H-PESAGRO.Images from the MODIS and SEBAL algorithm were used to evaluate two proposals for estimating sensible heat flux (H based on the selection of anchor pixels used to determine the surface temperature difference (dT. The proposition in which pixels with extreme temperatures were used was called H-CLASSIC. The other one H-PESAGRO adopted for cold pixels the lowest temperature and for the hot pixels the value of H as a residue of the equation of Penman-Monteith FAO 56, using observed data from agrometeorological station. The results showed that the H-PESAGRO required a smaller number of interactions for the stabilization of the

  5. Algorithms

    Indian Academy of Sciences (India)

    algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).

  6. Algorithms

    Indian Academy of Sciences (India)

    algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...

  7. Operationalizing a Research Sensor: MODIS to VIIRS

    Science.gov (United States)

    Grant, K. D.; Miller, S. W.; Puschell, J.

    2012-12-01

    Radiometer Suite (VIIRS). VIIRS combines the demonstrated high value spectral coverage and radiometric accuracy of MODIS with the legacy spectral bands and radiometric accuracy of the Advanced Very High Resolution Radiometer (AVHRR) and the high spatial resolution (0.75 km) of the Operational Linescan System (OLS). Except for MODIS bands designed for deriving vertical temperature and humidity structure in the atmosphere, VIIRS uses identical or very similar bands from MODIS that have the most interest and usefulness to operational customers in NOAA, the USAF and the USN. The development of VIIRS and JPSS reaps the benefit of investments in MODIS and the NASA EOS and the early development of operational algorithms by NOAA and DoD using MODIS data. This presentation will cover the different aspects of transitioning a research system into an operational system. These aspects include: (1) sensor (hardware & software) operationalization, (2) system performance operational factors, (3) science changes to algorithms reflecting the operational performance factors, and (4) the operationalization and incorporation of the science into a fully 24 x 7 production system, tasked with meeting stringent operational needs. Benefits of early operationalization are discussed along with suggested areas for improvement in this process that could benefit future work such as operationalizing Earth Science Decadal Survey missions.

  8. Large-sized seaweed monitoring based on MODIS

    Science.gov (United States)

    Ma, Long; Li, Ying; Lan, Guo-xin; Li, Chuan-long

    2009-10-01

    In recent years, large-sized seaweed, such as ulva lactuca, blooms frequently in coastal water in China, which threatens marine eco-environment. In order to take effective measures, it is important to make operational surveillance. A case of large-sized seaweed blooming (i.e. enteromorpha), occurred in June, 2008, in the sea near Qingdao city, is studied. Seaweed blooming is dynamically monitored using Moderate Resolution Imaging Spectroradiometer (MODIS). After analyzing imaging spectral characteristics of enteromorpha, MODIS band 1 and 2 are used to create a band ratio algorithm for detecting and mapping large-sized seaweed blooming. In addition, chlorophyll-α concentration is inversed based on an empirical model developed using MODIS. Chlorophyll-α concentration maps are derived using multitemporal MODIS data, and chlorophyll-α concentration change is analyzed. Results show that the presented methods are useful to get the dynamic distribution and the growth of large-sized seaweed, and can support contingency planning.

  9. MODIS Snow Cover Recovery Using Variational Interpolation

    Science.gov (United States)

    Tran, H.; Nguyen, P.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Cloud obscuration is one of the major problems that limit the usages of satellite images in general and in NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) global Snow-Covered Area (SCA) products in particular. Among the approaches to resolve the problem, the Variational Interpolation (VI) algorithm method, proposed by Xia et al., 2012, obtains cloud-free dynamic SCA images from MODIS. This method is automatic and robust. However, computational deficiency is a main drawback that degrades applying the method for larger scales (i.e., spatial and temporal scales). To overcome this difficulty, this study introduces an improved version of the original VI. The modified VI algorithm integrates the MINimum RESidual (MINRES) iteration (Paige and Saunders., 1975) to prevent the system from breaking up when applied to much broader scales. An experiment was done to demonstrate the crash-proof ability of the new algorithm in comparison with the original VI method, an ability that is obtained when maintaining the distribution of the weights set after solving the linear system. After that, the new VI algorithm was applied to the whole Contiguous United States (CONUS) over four winter months of 2016 and 2017, and validated using the snow station network (SNOTEL). The resulting cloud free images have high accuracy in capturing the dynamical changes of snow in contrast with the MODIS snow cover maps. Lastly, the algorithm was applied to create a Cloud free images dataset from March 10, 2000 to February 28, 2017, which is able to provide an overview of snow trends over CONUS for nearly two decades. ACKNOWLEDGMENTSWe would like to acknowledge NASA, NOAA Office of Hydrologic Development (OHD) National Weather Service (NWS), Cooperative Institute for Climate and Satellites (CICS), Army Research Office (ARO), ICIWaRM, and UNESCO for supporting this research.

  10. Algorithms

    Indian Academy of Sciences (India)

    will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...

  11. Detecting land cover change using an extended Kalman filter on MODIS NDVI time-series data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-05-01

    Full Text Available A method for detecting land cover change using NDVI time-series data derived from 500-m MODIS satellite data is proposed. The algorithm acts as a per-pixel change alarm and takes the NDVI time series of a 3 × 3 grid of MODIS pixels as the input...

  12. Improvement in the Characterization of MODIS Subframe Difference

    Science.gov (United States)

    Li, Yonghong; Angal, Amit; Chen, Na; Geng, Xu; Link, Daniel; Wang, Zhipeng; Wu, Aisheng; Xiong, Xiaoxiong

    2016-01-01

    MODIS is a key instrument of NASA's Earth Observing System. It has successfully operated for 16+ years on the Terra satellite and 14+ years on the Aqua satellite, respectively. MODIS has 36 spectral bands at three different nadir spatial resolutions, 250m (bands 1-2), 500m (bands 3-7), and 1km (bands 8-36). MODIS subframe measurement is designed for bands 1-7 to match their spatial resolution in the scan direction to that of the track direction. Within each 1 km frame, the MODIS 250 m resolution bands sample four subframes and the 500 m resolution bands sample two subframes. The detector gains are calibrated at a subframe level. Due to calibration differences between subframes, noticeable subframe striping is observed in the Level 1B (L1B) products, which exhibit a predominant radiance-level dependence. This paper presents results of subframe differences from various onboard and earth-view data sources (e.g. solar diffuser, electronic calibration, spectro-radiometric calibration assembly, Earth view, etc.). A subframe bias correction algorithm is proposed to minimize the subframe striping in MODIS L1B image. The algorithm has been tested using sample L1B images and the vertical striping at lower radiance value is mitigated after applying the corrections. The subframe bias correction approach will be considered for implementation in future versions of the calibration algorithm.

  13. Undiagnosed MODY: Time for Action

    Science.gov (United States)

    Kleinberger, Jeffrey W.; Pollin, Toni I.

    2016-01-01

    Maturity-Onset Diabetes of the Young (MODY) is a monogenic form of diabetes that accounts for at least 1% of all cases of diabetes mellitus. MODY classically presents as non-insulin requiring diabetes in lean individuals younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of MODY is important for selecting the right treatment, yet ~95% of MODY cases in the U.S. are misdiagnosed. MODY prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible. This review will cover the current epidemiological studies of MODY and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals. PMID:26458381

  14. Estimating Coastal Turbidity using MODIS 250 m Band Observations

    Science.gov (United States)

    Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.

    2004-01-01

    Terra MODIS 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where reflectance is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on MODIS observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing reflectance in the MODIS 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing reflectance are based on accepted inherent optical properties of sediment types known to be prevalent in the U.S. Gulf of Mexico coastal zone. We present our findings for the Atchafalaya Bay region of the Louisiana Coast, in the form of processed imagery over the annual cycle. We also apply our algorithm to selected sites worldwide with a goal of extending the utility of our approach to the global direct broadcast community.

  15. MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2017-06-01

    Full Text Available We present a new approach to retrieve Aerosol Optical Depth (AOD using the Moderate Resolution Imaging Spectroradiometer (MODIS over the turbid coastal water. This approach supplements the operational Dark Target (DT aerosol retrieval algorithm that currently does not conduct AOD retrieval in shallow waters that have visible sediments or sea-floor (i.e., Class 2 waters. Over the global coastal water regions in cloud-free conditions, coastal screening leads to ~20% unavailability of AOD retrievals. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 μm to be negligible regardless of water turbidity, and therefore the 2.1 μm reflectance at the top of the atmosphere is sensitive to both change of fine-mode and coarse-mode AODs. By assuming that the aerosol single scattering properties over coastal turbid water are similar to those over the adjacent open-ocean pixels, the new algorithm can derive AOD over these shallow waters. The test algorithm yields ~18% more MODIS-AERONET collocated pairs for six AERONET stations in the coastal water regions. Furthermore, comparison of the new retrieval with these AERONET observations show that the new AOD retrievals have equivalent or better accuracy than those retrieved by the MODIS operational algorithm’s over coastal land and non-turbid coastal water product. Combining the new retrievals with the existing MODIS operational retrievals yields an overall improvement of AOD over those coastal water regions. Most importantly, this refinement extends the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides. This expanded coverage is crucial for better understanding of impact of anthropogenic aerosol particles on coastal air quality and climate.

  16. Evaluation of the MODIS C6 Aerosol Optical Depth Products over Chongqing, China

    Directory of Open Access Journals (Sweden)

    Guangming Shi

    2017-11-01

    Full Text Available The Moderate Resolution Imaging Spectroradiometer (MODIS Collection 6 (C6 aerosol optical depth (AOD products from the 10/3 km Dark Target (DT and Deep Blue (DB algorithms are firstly evaluated using ground observed AODs by the sun photometer in Chongqing, a mountainous mega-city in southwest China. The validation results show that MODIS AODs from 10/3 km DT algorithm are comparable with those of the sun photometer, although there are slight overestimations. However, the DB algorithm substantially underestimates MODIS AODs when comparing with those of the sun photometer. Error analyses imply that the bias of surface reflectance estimation is the main error source for both algorithms. The cloud screening scheme of the DT algorithm is more effective than the DB algorithm. The cloud vicinity effect should be considered in the quality control processes for both of the algorithms. A sensitivity test suggests that in complex terrain area, like Chongqing, the collocation method in the validation of satellite products should be carefully selected according to local circumstances. When comparing the monthly mean AODs of MODIS products with sun photometer observations, it shows that the Terra MODIS AOD products are valid to represent the mean statuses in summer and autumn, but the monthly mean of Aqua MODIS AODs are limited in Chongqing.

  17. Improved VIIRS and MODIS SST Imagery

    Directory of Open Access Journals (Sweden)

    Irina Gladkova

    2016-01-01

    Full Text Available Moderate Resolution Imaging Spectroradiometers (MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS radiometers, flown onboard Terra/Aqua and Suomi National Polar-orbiting Partnership (S-NPP/Joint Polar Satellite System (JPSS satellites, are capable of providing superior sea surface temperature (SST imagery. However, the swath data of these multi-detector sensors are subject to several artifacts including bow-tie distortions and striping, and require special pre-processing steps. VIIRS additionally does two irreversible data reduction steps onboard: pixel aggregation (to reduce resolution changes across the swath and pixel deletion, which complicate both bow-tie correction and destriping. While destriping was addressed elsewhere, this paper describes an algorithm, adopted in the National Oceanic and Atmospheric Administration (NOAA Advanced Clear-Sky Processor for Oceans (ACSPO SST system, to minimize the bow-tie artifacts in the SST imagery and facilitate application of the pattern recognition algorithms for improved separation of ocean from cloud and mapping fine SST structure, especially in the dynamic, coastal and high-latitude regions of the ocean. The algorithm is based on a computationally fast re-sampling procedure that ensures a continuity of corresponding latitude and longitude arrays. Potentially, Level 1.5 products may be generated to benefit a wide range of MODIS and VIIRS users in land, ocean, cryosphere, and atmosphere remote sensing.

  18. MISR Aerosol Product Attributes and Statistical Comparisons with MODIS

    Science.gov (United States)

    Kahn, Ralph A.; Nelson, David L.; Garay, Michael J.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Paradise, Susan R.; Hansen, Earl G.; Remer, Lorraine A.

    2009-01-01

    In this paper, Multi-angle Imaging SpectroRadiometer (MISR) aerosol product attributes are described, including geometry and algorithm performance flags. Actual retrieval coverage is mapped and explained in detail using representative global monthly data. Statistical comparisons are made with coincident aerosol optical depth (AOD) and Angstrom exponent (ANG) retrieval results from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The relationship between these results and the ones previously obtained for MISR and MODIS individually, based on comparisons with coincident ground-truth observations, is established. For the data examined, MISR and MODIS each obtain successful aerosol retrievals about 15% of the time, and coincident MISR-MODIS aerosol retrievals are obtained for about 6%-7% of the total overlap region. Cloud avoidance, glint and oblique-Sun exclusions, and other algorithm physical limitations account for these results. For both MISR and MODIS, successful retrievals are obtained for over 75% of locations where attempts are made. Where coincident AOD retrievals are obtained over ocean, the MISR-MODIS correlation coefficient is about 0.9; over land, the correlation coefficient is about 0.7. Differences are traced to specific known algorithm issues or conditions. Over-ocean ANG comparisons yield a correlation of 0.67, showing consistency in distinguishing aerosol air masses dominated by coarse-mode versus fine-mode particles. Sampling considerations imply that care must be taken when assessing monthly global aerosol direct radiative forcing and AOD trends with these products, but they can be used directly for many other applications, such as regional AOD gradient and aerosol air mass type mapping and aerosol transport model validation. Users are urged to take seriously the published product data-quality statements.

  19. Investigation of Cloud Properties and Atmospheric Profiles with Modis

    Science.gov (United States)

    Menzel, Paul; Ackerman, Steve; Moeller, Chris; Gumley, Liam; Strabala, Kathy; Frey, Richard; Prins, Elaine; Laporte, Dan; Wolf, Walter

    1997-01-01

    A major milestone was accomplished with the delivery of all five University of Wisconsin MODIS Level 2 science production software packages to the Science Data Support Team (SDST) for integration. These deliveries were the culmination of months of design and testing, with most of the work focused on tasks peripheral to the actual science contained in the code. LTW hosted a MODIS infrared calibration workshop in September. Considerable progress has been made by MCST, with help from LTW, in refining the calibration algorithm, and in identifying and characterization outstanding problems. Work continues on characterizing the effects of non-blackbody earth surfaces on atmospheric profile retrievals and modeling radiative transfer through cirrus clouds.

  20. Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

    Directory of Open Access Journals (Sweden)

    Mathias Neumann

    2016-06-01

    Full Text Available Net primary production (NPP is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country and gradients (elevation, location, tree age, dominant species, etc.. The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.

  1. Fuel type characterization based on coarse resolution MODIS satellite data

    Directory of Open Access Journals (Sweden)

    Lanorte A

    2007-01-01

    Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (I adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

  2. MODIS Snow and Sea Ice Products

    Science.gov (United States)

    Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

    2004-01-01

    In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

  3. Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

    Science.gov (United States)

    Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

    2009-01-01

    Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

  4. NAMMA MODIS/AQUA AND MODIS/TERRA DEEP BLUE PRODUCTS V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The NAMMA MODIS/AQUA and MODIS/TERRA Deep Blue Products dataset is a collection of images depicting the aerosol optical depth derived from the MODIS deep blue...

  5. Undiagnosed MODY: Time for Action.

    Science.gov (United States)

    Kleinberger, Jeffrey W; Pollin, Toni I

    2015-12-01

    Maturity-onset diabetes of the young (MODY) is a monogenic form of diabetes that accounts for at least 1 % of all cases of diabetes mellitus. MODY classically presents as non-insulin-requiring diabetes in lean individuals typically younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of MODY is important for selecting the right treatment, yet ~95 % of MODY cases in the USA are misdiagnosed. MODY prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible; at the same time, they are detecting other mutations in the same genes of unknown clinical significance. This review will cover the current epidemiological studies of MODY and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals.

  6. Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

    Science.gov (United States)

    Platnick, Steven

    2004-01-01

    MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

  7. Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

    Science.gov (United States)

    Xiao, Qingyang; Wang, Yujie; Chang, Howard H.; Meng, Xia; Geng, Guannan; Lyapustin, Alexei Ivanovich; Liu, Yang

    2017-01-01

    Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

  8. The MODIS Vegetation Canopy Water Content product

    Science.gov (United States)

    Ustin, S. L.; Riano, D.; Trombetti, M.

    2008-12-01

    Vegetation water stress drives wildfire behavior and risk, having important implications for biogeochemical cycling in natural ecosystems, agriculture, and forestry. Water stress limits plant transpiration and carbon gain. The regulation of photosynthesis creates close linkages between the carbon, water, and energy cycles and through metabolism to the nitrogen cycle. We generated systematic weekly CWC estimated for the USA from 2000-2006. MODIS measures the sunlit reflectance of the vegetation in the visible, near-infrared, and shortwave infrared. Radiative transfer models, such as PROSPECT-SAILH, determine how sunlight interacts with plant and soil materials. These models can be applied over a range of scales and ecosystem types. Artificial Neural Networks (ANN) were used to optimize the inversion of these models to determine vegetation water content. We carried out multi-scale validation of the product using field data, airborne and satellite cross-calibration. An Algorithm Theoretical Basis Document (ATBD) of the product is under evaluation by NASA. The CWC product inputs are 1) The MODIS Terra/Aqua surface reflectance product (MOD09A1/MYD09A1) 2) The MODIS land cover map product (MOD12Q1) reclassified to grassland, shrub-land and forest canopies; 3) An ANN trained with PROSPECT-SAILH; 4) A calibration file for each land cover type. The output is an ENVI file with the CWC values. The code is written in Matlab environment and is being adapted to read not only the 8 day MODIS composites, but also daily surface reflectance data. We plan to incorporate the cloud and snow mask and generate as output a geotiff file. Vegetation water content estimates will help predicting linkages between biogeochemical cycles, which will enable further understanding of feedbacks to atmospheric concentrations of greenhouse gases. It will also serve to estimate primary productivity of the biosphere; monitor/assess natural vegetation health related to drought, pollution or diseases

  9. Land surface temperature retrieval from MODIS and VIRR data in northwest China

    International Nuclear Information System (INIS)

    Wang, L J; Zuo, H C; Ren, P C; Qiang, B

    2014-01-01

    By using the Gulang Heterogeneous Underlying Surface Layer Experiment (GHUSLE) data, the accuracy of land surface temperature (LST) in Northwest China retrieved by the Moderate-Resolution Imaging Spectroradiometer(MODIS) and Visible and InfraRed Radiometer(VIRR) data is verified. Furthermore, a new LST algorithm for heterogeneous underlying surface is developed and the LST retrieved by the two remote sensing data using three algorithms are compared with the observed data. Results suggest that the new algorithm is the best one in the case of heterogeneous underlying surface, Kerr algorithm accuracy is not satisfying and Becker algorithm is ranked just ahead Kerr algorithm. Especially, the differences in retrieval accuracy among them are more obvious when using the VIRR data. Compared with the observed LST, the root mean square errors of the LST retrieved by MODIS and VIRR data are the least when using the new algorithm, the specific values are 2.55 K and 3.78 K, respectively. The LST retrieved by MODIS data are closer to observed values and higher than its counterpart retrieved by VIRR data. When the new LST retrieval algorithm used, the LST retrieved by MODIS and VIRR data are the closest

  10. MODIS/Aqua Atmosphere Aeronet Subsetting Product

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS/Aqua Atmosphere Aeronet Subsetting Product (MYDARNSS) consists of MODIS Atmosphere and Ancillary Products subsets that are generated over a number of...

  11. Quality Assessment of Collection 6 MODIS Atmospheric Science Products

    Science.gov (United States)

    Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.

    2015-12-01

    Since the launch of the NASA Terra and Aqua satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (MODIS Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA MODIS science team investigators. MODAPS completed Collection 6 reprocessing of MODIS Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the MODIS Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of MODIS operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the

  12. Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

    Science.gov (United States)

    Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

    2010-01-01

    The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

  13. Validation of MODIS aerosol optical depth over the Mediterranean Coast

    Science.gov (United States)

    Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

    2013-04-01

    Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial

  14. History and Future for the Happy Marriage between the MODIS Land team and Fluxnet

    Science.gov (United States)

    Running, S. W.

    2015-12-01

    When I wrote the proposal to NASA in 1988 for daily global evapotranspiration and gross primary production algorithms for the MODIS sensor, I had no validation plan. Fluxnet probably saved my MODIS career by developing a global network of rigorously calibrated towers measuring water and carbon fluxes over a wide variety of ecosystems that I could not even envision at the time that first proposal was written. However my enthusiasm for Fluxnet was not reciprocated by the Fluxnet community until we began providing 7 x 7 pixel MODIS Land datasets exactly over each of their towers every 8 days, without them having to crawl thru the global datasets and make individual orders. This system, known informally as the MODIS ASCII cutouts, began in 2002 and operates at the Oak Ridge DAAC to this day, cementing a mutually beneficial data interchange between the Fluxnet and remote sensing communities. This talk will briefly discuss the history of MODIS validation with flux towers, and flux spatial scaling with MODIS data. More importantly I will detail the future continuity of global biophysical datasets in the post-MODIS era, and what next generation sensors will provide.

  15. MODIS Hotspot Validation over Thailand

    Directory of Open Access Journals (Sweden)

    Veerachai Tanpipat

    2009-11-01

    Full Text Available To ensure remote sensing MODIS hotspot (also known as active fire products or hotspots quality and precision in forest fire control and management in Thailand, an increased level of confidence is needed. Accuracy assessment of MODIS hotspots utilizing field survey data validation is described. A quantitative evaluation of MODIS hotspot products has been carried out since the 2007 forest fire season. The carefully chosen hotspots were scattered throughout the country and within the protected areas of the National Parks and Wildlife Sanctuaries. Three areas were selected as test sites for validation guidelines. Both ground and aerial field surveys were also conducted in this study by the Forest Fire Control Division, National Park, Wildlife and Plant Conversation Department, Ministry of Natural Resources and Environment, Thailand. High accuracy of 91.84 %, 95.60% and 97.53% for the 2007, 2008 and 2009 fire seasons were observed, resulting in increased confidence in the use of MODIS hotspots for forest fire control and management in Thailand.

  16. Simulation of tsunami effects on sea surface salinity using MODIS satellite data

    International Nuclear Information System (INIS)

    Ramlan, N E F; Genderen, J van; Hashim, M; Marghany, M

    2014-01-01

    Remote sensing technology has been recognized as powerful tool for environmental disaster studies. Ocean surface salinity is considered as a major element in the marine environment. In this study, we simulate the 2004 tsunami's impact on a physical ocean parameter using the least square algorithm to retrieve sea surface salinity (SSS) from MODIS satellite data. The accuracy of this work has been examined using the root mean of sea surface salinity retrieved from MODIS satellite data. The study shows a comprehensive relationship between the in situ measurements and least square algorithm with high r 2 of 0.95, and RMS of bias value of ±0.9 psu. In conclusion, the least square algorithm can be used to retrieve SSS from MODIS satellite data during a tsunami event

  17. Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

    Science.gov (United States)

    Platnick, Steven E.

    2011-01-01

    The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

  18. Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS.

    Science.gov (United States)

    Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.

    2005-04-01

    The Chesapeake Lighthouse Aircraft Measurements for Satellites (CLAMS) experiment took place from 10 July to 2 August 2001 in a combined ocean-land region that included the Chesapeake Lighthouse [Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE)] and the Wallops Flight Facility (WFF), both along coastal Virginia. This experiment was designed mainly for validating instruments and algorithms aboard the Terra satellite platform, including the Moderate Resolution Imaging Spectroradiometer (MODIS). Over the ocean, MODIS retrieved aerosol optical depths (AODs) at seven wavelengths and an estimate of the aerosol size distribution. Over the land, MODIS retrieved AOD at three wavelengths plus qualitative estimates of the aerosol size. Temporally coincident measurements of aerosol properties were made with a variety of sun photometers from ground sites and airborne sites just above the surface. The set of sun photometers provided unprecedented spectral coverage from visible (VIS) to the solar near-infrared (NIR) and infrared (IR) wavelengths. In this study, AOD and aerosol size retrieved from MODIS is compared with similar measurements from the sun photometers. Over the nearby ocean, the MODIS AOD in the VIS and NIR correlated well with sun-photometer measurements, nearly fitting a one-to-one line on a scatterplot. As one moves from ocean to land, there is a pronounced discontinuity of the MODIS AOD, where MODIS compares poorly to the sun-photometer measurements. Especially in the blue wavelength, MODIS AOD is too high in clean aerosol conditions and too low under larger aerosol loadings. Using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative code to perform atmospheric correction, the authors find inconsistency in the surface albedo assumptions used by the MODIS lookup tables. It is demonstrated how the high bias at low aerosol loadings can be corrected. By using updated urban/industrial aerosol

  19. The normalization of surface anisotropy effects present in SEVIRI reflectances by using the MODIS BRDF method

    DEFF Research Database (Denmark)

    Proud, Simon Richard; Zhang, Qingling; Schaaf, Crystal

    2014-01-01

    A modified version of the MODerate resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) algorithm is presented for use in the angular normalization of surface reflectance data gathered by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI...... acquisition period than the comparable MODIS products while, at the same time, removing many of the angular perturbations present within the original MSG data. The NBAR data are validated against reflectance data from the MODIS instrument and in situ data gathered at a field location in Africa throughout 2008....... It is found that the MSG retrievals are stable and are of high-quality across much of the SEVIRI disk while maintaining a higher temporal resolution than the MODIS BRDF products. However, a number of circumstances are discovered whereby the BRDF model is unable to function correctly with the SEVIRI...

  20. Characterization of beta cell and incretin function in patients with MODY1 (HNF4A MODY) and MODY3 (HNF1A MODY) in a Swedish patient collection.

    Science.gov (United States)

    Ekholm, E; Shaat, N; Holst, J J

    2012-10-01

    The aim of this study was to evaluate the beta cell and incretin function in patients with HNF4A and HNF1A MODY during a test meal. Clinical characteristics and biochemical data (glucose, proinsulin, insulin, C-peptide, GLP-1 and GIP) during a test meal were compared between MODY patients from eight different families. BMI-matched T2D and healthy subjects were used as two separate control groups. The early phase of insulin secretion was attenuated in HNF4A, HNF1A MODY and T2D (AUC0-30 controls: 558.2 ± 101.2, HNF4A MODY: 93.8 ± 57.0, HNF1A MODY: 170.2 ± 64.5, T2D: 211.2 ± 65.3, P MODY compared to T2D and that tended to be so also in HNF1A MODY (HNF4A MODY: 3.7 ± 1.2, HNF1A MODY: 8.3 ± 3.8 vs. T2D: 26.6 ± 14.3). Patients with HNF4A MODY had similar total GLP-1 and GIP responses as controls (GLP-1 AUC: (control: 823.9 ± 703.8, T2D: 556.4 ± 698.2, HNF4A MODY: 1,257.0 ± 999.3, HNF1A MODY: 697.1 ± 818.4) but with a different secretion pattern. The AUC insulin during the test meal was strongly correlated with the GIP secretion (Correlation coefficient 1.0, P MODY showed an attenuated early phase of insulin secretion similar to T2Ds. AUC insulin during the test meal was strongly correlated with GIP secretion, whereas no such correlation was seen for insulin and GLP-1. Thus, GIP may be a more important factor for insulin secretion than GLP-1 in MODY patients.

  1. Derivation of Aerosol Columnar Mass from MODIS Optical Depth

    Science.gov (United States)

    Gasso, Santiago; Hegg, Dean A.

    2003-01-01

    In order to verify performance, aerosol transport models (ATM) compare aerosol columnar mass (ACM) with those derived from satellite measurements. The comparison is inherently indirect since satellites derive optical depths and they use a proportionality constant to derive the ACM. Analogously, ATMs output a four dimensional ACM distribution and the optical depth is linearly derived. In both cases, the proportionality constant requires a direct intervention of the user by prescribing the aerosol composition and size distribution. This study introduces a method that minimizes the direct user intervention by making use of the new aerosol products of MODIS. A parameterization is introduced for the derivation of columnar aerosol mass (AMC) and CCN concentration (CCNC) and comparisons between sunphotometer, MODIS Airborne Simulator (MAS) and in-measurements are shown. The method still relies on the scaling between AMC and optical depth but the proportionality constant is dependent on the MODIS derived r$_{eff}$,\\eta (contribution of the accumulation mode radiance to the total radiance), ambient RH and an assumed constant aerosol composition. The CCNC is derived fkom a recent parameterization of CCNC as a function of the retrieved aerosol volume. By comparing with in-situ data (ACE-2 and TARFOX campaigns), it is shown that retrievals in dry ambient conditions (dust) are improved when using a proportionality constant dependent on r$ {eff}$ and \\eta derived in the same pixel. In high humidity environments, the improvement inthe new method is inconclusive because of the difficulty in accounting for the uneven vertical distribution of relative humidity. Additionally, two detailed comparisons of AMC and CCNC retrieved by the MAS algorithm and the new method are shown. The new method and MAS retrievals of AMC are within the same order of magnitude with respect to the in-situ measurements of aerosol mass. However, the proposed method is closer to the in-situ measurements than

  2. Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

    Science.gov (United States)

    Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric; Masek, Jeffrey G.; Townshend, John R.

    2012-01-01

    Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

  3. Characterization of beta cell and incretin function in patients with MODY1 (HNF4A MODY) and MODY3 (HNF1A MODY) in a Swedish patient collection

    DEFF Research Database (Denmark)

    Ekholm, E; Shaat, N; Holst, Jens Juul

    2012-01-01

    eight different families. BMI-matched T2D and healthy subjects were used as two separate control groups. The early phase of insulin secretion was attenuated in HNF4A, HNF1A MODY and T2D (AUC0-30 controls: 558.2 ± 101.2, HNF4A MODY: 93.8 ± 57.0, HNF1A MODY: 170.2 ± 64.5, T2D: 211.2 ± 65.3, P ....01). Markedly reduced levels of proinsulin were found in HNF4A MODY compared to T2D and that tended to be so also in HNF1A MODY (HNF4A MODY: 3.7 ± 1.2, HNF1A MODY: 8.3 ± 3.8 vs. T2D: 26.6 ± 14.3). Patients with HNF4A MODY had similar total GLP-1 and GIP responses as controls (GLP-1 AUC: (control: 823.9 ± 703.......8, T2D: 556.4 ± 698.2, HNF4A MODY: 1,257.0 ± 999.3, HNF1A MODY: 697.1 ± 818.4) but with a different secretion pattern. The AUC insulin during the test meal was strongly correlated with the GIP secretion (Correlation coefficient 1.0, P

  4. Crosstalk effect and its mitigation in Aqua MODIS middle wave infrared bands

    Science.gov (United States)

    Sun, Junqiang; Madhavan, Sriharsha; Wang, Menghua

    2017-09-01

    The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS). The first MODIS instrument was launched in December 1999 on-board the Terra spacecraft. A follow on MODIS was launched on an afternoon orbit in 2002 and is aboard the Aqua spacecraft. Both MODIS instruments are very akin, has 36 bands, among which bands 20 to 25 are Middle Wave Infrared (MWIR) bands covering a wavelength range from approximately 3.750 μm to 4.515 μm. It was found that there was severe contamination in these bands early in mission but the effect has not been characterized and mitigated at the time. The crosstalk effect induces strong striping in the Earth View (EV) images and causes significant retrieval errors in the EV Brightness Temperature (BT) in these bands. An algorithm using a linear approximation derived from on-orbit lunar observations has been developed to correct the crosstalk effect and successfully applied to mitigate the effect in both Terra and Aqua MODIS Long Wave Infrared (LWIR) Photovoltaic (PV) bands. In this paper, the crosstalk effect in the Aqua MWIR bands is investigated and characterized by deriving the crosstalk coefficients using the scheduled Aqua MODIS lunar observations for the MWIR bands. It is shown that there are strong crosstalk contaminations among the five MWIR bands and they also have significant crosstalk contaminations from Short Wave Infrared (SWIR) bands. The crosstalk correction algorithm previously developed is applied to correct the crosstalk effect in these bands. It is demonstrated that the crosstalk correction successfully reduces the striping in the EV images and improves the accuracy of the EV BT in the five bands as was done similarly for LWIR PV bands. The crosstalk correction algorithm should thus be applied to improve both the image quality and radiometric accuracy of the Aqua MODIS MWIR bands Level 1B (L1B) products.

  5. Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

    Science.gov (United States)

    Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

    2016-01-01

    A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

  6. Dissolved Organic Carbon along the Louisiana coast from MODIS and MERIS satellite data

    Science.gov (United States)

    Chaichi Tehrani, N.; D'Sa, E. J.

    2012-12-01

    Dissolved organic carbon (DOC) plays a critical role in the coastal and ocean carbon cycle. Hence, it is important to monitor and investigate its the distribution and fate in coastal waters. Since DOC cannot be measured directly through satellite remote sensors, chromophoric dissolved organic matter (CDOM) as an optically active fraction of DOC can be used as an alternative proxy to trace DOC concentrations. Here, satellite ocean color data from MODIS, MERIS, and field measurements of CDOM and DOC were used to develop and assess CDOM and DOC ocean color algorithms for coastal waters. To develop a CDOM retrieval algorithm, empirical relationships between CDOM absorption coefficient at 412 nm (aCDOM(412)) and reflectance ratios Rrs(488)/Rrs(555) for MODIS and Rrs(510)/Rrs(560) for MERIS were established. The performance of two CDOM empirical algorithms were evaluated for retrieval of (aCDOM(412)) from MODIS and MERIS in the northern Gulf of Mexico. Further, empirical algorithms were developed to estimate DOC concentration using the relationship between in situ aCDOM(412) and DOC, as well as using the newly developed CDOM empirical algorithms. Accordingly, our results revealed that DOC concentration was strongly correlated to aCDOM (412) for summer and spring-winter periods (r2 = 0.9 for both periods). Then, using the aCDOM(412)-Rrs and the aCDOM(412)-DOC relationships derived from field measurements, a relationship between DOC-Rrs was established for MODIS and MERIS data. The DOC empirical algorithms performed well as indicated by match-up comparisons between satellite estimates and field data (R2=0.52 and 0.58 for MODIS and MERIS for summer period, respectively). These algorithms were then used to examine DOC distribution along the Louisiana coast.

  7. Using ALS and MODIS data to evaluate degradation in different forests types over the Xingu basin - Brazilian Amazon

    Science.gov (United States)

    Moura, Y.; Aragão, L. E.; Galvão, L. S.; Dalagnol, R.; Lyapustin, A.; Santos, E. G.; Espirito-Santo, F.

    2017-12-01

    Degradation of Amazon rainforests represents a vital threat to carbon storage, climate regulation and biodiversity; however its effect on tropical ecosystems is largely unknown. In this study we evaluate the effects of forest degradation on forest structure and functioning over the Xingu Basin in the Brazilian Amazon. The vegetation types in the area is dominated by Open Ombrophilous Forest (Asc), Semi-decidiuous Forest (Fse) and Dense Ombrophilous Forest (Dse). We used Airborne Laser Scanning (ALS) data together with time series of optical remote sensing images from the Moderate Resolution Imaging Spectroradiometer (MODIS) bi-directional corrected using the Multi-Angle Implementation for Atmospheric Correction (MAIAC). We derive time-series (2008 to 2016) of the Enhanced Vegetation Index (EVI) and Green-Red Normalized Difference (GRND) to analyze the dynamics of degraded areas with related changes in canopy structure and greenness values, respectively. Airborne ALS measurements showed the largest tree heights in the Dse class with values up to 40m tall. Asc and Fse vegetation types reached up to 30m and 25m in height, respectively. Differences in canopy structure were also evident from the analysis of canopy volume models (CVMs). Asc showed higher proportion of sunlit, as expected for open forest types. Fse showed gaps predominantly in lower height levels, and a higher overall proportion of shaded crown. Full canopy closure was reached at about15 m height for both Asc and Dse, and at about 20 m height for Fse. We also used a base map of degraded areas (available from Imazon - Instituto do Homen e Meio Ambiente da Amazônia) to follow these regions throughout time using EVI and GRND from MODIS. All three forest types displayed seasonal cycles. Notable differences in amplitude were detected during the periods when degradation occurred and both indexes showed a decrease in their response. However, there were marked differences in timing and amplitude depending on

  8. Evaluating MODIS Collection 6 Dark Target Over Water Aerosol Products for Multi-sensor Data Fusion

    Science.gov (United States)

    Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; McHardy, T. M.; Lee, L.

    2014-12-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been widely used in aerosol related climate, visibility, and air quality studies for more than a decade. Recently, the MODIS collection 6 (c6) aerosol products from MODIS-Aqua have been released. The reported changes between Collection 5 and Collection 6 include updates in the retrieving algorithms and a new cloud filtering process for the over-ocean products. Thus it is necessary to fully evaluate the collection 6 products for applications that require high quality MODIS aerosol optical depth data, such as operational aerosol data assimilation. The uncertainties in the MODIS c6 DT over ocean products are studied through both inter-comparing with the Multi-angle Imaging Spectroradiometer (MISR) aerosol products and by evaluation against ground truth. Special attention is given to the low bias in MODIS DT products due to the misclassifications of heavy aerosol plumes as clouds. Finally, a quality assured data assimilation grade aerosol optical product is constructed for aerosol data assimilation related applications.

  9. Multitemporal cross-calibration of the Terra MODIS and Landsat 7 ETM+ reflective solar bands

    Science.gov (United States)

    Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Chander, Gyanesh; Choi, Taeyoung

    2013-01-01

    In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

  10. Comparasion of Cloud Cover restituted by POLDER and MODIS

    Science.gov (United States)

    Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

    2009-04-01

    of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes

  11. Inventory of Agricultural Land Area of Egypt Using Modis Data

    International Nuclear Information System (INIS)

    Hereher, M.E.

    2009-01-01

    A new generation of satellite data has been emerged since the launch of the Moderate Resolution Imaging Spectro radiometer (MODIS), in 1999, for monitoring land resources and terrestrial environments. Agricultural land area of Egypt in 2005 was estimated using MODIS data. Four scenes were utilized to extract the total country area. MODIS vegetation Indices product (MOD 13 QI) was the most suitable to extract the total gross cultivated land area of Egypt. An unsupervised classification algorithm was applied to estimate the cultivated land area, which approached 8.2 million feddans in 2005. The Nile Delta contains the majority of agricultural lands (63.2%). The Nile Valley and EI-Fayoum Depression possess 33.9% and the remaining little percent (∼3%) represents the scattered agricultural land along the Suez Canal, Sinai and the Western Desert. The classification accuracy of agricultural land reached 84%, revealing higher confidence of assessment. The present study asserts on the importance of using remote sensing in monitoring agricultural land resources

  12. Creating a regional MODIS satellite-driven net primary production dataset for european forests

    NARCIS (Netherlands)

    Neumann, Mathias; Moreno, Adam; Thurnher, Christopher; Mues, Volker; Härkönen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Cardellini, Giuseppe; Thivolle-Cazat, Alain; Bronisz, Karol; Merganic, Jan; Alberdi, Iciar; Astrup, Rasmus; Mohren, Frits; Zhao, Maosheng; Hasenauer, Hubert

    2016-01-01

    Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm

  13. MODIS Collection 6 Land Product Subsets Web Service

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS Web Service provides data access capabilities for Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 land products. The web service...

  14. Detection of Asian Dust Storm Using MODIS Measurements

    Directory of Open Access Journals (Sweden)

    Yong Xie

    2017-08-01

    Full Text Available Every year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remote sensing has been demonstrated as an effective means for observing dust aerosols. In this paper, an algorithm based on the multi-spectral technique for detecting dust aerosols was developed by combining measurements of moderate resolution imaging spectroradiometer (MODIS reflective solar bands and thermal emissive bands. Data from dust events that occurred during the past several years were collected as training data for spectral and statistical analyses. According to the spectral curves of various scene types, a series of spectral bands was selected individually or jointly, and corresponding thresholds were defined for step-by-step scene classification. The multi-spectral algorithm was applied mainly to detect dust storms in Asia. The detection results were validated not only visually with MODIS true color images, but also quantitatively with products of Ozone Monitoring Instrument (OMI and Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP. The validations showed that this multi-spectral detection algorithm was suitable to monitor dust aerosols in the selected study areas.

  15. Assessment of MODIS RSB Detector Uniformity Using Deep Convective Clouds

    Science.gov (United States)

    Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen

    2016-01-01

    For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select reflective solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (MODIS). Each detector of MODIS RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra MODIS Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most Aqua bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for MODIS band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to reflectance images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.

  16. Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

    Science.gov (United States)

    Underwood, L. W.; Kalcic, Maria; Fletcher, Rose

    2012-01-01

    -m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

  17. Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

    Science.gov (United States)

    Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jerome; Mottus, Matti; Aragao, Luiz E.O.C.; Shimabukuro, Yosio

    2016-01-01

    Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

  18. Consistency of vegetation index seasonality across the Amazon rainforest

    Science.gov (United States)

    Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jérôme; Mõttus, Matti; Aragão, Luiz E. O. C.; Shimabukuro, Yosio

    2016-10-01

    Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

  19. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  20. [MODY type diabetes: overview and recent findings].

    Science.gov (United States)

    Ben Khelifa, Souhaïra; Barboura, Ilhem; Dandana, Azza; Ferchichi, Selima; Miled, Abdelhedi

    2011-01-01

    We present an update of knowledge on diabetes MODY (maturity onset diabetes of the young), including the recent molecular discoveries, and new diagnostic strategies. Considerable progress has been made in understanding the different molecular abnormalities that cause MODY and the phenotypic consequences resulting therefrom. MODY diabetes is very heterogeneous and is the most common form of monogenic diabetes. Its distribution is worldwide. MODY is an autosomal dominant diabetes mellitus, nonketotic and occurs at an early age (usually before 25 years). To date, at least seven genes are associated with MODY, with frequencies that differ from one population to another. Both 2 and 3 subtypes predominate, while other subtypes (1, 4, 5, 6 and 7) concern only a few families. Since its discovery in the sixties, studies have succeeded to fully clarify the epidemiological, molecular and clinical diagnosis of each subtype, to provide better care for patients. However, the subject of MODY has not yet revealed all its secrets. Indeed, it remains to identify other genes that are associated with MODY X.

  1. The Collection 6 'dark-target' MODIS Aerosol Products

    Science.gov (United States)

    Levy, Robert C.; Mattoo, Shana; Munchak, Leigh A.; Kleidman, Richard G.; Patadia, Falguni; Gupta, Pawan; Remer, Lorraine

    2013-01-01

    Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and

  2. [Humoral response markers in GCK MODY].

    Science.gov (United States)

    Skała-Zamorowska, Eliza; Deja, Grażyna; Borowiec, Maciej; Fendler, Wojciech; Małachowska, Beata; Kamińska, Halla; Wyka, Krystyna; Młynarski, Wojciech; Jarosz-Chobot, Przemysława

    2016-01-01

    The prevalence of antibodies to pancreatic islets in monogenic diabetes remains unknown and the incidence estimation is difficult as the occurrence of autoantibodies in patient is one of the well-known exclusion criteria for further genetic diagnostics. They has been found not only among patients with type 1 diabetes, but also in other types of diabetes: Type 2 diabetes, Latent Autoimmune Diabetes in Adults (LADA) (16) and monogenic diabetes (MD). Immunological characteristic of GCK MODY patients. The study group included families of 27 adolescent patients with GCK MODY (39 parents and 19 siblings) monitored in the Department of Pediatrics, Endocrinology and Diabetes and in the Diabetes Clinic of John Paul II Upper Silesian Child Health Centre in Katowice in the years 2007-2012. All patients and family members with GCK MODY underwent a blood sample drawing for immunological (classic humoral response markers: ICA, GAD, IA-2, IAA) and biochemical diagnostics. Pediatric, diabetes and family medical history was collected from the subjects and parents. Immunological diagnostics was performed in all patients except 1 (96.3%). Immunological diagnostics included 17 (89.5%) parents and 7 (87.5%) siblings with diagnosed GCK MODY. 8 (30.8%) adolescent patients with GCK MODY, 3 subjects (17.64%) among parents (with GCK MODY), as well as 2 subjects (28.57%) among siblings (with GCK MODY) showed a positive antibodies screen. The results of our study in children with GCK MODY and their family members suggest that the occurrence of classic antibodies directed against pancreatic islets antigens is fairly common in patients with GCK MODY. Despite various observations and many legitimate discussions, it is difficult to clarify the pathogenesis of the occurrence of autoantibodies in monogenic diabetes. © Polish Society for Pediatric Endocrinology and Diabetology.

  3. Effects of canopy photosynthesis saturation on the estimation of gross primary productivity from MODIS data in a tropical forest

    DEFF Research Database (Denmark)

    Propastin, P.; Ibrom, Andreas; Knohl, A.

    2012-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (GPPMOD17A2) was evaluated against GPP from the eddy covariance flux measurements (GPPm) at a CO2 flux tower test site in a tropical rainforest in Sulawesi, Indonesia. The dynamics of 8-day GPPMOD17A2...... conditions. Obviously, these seasonal differences are caused by too large seasonal amplitudes in GPPMOD17A2. The observed inconsistencies of the GPPMOD17A2with GPPm were traced to the inputs of the MODIS GPP algorithm, including fraction of absorbed photosynthetically active radiation (fAPAR) and light use...... efficiency (εg). This showed that underestimation of low values is caused by several uncertainties in the MODIS fAPAR input, whereas overestimation at high irradiance is caused by the MODIS light use efficiency approach which does not account for saturation of canopy photosynthesis under clear sky conditions...

  4. Neural network cloud top pressure and height for MODIS

    Science.gov (United States)

    Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

    2018-06-01

    Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found

  5. Calculations of Aerosol Radiative Forcing in the SAFARI Region from MODIS Data

    Science.gov (United States)

    Remer, L. A.; Ichoku, C.; Kaufman, Y. J.; Chu, D. A.

    2003-01-01

    SAFARI 2000 provided the opportunity to validate MODIS aerosol retrievals and to correct any assumptions in the retrieval process. By comparing MODIS retrievals with ground-based sunphotometer data, we quantified the degree to which the MODIS algorithm underestimated the aerosol optical thickness. This discrepancy was attributed to underestimating the degree of light absorption by the southern African smoke aerosol. Correcting for this underestimation of absorption, produces more realistic aerosol retrievals that allow various applications of the MODIS aerosol products. One such application is the calculation of the aerosol radiative forcing at the top and bottom of the atmosphere. The combination of MODIS accuracy, coverage, resolution and the ability to separate fine and coarse mode make this calculation substantially advanced over previous attempts with other satellites. We focus on the oceans adjacent to southern Africa and use a solar radiative transfer model to perform the flux calculations. The forcing at the top of atmosphere is calculated to be 10 W/sq m, while the forcing at the surface is -26 W/sq m. These results resemble those calculated from INDOEX data, and are most sensitive to assumptions of aerosol absorption, the same parameter that initially interfered with our retrievals.

  6. Estimates of Single Sensor Error Statistics for the MODIS Matchup Database Using Machine Learning

    Science.gov (United States)

    Kumar, C.; Podesta, G. P.; Minnett, P. J.; Kilpatrick, K. A.

    2017-12-01

    Sea surface temperature (SST) is a fundamental quantity for understanding weather and climate dynamics. Although sensors aboard satellites provide global and repeated SST coverage, a characterization of SST precision and bias is necessary for determining the suitability of SST retrievals in various applications. Guidance on how to derive meaningful error estimates is still being developed. Previous methods estimated retrieval uncertainty based on geophysical factors, e.g. season or "wet" and "dry" atmospheres, but the discrete nature of these bins led to spatial discontinuities in SST maps. Recently, a new approach clustered retrievals based on the terms (excluding offset) in the statistical algorithm used to estimate SST. This approach resulted in over 600 clusters - too many to understand the geophysical conditions that influence retrieval error. Using MODIS and buoy SST matchups (2002 - 2016), we use machine learning algorithms (recursive and conditional trees, random forests) to gain insight into geophysical conditions leading to the different signs and magnitudes of MODIS SST residuals (satellite SSTs minus buoy SSTs). MODIS retrievals were first split into three categories: 0.4 C. These categories are heavily unbalanced, with residuals > 0.4 C being much less frequent. Performance of classification algorithms is affected by imbalance, thus we tested various rebalancing algorithms (oversampling, undersampling, combinations of the two). We consider multiple features for the decision tree algorithms: regressors from the MODIS SST algorithm, proxies for temperature deficit, and spatial homogeneity of brightness temperatures (BTs), e.g., the range of 11 μm BTs inside a 25 km2 area centered on the buoy location. These features and a rebalancing of classes led to an 81.9% accuracy when classifying SST retrievals into the cloud contamination still is one of the causes leading to negative SST residuals. Precision and accuracy of error estimates from our decision tree

  7. Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky; hide

    2015-01-01

    The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

  8. The SeaDAS Processing and Analysis System: SeaWiFS, MODIS, and Beyond

    Science.gov (United States)

    MacDonald, M. D.; Ruebens, M.; Wang, L.; Franz, B. A.

    2005-12-01

    The SeaWiFS Data Analysis System (SeaDAS) is a comprehensive software package for the processing, display, and analysis of ocean data from a variety of satellite sensors. Continuous development and user support by programmers and scientists for more than a decade has helped to make SeaDAS the most widely used software package in the world for ocean color applications, with a growing base of users from the land and sea surface temperature community. Full processing support for past (CZCS, OCTS, MOS) and present (SeaWiFS, MODIS) sensors, and anticipated support for future missions such as NPP/VIIRS, enables end users to reproduce the standard ocean archive product suite distributed by NASA's Ocean Biology Processing Group (OBPG), as well as a variety of evaluation and intermediate ocean, land, and atmospheric products. Availability of the processing algorithm source codes and a software build environment also provide users with the tools to implement custom algorithms. Recent SeaDAS enhancements include synchronization of MODIS processing with the latest code and calibration updates from the MODIS Calibration Support Team (MCST), support for all levels of MODIS processing including Direct Broadcast, a port to the Macintosh OS X operating system, release of the display/analysis-only SeaDAS-Lite, and an extremely active web-based user support forum.

  9. Assessment of biases in MODIS surface reflectance due to Lambertian approximation

    Energy Technology Data Exchange (ETDEWEB)

    Cook, Robert B [ORNL; SanthanaVannan, Suresh K [ORNL

    2010-08-01

    Using MODIS data and the AERONET-based Surface Reflectance Validation Network (ASRVN), this work studies errors of MODIS atmospheric correction caused by the Lambertian approximation. On one hand, this approximation greatly simplifies the radiative transfer model, reduces the size of the look-up tables, and makes operational algorithm faster. On the other hand, uncompensated atmospheric scattering caused by Lambertian model systematically biases the results. For example, for a typical bowl-shaped bidirectional reflectance distribution function (BRDF), the derived reflectance is underestimated at high solar or view zenith angles, where BRDF is high, and is overestimated at low zenith angles where BRDF is low. The magnitude of biases grows with the amount of scattering in the atmosphere, i.e., at shorter wavelengths and at higher aerosol concentration. The slope of regression of Lambertian surface reflectance vs. ASRVN bidirectional reflectance factor (BRF) is about 0.85 in the red and 0.6 in the green bands. This error propagates into the MODIS BRDF/albedo algorithm, slightly reducing the magnitude of overall reflectance and anisotropy of BRDF. This results in a small negative bias of spectral surface albedo. An assessment for the GSFC (Greenbelt, USA) validation site shows the albedo reduction by 0.004 in the near infrared, 0.005 in the red, and 0.008 in the green MODIS bands.

  10. MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

    Science.gov (United States)

    Albayrak, Arif; Wei, Jennifer; Petrenko, Maksym; Lary, David; Leptoukh, Gregory

    2011-01-01

    To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.

  11. Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

    Science.gov (United States)

    Ross, Kenton W.; Russell, Jeffrey; Ryan, Robert E.

    2006-01-01

    The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion

  12. Time-Dependent Response Versus Scan Angle for MODIS Reflective Solar Bands

    Science.gov (United States)

    Sun, Junqiang; Xiong, Xiaoxiong; Angal, Amit; Chen, Hongda; Wu, Aisheng; Geng, Xu

    2014-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently operate onboard the National Aeronautics and Space Administration (NASA's) Terra and Aqua spacecraft, launched on December 18, 1999 and May 4, 2002, respectively. MODIS has 36 spectral bands, among which 20 are reflective solar bands (RSBs) covering a spectral range from 0.412 to 2.13 µm. The RSBs are calibrated on orbit using a solar diffuser (SD) and an SD stability monitor and with additional measurements from lunar observations via a space view (SV) port. Selected pseudo-invariant desert sites are also used to track the RSB on-orbit gain change, particularly for short-wavelength bands. MODIS views the Earth surface, SV, and the onboard calibrators using a two-sided scan mirror. The response versus scan angle (RVS) of the scan mirror was characterized prior to launch, and its changes are tracked using observations made at different angles of incidence from onboard SD, lunar, and Earth view (EV) measurements. These observations show that the optical properties of the scan mirror have experienced large wavelength-dependent degradation in both the visible and near infrared spectral regions. Algorithms have been developed to track the on-orbit RVS change using the calibrators and the selected desert sites. These algorithms have been applied to both Terra and Aqua MODIS Level 1B (L1B) to improve the EV data accuracy since L1B Collection 4, refined in Collection 5, and further improved in the latest Collection 6 (C6). In C6, two approaches have been used to derive the time-dependent RVS for MODIS RSB. The first approach relies on data collected from sensor onboard calibrators and mirror side ratios from EV observations. The second approach uses onboard calibrators and EV response trending from selected desert sites. This approach is mainly used for the bands with much larger changes in their time-dependent RVS, such as the Terra MODIS bands 1-4, 8, and 9 and the Aqua MODIS bands 8- and 9

  13. Unmanned aerial system nadir reflectance and MODIS nadir BRDF-adjusted surface reflectances intercompared over Greenland

    Science.gov (United States)

    Faulkner Burkhart, John; Kylling, Arve; Schaaf, Crystal B.; Wang, Zhuosen; Bogren, Wiley; Storvold, Rune; Solbø, Stian; Pedersen, Christina A.; Gerland, Sebastian

    2017-07-01

    Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300-920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.

  14. Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

    Science.gov (United States)

    Sun-Mack, Sunny; Chen, Yan; Minnis, Patrick; Young, DavidF.; Smith, William J., Jr.

    2004-01-01

    The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

  15. ASTER cloud coverage reassessment using MODIS cloud mask products

    Science.gov (United States)

    Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

    2010-10-01

    In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

  16. Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

    Science.gov (United States)

    Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

    2008-05-01

    CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

  17. Spatio-temporal approach to detecting land cover change using an extended kalman filter on modis time series data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2010-01-01

    Full Text Available A method for detecting land cover change using NDVI timeseries data derived fromMODerate-resolution Imaging Spectroradiometer (MODIS) satellite data is proposed. The algorithm acts as a per pixel change alarm and takes as input the NDVI time...

  18. Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

    OpenAIRE

    Neumann, Mathias; Moreno, Adam; Thurnher, Christopher; Mues, Volker; Härkönen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Cardellini, Giuseppe; Thivolle-Cazat, Alain; Bronisz, Karol; Merganic, Jan; Alberdi, Iciar; Astrup, Rasmus; Mohren, Frits

    2016-01-01

    Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily g...

  19. [Diagnosis of MODY - brief overview for clinical practice].

    Science.gov (United States)

    Urbanová, Jana; Brunerová, Ludmila; Brož, Jan

    2018-01-01

    Maturity Onset Diabetes of the Young (MODY) comprises inherited forms of diabetes mellitus caused by the mutations in the genes involved in the development, differentiation and function of beta-cells. The majority of patients with MODY remains misdiagnosed and erroneously classified as type 1 or type 2 diabetic patients. Correct MODY diagnosis is, however, essential since it enables individualization of treatment, assessment of the prognosis and identification of diabetes among patient´s relatives. Clinical presentation of MODY is highly variable and it could resemble other types of diabetes, thus identification of MODY patients might be difficult. In this review, we describe typical clinical presentation of the most common MODY subtypes, we summarize current diagnostic guidelines in confirmation of MODY and we raise the question of possible need for extension of current clinical criteria indicating a patient for molecular-genetic testing.Key words: clinical course - diagnosis - differential diagnosis - glucokinase - hepatocyte nuclear factors - MODY.

  20. Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Román, Miguel O.

    2017-10-01

    Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375

  1. Reducing Striping and Near Field Response Influence in the MODIS 1.38um Cirrus Detection Band.

    Science.gov (United States)

    Ackerman, S. A.; Moeller, C. C.; Frey, R. A.; Gumley, L. E.; Menzel, W. P.

    2002-05-01

    Since first light in February 2000, the MODIS L1B data from Terra has exhibited detector striping in the cirrus detection band at 1.38 um (B26). This band's unique characteristic is that it is potentially able to discriminate very thin cirrus (optical depth of 0.1) because water vapor absorption effectively attenuates the upwelling signal from the earth's surface, leaving a flat dark background underneath the thin cirrus. The striping has diminished the power of this band for detecting thin cirrus in the MODIS Cloud Mask (MOD35) over the global environment by imparting a structure on the background. The striping amplitude (valley to peak) is 10 - 15% of the MODIS Ltyp radiance in B26 over land backgrounds, thus exceeding the 5% radiance prelaunch accuracy specification for the band. Also unexpected has been the presence of earth surface reflectance in B26. Forward model calculations indicate that the two-way transmittance of B26 in-band (1% to 1% response) should be water (TPW) exceeds about 12 mm. However, MODIS B26 imagery has routinely shown land surface reflectance, such as Florida, even in very moist (TPW > 30 mm) tropical air masses. MODIS prelaunch test data suggests that a near field response (NFR) at about 1.3 um in the B26 filter may be contributing to this behavior. A destriping and out-of-band correction algorithm has been under development at the University of Wisconsin to address the these issues. The simple linear algorithm is based on tuning detector dependent influence coefficients for B26 as a function of B5 (1.24 um) radiance so that the corrected B26 radiance is near zero for all B26 detectors in moist atmospheric conditions. B5 was chosen as a surrogate to characterize the NFR leak in the B26 filter because of its close spectral proximity to the NFR leak. Real MODIS L1B data is being used to estimate the influence coefficients. The paper will describe the B5 based destriping and NFR correction algorithm and influence coefficient development. It

  2. GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

    Directory of Open Access Journals (Sweden)

    K. Fukue

    2016-06-01

    Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.

  3. Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Yinghai Ke

    2016-03-01

    Full Text Available This study presented a MODIS 8-day 1 km evapotranspiration (ET downscaling method based on Landsat 8 data (30 m and machine learning approaches. Eleven indicators including albedo, land surface temperature (LST, and vegetation indices (VIs derived from Landsat 8 data were first upscaled to 1 km resolution. Machine learning algorithms including Support Vector Regression (SVR, Cubist, and Random Forest (RF were used to model the relationship between the Landsat indicators and MODIS 8-day 1 km ET. The models were then used to predict 30 m ET based on Landsat 8 indicators. A total of thirty-two pairs of Landsat 8 images/MODIS ET data were evaluated at four study sites including two in United States and two in South Korea. Among the three models, RF produced the lowest error, with relative Root Mean Square Error (rRMSE less than 20%. Vegetation greenness related indicators such as Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Soil Adjusted Vegetation Index (SAVI, and vegetation moisture related indicators such as Normalized Difference Infrared Index—Landsat 8 OLI band 7 (NDIIb7 and Normalized Difference Water Index (NDWI were the five most important features used in RF model. Temperature-based indicators were less important than vegetation greenness and moisture-related indicators because LST could have considerable variation during each 8-day period. The predicted Landsat downscaled ET had good overall agreement with MODIS ET (average rRMSE = 22% and showed a similar temporal trend as MODIS ET. Compared to the MODIS ET product, the downscaled product demonstrated more spatial details, and had better agreement with in situ ET observations (R2 = 0.56. However, we found that the accuracy of MODIS ET was the main control factor of the accuracy of the downscaled product. Improved coarse-resolution ET estimation would result in better finer-resolution estimation. This study proved the potential of using machine learning

  4. MODIS/Terra Land Water Mask Derived from MODIS and SRTM L3 Global 250m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS 250 m land-water mask (Short Name: MOD44W) is an improvement over the existing MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted...

  5. Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

    2010-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

  6. Level 1 Processing of MODIS Direct Broadcast Data From Terra

    Science.gov (United States)

    Lynnes, Christopher; Smith, Peter; Shotland, Larry; El-Ghazawi, Tarek; Zhu, Ming

    2000-01-01

    In February 2000, an effort was begun to adapt the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1 production software to process direct broadcast data. Three Level 1 algorithms have been adapted and packaged for release: Level 1A converts raw (level 0) data into Hierarchical Data Format (HDF), unpacking packets into scans; Geolocation computes geographic information for the data points in the Level 1A; and the Level 1B computes geolocated, calibrated radiances from the Level 1A and Geolocation products. One useful aspect of adapting the production software is the ability to incorporate enhancements contributed by the MODIS Science Team. We have therefore tried to limit changes to the software. However, in order to process the data immediately on receipt, we have taken advantage of a branch in the geolocation software that reads orbit and altitude information from the packets themselves, rather than external ancillary files used in standard production. We have also verified that the algorithms can be run with smaller time increments (2.5 minutes) than the five-minute increments used in production. To make the code easier to build and run, we have simplified directories and build scripts. Also, dependencies on a commercial numerics library have been replaced by public domain software. A version of the adapted code has been released for Silicon Graphics machines running lrix. Perhaps owing to its origin in production, the software is rather CPU-intensive. Consequently, a port to Linux is underway, followed by a version to run on PC clusters, with an eventual goal of running in near-real-time (i.e., process a ten-minute pass in ten minutes).

  7. Monitoring cropland evapotranspiration using MODIS products in Southern Brazil

    Science.gov (United States)

    Ruhoff, Anderson; Aparecida Moreira, Adriana; de Arruda Souza, Vanessa; Roberti, Debora Regina

    2017-04-01

    Evapotranspiration (ET), including water loss from plant transpiration and land evaporation, is of vital importance for understanding hydrological processes and climate dynamics. In this context, remote sensing is considered as the most important tool for estimate ET over large areas. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers an interesting opportunity to evaluate ET with spatial resolution of 1 km. The MODIS global evapotranspiration algorithm (MOD16) considers both surface energy fluxes and climatic constraints on ET (water or temperature stress) to estimate plant transpiration and soil evaporation based on Penman-Monteith equation. The algorithm is driven by remotely sensed and reanalysis meteorological data. In this study, MOD16 algorithm was applied to the State of Rio Grande do Sul (in Southern Brazil) to analyse cropland and natural vegetation evapotranspiration and its impacts during drought events. We validated MOD16 estimations using eddy correlation measurements and water balance closure at monthly and annual time scales. We used observed discharge data from three large rivers in Southern Brazil (Jacuí, Taquari and Ibicuí), precipitation data from TRMM Multi-satellite Precipitation Analysis (3B43 version 7) and terrestrial water storage estimations from the Gravity Recovery and climate Experiment (GRACE). MOD16 algorithm detected evapotranspiration in different land use and land cover conditions. In cropland areas, the average evapotranspiration was 705 mm/y, while in pasture/grassland was 750 mm/y and in forest areas was 1099 mm/y. Compared to the annual water balance, evapotranspiration was underestimated, with mean relative errors between 8 and 30% and coefficients of correlation between 0.42 to 0.53. The water storage change (dS/dt) computed from the water balance closure at monthly time scales showed a significant correlation with the terrestrial water storage obtained from GRACE data, with a coefficient of correlation of 0

  8. Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

    Science.gov (United States)

    Sobrino, Jose Antonio; Franch, B.; Oltra-Carrio, R.; Vermote, E. F.; Fedele, E.

    2013-01-01

    In this article, the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF)/Albedo product (MCD43) is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction (EODIX) project campaign, which was developed in Barrax (Spain) in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal (RTLSR) (which corresponds to the MODIS BRDF algorithm) and the RossThick-Maignan-LiSparse-Reciprocal (RTLSR-HS), were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor. During the campaign, airborne images were retrieved with different view zenith angles along the principal and orthogonal planes. Comparing the results of applying the models to the airborne data with ground measurements, we obtained a root mean square error (RMSE) of 0.018 with both RTLSR and RTLSR-HS models. The evaluation of the MODIS BRDF/Albedo product (MCD43) was performed by comparing satellite images with AHS estimations. The results reported an RMSE of 0.04 with both models. Additionally, taking advantage of a homogeneous barley pixel, we compared in situ albedo data to satellite albedo data. In this case, the MODIS albedo estimation was (0.210 +/- 0.003), while the in situ measurement was (0.204 +/- 0.003). This result shows good agreement in regard to a homogeneous pixel.

  9. Consistency of two global MODIS aerosol products over ocean on Terra and Aqua CERES SSF datasets

    Science.gov (United States)

    Ignatov, Alexander; Minnis, Patrick; Wielicki, Bruce; Loeb, Norman G.; Remer, Lorraine A.; Kaufman, Yoram J.; Miller, Walter F.; Sun-Mack, Sunny; Laszlo, Istvan; Geier, Erika B.

    2004-12-01

    MODIS aerosol retrievals over ocean from Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side by side. The primary M product is generated by subsetting and remapping the multi-spectral (0.44 - 2.1 μm) MOD04 aerosols onto CERES footprints. MOD04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary (AVHRR-like) A product is generated in only two MODIS bands: 1 and 6 on Terra, and ` and 7 on Aqua. The A processing uses NASA/LaRC cloud-screening and NOAA/NESDIS single channel aerosol algorthm. The M and A products have been documented elsewhere and preliminarily compared using two weeks of global Terra CERES SSF (Edition 1A) data in December 2000 and June 2001. In this study, the M and A aerosol optical depths (AOD) in MODIS band 1 and (0.64 μm), τ1M and τ1A, are further checked for cross-platform consistency using 9 days of global Terra CERES SSF (Edition 2A) and Aqua CERES SSF (Edition 1A) data from 13 - 21 October 2002.

  10. The Normalization of Surface Anisotropy Effects Present in SEVIRI Reflectances by Using the MODIS BRDF Method

    Science.gov (United States)

    Proud, Simon Richard; Zhang, Qingling; Schaaf, Crystal; Fensholt, Rasmus; Rasmussen, Mads Olander; Shisanya, Chris; Mutero, Wycliffe; Mbow, Cheikh; Anyamba, Assaf; Pak, Ed; hide

    2014-01-01

    A modified version of the MODerate resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) algorithm is presented for use in the angular normalization of surface reflectance data gathered by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellites. We present early and provisional daily nadir BRDFadjusted reflectance (NBAR) data in the visible and near-infrared MSG channels. These utilize the high temporal resolution of MSG to produce BRDF retrievals with a greatly reduced acquisition period than the comparable MODIS products while, at the same time, removing many of the angular perturbations present within the original MSG data. The NBAR data are validated against reflectance data from the MODIS instrument and in situ data gathered at a field location in Africa throughout 2008. It is found that the MSG retrievals are stable and are of high-quality across much of the SEVIRI disk while maintaining a higher temporal resolution than the MODIS BRDF products. However, a number of circumstances are discovered whereby the BRDF model is unable to function correctly with the SEVIRI observations-primarily because of an insufficient spread of angular data due to the fixed sensor location or localized cloud contamination.

  11. Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

    Science.gov (United States)

    Levitan, Nathaniel; Gross, Barry

    2016-10-01

    New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

  12. Mapping Crop Cycles in China Using MODIS-EVI Time Series

    Directory of Open Access Journals (Sweden)

    Le Li

    2014-03-01

    Full Text Available As the Earth’s population continues to grow and demand for food increases, the need for improved and timely information related to the properties and dynamics of global agricultural systems is becoming increasingly important. Global land cover maps derived from satellite data provide indispensable information regarding the geographic distribution and areal extent of global croplands. However, land use information, such as cropping intensity (defined here as the number of cropping cycles per year, is not routinely available over large areas because mapping this information from remote sensing is challenging. In this study, we present a simple but efficient algorithm for automated mapping of cropping intensity based on data from NASA’s (NASA: The National Aeronautics and Space Administration MODerate Resolution Imaging Spectroradiometer (MODIS. The proposed algorithm first applies an adaptive Savitzky-Golay filter to smooth Enhanced Vegetation Index (EVI time series derived from MODIS surface reflectance data. It then uses an iterative moving-window methodology to identify cropping cycles from the smoothed EVI time series. Comparison of results from our algorithm with national survey data at both the provincial and prefectural level in China show that the algorithm provides estimates of gross sown area that agree well with inventory data. Accuracy assessment comparing visually interpreted time series with algorithm results for a random sample of agricultural areas in China indicates an overall accuracy of 91.0% for three classes defined based on the number of cycles observed in EVI time series. The algorithm therefore appears to provide a straightforward and efficient method for mapping cropping intensity from MODIS time series data.

  13. The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua

    Science.gov (United States)

    Platnick, Steven; Meyer, Kerry G.; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas; Zhang, Zhibo; Hubanks, Paul A.; Holz, Robert E.; Yang, Ping; Ridgway, William L.; Riedi, Jérôme

    2018-01-01

    The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases–daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes collectively can result in significant changes relative to C5, though the magnitude depends on the dataset and the pixel’s retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud optical property datasets, other MODIS cloud datasets are discussed when relevant. PMID:29657349

  14. Snow Cover Maps from MODIS Images at 250 m Resolution, Part 2: Validation

    Directory of Open Access Journals (Sweden)

    Marc Zebisch

    2013-03-01

    Full Text Available The performance of a new algorithm for binary snow cover monitoring based on Moderate Resolution Imaging Spectroradiometer (MODIS satellite images at 250 m resolution is validated using snow cover maps (SCA based on Landsat 7 ETM+ images and in situ snow depth measurements from ground stations in selected test sites in Central Europe. The advantages of the proposed algorithm are the improved ground resolution of 250 m and the near real-time availability with respect to the 500 m standard National Aeronautics and Space Administration (NASA MODIS snow products (MOD10 and MYD10. It allows a more accurate snow cover monitoring at a local scale, especially in mountainous areas characterized by large landscape heterogeneity. The near real-time delivery makes the product valuable as input for hydrological models, e.g., for flood forecast. A comparison to sixteen snow cover maps derived from Landsat ETM/ETM+ showed an overall accuracy of 88.1%, which increases to 93.6% in areas outside of forests. A comparison of the SCA derived from the proposed algorithm with standard MODIS products, MYD10 and MOD10, indicates an agreement of around 85.4% with major discrepancies in forested areas. The validation of MODIS snow cover maps with 148 in situ snow depth measurements shows an accuracy ranging from 94% to around 82%, where the lowest accuracies is found in very rugged terrain restricted to in situ stations along north facing slopes, which lie in shadow in winter during the early morning acquisition.

  15. A Technique For Remote Sensing Of Suspended Sediments And Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

    Science.gov (United States)

    Li, R.; Kaufman, Y.

    2002-12-01

    ABSTRACT We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 æm that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

  16. eMODIS: A User-Friendly Data Source

    Science.gov (United States)

    Jenkerson, Calli B.; Maiersperger, Thomas; Schmidt, Gail

    2010-01-01

    The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'eMODIS' based on Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), MODIS is well suited for vegetation studies. For operational monitoring, however, the benefits of MODIS are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. eMODIS responds to a community-specific need for alternatively packaged MODIS data, addressing each of these factors for real-time monitoring and historical trend analysis. eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS MODIS Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. eMODIS is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. eMODIS composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see eMODIS Product Description below). For eMODIS products generated over the continental United States (eMODIS CONUS), the Terra (from 2000) and Aqua (from 2002) records are available and continue through present time. eMODIS CONUS also is generated in an expedited process that delivers a 7-day rolling composite

  17. Prevalence of Retinopathy in Adult Patients with GCK-MODY and HNF1A-MODY.

    Science.gov (United States)

    Szopa, M; Wolkow, J; Matejko, B; Skupien, J; Klupa, T; Wybrańska, I; Trznadel-Morawska, I; Kiec-Wilk, B; Borowiec, M; Malecki, M T

    2015-10-01

    We aimed to assess the prevalence of diabetic retinopathy (DR) in adult patients with GCK-MODY and HNF1A-MODY in Poland and to identify biochemical and clinical risk factors associated with its occurrence.We examined 74 GCK mutation carriers, 51 with diabetes and 23 with prediabetes, respectively, and 63 patients with HNF1A-MODY. Retinal photographs, 12 for each patient, were done by a fundus camera. Signs of DR were graded according to the DR disease severity scale. Statistical tests were performed to assess differences between the groups and logistic regression was done for the association with DR.The mean age at examination was 34.5±14.8 and 39.9±15.2 in the GCK-MODY and HNF1A-MODY groups, respectively. Mild nonproliferative DR (NPDR) was found in one patient with the GCK mutation and likely concomitant type 1 diabetes, whereas DR was diagnosed in 15 HNF1A-MODY patients: 9 with proliferative, 3 with moderate NPDR and 2 with mild NPDR. In univariate logistic regression analysis in the HNF1A-MODY group, significant results were found for diabetes duration, fasting glycemia, HbA1c, arterial hypertension, age at the examination, and eGFR. The strongest independent predictors of DR in HNF1A-MODY were markers of glucose control: HbA1c (OR: 2.05, CL%95: 1.2-3.83, p=0.01) and glucose (p=0.006, OR: 1.40, CL%95: 1.12-1.83) analyzed in 2 separated models. Additionally, arterial hypertension independently predicted DR (OR: 9.06, CL%95: 1.19-98.99, p=0.04) in the model with HbA1c as glycaemic control marker.In conclusion, DR of any degree was not present in our GCK-MODY group, while in spite of young age almost every fourth subject with HNF1A-MODY showed signs of this complication. © Georg Thieme Verlag KG Stuttgart · New York.

  18. Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

    Science.gov (United States)

    Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier

    2011-01-01

    The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.

  19. Implementation of electronic crosstalk correction for terra MODIS PV LWIR bands

    Science.gov (United States)

    Geng, Xu; Madhavan, Sriharsha; Chen, Na; Xiong, Xiaoxiong

    2015-09-01

    The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the fleet of NASA's Earth Observing Systems (EOS) in space. Terra MODIS has completed 15 years of operation far exceeding its design lifetime of 6 years. The MODIS Level 1B (L1B) processing is the first in the process chain for deriving various higher level science products. These products are used mainly in understanding the geophysical changes occurring in the Earth's land, ocean, and atmosphere. The L1B code is designed to carefully calibrate the responses of all the detectors of the 36 spectral bands of MODIS and provide accurate L1B radiances (also reflectances in the case of Reflective Solar Bands). To fulfill this purpose, Look Up Tables (LUTs), that contain calibration coefficients derived from both on-board calibrators and Earth-view characterized responses, are used in the L1B processing. In this paper, we present the implementation mechanism of the electronic crosstalk correction in the Photo Voltaic (PV) Long Wave InfraRed (LWIR) bands (Bands 27-30). The crosstalk correction involves two vital components. First, a crosstalk correction modular is implemented in the L1B code to correct the on-board Blackbody and Earth-View (EV) digital number (dn) responses using a linear correction model. Second, the correction coefficients, derived from the EV observations, are supplied in the form of LUTs. Further, the LUTs contain time stamps reflecting to the change in the coefficients assessed using the Noise Equivalent difference Temperature (NEdT) trending. With the algorithms applied in the MODIS L1B processing it is demonstrated that these corrections indeed restore the radiometric balance for each of the affected bands and substantially reduce the striping noise in the processed images.

  20. Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

    Science.gov (United States)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

    2015-01-01

    The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

  1. MODIS snow cover mapping accuracy in a small mountain catchment – comparison between open and forest sites

    Directory of Open Access Journals (Sweden)

    G. Blöschl

    2012-07-01

    Full Text Available Numerous global and regional validation studies have examined MODIS snow mapping accuracy by using measurements at climate stations, which are mainly at open sites. MODIS accuracy in alpine and forested regions is, however, still not well understood. The main objective of this study is to evaluate MODIS (MOD10A1 and MYD10A1 snow cover products in a small experimental catchment by using extensive snow course measurements at open and forest sites. The MODIS accuracy is tested in the Jalovecky creek catchment (northern Slovakia in the period 2000–2011. The results show that the combined Terra and Aqua images enable snow mapping at an overall accuracy of 91.5%. The accuracies at forested, open and mixed land uses at the Červenec sites are 92.7%, 98.3% and 81.8%, respectively. The use of a 2-day temporal filter enables a significant reduction in the number of days with cloud coverage and an increase in overall snow mapping accuracy. In total, the 2-day temporal filter decreases the number of cloudy days from 61% to 26% and increases the snow mapping accuracy to 94%. The results indicate three possible factors leading to misclassification of snow as land: patchy snow cover, limited MODIS geolocation accuracy and mapping algorithm errors. Out of a total of 27 misclassification cases, patchy snow cover, geolocation issues and mapping errors occur in 12, 12 and 3 cases, respectively.

  2. Analysis, improvement and application of the MODIS leaf area index products

    Science.gov (United States)

    Yang, Wenze

    Green leaf area governs the exchanges of energy, mass and momentum between the Earth's surface and the atmosphere. Therefore, leaf area index (LAI) and fraction of incident photosynthetically active radiation (0.4-0.7 mum) absorbed by the vegetation canopy (FPAR) are widely used in vegetation monitoring and modeling. The launch of Terra and Aqua satellites with the moderate resolution imaging spectroradiometer (MODIS) instrument onboard provided the first global products of LAI and FPAR, derived mainly from an algorithm based on radiative transfer. The objective of this research is to comprehensively evaluate the Terra and Aqua MODIS LAI/FPAR products. Large volumes of these products have been analyzed with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus back-up), snow (snow-free versus snow on the ground) and cloud (cloud-free versus cloudy) conditions. Field validation efforts identified several key factors that influence the accuracy of algorithm retrievals. The strategy of validation efforts guiding algorithm refinements has led to progressively more accurate LAI/FPAR products. The combination of products derived from the Terra and Aqua MODIS sensors increases the success rate of the main radiative transfer algorithm by 10-20 percent over woody vegetation. The Terra Collection 4 LAI data reveal seasonal swings in green leaf area of about 25 percent in a majority of the Amazon rainforests caused by variability in cloud cover and light. The timing and the influence of this seasonal cycle are critical to understanding tropical plant adaptation patterns and ecological processes. The results presented in this dissertation suggest how the product quality has gradually improved largely through the efforts of validation activities. The Amazon case study highlights the utility of these data sets for monitoring global vegetation dynamics. Thus, these results can be seen as a benchmark for evaluation of

  3. Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Roman, Miguel O.

    2017-01-01

    Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data

  4. Preliminary results of algorithms to determine horizontal and vertical underwater visibilities of coastal waters

    Digital Repository Service at National Institute of Oceanography (India)

    Suresh, T.; Joshi, Shreya; Talaulikar, M.; Desa, E.J.

    the underwater average cosine. These algorithms for vertical and horizontal visibilities have been validated for the coastal waters of Goa with the measured and those derived from the ocean color data of OCM-2 and MODIS...

  5. Mapping the Distribution of Cloud Forests Using MODIS Imagery

    Science.gov (United States)

    Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.

    2007-05-01

    Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in satellite imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using MODIS Terra and Aqua visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more reflective clouds to separate clouds from the underlying background. A major advantage of MODIS imagery over many other sources of satellite imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from satellite and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of MODIS imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable

  6. Response to Toward Unified Satellite Climatology of Aerosol Properties. 3; MODIS versus MISR versus AERONET

    Science.gov (United States)

    Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didler

    2010-01-01

    A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD), and gives a much less favorable impression of the utility of the satellite products than that presented by the instrument teams and other groups. We trace the reasons for the differing pictures to whether known and previously documented limitations of the products are taken into account in the assessments. Specifically, the analysis approaches differ primarily in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account. Mishchenko et al. also do not distinguish between observational sampling differences and retrieval algorithm error. We assess the implications of the different analysis approaches, and cite examples demonstrating how the MISR and MODIS aerosol products have been applied successfully to a range of scientific investigations.

  7. Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

    Science.gov (United States)

    Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

    2006-01-01

    A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

  8. Maturity-onset diabetes of the young (MODY): an update.

    Science.gov (United States)

    Anık, Ahmet; Çatlı, Gönül; Abacı, Ayhan; Böber, Ece

    2015-03-01

    Maturity-onset diabetes of the young (MODY) is a group of monogenic disorders characterized by autosomal dominantly inherited non-insulin dependent form of diabetes classically presenting in adolescence or young adults before the age of 25 years. MODY is a rare cause of diabetes (1% of all cases) and is frequently misdiagnosed as Type 1 diabetes (T1DM) or Type 2 diabetes (T2DM). A precise molecular diagnosis is essential because it leads to optimal treatment of the patients and allows early diagnosis for their asymptomatic family members. Mutations in the glucokinase (GCK) (MODY 2) and hepatocyte nuclear factor (HNF)1A/4A (MODY 3 and MODY 1) genes are the most common causes of MODY. GCK mutations cause a mild, asymptomatic, and stable fasting hyperglycemia usually requiring no specific treatment. However, mutations in the HNF1A and HNF4A cause a progressive pancreatic β-cell dysfunction and hyperglycemia that can result in microvascular complications. Sulfonylureas are effective in these patients by acting on adenosine triphosphate (ATP)-sensitive potassium channels, although insulin therapy may be required later in life. Mutations in the HNF1B (MODY 5) is associated with pancreatic agenesis, renal abnormalities, genital tract malformations, and liver dysfunction. Compared to MODY 1, 2, 3, and 5, the remaining subtypes of MODY have a much lower prevalence. In this review, we summarize the main clinical and laboratory characteristics of the common and rarer causes of MODY.

  9. When is it MODY? Challenges in the Interpretation of Sequence Variants in MODY Genes

    Science.gov (United States)

    Althari, Sara; Gloyn, Anna L.

    2015-01-01

    The genomics revolution has raised more questions than it has provided answers. Big data from large population-scale resequencing studies are increasingly deconstructing classic notions of Mendelian disease genetics, which support a simplistic correlation between mutational severity and phenotypic outcome. The boundaries are being blurred as the body of evidence showing monogenic disease-causing alleles in healthy genomes, and in the genomes of individu-als with increased common complex disease risk, continues to grow. In this review, we focus on the newly emerging challenges which pertain to the interpretation of sequence variants in genes implicated in the pathogenesis of maturity-onset diabetes of the young (MODY), a presumed mono-genic form of diabetes characterized by Mendelian inheritance. These challenges highlight the complexities surrounding the assignments of pathogenicity, in particular to rare protein-alerting variants, and bring to the forefront some profound clinical diagnostic implications. As MODY is both genetically and clinically heterogeneous, an accurate molecular diagnosis and cautious extrapolation of sequence data are critical to effective disease management and treatment. The biological and translational value of sequence information can only be attained by adopting a multitude of confirmatory analyses, which interrogate variant implication in disease from every possible angle. Indeed, studies which have effectively detected rare damaging variants in known MODY genes in normoglycemic individuals question the existence of a sin-gle gene mutation scenario: does monogenic diabetes exist when the genetic culprits of MODY have been systematical-ly identified in individuals without MODY? PMID:27111119

  10. MODIS NDVI Response Following Fires in Siberia

    Science.gov (United States)

    Ranson, K. Jon; Sun, G.; Kovacs, K.; Kharuk, V. I.

    2003-01-01

    The Siberian boreal forest is considered a carbon sink but may become an important source of carbon dioxide if climatic warming predictions are correct. The forest is continually changing through various disturbance mechanisms such as insects, logging, mineral exploitation, and especially fires. Patterns of disturbance and forest recovery processes are important factors regulating carbon flux in this area. NASA's Terra MODIS provides useful information for assessing location of fires and post fire changes in forests. MODIS fire (MOD14), and NDVI (MOD13) products were used to examine fire occurrence and post fire variability in vegetation cover as indicated by NDVI. Results were interpreted for various post fire outcomes, such as decreased NDVI after fire, no change in NDVI after fire and positive NDVI change after fire. The fire frequency data were also evaluated in terms of proximity to population centers, and transportation networks.

  11. Genetic counseling in monogenic diabetes GCK MODY.

    Science.gov (United States)

    Skała-Zamorowska, Eliza; Deja, Grażyna; Borowiec, Maciej; Fendler, Wojciech; Małachowska, Beata; Kamińska, Halla; Młynarski, Wojciech; Jarosz-Chobot, Przemysława

    2016-01-01

    Genetic testing in families with monogenic GCK MODY has predictive, diagnostic, and preventive utility. Predictive tests relate to people who have no features of the disorder themselves at the time of testing. Diagnostic tests relate to family members who have been previously diagnosed with diabetes mellitus or glucose metabolism disturbances. The preventive value of genetic testing for families is to raise awareness of the circumstances leading to glucose metabolism disorders. The detection of mutation carriers among family members of patients with GCK MODY and the determination of the clinical significance of the genetic test result. The study group included 27 families of adolescent patients with GCK MODY (39 (75%) of parents and 19 (73.08%) of siblings) monitored in the Department of Pediatrics, Endocrinology and Diabetes and in the Diabetes Clinic of John Paul II Upper Silesian Child Health Centre in Katowice in the years 2007-2012. Subjects underwent a blood sample drawing for genetic and biochemical testing. Through the genetic diagnostics we diagnosed GCK MODY in 14 (63.64%) mothers, 6 (35.29%) fathers and in 7 (36,84%) siblings. Genetic testing has contributed to the detection of 7 (26.92%) asymptomatic carriers of GCK gene mutation among parents and 3 (15,79%) asymptomatic carriers among siblings declaring no carbohydrate metabolism disturbances (before genetic testing there were no indications suggesting carbohydrate metabolism disturbances; OGTT were performed after positive genetic testing). Each case of mutation detection, which is the cause of monogenic diabetes in a patient, justifies the genetic testing in other members of his/her family. Awareness of the genetic status may allow sick family member to confirm the diagnosis, while asymptomatic mutation carriers could benefit from an early clinical observation. Consequently, in each case it gives an opportunity to take diagnostic and therapeutic measures in accordance with the current state of

  12. Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

    Science.gov (United States)

    Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

    2011-12-01

    Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

  13. Using VIIRS/NPP and MODIS/Aqua data to provide a continuous record of suspended particulate matter in a highly turbid inland lake

    Science.gov (United States)

    Cao, Zhigang; Duan, Hongtao; Shen, Ming; Ma, Ronghua; Xue, Kun; Liu, Dong; Xiao, Qitao

    2018-02-01

    Inland lakes are generally an important source of drinking water, and information on their water quality needs to be obtained in real time. To date, Moderate-resolution imaging spectroradiometer (MODIS) data have played a critical, effective and long-term role in fulfilling this function. However, the MODIS instruments on board both the Terra and Aqua satellites have operated beyond their designed five-year mission lifespans (Terra was launched in 1999, whereas Aqua was launched in 2002), and these instruments may stop running at any time in the near future. The Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-Orbiting Partnership (Suomi NPP, which was launched in Oct 2011) is expected to provide a consistent, long-term data record and continue the series of observations initiated by MODIS. To date, few evaluations of the consistency between VIIRS and MODIS have been conducted for turbid inland waters. In this study, we first used synchronous MODIS/Aqua and VIIRS/NPP data (±1 h) collected during 2012-2015 to evaluate the consistency of Rayleigh-corrected reflectance (Rrc) observations over Lake Hongze (the fourth-largest freshwater lake in China), since accurate remote sensing reflectance (Rrs) values cannot be acquired over turbid inland waters. Second, we used recently developed algorithms based on Rrc in the red band to estimate the concentrations of suspended particulate matter (SPM) from MODIS/Aqua and VIIRS/NPP data. Finally, we assessed the consistency of the SPM products derived from MODIS/Aqua and VIIRS/NPP. The results show the following. (1) The differences in Rrc among the green (VIIRS 551 nm and MODIS 555 nm) and red bands (VIIRS 671 nm and MODIS 645 nm) indicate a satisfactory consistency, and the unbiased percentage difference (UPD) is MODIS 859 nm and VIIRS 862 nm) indicate relatively large differences (UPD = 21.84%). (2) The satellite-derived SPM products obtained using MODIS/Aqua and VIIRS/NPP have a satisfactory

  14. Spatial scales of pollution from variable resolution satellite imaging

    International Nuclear Information System (INIS)

    Chudnovsky, Alexandra A.; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM 2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM 2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM 2.5 levels and wind speed. - Highlights: ► The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM 2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM 2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM 2.5 variability at the intra-urban scale.

  15. Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network

    Directory of Open Access Journals (Sweden)

    A. Rösel

    2012-04-01

    Full Text Available Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like the Moderate Resolution Image Spectroradiometer (MODIS using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron to reduce computational costs.

    Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 MODIS surface reflectance product. The validation of the MODIS melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with coefficient of determination ranging from R2=0.28 to R2=0.45. The mean annual cycle of the melt pond fraction per grid cell for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds on the geographical latitude, and has its maximum in mid-July at latitudes between 80° and 88° N.

    Furthermore, the MODIS results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ARTIST Sea Ice-, NASA Team 2-, and Bootstrap-algorithms with MODIS sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave

  16. Analysis of Extracting Prior BRDF from MODIS BRDF Data

    OpenAIRE

    Hu Zhang; Ziti Jiao; Yadong Dong; Peng Du; Yang Li; Yi Lian; Tiejun Cui

    2016-01-01

    Many previous studies have attempted to extract prior reflectance anisotropy knowledge from the historical MODIS Bidirectional Reflectance Distribution Function (BRDF) product based on land cover or Normalized Difference Vegetation Index (NDVI) data. In this study, the feasibility of the method is discussed based on MODIS data and archetypal BRDFs. The BRDF is simplified into six archetypal BRDFs that represent different reflectance anisotropies. Five-year time series of MODIS BRDF data over ...

  17. Unmanned aerial system nadir reflectance and MODIS nadir BRDF-adjusted surface reflectances intercompared over Greenland

    Directory of Open Access Journals (Sweden)

    J. F. Burkhart

    2017-07-01

    Full Text Available Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS bidirectional reflectance distribution function (BRDF/albedo (MCD43 algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS. The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300–920 nm with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.

  18. Variability of particulate organic carbon in inland waters observed from MODIS Aqua imagery

    International Nuclear Information System (INIS)

    Duan, Hongtao; Ma, Ronghua; Zhang, Yuchao; Feng, Lian; Arthur Loiselle, Steven

    2014-01-01

    Surface concentrations of particulate organic carbon (POC) in shallow inland lakes were estimated using MODIS Aqua data. A power regression model of the direct empirical relationship between POC and the atmospherically Rayleigh-corrected MODIS product (R rc,645 -R rc,1240 )/(R rc,859 -R rc,1240 ) was developed (R 2  = 0.72, RMSE = 35.86 μgL −1 , p < 0.0001, N = 47) and validated (RMSE = 44.46 μgL −1 , N = 16) with field data from 56 lakes in the Middle and Lower reaches of the Yangtze River, China. This algorithm was applied to an 11 year series of MODIS data to determine the spatial and temporal distribution of POC in a wide range of lakes with different trophic and optical properties. The results indicate that there is a general increase in minimum POC concentrations in lakes from middle to lower reaches of the Yangtze River. The temporal dynamics of springtime POC in smaller lakes were found to be influenced by local meteorological conditions, in particular precipitation and wind speed, while larger lakes were found to be more sensitive to air temperature. (letter)

  19. Fusion of MODIS and landsat-8 surface temperature images: a new approach.

    Science.gov (United States)

    Hazaymeh, Khaled; Hassan, Quazi K

    2015-01-01

    Here, our objective was to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS); and implement the developed algorithm over a heterogeneous semi-arid study area in Jordan, Middle East. The STI-FM technique consisted of two major components: (i) establishing a linear relationship between two consecutive MODIS 8-day composite LST images acquired at time 1 and time 2; and (ii) utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat-8 LST image at time 2. It revealed that strong linear relationships (i.e., r2, slopes, and intercepts were in the range 0.93-0.94, 0.94-0.99; and 2.97-20.07) existed between the two consecutive MODIS LST images. We evaluated the synthetic LST images qualitatively and found high visual agreements with the actual Landsat-8 LST images. In addition, we conducted quantitative evaluations of these synthetic images; and found strong agreements with the actual Landsat-8 LST images. For example, r2, root mean square error (RMSE), and absolute average difference (AAD)-values were in the ranges 084-0.90, 0.061-0.080, and 0.003-0.004, respectively.

  20. Anopheles atroparvus density modeling using MODIS NDVI in a former malarious area in Portugal.

    Science.gov (United States)

    Lourenço, Pedro M; Sousa, Carla A; Seixas, Júlia; Lopes, Pedro; Novo, Maria T; Almeida, A Paulo G

    2011-12-01

    Malaria is dependent on environmental factors and considered as potentially re-emerging in temperate regions. Remote sensing data have been used successfully for monitoring environmental conditions that influence the patterns of such arthropod vector-borne diseases. Anopheles atroparvus density data were collected from 2002 to 2005, on a bimonthly basis, at three sites in a former malarial area in Southern Portugal. The development of the Remote Vector Model (RVM) was based upon two main variables: temperature and the Normalized Differential Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite. Temperature influences the mosquito life cycle and affects its intra-annual prevalence, and MODIS NDVI was used as a proxy for suitable habitat conditions. Mosquito data were used for calibration and validation of the model. For areas with high mosquito density, the model validation demonstrated a Pearson correlation of 0.68 (pNDVI. RVM is a satellite data-based assimilation algorithm that uses temperature fields to predict the intra- and inter-annual densities of this mosquito species using MODIS NDVI. RVM is a relevant tool for vector density estimation, contributing to the risk assessment of transmission of mosquito-borne diseases and can be part of the early warning system and contingency plans providing support to the decision making process of relevant authorities. © 2011 The Society for Vector Ecology.

  1. Global dust sources detection using MODIS Deep Blue Collection 6 aerosol products

    Science.gov (United States)

    Pérez García-Pando, C.; Ginoux, P. A.

    2015-12-01

    Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Remote sensing sensors are the most useful tool to locate dust sources. These sensors include microwaves, visible channels, and lidar. On the global scale, major dust source regions have been identified using polar orbiting satellite instruments. The MODIS Deep Blue algorithm has been particularly useful to detect small-scale sources such as floodplains, alluvial fans, rivers, and wadis , as well as to identify anthropogenic sources from agriculture. The recent release of Collection 6 MODIS aerosol products allows to extend dust source detection to the entire land surfaces, which is quite useful to identify mid to high latitude dust sources and detect not only dust from agriculture but fugitive dust from transport and industrial activities. This presentation will overview the advantages and drawbacks of using MODIS Deep Blue for dust detection, compare to other instruments (polar orbiting and geostationary). The results of Collection 6 with a new dust screening will be compared against AERONET. Applications to long range transport of anthropogenic dust will be presented.

  2. Improved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF

    Directory of Open Access Journals (Sweden)

    Yanli Zhang

    2015-05-01

    Full Text Available In rugged terrain, the accuracy of surface reflectance estimations is compromised by atmospheric and topographic effects. We propose a new method to simultaneously eliminate atmospheric and terrain effects in Landsat Thematic Mapper (TM images based on a 30 m digital elevation model (DEM and Moderate Resolution Imaging Spectroradiometer (MODIS atmospheric products. Moreover, we define a normalized factor of a Bidirectional Reflectance Distribution Function (BRDF to convert the sloping pixel reflectance into a flat pixel reflectance by using the Ross Thick-Li Sparse BRDF model (Ambrals algorithm and MODIS BRDF/albedo kernel coefficient products. Sole atmospheric correction and topographic normalization were performed for TM images in the upper stream of the Heihe River Basin. The results show that using MODIS atmospheric products can effectively remove atmospheric effects compared with the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH model and the Landsat Climate Data Record (CDR. Moreover, superior topographic effect removal can be achieved by considering the surface BRDF when compared with the surface Lambertian assumption of topographic normalization.

  3. Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods

    Science.gov (United States)

    Zhuosen Wang; Crystal B. Schaaf; Alan H. Strahler; Mark J. Chopping; Miguel O. Román; Yanmin Shuai; Curtis E. Woodcock; David Y. Hollinger; David R. Fitzjarrald

    2014-01-01

    This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and...

  4. The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

    Science.gov (United States)

    Wu, Yerong; de Graaf, Martin; Menenti, Massimo

    2017-08-01

    Global quantitative aerosol information has been derived from MODerate Resolution Imaging SpectroRadiometer (MODIS) observations for decades since early 2000 and widely used for air quality and climate change research. However, the operational MODIS Aerosol Optical Depth (AOD) products Collection 6 (C6) can still be biased, because of uncertainty in assumed aerosol optical properties and aerosol vertical distribution. This study investigates the impact of aerosol vertical distribution on the AOD retrieval. We developed a new algorithm by considering dynamic vertical profiles, which is an adaptation of MODIS C6 Dark Target (C6_DT) algorithm over land. The new algorithm makes use of the aerosol vertical profile extracted from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements to generate an accurate top of the atmosphere (TOA) reflectance for the AOD retrieval, where the profile is assumed to be a single layer and represented as a Gaussian function with the mean height as single variable. To test the impact, a comparison was made between MODIS DT and Aerosol Robotic Network (AERONET) AOD, over dust and smoke regions. The results show that the aerosol vertical distribution has a strong impact on the AOD retrieval. The assumed aerosol layers close to the ground can negatively bias the retrievals in C6_DT. Regarding the evaluated smoke and dust layers, the new algorithm can improve the retrieval by reducing the negative biases by 3-5%.

  5. Exome sequencing and genetic testing for MODY.

    Directory of Open Access Journals (Sweden)

    Stefan Johansson

    Full Text Available Genetic testing for monogenic diabetes is important for patient care. Given the extensive genetic and clinical heterogeneity of diabetes, exome sequencing might provide additional diagnostic potential when standard Sanger sequencing-based diagnostics is inconclusive.The aim of the study was to examine the performance of exome sequencing for a molecular diagnosis of MODY in patients who have undergone conventional diagnostic sequencing of candidate genes with negative results.We performed exome enrichment followed by high-throughput sequencing in nine patients with suspected MODY. They were Sanger sequencing-negative for mutations in the HNF1A, HNF4A, GCK, HNF1B and INS genes. We excluded common, non-coding and synonymous gene variants, and performed in-depth analysis on filtered sequence variants in a pre-defined set of 111 genes implicated in glucose metabolism.On average, we obtained 45 X median coverage of the entire targeted exome and found 199 rare coding variants per individual. We identified 0-4 rare non-synonymous and nonsense variants per individual in our a priori list of 111 candidate genes. Three of the variants were considered pathogenic (in ABCC8, HNF4A and PPARG, respectively, thus exome sequencing led to a genetic diagnosis in at least three of the nine patients. Approximately 91% of known heterozygous SNPs in the target exomes were detected, but we also found low coverage in some key diabetes genes using our current exome sequencing approach. Novel variants in the genes ARAP1, GLIS3, MADD, NOTCH2 and WFS1 need further investigation to reveal their possible role in diabetes.Our results demonstrate that exome sequencing can improve molecular diagnostics of MODY when used as a complement to Sanger sequencing. However, improvements will be needed, especially concerning coverage, before the full potential of exome sequencing can be realized.

  6. New Approach for Snow Cover Detection through Spectral Pattern Recognition with MODIS Data

    Directory of Open Access Journals (Sweden)

    Kyeong-Sang Lee

    2017-01-01

    Full Text Available Snow cover plays an important role in climate and hydrology, at both global and regional scales. Most previous studies have used static threshold techniques to detect snow cover, which can lead to errors such as misclassification of snow and clouds, because the reflectance of snow cover exhibits variability and is affected by several factors. Therefore, we present a simple new algorithm for mapping snow cover from Moderate Resolution Imaging Spectroradiometer (MODIS data using dynamic wavelength warping (DWW, which is based on dynamic time warping (DTW. DTW is a pattern recognition technique that is widely used in various fields such as human action recognition, anomaly detection, and clustering. Before performing DWW, we constructed 49 snow reflectance spectral libraries as reference data for various solar zenith angle and digital elevation model conditions using approximately 1.6 million sampled data. To verify the algorithm, we compared our results with the MODIS swath snow cover product (MOD10_L2. Producer’s accuracy, user’s accuracy, and overall accuracy values were 92.92%, 78.41%, and 92.24%, respectively, indicating good overall classification accuracy. The proposed algorithm is more useful for discriminating between snow cover and clouds than threshold techniques in some areas, such as those with a high viewing zenith angle.

  7. Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic.

    Science.gov (United States)

    Kampel, Milton; Lorenzzetti, João A; Bentz, Cristina M; Nunes, Raul A; Paranhos, Rodolfo; Rudorff, Frederico M; Politano, Alexandre T

    2009-01-01

    Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3M(RAD)), Ocean Chlorophyll 4 bands (OC4v4(RAD)), and Ocean Chlorophyll 2 bands (OC2v4(RAD)). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3M(SAT), and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01(SAT)), and Carder(SAT). In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m(3). In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m(3) (OC2v4(RAD)). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m(3)) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m(3), respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm

  8. Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

    Directory of Open Access Journals (Sweden)

    Cristina M. Bentz

    2009-01-01

    Full Text Available Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD, Ocean Chlorophyll 4 bands (OC4v4RAD, and Ocean Chlorophyll 2 bands (OC2v4RAD. The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT, and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg·m-3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD. The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3 than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively. We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed

  9. MODIS multi-temporal data retrieval and processing toolbox

    NARCIS (Netherlands)

    Mattiuzzi, M.; Verbesselt, J.; Klisch, A.

    2012-01-01

    The package functionalities are focused for the download and processing of multi-temporal datasets from MODIS sensors. All standard MODIS grid data can be accessed and processed by the package routines. The package is still in alpha development and not all the functionalities are available for now.

  10. MODIS Based Estimation of Forest Aboveground Biomass in China

    Science.gov (United States)

    Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha−1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y−1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y−1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y−1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests. PMID:26115195

  11. MODIS Based Estimation of Forest Aboveground Biomass in China.

    Science.gov (United States)

    Yin, Guodong; Zhang, Yuan; Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

  12. MODIS Based Estimation of Forest Aboveground Biomass in China.

    Directory of Open Access Journals (Sweden)

    Guodong Yin

    Full Text Available Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS dataset in a machine learning algorithm (the model tree ensemble, MTE. We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

  13. Maturity-onset diabetes of the young--MODY. Molekylaergenetiske, patofysiologiske og kliniske karakteristika

    DEFF Research Database (Denmark)

    Hansen, Torben; Urhammer, Søren A; Pedersen, Oluf Borbye

    2002-01-01

    Maturity-onset diabetes of the young (MODY) is a genetically and clinically heterogeneous subtype of type 2 diabetes characterised by an early onset, an autosomal dominant inheritance, and a primary defect in insulin secretion. MODY comprises 2-5% of cases of type 2 diabetes. So far, six MODY genes...... have been identified (MODY1-6): hepatocyte nuclear factor (HNF-4 alpha), glucokinase, HNF-1 alpha, HNF-1 beta, insulin promoter factor 1(IPF-1), and neurogenic differentiation factor 1 (NEUROD1). MODY2 and MODY3 are the most common forms of MODY. Mutations in glucokinase/MODY2 result in a mild form...... of diabetes. In contrast, MODY3 and some of the other MODY forms are characterised by major insulin secretory defects and severe hyperglycaemia associated with microvascular complications. About 25% of known MODY is caused by mutations in yet unknown genes and present results suggest that other monogenic...

  14. Towards a long-term chlorophyll-a data record in a turbid estuary using MODIS observations

    Science.gov (United States)

    Le, Chengfeng; Hu, Chuanmin; English, David; Cannizzaro, Jennifer; Chen, Zhiqiang; Feng, Lian; Boler, Richard; Kovach, Charles

    2013-02-01

    Despite recent advances in using satellite data for continuous monitoring of estuarine water quality parameters such as turbidity and water clarity, estimating chlorophyll-a concentrations (Chla) has remained problematic due to the optical complexity of estuarine waters and imperfect atmospheric correction. This poses a significant challenge to the community as synoptic and frequent Chla “measurements” from satellites are in high demand by various government agencies and environmental groups to help make management decisions. Here, using 10 years of in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from a moderately sized, turbid estuary, Tampa Bay (Florida, USA), we developed and validated a new algorithm specifically designed for retrieving Chla from MODIS data. The algorithm takes the red-to-green remote-sensing reflectance (Rrs(λ)) band ratio of [Rrs(667) + Rrs(678)]/[Rrs(531) + Rrs(547)] as the independent variable, and estimates Chla through the non-linear regression function: Ln(Chla) = 1.91Ln(x) + 3.40 (R2 = 0.87, N = 97, p < 0.01, 1.5 < Chla < 80 mg m-3) where ‘x' is the band ratio. Validation of the algorithm using two independent datasets collected by different groups and near-concurrent MODIS measurements showed robust algorithm performance for Chla within this range, with mean relative errors of 25.8% and 41.7% for the two datasets. Time-series analyses at representative stations using both in situ and MODIS Chla also showed general agreement, with instances of noticeable discrepancy attributed to different measurement frequencies. The algorithm was implemented to establish a 10-year Chla data record for Tampa Bay in order to serve as a baseline for monitoring future phytoplankton bloom events. The 10-year Chla data record showed substantial variability in both space and time, with generally higher Chla observed during the wet season and in upper bay segments, and Chla minima observed in all bay segments during May

  15. Radiative effects of global MODIS cloud regimes

    Science.gov (United States)

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji

    2018-01-01

    We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations. PMID:29619289

  16. Surface spectral emissivity derived from MODIS data

    Science.gov (United States)

    Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

    2003-04-01

    Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

  17. Radiative Effects of Global MODIS Cloud Regimes

    Science.gov (United States)

    Oraiopoulos, Lazaros; Cho, Nayeong; Lee, Dong Min; Kato, Seiji

    2016-01-01

    We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations.

  18. A review of maturity onset diabetes of the young (MODY) and challenges in the management of glucokinase-MODY.

    Science.gov (United States)

    Bishay, Ramy H; Greenfield, Jerry R

    2016-11-21

    Maturity onset diabetes of the young (MODY), the most common monogenic form of diabetes, accounts for 1-2% of all diabetes diagnoses. Glucokinase (GCK)-MODY (also referred to as MODY2) constitutes 10-60% of all MODY cases and is inherited as an autosomal dominant heterozygous mutation, resulting in loss of function of the GCK gene. Patients with GCK-MODY generally have mild, fasting hyperglycaemia that is present from birth, are commonly leaner and diagnosed at a younger age than patients with type 2 diabetes, and rarely develop complications from diabetes. Hence, treatment is usually unnecessary and may be ceased. Therefore, genetic screening is recommended in all young patients (MODY, such as hepatocyte nuclear factor 1A mutations (MODY3) where hyperglycaemia is managed with low dose sulfonylurea rather than insulin. Patients with GCK-MODY, in line with trends in the general population, are becoming older and more overweight and obese, and are concomitantly developing features of insulin resistance and glucose intolerance. Therefore, controversy exists as to whether such "treatment-exempt" patients should be reassessed for treatment later in life. As testing becomes more accessible, clinicians and patients are likely to embrace genetic screening earlier in the course of diabetes, which may avert the consequences of delayed testing years after diagnosis and treatment initiation.

  19. Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds

    Directory of Open Access Journals (Sweden)

    Xiwei Fan

    2015-04-01

    Full Text Available Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST retrieval error of 11.0 K when using the generalized split-window (GSW algorithm with a cirrus optical depth (COD at 0.55 μm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 μm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31–34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies.

  20. Mapping rice areas of South Asia using MODIS multitemporal data

    Science.gov (United States)

    Gumma, Murali Krishna; Nelson, Andrew; Thenkabail, Prasad S.; Singh, Amrendra N.

    2011-01-01

    Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating

  1. Mapping rice areas of South Asia using MODIS multitemporal data

    Science.gov (United States)

    Gumma, M.K.; Nelson, A.; Thenkabail, P.S.; Singh, A.N.

    2011-01-01

    Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating

  2. Applications of MODIS Fluorescent Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity

    Science.gov (United States)

    Fischer, Andrew; Moreno-Mardinan, Max; Ryan, John P.

    2012-01-01

    Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations, processing techniques and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean-color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS) sensor calibration updates, improved aerosol retrievals and new aerosol models has led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean color in coastal waters. This has opened the way for studying ocean phenomena and processes at finer spatial scales, such as the interactions at the land-sea interface, trends in coastal water quality and algal blooms. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and have increase local concentrations of phytoplankton, which cause harmful algal blooms. In two case studies we present MODIS observations of fluorescence line height (FLH) to 1) assess trends in water quality for Tampa Bay, Florida and 2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and satellite imagery from Tampa Bay we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions and to develop a near decadal trend in

  3. Sea Surface Temperature from MODIS during Saharan Air Layer outbreaks: Multichannel vs Optimal Estimation.

    Science.gov (United States)

    Szczodrak, G.; Minnett, P. J.

    2017-12-01

    The current Sea-Surface Temperature (SST) retrieval algorithms applied to MODIS and VIIRS data are build on the Non-Linear SST algorithm (NLSST Walton et al., 1998). This algorithm is based on combination of top-of-atmosphere brightness temperatures, T11 and T12 measured at λ= 11µm and 12µm. The algorithm has a set of coefficients derived using collocated measurements of SST temperature from drifting buoys (Match-Up Data Base - MUDB). NLSST produces accurate SST retrievals in conditions that are similar to those of the represented in the MUDB. When conditions deviate from typical, the errors are larger. An alternative approach of estimating the SST from radiance measurements is based on the Optimal Estimation (OE). The OE approach is not tied to a MUDB so OESST should be free of the systematic biases seen in NLSST retrievals in anomalous conditions. OE uses prior knowledge or estimation of a system as an input of a forward model to simulate `observations' and seeks to minimize the difference between these simulated observation and actual measurements in the space of the state variables. One situation that leads to significant bias in NLSST occurs in Northern Atlantic near the African coast during Saharan Air Layer (SAL) outbreaks. Typically, the atmosphere in this region is moist and these conditions are represented in the coefficients of the NLSST algorithm. During SAL events, moist air is replaced by a layer of very dry air; the established coefficients are no longer representative. During a number of research cruises in the North Atlantic affected by the SAL, we have collected radiometric SST measurements from ships using the Marine Atmosphere Emitted Radiance Interferometer (M-AERI), and frequent measurements of the atmospheric state with radiosondes launched from the ships. Using these data, we investigate if the OE approach is capable of improving the accuracy of the SST retrieval from MODIS under the conditions of the dry air outbreak from the Sahara.

  4. The MODIS Cloud Optical and Microphysical Products: Collection 6 Up-dates and Examples From Terra and Aqua

    Science.gov (United States)

    Platnick, Steven; Meyer, Kerry G.; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin G.; Arnold, G. Thomas; Zhang, Zhibo; Hubanks, Paul A.; Holz, Robert E.; hide

    2016-01-01

    The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties(optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations.The C6 algorithm changes collectively can result in significant changes relative to C5,though the magnitude depends on the dataset and the pixels retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud opticalproperty datasets, other MODIS cloud datasets are discussed when relevant.

  5. Properties of Linear Contrails Detected in 2012 Northern Hemisphere MODIS Imagery

    Science.gov (United States)

    Duda, David P.; Chee, Thad; Khlopenkov, Konstantin; Bedka, Sarah; Spangenberg, Doug; Minnis, Patrick

    2015-01-01

    Observation of linear contrail cirrus coverage and retrieval of their optical properties are valuable data for validating atmospheric climate models that represent contrail formation explicitly. These data can reduce our uncertainty of the regional effects of contrail-generated cirrus on global radiative forcing, and thus improve our estimation of the impact of commercial aviation on climate change. We use an automated contrail detection algorithm (CDA) to determine the coverage of linear persistent contrails over the Northern Hemisphere during 2012. The contrail detection algorithm is a modified form of the Mannstein et al. (1999) method, and uses several channels from thermal infrared MODIS data to reduce the occurrence of false positive detections. A set of contrail masks of varying sensitivity is produced to define the potential range of uncertainty in contrail coverage estimated by the CDA. Global aircraft emissions waypoint data provided by FAA allow comparison of detected contrails with commercial aircraft flight tracks. A pixel-level product based on the advected flight tracks defined by the waypoint data and U-V wind component profiles from the NASA GMAO GEOS-4 reanalysis has been developed to assign a confidence of contrail detection for the contrail mask. To account for possible contrail cirrus missed by the CDA, a post-processing method based on the assumption that pixels adjacent to detected linear contrails will have radiative signatures similar to those of the detected contrails is applied to the Northern Hemisphere data. Results from several months of MODIS observations during 2012 will be presented, representing a near-global climatology of contrail coverage. Linear contrail coverage will be compared with coverage estimates determined previously from 2006 MODIS data.

  6. MODY in Ukraine: genes, clinical phenotypes and treatment.

    Science.gov (United States)

    Globa, Evgenia; Zelinska, Nataliya; Elblova, Lenka; Dusatkova, Petra; Cinek, Ondrej; Lebl, Jan; Colclough, Kevin; Ellard, Sian; Pruhova, Stepanka

    2017-10-26

    Maturity-onset diabetes of the young (MODY) has not been previously studied in Ukraine. We investigated the genetic etiology in a selected cohort of patients with diabetes diagnosed before 18 years of age, and in their family members. Genetic testing of the most prevalent MODY genes (GCK, HNF1A, HNF4A, HNF1B and INS) was undertaken for 36 families (39 affected individuals) by Sanger or targeted next generation sequencing. A genetic diagnosis of MODY was made in 15/39 affected individuals from 12/36 families (33%). HNF1A and HNF4A MODY were the most common subtypes, accounting for 9/15 of MODY cases. Eight patients with HNF1A or HNF4A MODY and inadequate glycemic control were successfully transferred to sulfonylureas. Median HbA1c decreased from 67 mmol/mol (range 58-69) to 47 mmol/mol (range 43-50) (8.3% [7.5-8.5] to 6.4% [6.1-6.7]) 3 months after transfer (p=0.006). Genetic testing identified pathogenic HNF1A and HNF4A variants as the most common cause of MODY in Ukraine. Transfer to sulfonylureas substantially improved the glycemic control of these patients.

  7. Validation of MODIS snow cover images over Austria

    Directory of Open Access Journals (Sweden)

    J. Parajka

    2006-01-01

    Full Text Available This study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product over the territory of Austria. The aims are (a to analyse the spatial and temporal variability of the MODIS snow product classes, (b to examine the accuracy of the MODIS snow product against in situ snow depth data, and (c to identify the main factors that may influence the MODIS classification accuracy. We use daily MODIS grid maps (version 4 and daily snow depth measurements at 754 climate stations in the period from February 2000 to December 2005. The results indicate that, on average, clouds obscured 63% of Austria, which may significantly restrict the applicability of the MODIS snow cover images to hydrological modelling. On cloud-free days, however, the classification accuracy is very good with an average of 95%. There is no consistent relationship between the classification errors and dominant land cover type and local topographical variability but there are clear seasonal patterns to the errors. In December and January the errors are around 15% while in summer they are less than 1%. This seasonal pattern is related to the overall percentage of snow cover in Austria, although in spring, when there is a well developed snow pack, errors tend to be smaller than they are in early winter for the same overall percent snow cover. Overestimation and underestimation errors balance during most of the year which indicates little bias. In November and December, however, there appears to exist a tendency for overestimation. Part of the errors may be related to the temporal shift between the in situ snow depth measurements (07:00 a.m. and the MODIS acquisition time (early afternoon. The comparison of daily air temperature maps with MODIS snow cover images indicates that almost all MODIS overestimation errors are caused by the misclassification of cirrus clouds as snow.

  8. MODY in Siberia – molecular genetics and clinical characteristics

    Directory of Open Access Journals (Sweden)

    Alla Konstantinovna Ovsyannikova

    2017-05-01

    Full Text Available The diagnosis of maturity onset diabetes of the young (MODY has high clinical significance in young patients (no absolute need for exogenous insulin; normoglycaemia in most patients achieved by dieting or taking oral hypoglycaemic agents and their relatives (high probability of first-degree relatives being carriers of mutations, which requires a thorough collection of family history and determination of the parameters of carbohydrate metabolism. Aim. This study aimed was to determine the clinical characteristics of different subtypes of MODY in a Siberian region. Materials and Methods. We performed an examination, biochemical and hormonal blood tests, ultrasound and molecular genetic testing of 20 patients with a clinical diagnosis of MODY. Results. Four subtypes of MODY were verified: MODY2 in 11 patients, MODY3 in two, MODY8 in one and MODY12 in two. Eleven patients (69% exhibited no clinical manifestations of carbohydrate metabolism disorders, and one patient showed weight loss during early stage of the disease. Comorbidities included dyslipidemia, thyroid gland disorders and arterial hypertension. One patient (6% exhibited diabetic nephropathy; two (13%, diabetic retinopathy and three (19%, peripheral neuropathy of lower legs. All patients achieved the target carbohydrate metabolism; the level of C-peptide was within the reference range. Conclusion. Four different subtypes of MODY (2, 3, 8, 12 were diagnosed in the present study, which differed in their clinical characteristics, presence of complications and treatment strategies. Our knowledge of monogenic forms of diabetes is expanding with the development in molecular genetics, but several aspects related to them require further study.

  9. Remote Sensing of Ecosystem Light Use Efficiency Using MODIS

    Science.gov (United States)

    Huemmrich, K. F.; Middleton, E.; Landis, D.; Black, T. A.; Barr, A. G.; McCaughey, J. H.; Hall, F.

    2009-12-01

    Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Optimal photosynthetic function is negatively affected by stress factors that cause down-regulation (i.e., reduced rate of photosynthesis). Present modeling approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic light use efficiency (LUE) from remote sensing, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses exhibited by photosynthetic pigments. This approach uses the Moderate-Resolution Spectroradiometer (MODIS) on Aqua and Terra to provide frequent, narrow-band measurements. The reflective ocean MODIS bands were used to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments in the xanthophyll cycle. MODIS PRI values were compared with LUE calculated from CO2 flux measured at four Canadian forest sites: A mature Douglas fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed forest site in Ontario, all part of the Canadian Carbon Program network. The relationships between LUE and MODIS PRI were different among forest types, with clear differences in the slopes of the relationships for conifer and deciduous forests. The MODIS based LUE measurements provide a more accurate estimation of observed LUE than the values calculated in the MODIS GPP model. This suggests the possibility of a GPP model that uses MODIS LUE instead of modeled LUE. This type of model may provide a useful contrast to existing

  10. Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

    Science.gov (United States)

    He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

    2017-12-01

    Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, pcrop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

  11. The Combined ASTER MODIS Emissivity over Land (CAMEL Part 1: Methodology and High Spectral Resolution Application

    Directory of Open Access Journals (Sweden)

    E. Eva Borbas

    2018-04-01

    Full Text Available As part of a National Aeronautics and Space Administration (NASA MEaSUREs (Making Earth System Data Records for Use in Research Environments Land Surface Temperature and Emissivity project, the Space Science and Engineering Center (UW-Madison and the NASA Jet Propulsion Laboratory (JPL developed a global monthly mean emissivity Earth System Data Record (ESDR. This new Combined ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer and MODIS (Moderate Resolution Imaging Spectroradiometer Emissivity over Land (CAMEL ESDR was produced by merging two current state-of-the-art emissivity datasets: the UW-Madison MODIS Infrared emissivity dataset (UW BF and the JPL ASTER Global Emissivity Dataset Version 4 (GEDv4. The dataset includes monthly global records of emissivity and related uncertainties at 13 hinge points between 3.6–14.3 µm, as well as principal component analysis (PCA coefficients at 5-km resolution for the years 2000 through 2016. A high spectral resolution (HSR algorithm is provided for HSR applications. This paper describes the 13 hinge-points combination methodology and the high spectral resolutions algorithm, as well as reports the current status of the dataset.

  12. Assigning dates and identifying areas affected by fires in Portugal based on MODIS data

    Directory of Open Access Journals (Sweden)

    JESSICA PANISSET

    Full Text Available ABSTRACT An automated procedure is here presented that allows identifying and dating burned areas in Portugal using values of daily reflectance from near-infrared and middle-infrared bands, as obtained from the MODIS instrument. The algorithm detects persistent changes in monthly composites of the so-called (V,W Burn-Sensitive Index and the day of maximum change in daily time series of W is in turn identified as the day of the burning event. The procedure is tested for 2005, the second worst fire season ever recorded in Portugal. Comparison between the obtained burned area map and the reference derived from Landsat imagery resulted in a Proportion Correct of 95.6%. Despite being applied only to the months of August and September, the algorithm is able to identify almost two-thirds of all scars that have occurred during the entire year of 2005. An assessment of the temporal accuracy of the dating procedure was also conducted, showing that 75% of estimated dates presented deviations between -5 and 5 days from dates of hotspots derived from the MODIS instrument. Information about location and date of burning events as provided by the proposed procedure may be viewed as complementary to the currently available official maps based on end-of-season Landsat imagery.

  13. A snow cover climatology for the Pyrenees from MODIS snow products

    Science.gov (United States)

    Gascoin, S.; Hagolle, O.; Huc, M.; Jarlan, L.; Dejoux, J.-F.; Szczypta, C.; Marti, R.; Sanchez, R.

    2015-05-01

    The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the

  14. Flood mapping with multitemporal MODIS data

    Science.gov (United States)

    Son, Nguyen-Thanh; Chen, Chi-Farn; Chen, Cheng-Ru

    2014-05-01

    Flood is one of the most devastating and frequent disasters resulting in loss of human life and serve damage to infrastructure and agricultural production. Flood is phenomenal in the Mekong River Delta (MRD), Vietnam. It annually lasts from July to November. Information on spatiotemporal flood dynamics is thus important for planners to devise successful strategies for flood monitoring and mitigation of its negative effects. The main objective of this study is to develop an approach for weekly mapping flood dynamics with the Moderate Resolution Imaging Spectroradiometer data in MRD using the water fraction model (WFM). The data processed for 2009 comprises three main steps: (1) data pre-processing to construct smooth time series of the difference in the values (DVLE) between land surface water index (LSWI) and enhanced vegetation index (EVI) using the empirical mode decomposition (EMD), (2) flood derivation using WFM, and (3) accuracy assessment. The mapping results were compared with the ground reference data, which were constructed from Envisat Advanced Synthetic Aperture Radar (ASAR) data. As several error sources, including mixed-pixel problems and low-resolution bias between the mapping results and ground reference data, could lower the level of classification accuracy, the comparisons indicated satisfactory results with the overall accuracy of 80.5% and Kappa coefficient of 0.61, respectively. These results were reaffirmed by a close correlation between the MODIS-derived flood area and that of the ground reference map at the provincial level, with the correlation coefficients (R2) of 0.93. Considering the importance of remote sensing for monitoring floods and mitigating the damage caused by floods to crops and infrastructure, this study eventually leads to the realization of the value of using time-series MODIS DVLE data for weekly flood monitoring in MRD with the aid of EMD and WFM. Such an approach that could provide quantitative information on

  15. Variations of Global Terrestrial Primary Production Observed by Moderate Resolution Imaging Spectroradiometer (MODIS) From 2000 to 2005

    Science.gov (United States)

    Zhao, M.; Running, S.; Heinsch, F. A.

    2006-12-01

    Since the first Earth Observing System (EOS) satellite Terra was launched in December 1999 and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra began to provide data in February 2000, we have had six-year MODIS global 1-km terrestrial Gross and Net Primary Production (GPP &NPP) datasets. In this article, we present the variations (seasonality and inter-annual variability) of global GPP/NPP from the latest improved Collection 4.8 (C4.8) MODIS datasets for the past six-year (2000 - 2005), as well as improvements of the algorithm, validations of GPP and NPP. Validation results show that the C4.8 data have higher accuracy and quality than the previous version. Analyses of the variations in GPP/NPP show that GPP not only can reflect strong seasonality of photosynthesis activities by plants in mid- and high-latitude, but importantly, can reveal enhanced growth of Amazon rainforests during dry season, consistent with the reports by Huete et al. (2006) on GRL. Spatially, plants over mid- and high-latitude (north to 22.5°N) are the major contributor of global GPP seasonality. Inter-annual variability of MODIS NPP for 2000 - 2005 reveals the negative effects of major droughts on carbon sequestration at the regional and continental scales. A striking phenomenon is that the severe drought in 2005 over Amazon reduced NPP, indicating water availability becomes the dominant limiting factor rather than solar radiation under normal conditions. GMAO and NCEP driven global total NPPs have the similar interannual anomalies, and they generally follow the inverted CO2 growth rate anomaly with correlation of 0.85 and 0.91, respectively, which are higher than the correlation of 0.7 found by Nemani et al. (2003) on Science. Though there are only 6 years of MODIS data, results show that global NPP decreased from 2000 to 2005, and spatially most decreased NPP areas are in tropic and south hemisphere.

  16. Algorithming the Algorithm

    DEFF Research Database (Denmark)

    Mahnke, Martina; Uprichard, Emma

    2014-01-01

    Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...

  17. Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data.

    Science.gov (United States)

    Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen

    2013-02-01

    The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on MODIS land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.

  18. Development of an Operational Land Water Mask for MODIS Collection 6, and Influence on Downstream Data Products

    Science.gov (United States)

    Carroll, M. L.; DiMiceli, C. M.; Townshend, J. R. G.; Sohlberg, R. A.; Elders, A. I.; Devadiga, S.; Sayer, A. M.; Levy, R. C.

    2016-01-01

    Data from the Moderate Resolution Imaging Spectro-radiometer (MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway. Entering the fourth reprocessing (Collection 6 (C6)) the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces. The new water mask represents more small water bodies for an overall increase in water surface from 1 to 2 of the continental surface. While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask. MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask. Here differences between the Collection 5 (C5) and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.

  19. Spatial scales of pollution from variable resolution satellite imaging.

    Science.gov (United States)

    Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. SST, Aqua MODIS, NPP, 0.0125 degrees, Indonesia, Daytime

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides SST data from NASA's Aqua Spacecraft. Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard...

  1. Monthly statistics for WRF with and without MODIS vegetation

    Data.gov (United States)

    U.S. Environmental Protection Agency — The 2006 monthly average statistical metrics for 2m Q (g kg-1) domain-wide for the base and MODIS WRF simulations against MADIS observations. This dataset is...

  2. Fluorescence, Aqua MODIS, NPP, 0.125 degrees, West US

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures chlorophyll fluorescence, which gives insight into the physiology of phytoplankton in the ocean. When phytoplankton are under stress, the rate at...

  3. Fluorescence, Aqua MODIS, NPP, 0.125 degrees, East US

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures chlorophyll fluorescence, which gives insight into the physiology of phytoplankton in the ocean. When phytoplankton are under stress, the rate at...

  4. AfSIS MODIS Collection: Vegetation Indices, April 2014

    Data.gov (United States)

    Center for International Earth Science Information Network, Columbia University — The Africa Soil Information Service (AfSIS) Moderate Resolution Imaging Spectroradiometer (MODIS) Collection's Vegetation Indices data set contains rasters with the...

  5. CAMEX-4 ER-2 MODIS AIRBORNE SIMULATOR (MAS) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS Airborne Simulator (MAS) is an airborne scanning spectrometer that acquires high spatial resolution imagery of cloud and surface features from its vantage...

  6. Land Surface Microwave Emissivities Derived from AMSR-E and MODIS Measurements with Advanced Quality Control

    Science.gov (United States)

    Moncet, Jean-Luc; Liang, Pan; Galantowicz, John F.; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher

    2011-01-01

    A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semi-arid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by

  7. Assessment of AOD variability over Saudi Arabia using MODIS Deep Blue products

    International Nuclear Information System (INIS)

    Butt, Mohsin Jamil; Assiri, Mazen Ebraheem; Ali, Md. Arfan

    2017-01-01

    The aim of this study is to investigate the variability of aerosol over The Kingdom of Saudi Arabia. For this analysis, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Aerosol Optical Depth (AOD) product from Terra and Aqua satellites for the years 2000–2013 is used. The product is validated using AERONET data from ground stations, which are situated at Solar Village Riyadh and King Abdullah University of Science and Technology (KAUST) Jeddah. The results show that both Terra and Aqua satellites exhibit a tendency to show the spatial variation of AOD with Aqua being better than Terra to represent the ground based AOD measurements over the study region. The results also show that the eastern, central, and southern regions of the country have a high concentration of AOD during the study period. The validation results show the highest correlation coefficient between Aqua and KAUST data with a value of 0.79, whilst the Aqua and Solar Village based AOD indicates the lowest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values which are, 0.17 and 0.12 respectively. Furthermore, the Relative Mean Bias (RMB) based analysis show that the DB algorithm overestimates the AOD when using Terra and Solar Village data, while it underestimates the AOD when using Aqua with Solar Village and KAUST data. The RMB value for Aqua and Solar Village data indicates that the DB algorithm is close to normal in the study region. - Highlights: • The significance of aerosol in the Kingdom of Saudi Arabia is addressed. • MODIS (Terra and Aqua), AERONET and ground based sand event data is used. • MODIS DB product is used to prepare annual aerosol maps and monthly AOD variability. • A comparison is made between Terra and Aqua AOD product over bright surface. • MODIS DB AOD product is validated using AERONET data at Solar Village and KAUST. - This research highlighted the aerosol variability over The Kingdom of Saudi Arabia by using Satellite, AERONET

  8. Multi-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bay

    KAUST Repository

    Gilerson, Alexander; Ondrusek, Michael; Tzortziou, Maria; Foster, Robert; El-Habashi, Ahmed; Tiwari, Surya Prakash; Ahmed, Sam

    2015-01-01

    on the two- or three band ratio algorithms in the red/NIR part of the spectrum, which require 665, 708, 753 nm bands (or similar) and which work well in various waters all over the world. The critical 708 nm band for these algorithms is not available on MODIS

  9. A MODIS-based vegetation index climatology

    Science.gov (United States)

    Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

  10. USAID Expands eMODIS Coverage for Famine Early Warning

    Science.gov (United States)

    Jenkerson, C.; Meyer, D. J.; Evenson, K.; Merritt, M.

    2011-12-01

    Food security in countries at risk is monitored by U.S. Agency for International Development (USAID) through its Famine Early Warning Systems Network (FEWS NET) using many methods including Moderate Resolution Imaging Spectroradiometer (MODIS) data processed by U.S. Geological Survey (USGS) into eMODIS Normalized Difference Vegetation Index (NDVI) products. Near-real time production is used comparatively with trends derived from the eMODIS archive to operationally monitor vegetation anomalies indicating threatened cropland and rangeland conditions. eMODIS production over Central America and the Caribbean (CAMCAR) began in 2009, and processes 10-day NDVI composites every 5 days from surface reflectance inputs produced using predicted spacecraft and climatology information at Land and Atmosphere Near real time Capability for Earth Observing Systems (EOS) (LANCE). These expedited eMODIS composites are backed by a parallel archive of precision-based NDVI calculated from surface reflectance data ordered through Level 1 and Atmosphere Archive and Distribution System (LAADS). Success in the CAMCAR region led to the recent expansion of eMODIS production to include Africa in 2010, and Central Asia in 2011. Near-real time 250-meter products are available for each region on the last day of an acquisition interval (generally before midnight) from an anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/eMODIS). The FTP site concurrently hosts the regional historical collections (2000 to present) which are also searchable using the USGS Earth Explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer). As eMODIS coverage continues to grow, these geographically gridded, georeferenced tagged image file format (GeoTIFF) NDVI composites increase their utility as effective tools for operational monitoring of near-real time vegetation data against historical trends.

  11. Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

    Science.gov (United States)

    Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

    2015-08-01

    Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

  12. MODIS volcanic ash retrievals vs FALL3D transport model: a quantitative comparison

    Science.gov (United States)

    Corradini, S.; Merucci, L.; Folch, A.

    2010-12-01

    Satellite retrievals and transport models represents the key tools to monitor the volcanic clouds evolution. Because of the harming effects of fine ash particles on aircrafts, the real-time tracking and forecasting of volcanic clouds is key for aviation safety. Together with the security reasons also the economical consequences of a disruption of airports must be taken into account. The airport closures due to the recent Icelandic Eyjafjöll eruption caused millions of passengers to be stranded not only in Europe, but across the world. IATA (the International Air Transport Association) estimates that the worldwide airline industry has lost a total of about 2.5 billion of Euro during the disruption. Both security and economical issues require reliable and robust ash cloud retrievals and trajectory forecasting. The intercomparison between remote sensing and modeling is required to assure precise and reliable volcanic ash products. In this work we perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands operating in the VIS-TIR spectral range and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 micron have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. Three MODIS images collected the October 28, 29 and 30 on Mt. Etna volcano during the 2002 eruption have been considered as test cases. The results show a general good agreement between the retrieved and the modeled volcanic clouds in the first 300 km from the vents. Even if the

  13. Heterozygous ABCC8 mutations are a cause of MODY.

    Science.gov (United States)

    Bowman, P; Flanagan, S E; Edghill, E L; Damhuis, A; Shepherd, M H; Paisey, R; Hattersley, A T; Ellard, S

    2012-01-01

    The ABCC8 gene encodes the sulfonylurea receptor 1 (SUR1) subunit of the pancreatic beta cell ATP-sensitive potassium (K(ATP)) channel. Inactivating mutations cause congenital hyperinsulinism (CHI) and activating mutations cause transient neonatal diabetes (TNDM) or permanent neonatal diabetes (PNDM) that can usually be treated with sulfonylureas. Sulfonylurea sensitivity is also a feature of HNF1A and HNF4A MODY, but patients referred for genetic testing with clinical features of these types of diabetes do not always have mutations in the HNF1A/4A genes. Our aim was to establish whether mutations in the ABCC8 gene cause MODY that is responsive to sulfonylurea therapy. We sequenced the ABCC8 gene in 85 patients with a BMI MODY criteria, with two diagnosed after 25 years and one patient, who had no family history of diabetes, as a result of a proven de novo mutation. ABCC8 mutations can cause MODY in patients whose clinical features are similar to those with HNF1A/4A MODY. Therefore, sequencing of ABCC8 in addition to the known MODY genes should be considered if such features are present, to facilitate optimal clinical management of these patients.

  14. Can MODIS detect trends in aerosol optical depth over land?

    Science.gov (United States)

    Fan, Xuehua; Xia, Xiang'ao; Chen, Hongbin

    2018-02-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Aqua satellite has been collecting valuable data about the Earth system for more than 14 years, and one of the benefits of this is that it has made it possible to detect the long-term variation in aerosol loading across the globe. However, the long-term aerosol optical depth (AOD) trends derived from MODIS need careful validation and assessment, especially over land. Using AOD products with at least 70 months' worth of measurements collected during 2002-15 at 53 Aerosol Robotic Network (AERONET) sites over land, Mann-Kendall (MK) trends in AOD were derived and taken as the ground truth data for evaluating the corresponding results from MODIS onboard Aqua. The results showed that the AERONET AOD trends over all sites in Europe and North America, as well as most sites in Africa and Asia, can be reproduced by MODIS/Aqua. However, disagreement in AOD trends between MODIS and AERONET was found at a few sites in Australia and South America. The AOD trends calculated from AERONET instantaneous data at the MODIS overpass times were consistent with those from AERONET daily data, which suggests that the AOD trends derived from satellite measurements of 1-2 overpasses may be representative of those from daily measurements.

  15. Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

    Science.gov (United States)

    Hilker, Thomas; Lyapustin, Alexei I.; Tucker, Compton J.; Sellers, Piers J.; Hall, Forrest G.; Wang, Yujie

    2012-01-01

    Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased

  16. Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

    Science.gov (United States)

    Zaitchik, Benjamin F.; Rodell, Matthew

    2008-01-01

    Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

  17. Lipoprotein composition in HNF1A-MODY: differentiating between HNF1A-MODY and type 2 diabetes.

    Science.gov (United States)

    McDonald, Tim J; McEneny, Jane; Pearson, Ewan R; Thanabalasingham, Gaya; Szopa, Magdalena; Shields, Beverley M; Ellard, Sian; Owen, Katharine R; Malecki, Maciej T; Hattersley, Andrew T; Young, Ian S

    2012-05-18

    The young-onset diabetes seen in HNF1A-MODY is often misdiagnosed as Type 2 diabetes. Type 2 diabetes, unlike HNF1A-MODY, is associated with insulin resistance and a characteristic dyslipidaemia. We aimed to compare the lipid profiles in HNF1A-MODY, Type 2 diabetes and control subjects and to determine if lipids can be used to aid the differential diagnosis of diabetes sub-type. 1) 14 subjects in each group (HNF1A-MODY, Type 2 diabetes and controls) were matched for gender and BMI. Fasting lipid profiles and HDL lipid constituents were compared in the 3 groups. 2) HDL-cholesterol was assessed in a further 267 patients with HNF1A-MODY and 297 patients with a diagnosis of Type 2 diabetes to determine its discriminative value. 1) In HNF1A-MODY subjects, plasma-triglycerides were lower (1.36 vs. 1.93 mmol/l, p = 0.07) and plasma-HDL-cholesterol was higher than in subjects with Type 2 diabetes (1.47 vs. 1.15 mmol/l, p = 0.0008), but was similar to controls. Furthermore, in the isolated HDL; HDL-phospholipid and HDL-cholesterol ester content were higher in HNF1A-MODY, than in Type 2 diabetes (1.59 vs. 1.33 mmol/L, p = 0.04 and 1.10 vs. 0.83 mmol/L, p = 0.019, respectively), but were similar to controls (1.59 vs. 1.45 mmol/L, p = 0.35 and 1.10 vs. 1.21 mmol/L, p = 0.19, respectively). 2) A plasma-HDL-cholesterol > 1.12 mmol/L was 75% sensitive and 64% specific (ROC AUC = 0.76) at discriminating HNF1A-MODY from Type 2 diabetes. The plasma-lipid profiles of HNF1A-MODY and the lipid constituents of HDL are similar to non-diabetic controls. However, HDL-cholesterol was higher in HNF1A-MODY than in Type 2 diabetes and could be used as a biomarker to aid in the identification of patients with HNF1A-MODY. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. An Analysis of the Discrepancies between MODIS and INSAT-3D LSTs in High Temperatures

    Directory of Open Access Journals (Sweden)

    Seyed Kazem Alavipanah

    2017-04-01

    Full Text Available In many disciplines, knowledge on the accuracy of Land Surface Temperature (LST as an input is of great importance. One of the most efficient methods in LST evaluation is cross validation. Well-documented and validated polar satellites with a high spatial resolution can be used as references for validating geostationary LST products. This study attempted to investigate the discrepancies between a Moderate Resolution Imaging Spectro-radiometer (MODIS and Indian National Satellite (INSAT-3D LSTs for high temperatures, focusing on six deserts with sand dune land cover in the Middle East from 3 March 2015 to 24 August 2016. Firstly, the variability of LSTs in the deserts of the study area was analyzed by comparing the mean, Standard Deviation (STD, skewness, minimum, and maximum criteria for each observation time. The mean value of the LST observations indicated that the MYD-D observation times are closer to those of diurnal maximum and minimum LSTs. At all times, the LST observations exhibited a negative skewness and the STD indicated higher variability during times of MOD-D. The observed maximum LSTs from MODIS collection 6 showed higher values in comparison with the last versions of LSTs for hot spot regions around the world. After the temporal, spatial, and geometrical matching of LST products, the mean of the MODIS—INSAT LST differences was calculated for the study area. The results demonstrated that discrepancies increased with temperature up to +15.5 K. The slopes of the mean differences were relatively similar for all deserts except for An Nafud, suggesting an effect of View Zenith Angle (VZA. For modeling the discrepancies between two sensors in continuous space, the Diurnal Temperature Cycles (DTC of both sensors were constructed and compared. The sample DTC models approved the results from discrete LST subtractions and proposed the uncertainties within MODIS DTCs. The authors proposed that the observed LST discrepancies in high

  19. Phenological monitoring of Acadia National Park using Landsat, MODIS and VIIRS observations and fused data

    Science.gov (United States)

    Liu, Y.; McDonough MacKenzie, C.; Primack, R.; Zhang, X.; Schaaf, C.; Sun, Q.; Wang, Z.

    2015-12-01

    Monitoring phenology with remotely sensed data has become standard practice in large-plot agriculture but remains an area of research in complex terrain. Landsat data (30m) provides a more appropriate spatial resolution to describe such regions but may only capture a few cloud-free images over a growing period. Daily data from the MODerate resolution Imaging Spectroradiometer(MODIS) and Visible Infrared Imaging Radiometer Suite(VIIRS) offer better temporal acquisitions but at coarse spatial resolutions of 250m to 1km. Thus fused data sets are being employed to provide the temporal and spatial resolutions necessary to accurately monitor vegetation phenology. This study focused on Acadia National Park, Maine, attempts to compare green-up from remote sensing and ground observations over varying topography. Three north-south field transects were established in 2013 on parallel mountains. Along these transects, researchers record the leaf out and flowering phenology for thirty plant species biweekly. These in situ spring phenological observations are compared with the dates detected by Landsat 7, Landsat 8, MODIS, and VIIRS observations, both separately and as fused data, to explore the ability of remotely sensed data to capture the subtle variations due to elevation. Daily Nadir BRDF Adjusted Reflectances(NBAR) from MODIS and VIIRS are fused with Landsat imagery to simulate 30m daily data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM) algorithm. Piecewise logistic functions are fit to the time series to establish spring leaf-out dates. Acadia National Park, a region frequently affected by coastal clouds, is a particularly useful study area as it falls in a Landsat overlap region and thus offers the possibility of acquiring as many as 4 Landsat observations in a 16 day period. With the recent launch of Sentinel 2A, the community will have routine access to such high spatial and temporal data for phenological monitoring.

  20. Dynamics of the turbidity maximum zone in a macrotidal estuary (the Gironde, France): Observations from field and MODIS satellite data

    Science.gov (United States)

    Doxaran, David; Froidefond, Jean-Marie; Castaing, Patrice; Babin, Marcel

    2009-02-01

    Over a 1-year period, field and satellite measurements of surface water turbidity were combined in order to study the dynamics of the turbidity maximum zone (TM) in a macrotidal estuary (the Gironde, France). Four fixed platforms equipped with turbidity sensors calibrated to give the suspended particulate matter (SPM) concentration provided continuous information in the upper estuary. Full resolution data recorded by the moderate resolution imaging spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellite platforms provided information in the central and lower estuary twice a day (depending on cloud cover). Field data were used to validate a recently developed SPM quantification algorithm applied to the MODIS 'surface reflectance' product. The algorithm is based on a relationship between the SPM concentration and a reflectance ratio of MODIS bands 2 (near-infrared) and 1 (red). Based on 62 and 75 match-ups identified in 2005 with MODIS Terra and Aqua data, the relative uncertainty of the algorithm applied to these sensors was found to be 22 and 18%, respectively. Field measurements showed the tidal variations of turbidity in the upper estuary, while monthly-averaged MODIS satellite data complemented by field data allowed observing the monthly movements of the TM in the whole estuary. The trapping of fine sediments occurred in the upper estuary during the period of low river flow. This resulted in the formation of a highly concentrated TM during a 4-month period. With increasing river flow, the TM moved rapidly to the central estuary. A part of the TM detached, moved progressively in the lower estuary and was finally either massively exported to the ocean during peak floods or temporary trapped (settled) on intertidal mudflats. The massive export to the ocean was apparently the result of combined favorable environmental conditions: presence of fluid mud near the mouth, high river flow, high tides and limited wind speeds. The mean SPM concentration

  1. Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

    Science.gov (United States)

    Antuña-Marrero, Juan Carlos; Cachorro Revilla, Victoria; García Parrado, Frank; de Frutos Baraja, Ángel; Rodríguez Vega, Albeth; Mateos, David; Estevan Arredondo, René; Toledano, Carlos

    2018-04-01

    In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AODt) and Aqua (AODa) satellites and those measured using a sun photometer (AODSP) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AODta) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AODt, AODa, AODta compared to AODSP. For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AODta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AODt, AODa, AODta vs. AODSP, with a slight overestimation of satellite data compared to AODSP, (f). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of

  2. Sound algorithms

    OpenAIRE

    De Götzen , Amalia; Mion , Luca; Tache , Olivier

    2007-01-01

    International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.

  3. Genetic algorithms

    Science.gov (United States)

    Wang, Lui; Bayer, Steven E.

    1991-01-01

    Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

  4. Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

    Science.gov (United States)

    de Leeuw, Gerrit; Sogacheva, Larisa; Rodriguez, Edith; Kourtidis, Konstantinos; Georgoulias, Aristeidis K.; Alexandri, Georgia; Amiridis, Vassilis; Proestakis, Emmanouil; Marinou, Eleni; Xue, Yong; van der A, Ronald

    2018-02-01

    The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth - AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV

  5. [Maturity onset diabetes of the young (MODY) - screening, diagnostic and therapy].

    Science.gov (United States)

    Kaser, Susanne; Resl, Michael

    2016-04-01

    Maturity onset diabetes of the young (MODY) is a group of monogenetic diabetes types affecting up to 2% all known diabetics. Transcription factor MODY (HNF1α, HNF4α), the most frequent forms of MODY, allow treatment with sulfonylureas, mutations of glucokinase (GCK-MODY) usually do not require any therapy. Especially in younger patients correct diagnosis of MODY often results in discontinuation of insulin therapy and initiation of a sulfonylurea. Accordingly, in patients with diabetes onset below age of 25 years, with a positive family history for diabetes and negative autoantibodies screening for MODY is recommended.

  6. HDL cholesterol as a diagnostic tool for clinical differentiation of GCK-MODY from HNF1A-MODY and type 1 diabetes in children and young adults.

    Science.gov (United States)

    Fendler, Wojciech; Borowiec, Maciej; Antosik, Karolina; Szadkowska, Agnieszka; Deja, Grazyna; Jarosz-Chobot, Przemyslawa; Mysliwiec, Malgorzata; Wyka, Krystyna; Pietrzak, Iwona; Skupien, Jan; Malecki, Maciej T; Mlynarski, Wojciech

    2011-09-01

    Confirmation of monogenic diabetes caused by glucokinase mutations (GCK-MODY) allows pharmacogenetic intervention in the form of insulin discontinuation. This is especially important among paediatric and young adult populations where GCK-MODY is most prevalent. The study evaluated the utility of lipid parameters in screening for patients with GCK-MODY. Eighty-nine children with type 1 diabetes and 68 with GCK-MODY were screened for triglyceride (TG), total and HDL cholesterol levels. Standardization against a control group of 171 healthy children was applied to eliminate the effect of development. Clinical applicability and cut-off value were evaluated in all available patients with GCK-MODY (n = 148), hepatocyte nuclear factor 1-alpha-MODY (HNF1A MODY) (n = 37) or type 1 diabetes (n = 221). Lower lipid parameter values were observed in GCK-MODY than in patients with type 1 diabetes. Standard deviation scores were -0·22 ± 2·24 vs 1·31 ± 2·17 for HDL cholesterol (P MODY selection [sensitivity 87%, specificity 54%, negative predictive value (NPV) 86%, positive PV 56%]. A threshold HDL concentration of 1·56 mm offered significantly better diagnostic efficiency than total cholesterol (cut-off value 4·51 mm; NPV 80%; PPV 38%; P MODY and differentiation from T1DM and HNF1A-MODY, regardless of treatment or metabolic control. © 2011 Blackwell Publishing Ltd.

  7. Overview of CERES Cloud Properties Derived From VIRS AND MODIS DATA

    Science.gov (United States)

    Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.

    2006-01-01

    Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and Aqua during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and Aqua scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible

  8. Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets.

    Science.gov (United States)

    Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanré, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

    2005-04-01

    Understanding the impact of aerosols on the earth's radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth's Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product.This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved

  9. a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

    Science.gov (United States)

    Hazaymeh, K.; Almagbile, A.

    2018-04-01

    In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

  10. Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products

    International Nuclear Information System (INIS)

    Qin, Jun; Chen, Zhuoqi; Yang, Kun; Liang, Shunlin; Tang, Wenjun

    2011-01-01

    Global solar radiation (GSR) is required in a large number of fields. Many parameterization schemes are developed to estimate it using routinely measured meteorological variables, since GSR is directly measured at a limited number of stations. Even so, meteorological stations are sparse, especially, in remote areas. Satellite signals (radiance at the top of atmosphere in most cases) can be used to estimate continuous GSR in space. However, many existing remote sensing products have a relatively coarse spatial resolution and these inversion algorithms are too complicated to be mastered by experts in other research fields. In this study, the artificial neural network (ANN) is utilized to build the mathematical relationship between measured monthly-mean daily GSR and several high-level remote sensing products available for the public, including Moderate Resolution Imaging Spectroradiometer (MODIS) monthly averaged land surface temperature (LST), the number of days in which the LST retrieval is performed in 1 month, MODIS enhanced vegetation index, Tropical Rainfall Measuring Mission satellite (TRMM) monthly precipitation. After training, GSR estimates from this ANN are verified against ground measurements at 12 radiation stations. Then, comparisons are performed among three GSR estimates, including the one presented in this study, a surface data-based estimate, and a remote sensing product by Japan Aerospace Exploration Agency (JAXA). Validation results indicate that the ANN-based method presented in this study can estimate monthly-mean daily GSR at a spatial resolution of about 5 km with high accuracy.

  11. Algorithms and Applications in Grass Growth Monitoring

    Directory of Open Access Journals (Sweden)

    Jun Liu

    2013-01-01

    Full Text Available Monitoring vegetation phonology using satellite data has been an area of growing research interest in recent decades. Validation is an essential issue in land surface phenology study at large scale. In this paper, double logistic function-fitting algorithm was used to retrieve phenophases for grassland in North China from a consistently processed Moderate Resolution Spectrodiometer (MODIS dataset. Then, the accuracy of the satellite-based estimates was assessed using field phenology observations. Results show that the method is valid to identify vegetation phenology with good success. The phenophases derived from satellite and observed on ground are generally similar. Greenup onset dates identified by Normalized Difference Vegetation Index (NDVI and in situ observed dates showed general agreement. There is an excellent agreement between the dates of maturity onset determined by MODIS and the field observations. The satellite-derived length of vegetation growing season is generally consistent with the surface observation.

  12. BRDF Characterization and Calibration Inter-Comparison between Terra MODIS, Aqua MODIS, and S-NPP VIIRS

    Science.gov (United States)

    Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Wu, Aisheng

    2016-01-01

    The inter-comparison of reflective solar bands (RSB) between Terra MODIS, Aqua MODIS, and SNPP VIIRS is very important for assessment of each instrument's calibration and to identify calibration improvements. One of the limitations of using their ground observations for the assessment is a lack of the simultaneous nadir overpasses (SNOs) over selected pseudo-invariant targets. In addition, their measurements over a selected Earth view target have significant difference in solar and view angles, and these differences magnify the effects of Bidirectional Reflectance Distribution Function (BRDF). In this work, an inter-comparison technique using a semi-empirical BRDF model is developed for reflectance correction. BRDF characterization requires a broad coverage of solar and view angles in the measurements over selected pseudo-invariant targets. Reflectance measurements over Libya 1, 2, and 4 desert sites from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for the calibration difference between the two instruments. The BRDF coefficients for three desert sites for MODIS bands 1 to 9 are derived and the wavelength dependencies are presented. The analysis and inter-comparison are for MODIS bands 1 to 9 and VIIRS moderate resolution radiometric bands (M bands) M1, M2, M4, M5, M7, M8, M10 and imaging bands (I bands) I1-I3. Results show that the ratios from different sites are in good agreement. The ratios between Terra and Aqua MODIS from year 2003 to 2014 are presented. The inter-comparison between MODIS and VIIRS are analyzed for year 2014.

  13. Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI

    Science.gov (United States)

    Pervez, Md Shahriar; Budde, Michael; Rowland, James

    2014-01-01

    Agricultural production capacity contributes to food security in Afghanistan and is largely dependent on irrigated farming, mostly utilizing surface water fed by snowmelt. Because of the high contribution of irrigated crops (> 80%) to total agricultural production, knowing the spatial distribution and year-to-year variability in irrigated areas is imperative to monitoring food security for the country. We used 16-day composites of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to create 23-point time series for each year from 2000 through 2013. Seasonal peak values and time series were used in a threshold-dependent decision tree algorithm to map irrigated areas in Afghanistan for the last 14 years. In the absence of ground reference irrigated area information, we evaluated these maps with the irrigated areas classified from multiple snapshots of the landscape during the growing season from Landsat 5 optical and thermal sensor images. We were able to identify irrigated areas using Landsat imagery by selecting as irrigated those areas with Landsat-derived NDVI greater than 0.30–0.45, depending on the date of the Landsat image and surface temperature less than or equal to 310 Kelvin (36.9 ° C). Due to the availability of Landsat images, we were able to compare with the MODIS-derived maps for four years: 2000, 2009, 2010, and 2011. The irrigated areas derived from Landsat agreed well r2 = 0.91 with the irrigated areas derived from MODIS, providing confidence in the MODIS NDVI threshold approach. The maps portrayed a highly dynamic irrigated agriculture practice in Afghanistan, where the amount of irrigated area was largely determined by the availability of surface water, especially snowmelt, and varied by as much as 30% between water surplus and water deficit years. During the past 14 years, 2001, 2004, and 2008 showed the lowest levels of irrigated area (~ 1.5 million hectares), attesting to

  14. Comparison of chlorophyll in the Red Sea derived from MODIS-Aqua and in vivo fluorescence

    KAUST Repository

    Brewin, Robert J W

    2013-09-01

    The Red Sea is a unique marine environment but relatively unexplored. The only available long-term biological dataset at large spatial and temporal scales is remotely-sensed chlorophyll observations (an index of phytoplankton biomass) derived using satellite measurements of ocean colour. Yet such observations have rarely been compared with in situ data in the Red Sea. In this paper, satellite chlorophyll estimates in the Red Sea from the MODIS instrument onboard the Aqua satellite are compared with three recent cruises of in vivo fluorometric chlorophyll measurements taken in October 2008, March 2010 and September to October 2011. The performance of the standard NASA chlorophyll algorithm, and that of a new band-difference algorithm, is found to be comparable with other oligotrophic regions in the global ocean, supporting the use of satellite ocean colour in the Red Sea. However, given the unique environmental conditions of the study area, regional algorithms are likely to fare better and this is demonstrated through a simple adjustment to the band-difference algorithm. © 2013 Elsevier Inc.

  15. Towards a systematic nationwide screening strategy for MODY.

    Science.gov (United States)

    Shields, Beverley; Colclough, Kevin

    2017-04-01

    MODY is an early-onset monogenic form of diabetes. Correctly identifying MODY is of considerable importance as diagnosing the specific genetic subtype can inform the optimal treatment, with many patients being able to discontinue unnecessary insulin treatment. Diagnostic molecular genetic testing to confirm MODY is expensive, so screening strategies are required to identify the most appropriate patients for testing. In this issue of Diabetologia, Johansson and colleagues (DOI 10.1007/s00125-016-4167-1 ) describe a nationwide systematic screening approach to identify individuals with MODY in the paediatric age range. They focused testing on patients negative for both GAD and islet antigen 2 (IA-2) islet autoantibodies, thereby ruling out those with markers of type 1 diabetes, the most common form of diabetes in this age group. This commentary discusses the advantages and limitations of the approach, and the caution required when interpreting variants of uncertain pathogenicity identified from testing whole populations rather than targeting only patients with a strong MODY phenotype.

  16. MODIS on-orbit thermal emissive bands lifetime performance

    Science.gov (United States)

    Madhavan, Sriharsha; Wu, Aisheng; Chen, Na; Xiong, Xiaoxiong

    2016-05-01

    MODerate resolution Imaging Spectroradiometer (MODIS), a leading heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and Aqua (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-MODIS currently functional beyond 15 years and the A-MODIS operating beyond 13 years respectively. The MODIS sensor characteristics include a spectral coverage from 0.41 μm - 14.4 μm, of which wavelengths ranging from 3.7 μm - 14. 4 μm cover the thermal infrared region also referred to as the Thermal Emissive Bands (TEBs). The TEBs is calibrated using a v-grooved BlackBody (BB) whose temperature measurements are traceable to the National Institute of Standards and Technology temperature scales. The TEBs calibration based on the onboard BB is extremely important for its high radiometric fidelity. In this paper, we provide a complete characterization of the lifetime instrument performance of both MODIS instruments in terms of the sensor gain, the Noise Equivalent difference Temperature, key instrument telemetry such as the BB lifetime trends, the instrument temperature trends, the Cold Focal Plane telemetry and finally, the total assessed calibration uncertainty of the TEBs.

  17. Impact of Sensor Degradation on the MODIS NDVI Time Series

    Science.gov (United States)

    Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

    2012-01-01

    Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

  18. Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China Using Multi-Spectral Phenological Metrics from MODIS Time Series

    Directory of Open Access Journals (Sweden)

    Sebastian van der Linden

    2013-05-01

    Full Text Available We developed and evaluated a new approach for mapping rubber plantations and natural forests in one of Southeast Asia’s biodiversity hot spots, Xishuangbanna in China. We used a one-year annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS, Enhanced Vegetation Index (EVI and short-wave infrared (SWIR reflectance data to develop phenological metrics. These phenological metrics were used to classify rubber plantations and forests with the Random Forest classification algorithm. We evaluated which key phenological characteristics were important to discriminate rubber plantations and natural forests by estimating the influence of each metric on the classification accuracy. As a benchmark, we compared the best classification with a classification based on the full, fitted time series data. Overall classification accuracies derived from EVI and SWIR time series alone were 64.4% and 67.9%, respectively. Combining the phenological metrics from EVI and SWIR time series improved the accuracy to 73.5%. Using the full, smoothed time series data instead of metrics derived from the time series improved the overall accuracy only slightly (1.3%, indicating that the phenological metrics were sufficient to explain the seasonal changes captured by the MODIS time series. The results demonstrate a promising utility of phenological metrics for mapping and monitoring rubber expansion with MODIS.

  19. Global two-channel AVHRR aerosol climatology: effects of stratospheric aerosols and preliminary comparisons with MODIS and MISR retrievals

    International Nuclear Information System (INIS)

    Geogdzhayev, Igor V.; Mishchenko, Michael I.; Liu Li; Remer, Lorraine

    2004-01-01

    We present an update on the status of the global climatology of the aerosol column optical thickness and Angstrom exponent derived from channel-1 and -2 radiances of the Advanced Very High Resolution Radiometer (AVHRR) in the framework of the Global Aerosol Climatology Project (GACP). The latest version of the climatology covers the period from July 1983 to September 2001 and is based on an adjusted value of the diffuse component of the ocean reflectance as derived from extensive comparisons with ship sun-photometer data. We use the updated GACP climatology and Stratospheric Aerosol and Gas Experiment (SAGE) data to analyze how stratospheric aerosols from major volcanic eruptions can affect the GACP aerosol product. One possible retrieval strategy based on the AVHRR channel-1 and -2 data alone is to infer both the stratospheric and the tropospheric aerosol optical thickness while assuming fixed microphysical models for both aerosol components. The second approach is to use the SAGE stratospheric aerosol data in order to constrain the AVHRR retrieval algorithm. We demonstrate that the second approach yields a consistent long-term record of the tropospheric aerosol optical thickness and Angstrom exponent. Preliminary comparisons of the GACP aerosol product with MODerate resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectro-Radiometer aerosol retrievals show reasonable agreement, the GACP global monthly optical thickness being lower than the MODIS one by approximately 0.03. Larger differences are observed on a regional scale. Comparisons of the GACP and MODIS Angstrom exponent records are less conclusive and require further analysis

  20. Remote sensing of tropospheric total column water vapor: Intercomparison of POLDER, AMSR-E and MODIS retrievals

    Science.gov (United States)

    Riedi, J.; Mcharek, L.; Dubuisson, P.; Parol, F.; Thieuleux, F.

    2013-05-01

    Since December 2004, the CNES Parasol (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) mission has been flying in the A-train with Aqua (NASA) providing more than 5 years of temporally and spatially coincident observations from POLDER, MODIS and AMSRE which enable total column water vapor amount retrievals. We are providing here a temporal and statistical analysis of water vapor near-infrared retrievals from POLDER against MODIS and AMSR-E products derived from nearinfrared, thermal infrared and microwave observations over ocean. A temporal analysis of POLDER official product is conducted in view of AMSR-E and MODIS coincident retrievals over ocean. In a second step, an alternative approach based on the use of simple multilayer perceptron (MLP) neural network (NN) is developed to improve the mathematical parameterization used to retrieve water vapor amount from near-infrared observation. The retrievals are further improved when an estimate of the 910 nm surface reflectance is obtained through interpolation between PARASOL 865 nm and 1020 nm channels. This last improvement now allows for a unified land/ocean retrieval algorithm for PARASOL/POLDER.

  1. Broadband IR Measurements for Modis Validation

    Science.gov (United States)

    Jessup, Andrew T.

    2003-01-01

    The primary objective of this research was the development and deployment of autonomous shipboard systems for infrared measurement of ocean surface skin temperature (SST). The focus was on demonstrating long-term, all-weather capability and supplying calibrated skin SST to the MODIS Ocean Science Team (MOCEAN). A secondary objective was to investigate and account for environmental factors that affect in situ measurements of SST for validation of satellite products. We developed and extensively deployed the Calibrated, InfraRed, In situ Measurement System, or CIRIMS, for at-sea validation of satellite-derived SST. The design goals included autonomous operation at sea for up to 6 months and an accuracy of +/- 0.1 C. We used commercially available infrared pyrometers and a precision blackbody housed in a temperature-controlled enclosure. The sensors are calibrated at regular interval using a cylindro-cone target immersed in a temperature-controlled water bath, which allows the calibration points to follow the ocean surface temperature. An upward-looking pyrometer measures sky radiance in order to correct for the non-unity emissivity of water, which can introduce an error of up to 0.5 C. One of the most challenging aspects of the design was protection against the marine environment. A wide range of design strategies to provide accurate, all-weather measurements were investigated. The CIRIMS uses an infrared transparent window to completely protect the sensor and calibration blackbody from the marine environment. In order to evaluate the performance of this approach, the design incorporates the ability to make measurements with and without the window in the optical path.

  2. Algorithmic cryptanalysis

    CERN Document Server

    Joux, Antoine

    2009-01-01

    Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic

  3. MODIS/Aqua Thermal Anomalies/Fire 5-Min L2 Swath 1km V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  4. MODIS/Aqua Aerosol 5-Min L2 Swath 10km V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  5. MODIS/Terra Aerosol 5-Min L2 Swath 10km V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  6. The Use of MODIS NDVI Data for Characterizing Cropland Across the Great Lakes Basin

    Science.gov (United States)

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides new opportunities for characterizing land-cover (LC) to support monitoring and assessment studies at watershed, regional and global scales. This research evaluated the potential for using the MODIS Normalized Diff...

  7. NLCD - MODIS land cover- albedo dataset for the continental United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution...

  8. MODIS/Aqua Raw Radiances in Counts 5-Min L1A Swath V006

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS/Aqua Raw Radiances in Counts 5-Min L1A Swath (MYD01) product contains reformatted and packaged raw instrument data. MODIS instrument data, in packetized...

  9. MODIS/Aqua Raw Radiances in Counts 5-Min L1A Swath - NRT

    Data.gov (United States)

    National Aeronautics and Space Administration — This is MODIS Level-1A Near Real Time (NRT) product containing reformatted and packaged raw instrument data. MODIS instrument data, in packetized form, is reversibly...

  10. MODIS/Terra Thermal Anomalies/Fire 5-Min L2 Swath 1km V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  11. Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa

    Directory of Open Access Journals (Sweden)

    Andreas Tewes

    2015-05-01

    Full Text Available Image time series of high temporal and spatial resolution capture land surface dynamics of heterogeneous landscapes. We applied the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model algorithm to multi-spectral images covering two semi-arid heterogeneous rangeland study sites located in South Africa. MODIS 250 m resolution and RapidEye 5 m resolution images were fused to produce synthetic RapidEye images, from June 2011 to July 2012. We evaluated the performance of the algorithm by comparing predicted surface reflectance values to real RapidEye images. Our results show that ESTARFM predictions are accurate, with a coefficient of determination for the red band 0.80 < R2 < 0.92, and for the near-infrared band 0.83 < R2 < 0.93, a mean relative bias between 6% and 12% for the red band and 4% to 9% in the near-infrared band. Heterogeneous vegetation at sub-MODIS resolution is captured adequately: A comparison of NDVI time series derived from RapidEye and ESTARFM data shows that the characteristic phenological dynamics of different vegetation types are reproduced well. We conclude that the ESTARFM algorithm allows us to produce synthetic remote sensing images at high spatial combined with high temporal resolution and so provides valuable information on vegetation dynamics in semi-arid, heterogeneous rangeland landscapes.

  12. Alternative Method of On-Orbit Response-Versus-Scan-Angle Characterization for MODIS Reflective Solar Bands

    Science.gov (United States)

    Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng

    2016-01-01

    The moderate resolution imaging spectroradiometer (MODIS) has 20 reflective solar bands (RSB), covering a spectral range from 0.41 to 2.2 microns, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the reflectance of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's reflectance over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and Aqua MODIS. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the MODIS characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard

  13. Modeling GPP in the Nordic forest landscape with MODIS time series data—Comparison with the MODIS GPP product

    DEFF Research Database (Denmark)

    Schubert, Per; Lagergren, Fredrik; Aurela, Mika

    2012-01-01

    . The main objective of this study was to investigate if MODIS 500m reflectance data can be used to drive empirical models for regional estimations of GPP in Nordic forests. The performance of the proposed models was compared with the MODIS 1km GPP product. Linear regression analyses were made on 8-day...... averages of eddy covariance GPP from three deciduous and ten coniferous sites in relation to MODIS 8-day composite data and 8-day averages of modeled incoming PPFD (photosynthetic photon flux density). Time series of EVI2 (two-band enhanced vegetation index) were calculated from MODIS 500m reflectance data...... and smoothed by a curve fitting procedure. For most sites, GPP was fairly strongly to strongly related to the product of EVI2 and PPFD (Deciduous: R2=0.45–0.86, Coniferous: R2=0.49–0.90). Similar strengths were found between GPP and the product of EVI2 and MODIS 1km daytime LST (land surface temperature) (R2...

  14. Validation of JAXA/MODIS Sea Surface Temperature in Water around Taiwan Using the Terra and Aqua Satellites

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2010-01-01

    Full Text Available The research vessel-based Conductivity Temperature Depth profiler (CTD provides underwater measurements of the bulk sea surface temperature (SST at the depths of shallower than 5 m. The CTD observations of the seas around Taiwan provide useful data for comparison with SST of MODIS (Moderate Resolution Imaging Spectroradiometers aboard Aqua and Terra satellites archived by JAXA (Japan Aerospace Exploration Agency. We produce a high-resolution (1 km MODIS SST by using Multi-Channel SST (MCSST algorithm. There were 1516 cloud-free match-up data pairs of MODIS SST and in situ measurements during the period from 2003 - 2005. The difference of the root mean square error (RMSE of satellite observations from each platform during the day and at night was: 0.88°C in Aqua daytime, 0.71°C in Aqua nighttime, 0.71°C in Terra daytime, and 0.60°C in Terra nighttime. The total analysis of MODIS-derived SST shows good agreement with a bias of 0.03°C and RMSE of 0.75°C. The analyses indicate that the bias of Aqua daytime was always positive throughout the year and the large RMSE should be attributed to the large positive bias (0.45°C under diurnal warming. It was also found that the bias of Terra daytime was usually negative with a mean bias of -0.41°C; its large RMSE should be treated with care because of low solar radiation in the morning.

  15. 21-Year-Old Pregnant Woman with MODY-5 Diabetes

    Directory of Open Access Journals (Sweden)

    Anastasia Mikuscheva

    2017-01-01

    Full Text Available The term “Maturity-Onset Diabetes of the Young” (MODY was first described in 1976 and is currently referred to as monogenic diabetes. There are 14 known entities accounting for 1-2% of diabetes and they are frequently misdiagnosed as either type 1 or type 2 diabetes. MODY-5 is an entity of monogenic diabetes that is associated with genitourinary malformations and should be considered by obstetricians in pregnant women with a screen positive for diabetes, genitourinary malformations, and fetal renal anomalies. Correct diagnosis of monogenic diabetes has implications on managing patients and their families. We are reporting a case of a 21-year-old pregnant woman with a bicornuate uterus, fetal renal anomalies, and a family history of diabetes that were suggestive of a MODY-5 diabetes.

  16. A MODIS-based begetation index climatology

    Science.gov (United States)

    Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The pa...

  17. Algorithmic mathematics

    CERN Document Server

    Hougardy, Stefan

    2016-01-01

    Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.

  18. Level 1 Processing of MODIS Direct Broadcast Data at the GSFC DAAC

    Science.gov (United States)

    Lynnes, Christopher; Kempler, Steven J. (Technical Monitor)

    2001-01-01

    The GSFC DAAC is working to test and package the MODIS Level 1 Processing software for Aqua Direct Broadcast data. This entails the same code base, but different lookup tables for Aqua and Terra. However, the most significant change is the use of ancillary attitude and ephemeris files instead of orbit/attitude information within the science data stream (as with Terra). In addition, we are working on Linux: ports of the algorithms, which could eventually enable processing on PC clusters. Finally, the GSFC DAAC is also working with the GSFC Direct Readout laboratory to ingest Level 0 data from the GSFC DB antenna into the main DAAC, enabling level 1 production in near real time in support of applications users, such as the Synergy project. The mechanism developed for this could conceivably be extended to other participating stations.

  19. Glucokinase gene mutations (MODY 2) in Asian Indians.

    Science.gov (United States)

    Kanthimathi, Sekar; Jahnavi, Suresh; Balamurugan, Kandasamy; Ranjani, Harish; Sonya, Jagadesan; Goswami, Soumik; Chowdhury, Subhankar; Mohan, Viswanathan; Radha, Venkatesan

    2014-03-01

    Heterozygous inactivating mutations in the glucokinase (GCK) gene cause a hyperglycemic condition termed maturity-onset diabetes of the young (MODY) 2 or GCK-MODY. This is characterized by mild, stable, usually asymptomatic, fasting hyperglycemia that rarely requires pharmacological intervention. The aim of the present study was to screen for GCK gene mutations in Asian Indian subjects with mild hyperglycemia. Of the 1,517 children and adolescents of the population-based ORANGE study in Chennai, India, 49 were found to have hyperglycemia. These children along with the six patients referred to our center with mild hyperglycemia were screened for MODY 2 mutations. The GCK gene was bidirectionally sequenced using BigDye(®) Terminator v3.1 (Applied Biosystems, Foster City, CA) chemistry. In silico predictions of the pathogenicity were carried out using the online tools SIFT, Polyphen-2, and I-Mutant 2.0 software programs. Direct sequencing of the GCK gene in the patients referred to our Centre revealed one novel mutation, Thr206Ala (c.616A>G), in exon 6 and one previously described mutation, Met251Thr (c.752T>C), in exon 7. In silico analysis predicted the novel mutation to be pathogenic. The highly conserved nature and critical location of the residue Thr206 along with the clinical course suggests that the Thr206Ala is a MODY 2 mutation. However, we did not find any MODY 2 mutations in the 49 children selected from the population-based study. Hence prevalence of GCK mutations in Chennai is MODY 2 mutations from India and confirms the importance of considering GCK gene mutation screening in patients with mild early-onset hyperglycemia who are negative for β-cell antibodies.

  20. Comparison of MODIS and VIIRS On-board Blackbody Performance

    Science.gov (United States)

    Xiong, Jack; Butler, Jim; Wu, Aisheng; Chiang, Vincent; McIntire, Jeff; Oudari, Hassan

    2012-01-01

    MODIS has 16 thermal emissive bands (TEBs), covering wavelengths from 3.7 to 14.4 microns. MODIS TEBs are calibrated on-orbit by a v-grooved blackbody (BB) on a scan-by-scan basis. The BB temperatures are measured by a set of 12 thennistors. As expected, the BB temperature uncertainty and stability have direct impact on the quality of TEB calibration and, therefore, the quality of the science products derived from TEB observations. Since launch, Terra and Aqua MODIS have successfully operated for more than 12 and 10 years, respectively. Their on-board BB performance has been satisfactory in meeting the TEB calibration requirements. The first VIIRS, launched on-board the Suomi NPP spacecraft on October 28, 2011, has successfully completed its initial Intensive Calibration and Validation (ICV) phase. VIIRS has 7 thermal emissive bands (TEBs), covering wavelengths from 3.7 to 12.4 microns. Designed with strong MODIS heritage, VIIRS uses a similar BB for its TEB calibration. Like MODIS, VIIRS BB is nominally controlled at a pre-determined temperature (set point). Periodically, a BB Warm-Up and Cool-Down (WUCD) operation is performed, during which the BB temperatures vary from instrument ambient (temperature) to 315K. This paper examines NPP VIIRS BB on-orbit performance. It focuses on its BB temperature scan-to-scan variations at nominally controlled temperature as well as during its WUCD operation and their impact on TEB calibration uncertainty. Comparisons of VIIRS (NPP) and MODIS (Terra and Aqua) BB on-orbit performance and lessons learned for future improvements are also presented in this paper.

  1. Estimating Global Cropland Extent with Multi-year MODIS Data

    Directory of Open Access Journals (Sweden)

    Christopher O. Justice

    2010-07-01

    Full Text Available This study examines the suitability of 250 m MODIS (MODerate Resolution Imaging Spectroradiometer data for mapping global cropland extent. A set of 39 multi-year MODIS metrics incorporating four MODIS land bands, NDVI (Normalized Difference Vegetation Index and thermal data was employed to depict cropland phenology over the study period. Sub-pixel training datasets were used to generate a set of global classification tree models using a bagging methodology, resulting in a global per-pixel cropland probability layer. This product was subsequently thresholded to create a discrete cropland/non-cropland indicator map using data from the USDA-FAS (Foreign Agricultural Service Production, Supply and Distribution (PSD database describing per-country acreage of production field crops. Five global land cover products, four of which attempted to map croplands in the context of multiclass land cover classifications, were subsequently used to perform regional evaluations of the global MODIS cropland extent map. The global probability layer was further examined with reference to four principle global food crops: corn, soybeans, wheat and rice. Overall results indicate that the MODIS layer best depicts regions of intensive broadleaf crop production (corn and soybean, both in correspondence with existing maps and in associated high probability matching thresholds. Probability thresholds for wheat-growing regions were lower, while areas of rice production had the lowest associated confidence. Regions absent of agricultural intensification, such as Africa, are poorly characterized regardless of crop type. The results reflect the value of MODIS as a generic global cropland indicator for intensive agriculture production regions, but with little sensitivity in areas of low agricultural intensification. Variability in mapping accuracies between areas dominated by different crop types also points to the desirability of a crop-specific approach rather than attempting

  2. Clinical differences between patients with MODY-3, MODY-2 and type 2 diabetes mellitus with I27L polymorphism in the HNF1alpha gene.

    Science.gov (United States)

    Pinés Corrales, Pedro José; López Garrido, María P; Aznar Rodríguez, Silvia; Louhibi Rubio, Lynda; López Jiménez, Luz M; Lamas Oliveira, Cristina; Alfaro Martínez, Jose J; Lozano García, Jose J; Hernández López, Antonio; Requejo Castillo, Ramón; Escribano Martínez, Julio; Botella Romero, Francisco

    2010-01-01

    The aim of our study was to describe and evaluate the clinical and metabolic characteristics of patients with MODY-3, MODY-2 or type 2 diabetes who presented I27L polymorphism in the HNF1alpha gene. The study included 31 previously diagnosed subjects under follow-up for MODY-3 (10 subjects from 5 families), MODY-2 (15 subjects from 9 families), or type 2 diabetes (6 subjects) with I27L polymorphism in the HNF1alpha gene. The demographic, clinical, metabolic, and genetic characteristics of all patients were analyzed. No differences were observed in distribution according to sex, age of onset, or form of diagnosis. All patients with MODY-2 or MODY-3 had a family history of diabetes. In contrast, 33.3% of patients with type 2 diabetes mellitus and I27L polymorphism in the HNF1alpha gene had no family history of diabetes (p MODY-3 patients, but not required by 100% of MODY-2 patients or 16.7% of patients with type 2 diabetes mellitus and I27L polymorphism in the HNF1alpha gene (p MODY-2, MODY-3 or type 2 diabetes of atypical characteristics, in this case patients who present I27L polymorphism in the HNF1alpha gene. Copyright 2010 Sociedad Española de Endocrinología y Nutrición. Published by Elsevier Espana. All rights reserved.

  3. Remote sensing of aerosols by synergy of caliop and modis

    OpenAIRE

    Kudo Rei; Nishizawa Tomoaki; Higurashi Akiko; Oikawa Eiji

    2018-01-01

    For the monitoring of the global 3-D distribution of aerosol components, we developed the method to retrieve the vertical profiles of water-soluble, light absorbing carbonaceous, dust, and sea salt particles by the synergy of CALIOP and MODIS data. The aerosol product from the synergistic method is expected to be better than the individual products of CALIOP and MODIS. We applied the method to the biomass-burning event in Africa and the dust event in West Asia. The reasonable results were obt...

  4. Total algorithms

    NARCIS (Netherlands)

    Tel, G.

    We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of

  5. The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote sensing-based evapotranspiration algorithms

    KAUST Repository

    Michel, D.; Jimé nez, C.; Miralles, Diego G.; Jung, M.; Hirschi, M.; Ershadi, A.; Martens, B.; McCabe, Matthew; Fisher, J. B.; Mu, Q.; Seneviratne, S. I.; Wood, E. F.; Ferná ndez-Prieto, D.

    2015-01-01

    algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODIS evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition

  6. Influence of composite period and date of observation on phenological metrics extracted from MODIS data

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2009-05-01

    Full Text Available ) The 8-day, 500m MODIS data (MOD09) for the Skukuza EOS site were downloaded from the MODIS ASCII Subsets website (http://daac.ornl.gov/cgi-bin/MODIS/GR_1/button.slim.pl). The data comprised 14 x 14 pixels of data covering a 7x7 km area for the period...

  7. [Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

    Science.gov (United States)

    Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

    2015-11-01

    With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

  8. The Combined ASTER MODIS Emissivity over Land (CAMEL Part 2: Uncertainty and Validation

    Directory of Open Access Journals (Sweden)

    Michelle Feltz

    2018-04-01

    Full Text Available Under the National Aeronautics and Space Administration’s (NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs Land Surface Temperature and Emissivity project, a new global land surface emissivity dataset has been produced by the University of Wisconsin–Madison Space Science and Engineering Center and NASA’s Jet Propulsion Laboratory (JPL. This new dataset termed the Combined ASTER MODIS Emissivity over Land (CAMEL, is created by the merging of the UW–Madison MODIS baseline-fit emissivity dataset (UWIREMIS and JPL’s ASTER Global Emissivity Dataset v4 (GEDv4. CAMEL consists of a monthly, 0.05° resolution emissivity for 13 hinge points within the 3.6–14.3 µm region and is extended to 417 infrared spectral channels using a principal component regression approach. An uncertainty product is provided for the 13 hinge point emissivities by combining temporal, spatial, and algorithm variability as part of a total uncertainty estimate. Part 1 of this paper series describes the methodology for creating the CAMEL emissivity product and the corresponding high spectral resolution algorithm. This paper, Part 2 of the series, details the methodology of the CAMEL uncertainty calculation and provides an assessment of the CAMEL emissivity product through comparisons with (1 ground site lab measurements; (2 a long-term Infrared Atmospheric Sounding Interferometer (IASI emissivity dataset derived from 8 years of data; and (3 forward-modeled IASI brightness temperatures using the Radiative Transfer for TOVS (RTTOV radiative transfer model. Global monthly results are shown for different seasons and International Geosphere-Biosphere Programme land classifications, and case study examples are shown for locations with different land surface types.

  9. Chromophoric Dissolved Organic Matter and Dissolved Organic Carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS, Moderate Resolution Imaging Spectroradiometer (MODIS and MERIS Sensors: Case Study for the Northern Gulf of Mexico

    Directory of Open Access Journals (Sweden)

    Blake A. Schaeffer

    2013-03-01

    Full Text Available Empirical band ratio algorithms for the estimation of colored dissolved organic matter (CDOM and dissolved organic carbon (DOC for Sea-viewing Wide Field-of-view Sensor (SeaWiFS, Moderate Resolution Imaging Spectroradiometer (MODIS and MERIS ocean color sensors were assessed and developed for the northern Gulf of Mexico. Match-ups between in situ measurements of CDOM absorption coefficients at 412 nm (aCDOM(412 with that derived from SeaWiFS were examined using two previously reported reflectance band ratio algorithms. Results indicate better performance using the Rrs(510/Rrs(555 (Bias = −0.045; RMSE = 0.23; SI = 0.49, and R2 = 0.66 than the Rrs(490/Rrs(555 reflectance band ratio algorithm. Further, a comparison of aCDOM(412 retrievals using the Rrs(488/Rrs(555 for MODIS and Rrs(510/Rrs(560 for MERIS reflectance band ratios revealed better CDOM retrievals with MERIS data. Since DOC cannot be measured directly by remote sensors, CDOM as the colored component of DOC is utilized as a proxy to estimate DOC remotely. A seasonal relationship between CDOM and DOC was established for the summer and spring-winter with high correlation for both periods (R2~0.9. Seasonal band ratio empirical algorithms to estimate DOC were thus developed using the relationships between CDOM-Rrs and seasonal CDOM-DOC for SeaWiFS, MODIS and MERIS. Results of match-up comparisons revealed DOC estimates by both MODIS and MERIS to be relatively more accurate during summer time, while both of them underestimated DOC during spring-winter time. A better DOC estimate from MERIS in comparison to MODIS in spring-winter could be attributed to its similarity with the SeaWiFS band ratio CDOM algorithm.

  10. Sensitivity Study for Sensor Optical and Electric Crosstalk Based on Spectral Measurements: An Application to Developmental Sensors Using Heritage Sensors Such As MODIS

    Science.gov (United States)

    Butler, James J.; Oudrari, Hassan; Xiong, Sanxiong; Che, Nianzeng; Xiong, Xiaoxiong

    2007-01-01

    The process of developing new sensors for space flight frequently builds upon the designs and experience of existing heritage space flight sensors. Frequently in the development and testing of new sensors, problems are encountered that pose the risk of serious impact on successful retrieval of geophysical products. This paper describes an approach to assess the importance of optical and electronic cross-talk on retrieval of geophysical products using new MODIS-like sensors through the use of MODIS data sets. These approaches may be extended to any sensor characteristic and any sensor where that characteristic may impact the Level 1 products so long as validated geophysical products are being developed from the heritage sensor. In this study, a set of electronic and/or optical cross-talk coefficients are postulated. These coefficients are sender-receiver influence coefficients and represent a sensor signal contamination on any detector on a focal plane when another band's detectors on that focal plane are stimulated with a monochromatic light. The approach involves using the postulated cross-talk coefficients on an actual set of MODIS data granules. The original MODIS data granules and the cross-talk impacted granules are used with validated geophysical algorithms to create the derived products. Comparison of the products produced with the original and cross-talk impacted granules indicates potential problems, if any, with the characteristics of the developmental sensor that are being studied.

  11. Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations

    Science.gov (United States)

    Nagler, Pamela L.; Pearlstein, Susanna; Glenn, Edward P.; Brown, Tim B.; Bateman, Heather L.; Bean, Dan W.; Hultine, Kevin R.

    2013-01-01

    We measured the rate of dispersal of saltcedar leaf beetles (Diorhabda carinulata), a defoliating insect released on western rivers to control saltcedar shrubs (Tamarix spp.), on a 63 km reach of the Virgin River, U.S. Dispersal was measured by satellite imagery, ground surveys and phenocams. Pixels from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite showed a sharp drop in NDVI in midsummer followed by recovery, correlated with defoliation events as revealed in networked digital camera images and ground surveys. Ground surveys and MODIS imagery showed that beetle damage progressed downstream at a rate of about 25 km yr−1 in 2010 and 2011, producing a 50% reduction in saltcedar leaf area index and evapotranspiration by 2012, as estimated by algorithms based on MODIS Enhanced Vegetation Index values and local meteorological data for Mesquite, Nevada. This reduction is the equivalent of 10.4% of mean annual river flows on this river reach. Our results confirm other observations that saltcedar beetles are dispersing much faster than originally predicted in pre-release biological assessments, presenting new challenges and opportunities for land, water and wildlife managers on western rivers. Despite relatively coarse resolution (250 m) and gridding artifacts, single MODIS pixels can be useful in tracking the effects of defoliating insects in riparian corridors.

  12. Cystatin C is not a good candidate biomarker for HNF1A-MODY.

    Science.gov (United States)

    Nowak, Natalia; Szopa, Magdalena; Thanabalasingham, Gaya; McDonald, Tim J; Colclough, Kevin; Skupien, Jan; James, Timothy J; Kiec-Wilk, Beata; Kozek, Elzbieta; Mlynarski, Wojciech; Hattersley, Andrew T; Owen, Katharine R; Malecki, Maciej T

    2013-10-01

    Cystatin C is a marker of glomerular filtration rate (GFR). Its level is influenced, among the others, by CRP whose concentration is decreased in HNF1A-MODY. We hypothesized that cystatin C level might be altered in HNF1A-MODY. We aimed to evaluate cystatin C in HNF1A-MODY both as a diagnostic marker and as a method of assessing GFR. We initially examined 51 HNF1A-MODY patients, 56 subjects with type 1 diabetes (T1DM), 39 with type 2 diabetes (T2DM) and 43 non-diabetic individuals (ND) from Poland. Subjects from two UK centres were used as replication panels: including 215 HNF1A-MODY, 203 T2DM, 39 HNF4A-MODY, 170 GCK-MODY, 17 HNF1B-MODY and 58 T1DM patients. The data were analysed with additive models, adjusting for gender, age, BMI and estimated GFR (creatinine). In the Polish subjects, adjusted cystatin C level in HNF1A-MODY was lower compared with T1DM, T2DM and ND (p MODY, while the two GFR estimates were similar or cystatin C-based lower in the other groups. In the UK subjects, there were no differences in cystatin C between HNF1A-MODY and the other diabetic subgroups, except HNF1B-MODY. In UK HNF1A-MODY, cystatin C-based GFR estimate was higher than the creatinine-based one (p MODY. In HNF1A-MODY, the cystatin C-based GFR estimate is higher than the creatinine-based one.

  13. Evaluating Terra MODIS Satellite Sensor Data Products for Maize ...

    African Journals Online (AJOL)

    Evaluating Terra MODIS Satellite Sensor Data Products for Maize Yield Estimation in South Africa. C Frost, N Thiebaut, T Newby. Abstract. The Free State Province of the Republic of South Africa contains some of the most important maize-producing areas in South Africa. For this reason this province has also been selected ...

  14. Fusion of MODIS Images Using Kriging With External Drift

    NARCIS (Netherlands)

    Ribeiro Sales, M.H.; Souza, C.M.; Kyriakidis, P.C.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) has been used in several remote sensing studies, including land, ocean, and atmospheric applications. The advantages of this sensor are its high spectral resolution, with 36 spectral bands; its high revisiting frequency; and its public domain

  15. Clear-sky narrowband albedos derived from VIRS and MODIS

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Arduini, Robert F.

    2004-02-01

    The Clouds and Earth"s Radiant Energy System (CERES) project is using multispectral imagers, the Visible Infrared Scanner (VIRS) on the tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, operating since spring 2000, and Aqua, operating since summer 2002, to provide cloud and clear-sky properties at various wavelengths. This paper presents the preliminary results of an analysis of the CERES clear-sky reflectances to derive a set top-of-atmosphere clear sky albedo for 0.65, 0.86, 1.6, 2.13 μm, for all major surface types using the combined MODIS and VIRS datasets. The variability of snow albedo with surface type is examined using MODIS data. Snow albedo was found to depend on the vertical structure of the vegetation. At visible wavelengths, it is least for forested areas and greatest for smooth desert and tundra surfaces. At 1.6 and 2.1-μm, the snow albedos are relatively insensitive to the underlying surface because snow decreases the reflectance. Additional analyses using all of the MODIS results will provide albedo models that should be valuable for many remote sensing, simulation and radiation budget studies.

  16. Evaluation of MODIS NPP and GPP products across multiple biomes.

    Science.gov (United States)

    David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Steve W. Running; Maosheng Zhao; Marcos H. Costa; Al A. Kirschbaum; Jay M. Ham; Scott R. Saleska; Douglas E. Ahl

    2006-01-01

    Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of...

  17. Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition

    Directory of Open Access Journals (Sweden)

    Bo Gao

    2016-09-01

    Full Text Available Clouds usually cause invalid observations for sensors aboard satellites, which corrupts the spatio-temporal continuity of land surface parameters retrieved from remote sensing data (e.g., MODerate Resolution Imaging Spectroradiometer (MODIS data and prevents the fusing of multi-source remote sensing data in the field of quantitative remote sensing. Based on the requirements of spatio-temporal continuity and the necessity of methods to restore bad pixels, primarily resulting from image processing, this study developed a novel method to derive the spectral reflectance for MODIS band of cloudy pixels in the visual–near infrared (VIS–NIR spectral channel based on the Bidirectional Reflectance Distribution Function (BRDF and multi-spatio-temporal observations. The proposed method first constructs the spatial distribution of land surface reflectance based on the corresponding BRDF and the solar-viewing geometry; then, a geographically weighted regression (GWR is introduced to individually derive the spectral surface reflectance for MODIS band of cloudy pixels. A validation of the proposed method shows that a total root-mean-square error (RMSE of less than 6% and a total R2 of more than 90% are detected, which indicates considerably better precision than those exhibited by other existing methods. Further validation of the retrieved white-sky albedo based on the spectral reflectance for MODIS band of cloudy pixels confirms an RMSE of 3.6% and a bias of 2.2%, demonstrating very high accuracy of the proposed method.

  18. Monogenic diabetes associated with PAX4 gene mutations (MODY9: first description in Russia

    Directory of Open Access Journals (Sweden)

    Natalya A. Zubkova

    2017-12-01

    Full Text Available Maturity-onset diabetes of the young (MODY is a heterogeneous group of disorders characterised by autosomal dominant type of inheritance and caused by genetic defects leading to dysfunction of pancreatic beta-cells. To date, at least 13 subtypes of MODY have been described in the literature, the most frequent of which are MODY types 1–3. MODY2 and MODY3 are the most prevalent subtypes, and were previously described in our country, Russia. Several cases of rare MODY subtypes were subsequently described in the Russian literature. The current report is the first in the Russian literature to present clinical and molecular genetic characteristics of two cases of another rare MODY subtype—MODY9. This type of MODY is associated with mutations in the PAX4 gene, which encodes transcription factor PAX4, one of the factors essential for pancreatic beta-cell differentiation. Molecular genetic analysis was performed using next-generation sequencing, a new method recently applied to verify monogenic diseases and, in particular, MODY. This study reports a novel mutation in the PAX4 gene in MODY patients.

  19. Application-Ready Expedited MODIS Data for Operational Land Surface Monitoring of Vegetation Condition

    Directory of Open Access Journals (Sweden)

    Jesslyn F. Brown

    2015-12-01

    Full Text Available Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1, the eMODIS Normalized Difference Vegetation Index (NDVI maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra or afternoon (Aqua orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

  20. Improved Global Ocean Color Using Polymer Algorithm

    Science.gov (United States)

    Steinmetz, Francois; Ramon, Didier; Deschamps, ierre-Yves; Stum, Jacques

    2010-12-01

    A global ocean color product has been developed based on the use of the POLYMER algorithm to correct atmospheric scattering and sun glint and to process the data to a Level 2 ocean color product. Thanks to the use of this algorithm, the coverage and accuracy of the MERIS ocean color product have been significantly improved when compared to the standard product, therefore increasing its usefulness for global ocean monitor- ing applications like GLOBCOLOUR. We will present the latest developments of the algorithm, its first application to MODIS data and its validation against in-situ data from the MERMAID database. Examples will be shown of global NRT chlorophyll maps produced by CLS with POLYMER for operational applications like fishing or oil and gas industry, as well as its use by Scripps for a NASA study of the Beaufort and Chukchi seas.

  1. A dizygotic twin pregnancy in a MODY 3-affected woman.

    Science.gov (United States)

    Bitterman, O; Iafusco, D; Torcia, F; Tinto, N; Napoli, A

    2016-10-01

    MODY diabetes includes rare familiar forms due to genetic mutations resulting in β-cell dysfunction. MODY 3 is due to mutations in the gene transcription factor HNF-1α, with diabetes diagnosis in adolescence or early adult life. Few data are available about MODY 3 in pregnancy. A 36-year-old Italian woman came to our unit at the 5th week of pregnancy. She was diagnosed with diabetes at 18 years, with negative autoimmunity and a strong familiarity for diabetes. She was treated with gliclazide and metformin. She had a previous pregnancy in which she was treated with insulin, giving birth at 38 weeks to a 3.210 kg baby girl, who showed neonatal hypoglycemia. We switched her to insulin treatment according to guidelines. We asked for genetic molecular testing, resulting in a HNF-1α gene mutation. A US examination at 7 weeks revealed a twin, bicorial, biamniotic pregnancy. At 37 weeks of gestation, she gave birth to two normal-weight baby girls; only one showed neonatal hypoglycemia and a genetic test revealed that she was affected by HNF-1α gene mutation. Subsequently, entire family of the woman was tested, showing that the father, the sister and the first daughter had the same HNF-1α mutation. A MODY 3 foetus needs a near-normal maternal glycemic control, because the exposure to intrauterine hyperglycemia can lead to an earlier age of diabetes onset. Neonatal hypoglycemia is generally observed in MODY 1 infants, but it is possible to hypothesize that some HNF-1α mutations could lead to a functionally impaired protein that might dysregulate HNF-4α expression determining hypoglycemia.

  2. Deriving Snow Cover Metrics for Alaska from MODIS

    Directory of Open Access Journals (Sweden)

    Chuck Lindsay

    2015-09-01

    Full Text Available Moderate Resolution Imaging Spectroradiometer (MODIS daily snow cover products provide an opportunity for determining snow onset and melt dates across broad geographic regions; however, cloud cover and polar darkness are limiting factors at higher latitudes. This study presents snow onset and melt dates for Alaska, portions of western Canada and the Russian Far East derived from Terra MODIS snow cover daily 500 m grid data (MOD10A1 and evaluates our method for filling data gaps caused by clouds or polar darkness. Pixels classified as cloud or no data were reclassified by: spatial filtering using neighboring pixel values; temporal filtering using pixel values for days before/after cloud cover; and snow-cycle filtering based on a time series assessment of a pixel’s position within snow accumulation, cover or melt periods. During the 2012 snow year, these gap-filling methods reduced cloud pixels from 27.7% to 3.1%. A total of 12 metrics (e.g., date of first and last snow, date of persistent snow cover and periods of intermittence for each pixel were calculated by snow year. A comparison of MODIS-derived snow onset and melt dates with in situ observations from 244 weather stations generally showed an early bias in MODIS-derived dates and an effect of increasing cloudiness exacerbating bias. Our results show that mean regional duration of seasonal snow cover is 179–311 days/year and that snow cover is often intermittent, with 41% of the area experiencing ≥2 snow-covered periods during a snow season. Other regional-scale patterns in the timing of snow onset and melt are evident in the yearly 500 m gridded products publically available at http://static.gina.alaska.edu/NPS_products/MODIS_snow/.

  3. Pipeline oil fire detection with MODIS active fire products

    Science.gov (United States)

    Ogungbuyi, M. G.; Martinez, P.; Eckardt, F. D.

    2017-12-01

    We investigate 85 129 MODIS satellite active fire events from 2007 to 2015 in the Niger Delta of Nigeria. The region is the oil base for Nigerian economy and the hub of oil exploration where oil facilities (i.e. flowlines, flow stations, trunklines, oil wells and oil fields) are domiciled, and from where crude oil and refined products are transported to different Nigerian locations through a network of pipeline systems. Pipeline and other oil facilities are consistently susceptible to oil leaks due to operational or maintenance error, and by acts of deliberate sabotage of the pipeline equipment which often result in explosions and fire outbreaks. We used ground oil spill reports obtained from the National Oil Spill Detection and Response Agency (NOSDRA) database (see www.oilspillmonitor.ng) to validate MODIS satellite data. NOSDRA database shows an estimate of 10 000 spill events from 2007 - 2015. The spill events were filtered to include largest spills by volume and events occurring only in the Niger Delta (i.e. 386 spills). By projecting both MODIS fire and spill as `input vector' layers with `Points' geometry, and the Nigerian pipeline networks as `from vector' layers with `LineString' geometry in a geographical information system, we extracted the nearest MODIS events (i.e. 2192) closed to the pipelines by 1000m distance in spatial vector analysis. The extraction process that defined the nearest distance to the pipelines is based on the global practices of the Right of Way (ROW) in pipeline management that earmarked 30m strip of land to the pipeline. The KML files of the extracted fires in a Google map validated their source origin to be from oil facilities. Land cover mapping confirmed fire anomalies. The aim of the study is to propose a near-real-time monitoring of spill events along pipeline routes using 250 m spatial resolution of MODIS active fire detection sensor when such spills are accompanied by fire events in the study location.

  4. Improvement in the cloud mask for Terra MODIS mitigated by electronic crosstalk correction in the 6.7 μm and 8.5 μm channels

    Science.gov (United States)

    Sun, Junqiang; Madhavan, S.; Wang, M.

    2016-09-01

    MODerate resolution Imaging Spectroradiometer (MODIS), a remarkable heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and Aqua (A) platforms which tracks the Earth in the morning and afternoon orbits. T-MODIS has continued to operate over 15 years easily surpassing the 6 year design life time on orbit. Of the several science products derived from MODIS, one of the primary derivatives is the MODIS Cloud Mask (MOD035). The cloud mask algorithm incorporates several of the MODIS channels in both reflective and thermal infrared wavelengths to identify cloud pixels from clear sky. Two of the thermal infrared channels used in detecting clouds are the 6.7 μm and 8.5 μm. Based on a difference threshold with the 11 μm channel, the 6.7 μm channel helps in identifying thick high clouds while the 8.5 μm channel being useful for identifying thin clouds. Starting 2010, it had been observed in the cloud mask products that several pixels have been misclassified due to the change in the thermal band radiometry. The long-term radiometric changes in these thermal channels have been attributed to the electronic crosstalk contamination. In this paper, the improvement in cloud detection using the 6.7 μm and 8.5 μm channels are demonstrated using the electronic crosstalk correction. The electronic crosstalk phenomena analysis and characterization were developed using the regular moon observation of MODIS and reported in several works. The results presented in this paper should significantly help in improving the MOD035 product, maintaining the long term dataset from T-MODIS which is important for global change monitoring.

  5. Retrieval of Secchi disk depth in the Yellow Sea and East China Sea using 8-day MODIS data

    International Nuclear Information System (INIS)

    Yu, D F; Xing, Q G; Lou, M J; Shi, P

    2014-01-01

    Secchi disk depth (SDD), is widely used as an indicator of water clarity. The traditional sampling method is not only time-consuming and labor-intensive but also limited in terms of temporal and spatial coverage. Remote sensing technology may deal with these limitations. In this paper, the applicability of 8-day MODIS-Aqua remote sensing reflectance data with 4 km spatial resolution for estimating water clarity in the Yellow Sea and the East China Sea was investigated. Field data such as Secchi depths were collected from two cruises conducted in the Yellow Sea and the East China Sea from 5 May to 7 June 2009. A three-band algorithm to retrieve SDD was developed based on remote sensing reflectance at bands of 488, 555, and 678 nm, which performed better than single-band model and band ratio algorithm, with a determination coefficient of 0.72 and a mean relative error of 19%. This suggests that 8-day MODIS-Aqua products of remote sensing reflectance could be used to assess water transparency in the study area

  6. A Comparison Between SST and AOT Derived from AVHRR and MODIS Data in the Frame of the CREPAD Program

    Science.gov (United States)

    Robles-Gonzalez, Cristina; Fernandez-Renau, Alix; Lopez Gordillo, Noelia; Sevilla, Angel Garcia; Suarez, Juana Santana

    2010-12-01

    Since 1997, the INTA-CREPAD (Centre for REception, Processing, Archiving and Dissemination of Earth Observation Data) program distributes freely some of the most demanded low-resolution remote sensing products: SST, Ocean Chl-a, NDVI, AOD... The data input for such products are captured at the Canary Space Station (Centro Espacial de Canarias, CEC). The data sensors received at the station and used in the CREPAD program are AVHRR, SEAWIFS and MODIS. In this study SST and AOD retrieved by CREPAD algorithms from AVHRR and the SEADAS derived SST and AOD from MODIS have compared. SST values agree very well within 0.1±0.5oC and the coefficient of correlation of the images is 0.9. AOD validation gives good results taking into account the differences in the algorithms used. Mean AOD difference at 0.630 μm is 0.01±0.05 and the correlation coefficient is 0.6.

  7. Validation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Data

    Science.gov (United States)

    Geogdzhayev, Igor V.; Mishchenko, Michael I.

    2015-01-01

    A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995-2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003-2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81-0.85 for GACP and 0.74-0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%-27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%-25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the

  8. A harmful algal bloom of Karenia brevis in the northeastern Gulf of Mexico as revealed by MODIS and VIIRS: a comparison.

    Science.gov (United States)

    Hu, Chuanmin; Barnes, Brian B; Qi, Lin; Corcoran, Alina A

    2015-01-28

    The most recent Visible Infrared Imager Radiometer Suite (VIIRS) is not equipped with a spectral band to detect solar-stimulated phytoplankton fluorescence. The lack of such a band may affect the ability of VIIRS to detect and quantify harmful algal blooms (HABs) in coastal waters rich in colored dissolved organic matter (CDOM) because of the overlap of CDOM and chlorophyll absorption within the blue-green spectrum. A recent HAB dominated by the toxin-producing dinoflagellate Karenia brevis in the northeastern Gulf of Mexico, offshore of Florida's Big Bend region, allowed for comparison of the capacities of VIIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) to detect blooms in CDOM-rich waters. Both VIIRS and MODIS showed general consistency in mapping the CDOM-rich dark water, which measured a maximum area of 8900 km2 by mid-July 2014. However, within the dark water, only MODIS allowed detection of bloom patches-as indicated by high normalized fluorescence line height (nFLH). Field surveys between late July and mid-September confirmed Karenia brevis at bloom abundances up to 20 million cells·L(-1) within these patches. The bloom patches were well captured by the MODIS nFLH images, but not by the default chlorophyll a concentration (Chla) images from either MODIS or VIIRS. Spectral analysis showed that VIIRS could not discriminate these high-phytoplankton water patches within the dark water due to its lack of fluorescence band. Such a deficiency may be overcome with new algorithms or future satellite missions such as the U.S. NASA's Pre-Aerosol-Clouds-Ecology mission and the European Space Agency's Sentinel-3 mission.

  9. Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

    Science.gov (United States)

    Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

    2014-12-01

    Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active

  10. Evaluation of Above Ground Biomass Estimation Accuracy for Alpine Meadow Based on MODIS Vegetation Indices

    Directory of Open Access Journals (Sweden)

    Meng Bao-Ping

    2017-01-01

    Full Text Available Animal husbandry is the main agricultural type over the Tibetan Plateau, above ground biomass (AGB is very important to monitor the productivity for administration of grassland resources and grazing balance. The MODIS vegetation indices have been successfully used in numerous studies on grassland AGB estimation in the Tibetan Plateau area. However, there are considerable differences of AGB estimation models both in the form of the models and the accuracy of estimation. In this study, field measurements of AGB data at Sangke Town, Gansu Province, China in four years (2013-2016 and MODIS indices (NDVI and EVI are combined to construct AGB estimation models of alpine meadow grassland. The field measured AGB are also used to evaluate feasibility of models developed for large scale in applying to small area. The results show that (1 the differences in biomass were relatively large among the 5 sample areas of alpine meadow grassland in the study area during 2013-2016, with the maximum and minimum biomass values of 3,963 kg DW/ha and 745.5 kg DW/ha, respectively, and mean value of 1,907.7 kg DW/ha; the mean of EVI value range (0.42-0.60 are slightly smaller than the NDVI’s (0.59-0.75; (2 the optimum estimation model of grassland AGB in the study area is the exponential model based on MODIS EVI, with root mean square error of 656.6 kg DW/ha and relative estimation errors (REE of 36.3%; (3 the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, the Gannan Prefecture, and Xiahe County are higher than those directly constructed based on the small area of this study by 9.5%–31.7%, with the increase of the modeling study area scales, the REE increasing as well. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing

  11. Noise Characterization and Performance of MODIS Thermal Emissive Bands

    Science.gov (United States)

    Madhavan, Sriharsha; Xiong, Xiaoxiong; Wu, Aisheng; Wenny, Brian; Chiang, Kwofu; Chen, Na; Wang, Zhipeng; Li, Yonghong

    2016-01-01

    The MODerate-resolution Imaging Spectroradiometer (MODIS) is a premier Earth-observing sensor of the early 21st century, flying onboard the Terra (T) and Aqua (A) spacecraft. Both instruments far exceeded their six-year design life and continue to operate satisfactorily for more than 15 and 13 years, respectively. The MODIS instrument is designed to make observations at nearly a 100% duty cycle covering the entire Earth in less than two days. The MODIS sensor characteristics include a spectral coverage from 0.41micrometers to 14.4 micrometers, of which those wavelengths ranging from 3.7 micrometers to 14.4 micrometers cover the thermal infrared region which is interspaced in 16 thermal emissive bands (TEBs). Each of the TEB contains ten detectors which record samples at a spatial resolution of 1 km. In order to ensure a high level of accuracy for the TEB-measured top-of-atmosphere radiances, an onboard blackbody (BB) is used as the calibration source. This paper reports the noise characterization and performance of the TEB on various counts. First, the stability of the onboard BB is evaluated to understand the effectiveness of the calibration source. Next, key noise metrics such as the noise equivalent temperature difference and the noise equivalent dn difference (NEdN) for the various TEBs are determined from multiple temperature sources. These sources include the nominally controlled BB temperature of 290 K for T-MODIS and 285 K for A-MODIS, as well as a BB warm up-cool down cycle that is performed over a temperature range from roughly 270 to 315 K. The space-view port that measures the background signal serves as a viable cold temperature source for measuring noise. In addition, a well characterized Earth-view target, the Dome Concordia site located in the Antarctic plateau, is used for characterizing the stability of the sensor, indirectly providing a measure of the NEdN. Based on this rigorous characterization, a list of the noisy and inoperable detectors for

  12. Volcanic ash detection and retrievals using MODIS data by means of neural networks

    Directory of Open Access Journals (Sweden)

    M. Picchiani

    2011-12-01

    Full Text Available Volcanic ash clouds detection and retrieval represent a key issue for aviation safety due to the harming effects on aircraft. A lesson learned from the recent Eyjafjallajokull eruption is the need to obtain accurate and reliable retrievals on a real time basis.

    In this work we have developed a fast and accurate Neural Network (NN approach to detect and retrieve volcanic ash cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS data in the Thermal InfraRed (TIR spectral range. Some measurements collected during the 2001, 2002 and 2006 Mt. Etna volcano eruptions have been considered as test cases.

    The ash detection and retrievals obtained from the Brightness Temperature Difference (BTD algorithm are used as training for the NN procedure that consists in two separate steps: ash detection and ash mass retrieval. The ash detection is reduced to a classification problem by identifying two classes: "ashy" and "non-ashy" pixels in the MODIS images. Then the ash mass is estimated by means of the NN, replicating the BTD-based model performances. A segmentation procedure has also been tested to remove the false ash pixels detection induced by the presence of high meteorological clouds. The segmentation procedure shows a clear advantage in terms of classification accuracy: the main drawback is the loss of information on ash clouds distal part.

    The results obtained are very encouraging; indeed the ash detection accuracy is greater than 90%, while a mean RMSE equal to 0.365 t km−2 has been obtained for the ash mass retrieval. Moreover, the NN quickness in results delivering makes the procedure extremely attractive in all the cases when the rapid response time of the system is a mandatory requirement.

  13. Global analysis of cloud field coverage and radiative properties, using morphological methods and MODIS observations

    Directory of Open Access Journals (Sweden)

    R. Z. Bar-Or

    2011-01-01

    Full Text Available The recently recognized continuous transition zone between detectable clouds and cloud-free atmosphere ("the twilight zone" is affected by undetectable clouds and humidified aerosol. In this study, we suggest to distinguish cloud fields (including the detectable clouds and the surrounding twilight zone from cloud-free areas, which are not affected by clouds. For this classification, a robust and simple-to-implement cloud field masking algorithm which uses only the spatial distribution of clouds, is presented in detail. A global analysis, estimating Earth's cloud field coverage (50° S–50° N for 28 July 2008, using the Moderate Resolution Imaging Spectroradiometer (MODIS data, finds that while the declared cloud fraction is 51%, the global cloud field coverage reaches 88%. The results reveal the low likelihood for finding a cloud-free pixel and suggest that this likelihood may decrease as the pixel size becomes larger. A global latitudinal analysis of cloud fields finds that unlike oceans, which are more uniformly covered by cloud fields, land areas located under the subsidence zones of the Hadley cell (the desert belts, contain proper areas for investigating cloud-free atmosphere as there is 40–80% probability to detect clear sky over them. Usually these golden-pixels, with higher likelihood to be free of clouds, are over deserts. Independent global statistical analysis, using MODIS aerosol and cloud products, reveals a sharp exponential decay of the global mean aerosol optical depth (AOD as a function of the distance from the nearest detectable cloud, both above ocean and land. Similar statistical analysis finds an exponential growth of mean aerosol fine-mode fraction (FMF over oceans when the distance from the nearest cloud increases. A 30 km scale break clearly appears in several analyses here, suggesting this is a typical natural scale of cloud fields. This work shows different microphysical and optical properties of cloud fields

  14. Remote Sensing of Leaf Area Index from LiDAR Height Percentile Metrics and Comparison with MODIS Product in a Selectively Logged Tropical Forest Area in Eastern Amazonia

    Directory of Open Access Journals (Sweden)

    Yonghua Qu

    2018-06-01

    Full Text Available Leaf area index (LAI is an important parameter to describe the capacity of forests to intercept light and thus affects the microclimate and photosynthetic capacity of canopies. In general, tropical forests have a higher leaf area index and it is a challenge to estimate LAI in a forest with a very dense canopy. In this study, it is assumed that the traditional Light Detection and Ranging (LiDAR-derived fractional vegetation cover (fCover has weak relationship with leaf area index in a dense forest. We propose a partial least squares (PLS regression model using the height percentile metrics derived from airborne LiDAR data to estimate the LAI of a dense forest. Ground inventory and airborne LiDAR data collected in a selectively logged tropical forest area in Eastern Amazonia are used to map LAI from the plot level to the landscape scale. The results indicate that the fCover, derived from the first return or the last return, has no significant correlations with the ground-based LAI. The PLS model evaluated by the leave-one-out validation shows that the estimated LAI is significantly correlated with the ground-based LAI with an R2 of 0.58 and a root mean square error (RMSE of 1.13. A data comparison indicates that the Moderate Resolution Imaging Spectrometer (MODIS LAI underestimates the landscape-level LAI by about 22%. The MODIS quality control data show that in the selected tile, the cloud state is not the primary factor affecting the MODIS LAI performance; rather, the LAI from the main radiative transfer (RT algorithm contributes much to the underestimation of the LAI in the tropical forest. In addition, the results show that the LiDAR-based LAI has a better response to the logging activities than the MODIS-based LAI, and that the leaf area reduction caused by logging is about 13%. In contrast, the MODIS-based LAI exhibits no apparent spatial correlation with the LiDAR-based LAI. It is suggested that the main algorithm of MODIS should be

  15. No novel, high penetrant gene might remain to be found in Japanese patients with unknown MODY.

    Science.gov (United States)

    Horikawa, Yukio; Hosomichi, Kazuyoshi; Enya, Mayumi; Ishiura, Hiroyuki; Suzuki, Yutaka; Tsuji, Shoji; Sugano, Sumio; Inoue, Ituro; Takeda, Jun

    2018-07-01

    MODY 5 and 6 have been shown to be low-penetrant MODYs. As the genetic background of unknown MODY is assumed to be similar, a new analytical strategy is applied here to elucidate genetic predispositions to unknown MODY. We examined to find whether there are major MODY gene loci remaining to be identified using SNP linkage analysis in Japanese. Whole-exome sequencing was performed with seven families with typical MODY. Candidates for novel MODY genes were examined combined with in silico network analysis. Some peaks were found only in either parametric or non-parametric analysis; however, none of these peaks showed a LOD score greater than 3.7, which is approved to be the significance threshold of evidence for linkage. Exome sequencing revealed that three mutated genes were common among 3 families and 42 mutated genes were common in two families. Only one of these genes, MYO5A, having rare amino acid mutations p.R849Q and p.V1601G, was involved in the biological network of known MODY genes through the intermediary of the INS. Although only one promising candidate gene, MYO5A, was identified, no novel, high penetrant MODY genes might remain to be found in Japanese MODY.

  16. Maturity-onset diabetes of the young (MODY): how many cases are we missing?

    Science.gov (United States)

    Shields, B M; Hicks, S; Shepherd, M H; Colclough, K; Hattersley, A T; Ellard, S

    2010-12-01

    Maturity-onset diabetes of the young is frequently misdiagnosed as type 1 or type 2 diabetes. A correct diagnosis of MODY is important for determining treatment, but can only be confirmed by molecular genetic testing. We aimed to compare the regional distribution of confirmed MODY cases in the UK and to estimate the minimum prevalence. UK referrals for genetic testing in 2,072 probands and 1,280 relatives between 1996 and 2009 were examined by region, country and test result. Referral rate and prevalence were calculated using UK Census 2001 figures. MODY was confirmed in 1,177 (35%) patients, with HNF1A (52%) and GCK mutations (32%) being most frequent in probands confirmed with MODY. There was considerable regional variation in proband referral rates (from 50 per million for South West England and Scotland) and patients diagnosed with MODY (5.3 per million in Northern Ireland, 48.9 per million in South West England). Referral rates and confirmed cases were highly correlated (r = 0.96, p MODY was estimated to be 108 cases per million. Assuming this minimal prevalence throughout the UK then >80% of MODY is not diagnosed by molecular testing. The marked regional variation in the prevalence of confirmed MODY directly results from differences in referral rates. This could reflect variation in awareness of MODY or unequal access to genetic testing. Increased referral for diagnostic testing is required if the majority of MODY patients are to have the genetic diagnosis necessary for optimal treatment.

  17. High-sensitivity CRP discriminates HNF1A-MODY from other subtypes of diabetes.

    Science.gov (United States)

    McDonald, Tim J; Shields, Beverley M; Lawry, Jane; Owen, Katharine R; Gloyn, Anna L; Ellard, Sian; Hattersley, Andrew T

    2011-08-01

    Maturity-onset diabetes of the young (MODY) as a result of mutations in hepatocyte nuclear factor 1-α (HNF1A) is often misdiagnosed as type 1 diabetes or type 2 diabetes. Recent work has shown that high-sensitivity C-reactive protein (hs-CRP) levels are lower in HNF1A-MODY than type 1 diabetes, type 2 diabetes, or glucokinase (GCK)-MODY. We aim to replicate these findings in larger numbers and other MODY subtypes. hs-CRP levels were assessed in 750 patients (220 HNF1A, 245 GCK, 54 HNF4-α [HNF4A], 21 HNF1-β (HNF1B), 53 type 1 diabetes, and 157 type 2 diabetes). hs-CRP was lower in HNF1A-MODY (median [IQR] 0.3 [0.1-0.6] mg/L) than type 2 diabetes (1.40 [0.60-3.45] mg/L; P MODY (1.45 [0.46-2.88] mg/L; P MODY (0.60 [0.30-1.80] mg/L; P MODY (0.60 [0.10-2.8] mg/L; P = 0.07). hs-CRP discriminated HNF1A-MODY from type 2 diabetes with hs-CRP MODY than other forms of diabetes and may be used as a biomarker to select patients for diagnostic HNF1A genetic testing.

  18. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

    Science.gov (United States)

    Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

    2010-01-01

    Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

  19. Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index

    Science.gov (United States)

    Nagler, Pamela L.; Glenn, Edward P.; Nguyen, Uyen; Scott, Russell; Doody, Tania

    2013-01-01

    Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI) − c], where the term (1 − e−bEVI) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

  20. Use of MODIS Images to Quantify the Radiation and Energy Balances in the Brazilian Pantanal

    Directory of Open Access Journals (Sweden)

    Antônio H. de C. Teixeira

    2015-11-01

    Full Text Available MODIS images during the year 2012 were used for modelling of the radiation and energy balance components with the application of the SAFER algorithm (Simple Algorithm for Evapotranspiration Retrieving in the Brazilian Pantanal area. Pixels from the main sub-regions of Barão de Melgaço (BR, Paiaguás (PA and Nhecolândia (NH were extracted in order to process microclimatic comparisons. In general, the net radiation (Rn relied much more on the global solar radiation (RG levels than on water conditions and ecosystem types, in accordance with the low Rn standard deviation values. The fraction of the available energy used as latent heat flux (λE were, on average, 65, 50 and 49% for the BR, PA and NH sub-regions, respectively. Horizontal heat advection, identified by the negative values of sensible heat flux (H, made several pixels with λE values higher than those for Rn in the middle of the year. Taking the evaporative fraction (Ef as a surface moisture indicator, the Tree-Lined Savanna (TLS was considered the moister ecosystem class, with 58% of the available energy being used as λE, while the driest one was the modified ecosystem Anthropogenic Changes (AC, presenting a λE/Rn fraction of 0.46. According to the spatial and temporal consistencies, and after comparisons with other previous point and large-scale studies, the SAFER algorithm proved to have sensibility to quantify and compare the large-scale radiation and energy balance components in the different ecosystems of the Brazilian Pantanal. The algorithm is useful for monitoring the energy exchange dynamics among the different terrestrial and aquatic ecosystem types throughout the seasons of the year.

  1. Estimating Riparian and Agricultural Actual Evapotranspiration by Reference Evapotranspiration and MODIS Enhanced Vegetation Index

    Directory of Open Access Journals (Sweden)

    Russell L. Scott

    2013-08-01

    Full Text Available Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa based on the Enhanced Vegetation Index (EVI from the Moderate Resolution Imaging Spectrometer (MODIS sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo. The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI − c], where the term (1 − e−bEVI is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73. It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89 difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

  2. IceMap250—Automatic 250 m Sea Ice Extent Mapping Using MODIS Data

    Directory of Open Access Journals (Sweden)

    Charles Gignac

    2017-01-01

    Full Text Available The sea ice cover in the North evolves at a rapid rate. To adequately monitor this evolution, tools with high temporal and spatial resolution are needed. This paper presents IceMap250, an automatic sea ice extent mapping algorithm using MODIS reflective/emissive bands. Hybrid cloud-masking using both the MOD35 mask and a visibility mask, combined with downscaling of Bands 3–7 to 250 m, are utilized to delineate sea ice extent using a decision tree approach. IceMap250 was tested on scenes from the freeze-up, stable cover, and melt seasons in the Hudson Bay complex, in Northeastern Canada. IceMap250 first product is a daily composite sea ice presence map at 250 m. Validation based on comparisons with photo-interpreted ground-truth show the ability of the algorithm to achieve high classification accuracy, with kappa values systematically over 90%. IceMap250 second product is a weekly clear sky map that provides a synthesis of 7 days of daily composite maps. This map, produced using a majority filter, makes the sea ice presence map even more accurate by filtering out the effects of isolated classification errors. The synthesis maps show spatial consistency through time when compared to passive microwave and national ice services maps.

  3. Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia

    Science.gov (United States)

    de Oliveira, Gabriel; Brunsell, Nathaniel A.; Moraes, Elisabete C.; Bertani, Gabriel; dos Santos, Thiago V.; Shimabukuro, Yosio E.; Aragão, Luiz E. O. C.

    2016-01-01

    In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001–December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance. PMID:27347957

  4. Comparison of Different GPP Models in China Using MODIS Image and ChinaFLUX Data

    Directory of Open Access Journals (Sweden)

    Zhengjia Liu

    2014-10-01

    Full Text Available Accurate quantification of gross primary production (GPP at regional and global scales is essential for carbon budgets and climate change studies. Five models, the vegetation photosynthesis model (VPM, the temperature and greenness model (TG, the alpine vegetation model (AVM, the greenness and radiation model (GR, and the MOD17 algorithm, were tested and calibrated at eight sites in China during 2003–2005. Results indicate that the first four models provide more reliable GPP estimation than MOD17 products/algorithm, although MODIS GPP products show better performance in grasslands, croplands, and mixed forest (MF. VPM and AVM produce better estimates in forest sites (R2 = 0.68 and 0.67, respectively; AVM and TG models show satisfactory GPP estimates for grasslands (R2 = 0.91 and 0.9, respectively. In general, the VPM model is the most suitable model for GPP estimation for all kinds of land cover types in China, with R2 higher than 0.34 and root mean square error (RMSE lower than 48.79%. The relationships between eddy CO2 flux and model parameters (Enhanced Vegetation Index (EVI, photosynthetically active radiation (PAR, land surface temperature (LST, air temperature, and Land Surface Water Index (LSWI are further analyzed to investigate the model’s application to various land cover types, which will be of great importance for studying the effects of climatic factors on ecosystem performances.

  5. Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia.

    Science.gov (United States)

    de Oliveira, Gabriel; Brunsell, Nathaniel A; Moraes, Elisabete C; Bertani, Gabriel; Dos Santos, Thiago V; Shimabukuro, Yosio E; Aragão, Luiz E O C

    2016-06-24

    In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001-December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance.

  6. Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data.

    Science.gov (United States)

    Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

    2015-09-18

    Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate daily synthetic Landsat imagery. This algorithm was designed to avoid the limitations of the conditional spatial temporal data fusion approach (STDFA) including the constant window for disaggregation and the sensor difference. An adaptive window size selection method is proposed in this study to select the best window size and moving steps for the disaggregation of coarse pixels. The linear regression method is used to remove the influence of differences in sensor systems using disaggregated mean coarse reflectance by testing and validation in two study areas located in Xinjiang Province, China. The results show that the MSTDFA algorithm can generate daily synthetic Landsat imagery with a high correlation coefficient (R) ranged from 0.646 to 0.986 between synthetic images and the actual observations. We further show that MSTDFA can be applied to 250 m 16-day MODIS MOD13Q1 products and the Landsat Normalized Different Vegetation Index (NDVI) data by generating a synthetic NDVI image highly similar to actual Landsat NDVI observation with a high R of 0.97.

  7. Evaluating land cover changes in Eastern and Southern Africa from 2000 to 2010 using validated Landsat and MODIS data

    Science.gov (United States)

    Al-Hamdan, Mohammad Z.; Oduor, Phoebe; Flores, Africa I.; Kotikot, Susan M.; Mugo, Robinson; Ababu, Jaffer; Farah, Hussein

    2017-10-01

    In this study, we assessed land cover land use (LCLU) changes and their potential environmental drivers (i.e., precipitation, temperature) in five countries in Eastern & Southern (E&S) Africa (Rwanda, Botswana, Tanzania, Malawi and Namibia) between 2000 and 2010. Landsat-derived LCLU products developed by the Regional Centre for Mapping of Resources for Development (RCMRD) through the SERVIR (Spanish for ;to serve;) program, a joint initiative of NASA and USAID, and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to evaluate and quantify the LCLU changes in these five countries. Given that the original development of the MODIS land cover type standard products included limited training sites in Africa, we performed a two-level verification/validation of the MODIS land cover product in these five countries. Precipitation data from CHIRPS dataset were used to evaluate and quantify the precipitation changes in these countries and see if it was a significant driver behind some of these LCLU changes. MODIS Land Surface Temperature (LST) data were also used to see if temperature was a main driver too. Our validation analysis revealed that the overall accuracies of the regional MODIS LCLU product for this African region alone were lower than that of the global MODIS LCLU product overall accuracy (63-66% vs. 75%). However, for countries with uniform or homogenous land cover, the overall accuracy was much higher than the global accuracy and as high as 87% and 78% for Botswana and Namibia, respectively. In addition, the wetland and grassland classes had the highest user's accuracies in most of the countries (89%-99%), which are the ones with the highest number of MODIS land cover classification algorithm training sites. Our LCLU change analysis revealed that Botswana's most significant changes were the net reforestation, net grass loss and net wetland expansion. For Rwanda, although there have been significant forest, grass and crop expansions in

  8. MODIS GPP/NPP for complex land use area: a case study of comparison between MODIS GPP/NPP and ground-based measurements over Korea

    Science.gov (United States)

    Shim, C.

    2013-12-01

    The Moderate Resolution Imaging Radiometer (MODIS) Gross Primary Productivity (GPP)/Net Primary Productivity (NPP) has been widely used for the study on global terrestrial ecosystem and carbon cycle. The current MODIS product with ~ 1 km spatial resolution, however, has limitation on the information on local scale environment (fairly comparable values of the MODIS here however, cannot assure the quality of the MOD17 over the complex vegetation area of Korea since the ground measurements except the eddy covariance tower flux measurements are highly inconsistent. Therefore, the comprehensive experiments to represents GPP/NPP over diverse vegetation types for a comparable scale of MODIS with a consistent measurement technique are necessary in order to evaluate the MODIS vegetation productivity data over Korea, which contains a large portion of highly heterogeneous vegetation area.

  9. Remote sensing of aerosols by synergy of caliop and modis

    Directory of Open Access Journals (Sweden)

    Kudo Rei

    2018-01-01

    Full Text Available For the monitoring of the global 3-D distribution of aerosol components, we developed the method to retrieve the vertical profiles of water-soluble, light absorbing carbonaceous, dust, and sea salt particles by the synergy of CALIOP and MODIS data. The aerosol product from the synergistic method is expected to be better than the individual products of CALIOP and MODIS. We applied the method to the biomass-burning event in Africa and the dust event in West Asia. The reasonable results were obtained; the much amount of the water-soluble and light absorbing carbonaceous particles were estimated in the biomass-burning event, and the dust particles were estimated in the dust event.

  10. Investigation of Cloud Properties and Atmospheric Profiles with MODIS

    Science.gov (United States)

    Menzel, Paul; Ackerman, Steve; Moeller, Chris; Gumley, Liam; Strabala, Kathy; Frey, Richard; Prins, Elaine; LaPorte, Dan; Wolf, Walter

    1997-01-01

    The WINter Cloud Experiment (WINCE) was directed and supported by personnel from the University of Wisconsin in January and February. Data sets of good quality were collected by the MODIS Airborne Simulator (MAS) and other instruments on the NASA ER2; they will be used to develop and validate cloud detection and cloud property retrievals over winter scenes (especially over snow). Software development focused on utilities needed for all of the UW product executables; preparations for Version 2 software deliveries were almost completed. A significant effort was made, in cooperation with SBRS and MCST, in characterizing and understanding MODIS PFM thermal infrared performance; crosstalk in the longwave infrared channels continues to get considerable attention.

  11. Remote sensing of aerosols by synergy of caliop and modis

    Science.gov (United States)

    Kudo, Rei; Nishizawa, Tomoaki; Higurashi, Akiko; Oikawa, Eiji

    2018-04-01

    For the monitoring of the global 3-D distribution of aerosol components, we developed the method to retrieve the vertical profiles of water-soluble, light absorbing carbonaceous, dust, and sea salt particles by the synergy of CALIOP and MODIS data. The aerosol product from the synergistic method is expected to be better than the individual products of CALIOP and MODIS. We applied the method to the biomass-burning event in Africa and the dust event in West Asia. The reasonable results were obtained; the much amount of the water-soluble and light absorbing carbonaceous particles were estimated in the biomass-burning event, and the dust particles were estimated in the dust event.

  12. Mapping soil degradation by topsoil grain size using MODIS data

    OpenAIRE

    XIAO, Jieying; SHEN, Yanjun; TATEISHI, Ryutaro

    2005-01-01

    [ABSTRACT] MODIS BRDF reflectance data at the end of April 2004 was selected to make a desertification map base on topsoil grain size by using Gain Size Index at arid and semiarid Asia. After data processing, GSI was applied into desertification mapping, and we find that high GSI area distributed at the desert and its’ marginal area, degraded grassland, desert steppe. The desertification map was output according to the correlation between GSI and grain size distribution, the classification of...

  13. Land cover mapping of Greater Mesoamerica using MODIS data

    Science.gov (United States)

    Giri, Chandra; Jenkins, Clinton N.

    2005-01-01

    A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

  14. CHARACTERISING VEGETATED SURFACES USING MODIS MULTIANGULAR SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    G. McCamley

    2012-07-01

    Full Text Available Bidirectional Reflectance Distribution Functions (BRDF seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value. The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km2. The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model. The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS. The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived

  15. Validation of MODIS FLH and In Situ Chlorophyll a from Tampa Bay, Florida (USA)

    Science.gov (United States)

    Fischer, Andrew; MorenoMadrinan, Max J.

    2012-01-01

    FLH and in situ chla measurements increases with increasing distance between monitoring sites and structures like bridges and shore. Due probably to confounding factors, expected improvement in the FLH- chla relationship was not clearly noted when increasing depth and distance from shore alone (not including bridges). Correlations between turbidity and nutrient concentrations are discussed further and principle component analyses are employed to address the relationships between the multivariate data sets. A thorough understanding of how satellite FLH algorithms relate to in situ water quality parameters will enhance our understanding of how MODIS s global FLH algorithm can be used empirically to monitor coastal waters worldwide.

  16. Comprehensive genomic analysis identifies pathogenic variants in maturity-onset diabetes of the young (MODY) patients in South India.

    Science.gov (United States)

    Mohan, Viswanathan; Radha, Venkatesan; Nguyen, Thong T; Stawiski, Eric W; Pahuja, Kanika Bajaj; Goldstein, Leonard D; Tom, Jennifer; Anjana, Ranjit Mohan; Kong-Beltran, Monica; Bhangale, Tushar; Jahnavi, Suresh; Chandni, Radhakrishnan; Gayathri, Vijay; George, Paul; Zhang, Na; Murugan, Sakthivel; Phalke, Sameer; Chaudhuri, Subhra; Gupta, Ravi; Zhang, Jingli; Santhosh, Sam; Stinson, Jeremy; Modrusan, Zora; Ramprasad, V L; Seshagiri, Somasekar; Peterson, Andrew S

    2018-02-13

    Maturity-onset diabetes of the young (MODY) is an early-onset, autosomal dominant form of non-insulin dependent diabetes. Genetic diagnosis of MODY can transform patient management. Earlier data on the genetic predisposition to MODY have come primarily from familial studies in populations of European origin. In this study, we carried out a comprehensive genomic analysis of 289 individuals from India that included 152 clinically diagnosed MODY cases to identify variants in known MODY genes. Further, we have analyzed exome data to identify putative MODY relevant variants in genes previously not implicated in MODY. Functional validation of MODY relevant variants was also performed. We found MODY 3 (HNF1A; 7.2%) to be most frequently mutated followed by MODY 12 (ABCC8; 3.3%). They together account for ~ 11% of the cases. In addition to known MODY genes, we report the identification of variants in RFX6, WFS1, AKT2, NKX6-1 that may contribute to development of MODY. Functional assessment of the NKX6-1 variants showed that they are functionally impaired. Our findings showed HNF1A and ABCC8 to be the most frequently mutated MODY genes in south India. Further we provide evidence for additional MODY relevant genes, such as NKX6-1, and these require further validation.

  17. Synergetic use of Aerosol Robotic Network (AERONET) and Moderate Image Spectrometer (MODIS)

    Science.gov (United States)

    Kaufman, Y.

    2004-01-01

    I shall describe several distinct modes in which AERONET data are used in conjunction with MODIS data to evaluate the global aerosol system and its impact on climate. These includes: 1) Evaluation of the aerosol diurnal cycle not available from MODIS, and the relationship between the aerosol properties derived from MODIS and the daily average of these properties; 2) Climatology of the aerosol size distribution and single scattering albedo. The climatology is used to formulate the assumptions used in the MODIS look up tables used in the inversion of MODIS data; 3) Measurement of the aerosol effect on irradiation of the surface, this is used in conjunction with the MODIS evaluation of the aerosol effect at the TOA; and 4) Assessment of the aerosol baseline on top off which the satellite data are used to find the amount of dust or anthropogenic aerosol.

  18. Comparison of SeaWiFS and MODIS time series of inherent optical properties for the Adriatic Sea

    Directory of Open Access Journals (Sweden)

    F. Mélin

    2011-05-01

    Full Text Available Time series of inherent optical properties (IOPs derived from SeaWiFS and MODIS are compared for the Adriatic Sea. The IOPs are outputs of the Quasi-Analytical Algorithm and include total absorption a, phytoplankton absorption aph, absorption associated with colored detrital material (CDM acdm, and particle backscattering coefficient bbp. The average root-mean square difference Δ computed for log-transformed distributions decreases for $a$ from 0.084 at 412 nm to 0.052 at 490 nm, is higher for aph(443 (0.149 than for acdm(443 (0.071, and is approximately 0.165 for bbp at various wavelengths. The SeaWiFS a at 443 and 490 nm, aph at 443 nm and bbp are on average higher than the MODIS counterparts. Statistics show significant variations in space and time. There is an overall increasing gradient for Δ associated with the absorption terms from the open southern and central Adriatic to the northwest part of the basin, and a reversed gradient for the particulate backscattering coefficient. For time series analysis, only a(412 and acdm(443 currently present an unbiased continuity bridging the SeaWiFS and MODIS periods for the Adriatic Sea.

  19. Comparison of bio-physical marine products from SeaWiFS, MODIS and a bio-optical model with in situ measurements from Northern European waters

    Science.gov (United States)

    Blondeau-Patissier, D.; Tilstone, G. H.; Martinez-Vicente, V.; Moore, G. F.

    2004-09-01

    In this paper, we compare bio-physical marine products from SeaWiFS, MODIS and a novel bio-optical absorption model with in situ measurements of chlorophyll-a (Chla) concentrations, total suspended material (TSM) concentrations, normalized water-leaving radiances (nLw) and absorption coefficients of coloured dissolved organic matter (aCDOM), total particulate (atotal) and phytoplankton (aphy) for 26 satellite match-ups in three Northern European seas. Cruises were undertaken in 2002 and 2003 in phytoplankton dominated open ocean waters of the Celtic Sea and optically complex waters of the Western English Channel (WEC) and North Sea. For all environments, Chla concentrations varied from 0.4 to 7.8 mg m-3, TSM from 0.2 to 6.0 mg l-1 and aCDOM at 440 nm from 0.02 to 0.30 m-1. SeaWiFS OC4v4, with the Remote Sensing Data Analysis Service (RSDAS) atmospheric correction for turbid waters, showed the most accurate retrieval of in situ Chla (RMS = 0.24; n = 26), followed by MODIS chlor_a_3 (RMS = 0.40; n = 26). This suggested that improving the atmospheric correction over optically complex waters results in more accurate Chla concentrations compared to those obtained using more complicated Chla algorithms. We found that the SeaWiFS OC4v4 and the MODIS chlor_a_2 switching band ratio algorithms, which mainly use longer wavebands than 443 nm, were less affected by CDOM. They were both more accurate than chlor_MODIS in the higher CDOM waters of the North Sea. Compared to MODIS the absorption model was better at retrieving atotal (RMS = 0.39; n = 78) and aCDOM (RMS = 0.79; n = 12) in all study areas and TSM in the WEC (RMS = 0.04; n = 10) but it underestimated Chla concentrations (RMS = 0.45; n = 26). The results are discussed in terms of atmospheric correction, sensor characteristics and the functioning and performance of Chla algorithms. This paper was presented at the Institute of Physics Meeting on Underwater Optics held during Photonex 03 at Warwick, UK, in October 2003

  20. Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET

    Science.gov (United States)

    Mishchenko, Michael I.; Liu, Li; Geogdzhayev, Igor V.; Travis, Larry D.; Cairns, Brian; Lacis, Andrew A.

    2010-01-01

    We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

  1. [Clinical parameters for molecular testing of Maturity Onset Diabetes of the Young (MODY)].

    Science.gov (United States)

    Datz, N; Nestoris, C; von Schütz, W; Danne, T; Driesel, A J; Maringa, M; Kordonouri, O

    2011-05-01

    Monogenic forms of diabetes are often diagnosed by chance, due to the variety of clinical presentation and limited experience of the diabetologists with this kind of diabetes. Aim of this study was to evaluate clinical parameters for an efficient screening. Clinical parameters were: negative diabetes-specific antibodies at onset of diabetes, positive family history of diabetes, and low to moderate insulin requirements after one year of diabetes treatment. Molecular testing was performed through sequencing of the programming regions of HNF-4alpha (MODY 1), glucokinase (MODY 2) and HNF-1alpha/TCF1 (MODY 3) and in one patient the HNF-1beta/TCF2 region (MODY 5). 39 of 292 patients treated with insulin were negative for GADA and IA2A, and 8 (20.5%) patients fulfilled both other criteria. Positive molecular results were found in five (63%) patients (two with MODY 2, two with MODY 3, one with MODY 5). At diabetes onset, the mean age of the 5 patients with MODY was 10.6 ± 5.3 yrs (range 2.6-15 yrs), HbA(1c) was 8.4 ± 3.1 % (6.5-13.9%), mean diabetes duration until diagnosis of MODY was 3.3 ± 3.6 yrs (0.8-9.6 yrs) with insulin requirements of 0.44 ± 0.17 U/kg/d (0.2-0.6 U/kg/d). Patients with MODY 3 were changed from insulin to repaglinide, those with MODY 2 were recommended discontinuing insulin treatment. In patients with negative diabetes-specific antibodies at onset of diabetes, with a positive family history, and low to moderate insulin needs a genetic screening for MODY is indicated. Watchful consideration of these clinical parameters may lead to an early genetic testing, and to an adequate treatment. © Georg Thieme Verlag KG Stuttgart · New York.

  2. Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data

    OpenAIRE

    Zhang, Hu; Jiao, Ziti; Dong, Yadong; Li, Xiaowen

    2015-01-01

    Bidirectional reflectance distribution function (BRDF) archetypes extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo product over the global Earth Observing System Land Validation Core Sites can be used to simplify BRDF models. The present study attempts to evaluate the representativeness of BRDF archetypes for surface reflectance anisotropy. Five-year forward-modeled MODIS multi-angular reflectance (MCD-ref) and aditional actual MODIS multi-angular observat...

  3. A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

    Directory of Open Access Journals (Sweden)

    Yadvinder S. Malhi

    2012-03-01

    Full Text Available Evapotranspiration (ET plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE yielded r 2= 0.64 and r2 = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r 2 = 0.76 and r2 = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km2 (r2 = 0.88. Inputs to which the algorithm is most sensitive are vegetation index (NDVI, gradient of temperature (dT to compute sensible heat flux (H and net radiation (Rn. It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

  4. A MODIS direct broadcast algorithm for mapping wildfire burned area in the western United States

    Science.gov (United States)

    S. P. Urbanski; J. M. Salmon; B. L. Nordgren; W. M. Hao

    2009-01-01

    Improved wildland fire emission inventory methods are needed to support air quality forecasting and guide the development of air shed management strategies. Air quality forecasting requires dynamic fire emission estimates that are generated in a timely manner to support real-time operations. In the regulatory and planning realm, emission inventories are essential for...

  5. A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion

    NARCIS (Netherlands)

    Gevaert, C.M.; Garcia-Haro, F.J.

    2015-01-01

    The focus of the current study is to compare data fusion methods applied to sensors with medium- and high-spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to

  6. Development and validation of a MODIS colored dissolved organic matter (CDOM) algorithm in northwest Florida estuaries

    Science.gov (United States)

    Satellite remote sensing provides synoptic and frequent monitoring of water quality parameters that aids in determining the health of aquatic ecosystems and the development of effective management strategies. Northwest Florida estuaries are classified as optically-complex, or wat...

  7. N-MODY: A Code for Collisionless N-body Simulations in Modified Newtonian Dynamics

    Science.gov (United States)

    Londrillo, Pasquale; Nipoti, Carlo

    2011-02-01

    N-MODY is a parallel particle-mesh code for collisionless N-body simulations in modified Newtonian dynamics (MOND). N-MODY is based on a numerical potential solver in spherical coordinates that solves the non-linear MOND field equation, and is ideally suited to simulate isolated stellar systems. N-MODY can be used also to compute the MOND potential of arbitrary static density distributions. A few applications of N-MODY indicate that some astrophysically relevant dynamical processes are profoundly different in MOND and in Newtonian gravity with dark matter.

  8. Substantial proportion of MODY among multiplex families participating in a Type 1 diabetes prediction programme.

    Science.gov (United States)

    Petruzelkova, L; Dusatkova, P; Cinek, O; Sumnik, Z; Pruhova, S; Hradsky, O; Vcelakova, J; Lebl, J; Kolouskova, S

    2016-12-01

    Patients with maturity-onset diabetes of the young (MODY) might be over-represented in families with histories of Type 1 diabetes. Our aim was to re-evaluate families participating in the Czech T1D Prediction Programme (PREDIA.CZ) with at least two members affected with diabetes to assess the proportion of MODY among these families and determine its most significant clinical predictors. Of the 557 families followed up by the PREDIA.CZ, 53 (9.5%) had two or more family members with diabetes. One proband with diabetes from these families was chosen for direct sequencing of the GCK, HNF1A, HNF4A and INS genes. Non-parametric tests and a linear logistic regression model were used to evaluate differences between MODY and non-MODY families. MODY was genetically diagnosed in 24 of the 53 families with multiple occurrences of diabetes (45%). Mutations were detected most frequently in GCK (58%), followed by HNF1A (38%) and INS (4%). MODY families were more likely to have a parent with diabetes and had a higher proportion of females with diabetes than non-MODY families. Higher age (P MODY families already presenting with diabetes. A prediction programme for Type 1 diabetes would provide a useful new source of patients with MODY most likely to benefit from an accurate diagnosis. This identification has implications for patient treatment and disease prognosis. © 2015 Diabetes UK.

  9. A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction

    OpenAIRE

    Chiman Kwan; Bence Budavari; Feng Gao; Xiaolin Zhu

    2018-01-01

    We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution, whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images to yield high spatial and high temporal resolution images. Our approach consists of two steps. First, a mapping is established between two MODIS images, where one is at an earlier time, t1, and the...

  10. SAFARI 2000 MODIS Airborne Simulator Data, Southern Africa, Dry Season 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset contains the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) multispectral data collected during the SAFARI 2000 project....

  11. MODIS/Terra Vegetation Indices Monthly L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  12. MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  13. MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  14. MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  15. MODIS/Terra Vegetation Indices 16-Day L3 Global 500m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  16. MODIS/Aqua Vegetation Indices Monthly L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  17. Identificação e mapeamento de áreas de milho na região sul do Brasil utilizando imagens MODIS Identification and mapping of maize areas in the south region of Brazil using MODIS images

    Directory of Open Access Journals (Sweden)

    José L. R. Yi

    2007-12-01

    Full Text Available O presente trabalho teve como proposta avaliar a identificação e o mapeamento das áreas de milho da região noroeste do Estado do Rio Grande do Sul a partir de dados multitemporais do sensor MODIS (Moderate Resolution Imaging Spectroradiometer a bordo do satélite Earth Observing System - EOS-AM (Terra. O algoritmo de classificação supervisionada Spectral Angle Mapper (SAM foi aplicado com sucesso em uma série multitemporal de imagens EVI pré-processadas. Verificou-se que as áreas classificadas como milho na imagem coincidiam plenamente com áreas mais extensas ou contínuas (> 90 ha de milho. Áreas de menor extensão ou localizadas em encostas de morros, ao lado de vegetação arbórea, não foram detectadas pelo classificador devido à baixa resolução espacial das imagens. A maior utilidade prática da identificação e da classificação digital das áreas de milho obtidas das imagens MODIS está na sua aplicação para isolar ou complementar o mapeamento das áreas agrícolas visando ao seu monitoramento a partir de diferentes índices de vegetação, derivados de imagens de alta resolução temporal e baixa resolução espacial.The present work had the proposal of evaluating the identification and mapping of maize areas in the northwestern region of the State of Rio Grande do Sul using multi-temporal data from MODIS (Moderate Resolution Imaging Spectroradiometer sensor on board of the Earth Observing System satellite - EOS-AM (Terra. The supervised classification algorithm Spectral Angle Mapper (SAM was successfully applied in a multi-temporal series of pre-processed EVI images. It was verified that the areas classified as maize in the image fully agree with more extensive or continuous maize areas (> 90 ha. Small or hillsides maize areas having close to shrub and wood vegetation were not detected by the classifier mainly due low spatial resolution of images. The main practical utility of maize’s areas digital classification

  18. Detecting Forest Disturbance Events from MODIS and Landsat Time Series for the Conterminous United States

    Science.gov (United States)

    Zhang, G.; Ganguly, S.; Saatchi, S. S.; Hagen, S. C.; Harris, N.; Yu, Y.; Nemani, R. R.

    2013-12-01

    Spatial and temporal patterns of forest disturbance and regrowth processes are key for understanding aboveground terrestrial vegetation biomass and carbon stocks at regional-to-continental scales. The NASA Carbon Monitoring System (CMS) program seeks key input datasets, especially information related to impacts due to natural/man-made disturbances in forested landscapes of Conterminous U.S. (CONUS), that would reduce uncertainties in current carbon stock estimation and emission models. This study provides a end-to-end forest disturbance detection framework based on pixel time series analysis from MODIS (Moderate Resolution Imaging Spectroradiometer) and Landsat surface spectral reflectance data. We applied the BFAST (Breaks for Additive Seasonal and Trend) algorithm to the Normalized Difference Vegetation Index (NDVI) data for the time period from 2000 to 2011. A harmonic seasonal model was implemented in BFAST to decompose the time series to seasonal and interannual trend components in order to detect abrupt changes in magnitude and direction of these components. To apply the BFAST for whole CONUS, we built a parallel computing setup for processing massive time-series data using the high performance computing facility of the NASA Earth Exchange (NEX). In the implementation process, we extracted the dominant deforestation events from the magnitude of abrupt changes in both seasonal and interannual components, and estimated dates for corresponding deforestation events. We estimated the recovery rate for deforested regions through regression models developed between NDVI values and time since disturbance for all pixels. A similar implementation of the BFAST algorithm was performed over selected Landsat scenes (all Landsat cloud free data was used to generate NDVI from atmospherically corrected spectral reflectances) to demonstrate the spatial coherence in retrieval layers between MODIS and Landsat. In future, the application of this largely parallel disturbance

  19. Circulating ghrelin level is higher in HNF1A-MODY and GCK-MODY than in polygenic forms of diabetes mellitus.

    Science.gov (United States)

    Nowak, Natalia; Hohendorff, Jerzy; Solecka, Iwona; Szopa, Magdalena; Skupien, Jan; Kiec-Wilk, Beata; Mlynarski, Wojciech; Malecki, Maciej T

    2015-12-01

    Ghrelin is a hormone that regulates appetite. It is likely to be involved in the pathophysiology of varying forms of diabetes. In animal studies, the ghrelin expression was regulated by the hepatocyte nuclear factor 1 alpha (HNF1A). Mutations of the HNF1A gene cause maturity onset diabetes of the young (MODY). We aimed to assess the circulating ghrelin levels in HNF1A-MODY and in other types of diabetes and to evaluate its association with HNF1A mutation status. Our cohort included 46 diabetic HNF1A gene mutation carriers, 55 type 2 diabetes (T2DM) subjects, 42 type 1 diabetes (T1DM) patients, and 31 glucokinase (GCK) gene mutation carriers with diabetes as well as 51 healthy controls. Plasma ghrelin concentration was measured using the immunoenzymatic assay with polyclonal antibody against the C-terminal fragment of its acylated and desacylated forms. Ghrelin concentrations were 0.75 ± 0.32, 0.70 ± 0.21, 0.50 ± 0.20, and 0.40 ± 0.16 ng/ml in patients with HNF1A-MODY, GCK-MODY, T1DM, and T2DM, respectively. The ghrelin levels were higher in HNF1A-MODY and GCK-MODY than in T1DM and T2DM (p MODY groups and common diabetes types remained significant. Analysis by a HNF1A mutation type indicated that ghrelin concentration is similar in patients with different types of sequence differences. Plasma ghrelin level is higher in HNF1A-MODY and GCK-MODY than in the common polygenic forms of diabetes.

  20. Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

    Science.gov (United States)

    Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

    2017-08-11

    Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

  1. NASA's MODIS/VIIRS Land Surface Temperature and Emissivity Products: Asssessment of Accuracy, Continuity and Science Uses

    Science.gov (United States)

    Hulley, G. C.; Malakar, N.; Islam, T.

    2017-12-01

    Land Surface Temperature and Emissivity (LST&E) are an important Earth System Data Record (ESDR) and Environmental Climate Variable (ECV) defined by NASA and GCOS respectively. LST&E data are key variables used in land cover/land use change studies, in surface energy balance and atmospheric water vapor retrieval models and retrievals, and in climate research. LST&E products are currently produced on a routine basis using data from the MODIS instruments on the NASA EOS platforms and by the VIIRS instrument on the Suomi-NPP platform that serves as a bridge between NASA EOS and the next-generation JPSS platforms. Two new NASA LST&E products for MODIS (MxD21) and VIIRS (VNP21) are being produced during 2017 using a new approach that addresses discrepancies in accuracy and consistency between the current suite of split-window based LST products. The new approach uses a Temperature Emissivity Separation (TES) algorithm, originally developed for the ASTER instrument, to physically retrieve both LST and spectral emissivity consistently for both sensors with high accuracy and well defined uncertainties. This study provides a rigorous assessment of accuracy of the MxD21/VNP21 products using temperature- and radiance-based validation strategies and demonstrates continuity between the products using collocated matchups over CONUS. We will further demonstrate potential science use of the new products with studies related to heat waves, monitoring snow melt dynamics, and land cover/land use change.

  2. Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

    Science.gov (United States)

    Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

    2016-03-01

    The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

  3. Algorithmic alternatives

    International Nuclear Information System (INIS)

    Creutz, M.

    1987-11-01

    A large variety of Monte Carlo algorithms are being used for lattice gauge simulations. For purely bosonic theories, present approaches are generally adequate; nevertheless, overrelaxation techniques promise savings by a factor of about three in computer time. For fermionic fields the situation is more difficult and less clear. Algorithms which involve an extrapolation to a vanishing step size are all quite closely related. Methods which do not require such an approximation tend to require computer time which grows as the square of the volume of the system. Recent developments combining global accept/reject stages with Langevin or microcanonical updatings promise to reduce this growth to V/sup 4/3/

  4. Combinatorial algorithms

    CERN Document Server

    Hu, T C

    2002-01-01

    Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9

  5. Time Series of Tropical-Forest Structure from TanDEM-X, Transformed to Time Series of Biomass by MODIS

    Science.gov (United States)

    Treuhaft, R. N.; Baccini, A.; Goncalves, F. G.; Lei, Y.; Keller, M.; Walker, W. S.

    2017-12-01

    Tropical forests account for about 50% of the world's forested biomass, and play a critical role in the control of atmospheric carbon dioxide. Large-scale (1000's of km) changes in forest structure and biomass bear on global carbon source-sink dynamics, while small-scale (phase-height observation, we show forest phase-height time series from the TanDEM-X radar interferometer at X-band (3 cm), taken with monthly and sub-hectare temporal and spatial resolution, respectively. The measurements were taken with more than 30 TanDEM-X passes over Tapajós National Forest in the Brazilian Amazon between 2011 and 2014. The transformation of phase-height rates into aboveground biomass (AGB) rates is based on the idea that the change in AGB due to a change in phase-height depends on the plot's AGB. Plots with higher AGB will produce more AGB for a given increase in height or phase-height. Postulating a power-law dependence of plot-level mass density on physical height, we previously found that the best conversion factors for transforming phase-height rate to AGB rate were indeed dependent on AGB. For 78 plots, we demonstrated AGB rates from InSAR phase-height rates using AGB from field measurements. For regional modeling of the Amazon Basin, field measurements of AGB, to specify the conversion factors, is impractical. Conversion factors from InSAR phase-height rate to AGB rate in this talk will be based on AGB derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). AGB measurement from MODIS is based on the spectral reflectance of 7 bands from the visible to short wave infrared, and auxiliary metrics describing the variance in reflectance. The mapping of MODIS reflectance to AGB is enabled by training a machine learning algorithm with lidar-derived AGB data, which are in turn trained by field measurements for small areas. The performance of TanDEM-X AGB rate from MODIS-derived conversion factors will be compared to that derived from field-based conversion

  6. Performance Evaluation of Machine Learning Methods for Leaf Area Index Retrieval from Time-Series MODIS Reflectance Data

    Science.gov (United States)

    Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang

    2017-01-01

    Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size. PMID:28045443

  7. Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes

    Science.gov (United States)

    Sayer, Andrew M.; Hsu, N. Christina; Bettenhausen, Corey; Holz, Robert E.; Lee, Jaehwa; Quinn, Greg; Veglio, Paolo

    2017-04-01

    The Visible Infrared Imaging Radiometer Suite (VIIRS) is being used to continue the record of Earth Science observations and data products produced routinely from National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. However, the absolute calibration of VIIRS's reflected solar bands is thought to be biased, leading to offsets in derived data products such as aerosol optical depth (AOD) as compared to when similar algorithms are applied to different sensors. This study presents a cross-calibration of these VIIRS bands against MODIS Aqua over dark water scenes, finding corrections to the NASA VIIRS Level 1 (version 2) reflectances between approximately +1 and -7 % (dependent on band) are needed to bring the two into alignment (after accounting for expected differences resulting from different band spectral response functions), and indications of relative trending of up to ˜ 0.35 % per year in some bands. The derived calibration gain corrections are also applied to the VIIRS reflectance and then used in an AOD retrieval, and they are shown to decrease the bias and total error in AOD across the mid-visible spectral region compared to the standard VIIRS NASA reflectance calibration. The resulting AOD bias characteristics are similar to those of NASA MODIS AOD data products, which is encouraging in terms of multi-sensor data continuity.

  8. Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

    Science.gov (United States)

    Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

    2011-12-01

    Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

  9. Improving correlations between MODIS aerosol optical thickness and ground-based PM 2.5 observations through 3D spatial analyses

    Science.gov (United States)

    Hutchison, Keith D.; Faruqui, Shazia J.; Smith, Solar

    The Center for Space Research (CSR) continues to focus on developing methods to improve correlations between satellite-based aerosol optical thickness (AOT) values and ground-based, air pollution observations made at continuous ambient monitoring sites (CAMS) operated by the Texas commission on environmental quality (TCEQ). Strong correlations and improved understanding of the relationships between satellite and ground observations are needed to formulate reliable real-time predictions of air quality using data accessed from the moderate resolution imaging spectroradiometer (MODIS) at the CSR direct-broadcast ground station. In this paper, improvements in these correlations are demonstrated first as a result of the evolution in the MODIS retrieval algorithms. Further improvement is then shown using procedures that compensate for differences in horizontal spatial scales between the nominal 10-km MODIS AOT products and CAMS point measurements. Finally, airborne light detection and ranging (lidar) observations, collected during the Texas Air Quality Study of 2000, are used to examine aerosol profile concentrations, which may vary greatly between aerosol classes as a result of the sources, chemical composition, and meteorological conditions that govern transport processes. Further improvement in correlations is demonstrated with this limited dataset using insights into aerosol profile information inferred from the vertical motion vectors in a trajectory-based forecast model. Analyses are ongoing to verify these procedures on a variety of aerosol classes using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (Calipso) lidar.

  10. Development of a High Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance with MODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China

    Directory of Open Access Journals (Sweden)

    Dongqin You

    2015-05-01

    Full Text Available A land-cover-based linear BRDF (bi-directional reflectance distribution function unmixing (LLBU algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI reflectance with the moderate resolution imaging spectroradiometer (MODIS daily reflectance product to derive the BRDF/albedo of the two sensors simultaneously in the foci experimental area (FEA of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER, which was carried out in the Heihe River basin, China. For each land cover type, an archetypal BRDF, which characterizes the shape of its anisotropic reflectance, is extracted by linearly unmixing from the MODIS reflectance with the assistance of a high-resolution classification map. The isotropic coefficients accounting for the differences within a class are derived from the CASI reflectance. The BRDF is finally determined by the archetypal BRDF and the corresponding isotropic coefficients. Direct comparisons of the cropland archetypal BRDF and CASI albedo with in situ measurements show good agreement. An indirect validation which compares retrieved BRDF/albedo with that of the MCD43A1 standard product issued by NASA and aggregated CASI albedo also suggests reasonable reliability. LLBU has potential to retrieve the high spatial resolution BRDF/albedo product for airborne and spaceborne sensors which have inadequate angular samplings. In addition, it can shorten the timescale for coarse spatial resolution product like MODIS.

  11. Autodriver algorithm

    Directory of Open Access Journals (Sweden)

    Anna Bourmistrova

    2011-02-01

    Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.

  12. Surface circulation patterns in the Gulf of California derived from MODIS Aqua 250 m

    Science.gov (United States)

    Martínez-Flores, G.; Salinas-González, F.; Gutiérrez de Velasco-Sanromán, G.; Godínez-Orta, L.

    2009-04-01

    The Gulf of California (GC) is a marginal elongated and semi-enclosed sea located at northwest of Mexico, between the Peninsula of Baja California and the mainland Mexico. The considered area average 150 km in width and 1500 km in length, from the mouth of the Colorado River to Cabo Corrientes, Jalisco. It has a maximum depth of 3600 m at the southern inlet and the northern region average 200 m in deep. The study of superficial circulation patterns in the GC is of interest because its relevance to the mechanisms of transport for distribution of a variety of materials -plankton, contaminants, microalgae, etc.- and its association with areas of sedimentary deposits, zones where there is a higher probability for fishing or related to the presence of certain species of marine life. Recent studies explain the circulation of the GC as a result of the Pacific Ocean's forcing, wind, heat fluxes on the sea surface and the interaction between the flow produced by these agents and bathymetry. The objective of this work was to obtain evidence of the patterns of surface circulation using a spatial resolution of 250 m over a period of two to seven days (depending on cloud cover), which offered images from the MODIS Level 1B. This essay is an attempt to contribute with more information to the understanding of the regional dynamics of the GC and its local influence on the zones bordering the coast. Thus, MODIS Aqua 250 m data was used, to which algorithms were applied in order to enhance the contrast of reflectance levels of these bands (0.620-0.670 and 0.841-0.876 µm) within the marine environment. The results are associated with suspended particulate matter (SPM), which we used as tracers of the surface circulation, using a sequence of images from January 2004 to December 2008. Algorithms for dust and cloud detection were used and incorporated with thermal band images, in which zones of terrigenous contribution by eolian transport were identified. Furthermore, pluvial

  13. Global cloud database from VIRS and MODIS for CERES

    Science.gov (United States)

    Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

    2003-04-01

    The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

  14. MODIS/Aqua Near Real Time (NRT) Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

  15. MODIS/Aqua Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  16. MODIS/Aqua Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  17. MODIS/Aqua Near Real Time (NRT) Thermal Anomalies/Fire 5-Min L2 Swath 1km

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

  18. MODIS/Terra Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  19. MODIS/Terra Near Real Time (NRT) Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

  20. MODIS/Aqua Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  1. MODIS/Terra Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  2. MODIS/Terra Near Real Time (NRT) Thermal Anomalies/Fire 5-Min L2 Swath 1km

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

  3. MODIS/Terra Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  4. MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG (MOD08_M3). MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am...

  5. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MYD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  6. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MOD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  7. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MYD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  8. MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  9. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MOD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  10. MODIS/Terra Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  11. MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  12. MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  13. MODIS/Terra Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  14. MODIS/Aqua Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  15. Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

    Science.gov (United States)

    Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

    2017-01-01

    The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

  16. MODY - calculation of ordered structures by symmetry-adapted functions

    Science.gov (United States)

    Białas, Franciszek; Pytlik, Lucjan; Sikora, Wiesława

    2016-01-01

    In this paper we focus on the new version of computer program MODY for calculations of symmetryadapted functions based on the theory of groups and representations. The choice of such a functional frame of coordinates for description of ordered structures leads to a minimal number of parameters which must be used for presentation of such structures and investigations of their properties. The aim of this work is to find those parameters, which are coefficients of a linear combination of calculated functions, leading to construction of different types of structure ordering with a given symmetry. A spreadsheet script for simplification of this work has been created and attached to the program.

  17. Model Development for MODIS Thermal Band Electronic Crosstalk

    Science.gov (United States)

    Chang, Tiejun; Wu, Aisheng; Geng, Xu; Li, Yonghonh; Brinkman, Jake; Keller, Graziela; Xiong, Xiaoxiong

    2016-01-01

    MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 m. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands developed substantial issues that cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 m and band 29 at 8.5 m increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk effect is evident in the near-monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. The development of an alternative approach is very helpful for independent verification.In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically to correct the Earth brightness temperature measurements. In the model development, the detectors nonlinear response is considered. The impact of the electronic crosstalk is assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detectors nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector non-linearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic cross talk can be implemented empirically from the processed bias at different brightness temperature. The implementation

  18. Moderate Image Spectrometer (MODIS) Fire Radiative Energy: Physics and Applications

    Science.gov (United States)

    Kaufman, Y.

    2004-01-01

    MODIS fire channel does not saturate in the presence of fires. The fire channel therefore is used to estimate the fire radiative energy, a measure of the rate of biomass consumption in the fire. We found correlation between the fire radiative energy, the rate of formation of burn scars and the rate of emission of aerosol from the fires. Others found correlations between the fire radiative energy and the rate of biomass consumption. This relationships can be used to estimates the emissions from the fires and to estimate the fire hazards.

  19. The impact of horizontal heterogeneities, cloud fraction, and cloud dynamics on warm cloud effective radii and liquid water path from CERES-like Aqua MODIS retrievals

    OpenAIRE

    D. Painemal; P. Minnis; S. Sun-Mack

    2013-01-01

    The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES Edition 4 algorithms are averaged at the CERES footprint resolution (~ 20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean...

  20. The impact of horizontal heterogeneities, cloud fraction, and liquid water path on warm cloud effective radii from CERES-like Aqua MODIS retrievals

    OpenAIRE

    Painemal, D.; Minnis, P.; Sun-Mack, S.

    2013-01-01

    The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. ...

  1. A Contextual Fire Detection Algorithm for Simulated HJ-1B Imagery

    Directory of Open Access Journals (Sweden)

    Xiangsheng Kong

    2009-02-01

    Full Text Available The HJ-1B satellite, which was launched on September 6, 2008, is one of the small ones placed in the constellation for disaster prediction and monitoring. HJ-1B imagery was simulated in this paper, which contains fires of various sizes and temperatures in a wide range of terrestrial biomes and climates, including RED, NIR, MIR and TIR channels. Based on the MODIS version 4 contextual algorithm and the characteristics of HJ-1B sensor, a contextual fire detection algorithm was proposed and tested using simulated HJ-1B data. It was evaluated by the probability of fire detection and false alarm as functions of fire temperature and fire area. Results indicate that when the simulated fire area is larger than 45 m2 and the simulated fire temperature is larger than 800 K, the algorithm has a higher probability of detection. But if the simulated fire area is smaller than 10 m2, only when the simulated fire temperature is larger than 900 K, may the fire be detected. For fire areas about 100 m2, the proposed algorithm has a higher detection probability than that of the MODIS product. Finally, the omission and commission error were evaluated which are important factors to affect the performance of this algorithm. It has been demonstrated that HJ-1B satellite data are much sensitive to smaller and cooler fires than MODIS or AVHRR data and the improved capabilities of HJ-1B data will offer a fine opportunity for the fire detection.

  2. MODIS land cover and LAI collection 4 product quality across nine states in the western hemisphere.

    Science.gov (United States)

    Warren B. Cohen; Thomas K. Maiersperger; David P. Turner; William D. Ritts; Dirk Pflugmacher; Robert E. Kennedy; Alan Kirschbaum; Steven W. Running; Marcos Costa; Stith T. Gower

    2006-01-01

    Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS...

  3. Assessment of MODIS NDVI time series data products for detecting forest defoliation by gypsy moth outbreaks

    Science.gov (United States)

    Joseph P. Spruce; Steven Sader; Robert E. Ryan; James Smoot; Philip Kuper; al. et.

    2011-01-01

    This paper discusses an assessment of Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data products for detecting forest defoliation from European gypsy moth (Lymantria dispar). This paper describes an effort to aid the United States Department of Agriculture (USDA) Forest Service in developing and assessing MODIS-based gypsy moth defoliation...

  4. Characterising fire hazard from temporal sequences of thermal infrared modis measurements

    NARCIS (Netherlands)

    Maffei, C.; Alfieri, S.M.; Menenti, M.

    2012-01-01

    The objective of the present research was the characterisation of fire hazard using temporal sequences of land surface temperature (LST) derived from Terra-MODIS measurements. The investigation was based on a complete sequence of MODIS LST data from 2000 to 2006 on Campania (Italy) and on a dataset

  5. Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection, Journal of Applied Remote Sensing Vol.3

    Science.gov (United States)

    W. Wang; J.J. Qu; X. Hao; Y. Liu

    2009-01-01

    In the southeastern United States, most wildland fires are of low intensity. A substantial number of these fires cannot be detected by the MODIS contextual algorithm. To improve the accuracy of fire detection for this region, the remote-sensed characteristics of these fires have to be...

  6. Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

    Science.gov (United States)

    Xiong, Xiaoxiong; Wolfe, Robert; Barnes, William; Guenther, Bruce; Vermote, Eric; Saleous, Nazmi; Salomonson, Vincent

    2011-01-01

    The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near

  7. Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

    Science.gov (United States)

    Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

    2018-05-01

    In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

  8. MODIS Collection 6 Clear Sky Restoral (CSR): Filtering Cloud Mast 'Not Clear' Pixels

    Science.gov (United States)

    Meyer, Kerry G.; Platnick, Steven Edward; Wind, Galina; Riedi, Jerome

    2014-01-01

    Correctly identifying cloudy pixels appropriate for the MOD06 cloud optical and microphysical property retrievals is accomplished in large part using results from the MOD35 1km cloud mask tests (note there are also two 250m subpixel cloud mask tests that can convert the 1km cloudy designations to clear sky). However, because MOD35 is by design clear sky conservative (i.e., it identifies "not clear" pixels), certain situations exist in which pixels identified by MOD35 as "cloudy" are nevertheless likely to be poor retrieval candidates. For instance, near the edge of clouds or within broken cloud fields, a given 1km MODIS field of view (FOV) may in fact only be partially cloudy. This can be problematic for the MOD06 retrievals because in these cases the assumptions of a completely overcast homogenous cloudy FOV and 1-dimensional plane-parallel radiative transfer no longer hold, and subsequent retrievals will be of low confidence. Furthermore, some pixels may be identified by MOD35 as "cloudy" for reasons other than the presence of clouds, such as scenes with thick smoke or lofted dust, and should therefore not be retrieved as clouds. With such situations in mind, a Clear Sky Restoral (CSR) algorithm was introduced in C5 that attempts to identify pixels expected to be poor retrieval candidates. Table 1 provides SDS locations for CSR and partly cloudy (PCL) pixels.

  9. Mapping US Urban Extents from MODIS Data Using One-Class Classification Method

    Directory of Open Access Journals (Sweden)

    Bo Wan

    2015-08-01

    Full Text Available Urban areas are one of the most important components of human society. Their extents have been continuously growing during the last few decades. Accurate and timely measurements of the extents of urban areas can help in analyzing population densities and urban sprawls and in studying environmental issues related to urbanization. Urban extents detected from remotely sensed data are usually a by-product of land use classification results, and their interpretation requires a full understanding of land cover types. In this study, for the first time, we mapped urban extents in the continental United States using a novel one-class classification method, i.e., positive and unlabeled learning (PUL, with multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS data for the year 2010. The Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS night stable light data were used to calibrate the urban extents obtained from the one-class classification scheme. Our results demonstrated the effectiveness of the use of the PUL algorithm in mapping large-scale urban areas from coarse remote-sensing images, for the first time. The total accuracy of mapped urban areas was 92.9% and the kappa coefficient was 0.85. The use of DMSP-OLS night stable light data can significantly reduce false detection rates from bare land and cropland far from cities. Compared with traditional supervised classification methods, the one-class classification scheme can greatly reduce the effort involved in collecting training datasets, without losing predictive accuracy.

  10. A new map of global urban extent from MODIS satellite data

    International Nuclear Information System (INIS)

    Schneider, A; Friedl, M A; Potere, D

    2009-01-01

    Although only a small percentage of global land cover, urban areas significantly alter climate, biogeochemistry, and hydrology at local, regional, and global scales. To understand the impact of urban areas on these processes, high quality, regularly updated information on the urban environment-including maps that monitor location and extent-is essential. Here we present results from efforts to map the global distribution of urban land use at 500 m spatial resolution using remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our approach uses a supervised decision tree classification algorithm that we process using region-specific parameters. An accuracy assessment based on sites from a stratified random sample of 140 cities shows that the new map has an overall accuracy of 93% (k = 0.65) at the pixel level and a high level of agreement at the city scale (R 2 = 0.90). Our results (available at http://sage.wisc.edu/urbanenvironment.html) also reveal that the land footprint of cities occupies less than 0.5% of the Earth's total land area.

  11. Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices

    Directory of Open Access Journals (Sweden)

    Youngjoo Kwak

    2015-11-01

    Full Text Available Flood mapping, particularly hazard and risk mapping, is an imperative process and a fundamental part of emergency response and risk management. This paper aims to produce a flood risk proxy map of damaged rice fields over the whole of Bangladesh, where monsoon river floods are dominant and frequent, affecting over 80% of the total population. This proxy risk map was developed to meet the request of the government on a national level. This study represents a rapid, straightforward methodology for estimating rice-crop damage in flood areas of Bangladesh during the large flood from July to September 2007, despite the lack of primary data. We improved a water detection algorithm to achieve a better discrimination capacity to discern flood areas by using a modified land surface water index (MLSWI. Then, rice fields were estimated utilizing a hybrid rice field map from land-cover classification and MODIS-derived indices, such as the normalized difference vegetation index (NDVI and enhanced vegetation index (EVI. The results showed that the developed method is capable of providing instant, comprehensive, nationwide mapping of flood risks, such as rice field damage. The detected flood areas and damaged rice fields during the 2007 flood were verified by comparing them with the Advanced Land Observing Satellite (ALOS AVNIR-2 images (a 10 m spatial resolution and in situ field survey data with moderate agreement (K = 0.57.

  12. Comparison of CERES Cloud Properties Derived from Aqua and Terra MODIS Data and TRMM VIRS Radiances

    Science.gov (United States)

    Minnis, P.; Young, D. F.; Sun-Mack, S.; Trepte, Q. Z.; Chen, Y.; Heck, P. W.; Wielicki, B. A.

    2003-12-01

    The Clouds and Earth's Radiant Energy System (CERES) Project is obtaining Earth radiation budget measurements of unprecedented accuracy as a result of improved instruments and an analysis system that combines simultaneous, high-resolution cloud property retrievals with the broadband radiance data. The cloud properties are derived from three different satellite imagers: the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) and the Moderate Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites. A single set of consistent algorithms using the 0.65, 1.6 or 2.1, 3.7, 10.8, and 12.0-æm channels are applied to all three imagers. The cloud properties include, cloud coverage, height, thickness, temperature, optical depth, phase, effective particle size, and liquid or ice water path. Because each satellite is in a different orbit, the results provide information on the diurnal cycle of cloud properties. Initial intercalibrations show excellent consistency between the three images except for some differences of ~ 1K between the 3.7-æm channel on Terra and those on VIRS and Aqua. The derived cloud properties are consistent with the known diurnal characteristics of clouds in different areas. These datasets should be valuable for exploring the role of clouds in the radiation budget and hydrological cycle.

  13. Reliability of MODIS Evapotranspiration Products for Heterogeneous Dry Forest: A Study Case of Caatinga

    Directory of Open Access Journals (Sweden)

    Rodrigo de Queiroga Miranda

    2017-01-01

    Full Text Available Evapotranspiration (ET is normally considered as the sum of all water that evaporates from the soil and transpires from plants. However, accurately estimating ET from complex landscapes can be difficult because of its high spatial heterogeneity and diversity of driver factors, which make extrapolation of data from a point to a larger area quite inaccurate. In this paper, we hypothesize that MODIS products can be of use to estimate ET in areas of Caatinga vegetation, the hydrology of which has not been adequately studied. The experiment was conducted in a preserved level area of Caatinga in which meteorological and water flux measures were taken throughout 2012 by eddy covariance. Evapotranspiration estimates from eddy covariance were compared with remotely sensed evapotranspiration estimates from MOD16A2 and SAFER products. Correlations were performed at monthly, 8-day, and daily scales; and produced r2 values of monthly scale = 0.92, 8-day scale = 0.88, and daily scale = 0.85 for the SAFER algorithm. Monthly MOD16A2 data produced a value of r2=0.82, and they may be useful because they are free, downloadable, and easy to use by researchers and governments.

  14. Mapping Cropland and Crop-type Distribution Using Time Series MODIS Data

    Science.gov (United States)

    Lu, D.; Chen, Y.; Moran, E. F.; Batistella, M.; Luo, L.; Pokhrel, Y.; Deb, K.

    2016-12-01

    Mapping regional and global cropland distribution has attracted great attention in the past decade, but the separation of crop types is challenging due to the spectral confusion and cloud cover problems during the growing season in Brazil. The objective of this study is to develop a new approach to identify crop types (including soybean, cotton, maize) and planting patterns (soybean-maize, soybean-cotton, and single crop) in Mato Grosso, Goias and Tocantins States, Brazil. The time series moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) (MOD13Q1) in 2015/2016 were used in this research and field survey data were collected in May 2016. The major steps include: (1) reconstruct time series NDVI data contaminated by noise and clouds using the temporal interpolation algorithm; (2) identify the best periods and develop temporal indices and phenology parameters to distinguish cropland from other land cover types based on time series NDVI data; (3) develop a crop temporal difference index (CTDI) to extract crop types and patterns using time series NDVI data. This research shows that (1) the cropland occupied approximately 16.85% of total land in these three states; (2) soybean-maize and soybean-cotton were two major crop patterns which occupied 54.80% and 19.30% of total cropland area. This research indicates that the proposed approach is promising for accurately and rapidly mapping cropland and crop-type distribution in these three states of Brazil.

  15. Algorithmic Self

    DEFF Research Database (Denmark)

    Markham, Annette

    This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....

  16. Spatio-Temporal Analysis of MODIS Retrieved Precipitable Water Vapor over Urban and Rural Areas in the Philippines

    Science.gov (United States)

    Galvez, M. C. D.; Castilla, R. M.; Catenza, J. L. U.; Soronio, H.; Vallar, E. A.

    2016-12-01

    Precipitable water vapor (PWV) is a component of the atmosphere that significantly influences many atmospheric processes. It plays a dominant role in the high-energy thermodynamics of the atmosphere, notably, the genesis of storm systems. Remote sensing of the atmosphere using MODerate resolution Imaging Spectroradiometer (MODIS) offers a relatively inexpensive method to estimate atmospheric water vapour in the form of columnar measurements from its 936 nm near-infrared band. Daily Level 3 data with 1 degree grid spatial resolution from MODIS was used in order to determine the temporal and spatial variability of precipitable water between urban and rural areas in the Philippines. The PWV values were rasterized and spatially interpolated to be stored in a 1 kilometer grid resolution using the nearest-neighbor algorithm. General Linear Models were established to determine the main and interaction effects on PWV values of several categorical factors e.g. time, administrative region, and geographic classification. Comparison between the urban and rural areas in the Philippines showed that there is a significant difference between the values between these demographic dimensions. The mean PWV in the urban areas was found to be 0.0473 cm greater than the mean PWV of the rural areas. Lower levels of precipitable water vapour in rural places can be attributed to the low humidity as a result of a deficit of precipitation; while higher levels in urban areas can be accounted for by vehicle exhaust, industrial emissions, and irrigation of parks and gardens. In general, PWV varies depending on the season when solar insolation affects surface temperature, thus influencing the rate of evaporation. Using the regression line algorithm, the PWV values for rural areas have increased to 0.904 cm and 0.434 cm for urban areas from the year 2005 to 2015.

  17. Characterization of turbidity in Florida's Lake Okeechobee and Caloosahatchee and St. Lucie estuaries using MODIS-Aqua measurements.

    Science.gov (United States)

    Wang, Menghua; Nim, Carl J; Son, Seunghyun; Shi, Wei

    2012-10-15

    This paper describes the use of ocean color remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to characterize turbidity in Lake Okeechobee and its primary drainage basins, the Caloosahatchee and St. Lucie estuaries from 2002 to 2010. Drainage modification and agricultural development in southern Florida transport sediments and nutrients from watershed agricultural areas to Lake Okeechobee. As a result of development around Lake Okeechobee and the estuaries that are connected to Lake Okeechobee, estuarine conditions have also been adversely impacted, resulting in salinity and nutrient fluctuations. The measurement of water turbidity in lacustrine and estuarine ecosystems allows researchers to understand important factors such as light limitation and the potential release of nutrients from re-suspended sediments. Based on a strong correlation between water turbidity and normalized water-leaving radiance at the near-infrared (NIR) band (nL(w)(869)), a new satellite water turbidity algorithm has been developed for Lake Okeechobee. This study has shown important applications with satellite-measured nL(w)(869) data for water quality monitoring and measurements for turbid inland lakes. MODIS-Aqua-measured water property data are derived using the shortwave infrared (SWIR)-based atmospheric correction algorithm in order to remotely obtain synoptic turbidity data in Lake Okeechobee and normalized water-leaving radiance using the red band (nL(w)(645)) in the Caloosahatchee and St. Lucie estuaries. We found varied, but distinct seasonal, spatial, and event driven turbidity trends in Lake Okeechobee and the Caloosahatchee and St. Lucie estuary regions. Wind waves and hurricanes have the largest influence on turbidity trends in Lake Okeechobee, while tides, currents, wind waves, and hurricanes influence the Caloosahatchee and St. Lucie estuarine areas. Published by Elsevier Ltd.

  18. Mapping paddy rice planting area in rice-wetland coexistent areas through analysis of Landsat 8 OLI and MODIS images.

    Science.gov (United States)

    Zhou, Yuting; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Wang, Jie; Li, Xiangping

    2016-04-01

    Accurate and up-to-date information on the spatial distribution of paddy rice fields is necessary for the studies of trace gas emissions, water source management, and food security. The phenology-based paddy rice mapping algorithm, which identifies the unique flooding stage of paddy rice, has been widely used. However, identification and mapping of paddy rice in rice-wetland coexistent areas is still a challenging task. In this study, we found that the flooding/transplanting periods of paddy rice and natural wetlands were different. The natural wetlands flood earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. We used this asynchronous flooding stage to extract the paddy rice planting area from the rice-wetland coexistent area. MODIS Land Surface Temperature (LST) data was used to derive the temperature-defined plant growing season. Landsat 8 OLI imagery was used to detect the flooding signal and then paddy rice was extracted using the difference in flooding stages between paddy rice and natural wetlands. The resultant paddy rice map was evaluated with in-situ ground-truth data and Google Earth images. The estimated overall accuracy and Kappa coefficient were 95% and 0.90, respectively. The spatial pattern of OLI-derived paddy rice map agrees well with the paddy rice layer from the National Land Cover Dataset from 2010 (NLCD-2010). The differences between Rice Landsat and Rice NLCD are in the range of ±20% for most 1-km grid cell. The results of this study demonstrate the potential of the phenology-based paddy rice mapping algorithm, via integrating MODIS and Landsat 8 OLI images, to map paddy rice fields in complex landscapes of paddy rice and natural wetland in the temperate region.

  19. Mapping Urban Areas with Integration of DMSP/OLS Nighttime Light and MODIS Data Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Wenlong Jing

    2015-09-01

    Full Text Available Mapping urban areas at global and regional scales is an urgent and crucial task for detecting urbanization and human activities throughout the world and is useful for discerning the influence of urban expansion upon the ecosystem and the surrounding environment. DMSP-OLS stable nighttime lights have provided an effective way to monitor human activities on a global scale. Threshold-based algorithms have been widely used for extracting urban areas and estimating urban expansion, but the accuracy can decrease because of the empirical and subjective selection of threshold values. This paper proposes an approach for extracting urban areas with the integration of DMSP-OLS stable nighttime lights and MODIS data utilizing training sample datasets selected from DMSP-OLS and MODIS NDVI based on several simple strategies. Four classification algorithms were implemented for comparison: the classification and regression tree (CART, k-nearest-neighbors (k-NN, support vector machine (SVM, and random forests (RF. A case study was carried out on the eastern part of China, covering 99 cities and 1,027,700 km2. The classification results were validated using an independent land cover dataset, and then compared with an existing contextual classification method. The results showed that the new method can achieve results with comparable accuracies, and is easier to implement and less sensitive to the initial thresholds than the contextual method. Among the four classifiers implemented, RF achieved the most stable results and the highest average Kappa. Meanwhile CART produced highly overestimated results compared to the other three classifiers. Although k-NN and SVM tended to produce similar accuracy, less-bright areas around the urban cores seemed to be ignored when using SVM, which led to the underestimation of urban areas. Furthermore, quantity assessment showed that the results produced by k-NN, SVM, and RFs exhibited better agreement in larger cities and low

  20. An Examination of the Nature of Global MODIS Cloud Regimes

    Science.gov (United States)

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.

    2014-01-01

    We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

  1. Clear-Sky Narrowband Albedo Datasets Derived from Modis Data

    Science.gov (United States)

    Chen, Y.; Minnis, P.; Sun-Mack, S.; Arduini, R. F.; Hong, G.

    2013-12-01

    Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting the clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the near-infrared (NIR; 1.24, 1.6 or 2.13 μm) and visible (VIS; 0.63 μm) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to help identify clouds and retrieve their properties. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. The clear-sky albedos are derived using a radiative transfer parameterization of the impact of the atmosphere, including aerosols, on the observed reflectances. This paper presents the method of generating monthly clear-sky overhead albedo maps for both snow-free and snow-covered surfaces of these channels using one year of MODIS (Moderate Resolution Imaging Spectroradiometer) CERES products. Maps of 1.24 and 1.6 μm are being used as the background to help retrieve cloud properties (e.g., effective particle size, optical depth) in CERES cloud retrievals in both snow-free and snow-covered conditions.

  2. Greenland ice sheet melt from MODIS and associated atmospheric variability.

    Science.gov (United States)

    Häkkinen, Sirpa; Hall, Dorothy K; Shuman, Christopher A; Worthen, Denise L; DiGirolamo, Nicolo E

    2014-03-16

    Daily June-July melt fraction variations over the Greenland ice sheet (GIS) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) (2000-2013) are associated with atmospheric blocking forming an omega-shape ridge over the GIS at 500 hPa height. Blocking activity with a range of time scales, from synoptic waves breaking poleward (days) to full-fledged blocks (≥5 days), brings warm subtropical air masses over the GIS controlling daily surface temperatures and melt. The temperature anomaly of these subtropical air mass intrusions is also important for melting. Based on the years with the greatest melt (2002 and 2012) during the MODIS era, the area-average temperature anomaly of 2 standard deviations above the 14 year June-July mean results in a melt fraction of 40% or more. Though the summer of 2007 had the most blocking days, atmospheric temperature anomalies were too small to instigate extreme melting. Short-term atmospheric blocking over Greenland contributes to melt episodesAssociated temperature anomalies are equally important for the meltDuration and strength of blocking events contribute to surface melt intensity.

  3. Identification of circulating microRNAs in HNF1A-MODY carriers.

    Science.gov (United States)

    Bonner, C; Nyhan, K C; Bacon, S; Kyithar, M P; Schmid, J; Concannon, C G; Bray, I M; Stallings, R L; Prehn, J H M; Byrne, M M

    2013-08-01

    HNF1A-MODY is a monogenic form of diabetes caused by mutations in the HNF1A gene. Here we identify, for the first time, HNF1A-MODY-associated microRNAs (miRNAs) that can be detected in the serum of HNF1A-MODY carriers. An miRNA array was carried out in rat INS-1 insulinoma cells inducibly expressing the common human Pro291fsinsC-HNF1A frame shift mutation. Differentially expressed miRNAs were validated by quantitative real-time PCR. Expression of miRNAs in the serum of HNF1A-MODY carriers (n = 31), MODY-negative family members (n = 10) and individuals with type 2 diabetes mellitus (n = 17) was quantified by absolute real-time PCR analysis. Inducible expression of Pro291fsinsC-HNF1A in INS-1 cells caused a significant upregulation of three miRNAs (miR-103, miR-224, miR-292-3p). The differential expression of two miRNAs (miR-103 and miR-224) was validated in vitro. Strongly elevated levels of miR-103 and miR-224 could be detected in the serum of HNF1A-MODY carriers compared with MODY-negative family controls. Serum levels of miR-103 distinguished HNF1A-MODY carriers from HbA1c-matched individuals with type 2 diabetes mellitus. Our study demonstrates that the pathophysiology of HNF1A-MODY is associated with the overexpression of miR-103 and miR-224. Furthermore, our study demonstrates that these miRNAs can be readily detected in the serum of HNF1A-MODY carriers.

  4. Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

    Science.gov (United States)

    Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

    2015-04-01

    Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.

  5. Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.

    Science.gov (United States)

    Bonnefond, Amélie; Philippe, Julien; Durand, Emmanuelle; Dechaume, Aurélie; Huyvaert, Marlène; Montagne, Louise; Marre, Michel; Balkau, Beverley; Fajardy, Isabelle; Vambergue, Anne; Vatin, Vincent; Delplanque, Jérôme; Le Guilcher, David; De Graeve, Franck; Lecoeur, Cécile; Sand, Olivier; Vaxillaire, Martine; Froguel, Philippe

    2012-01-01

    Maturity-onset of the young (MODY) is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X). Here, we aimed to use whole-exome sequencing (WES) in a four-generation MODY-X family to identify a new susceptibility gene for MODY. WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing) was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay) of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130) present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11) co-segregated with diabetes in the family (with a LOD-score of 3.68). No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. Beyond neonatal diabetes mellitus (NDM), KCNJ11 is also a MODY gene ('MODY13'), confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS). Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.

  6. Cost-effectiveness of MODY genetic testing: translating genomic advances into practical health applications.

    Science.gov (United States)

    Naylor, Rochelle N; John, Priya M; Winn, Aaron N; Carmody, David; Greeley, Siri Atma W; Philipson, Louis H; Bell, Graeme I; Huang, Elbert S

    2014-01-01

    OBJECTIVE To evaluate the cost-effectiveness of a genetic testing policy for HNF1A-, HNF4A-, and GCK-MODY in a hypothetical cohort of type 2 diabetic patients 25-40 years old with a MODY prevalence of 2%. RESEARCH DESIGN AND METHODS We used a simulation model of type 2 diabetes complications based on UK Prospective Diabetes Study data, modified to account for the natural history of disease by genetic subtype to compare a policy of genetic testing at diabetes diagnosis versus a policy of no testing. Under the screening policy, successful sulfonylurea treatment of HNF1A-MODY and HNF4A-MODY was modeled to produce a glycosylated hemoglobin reduction of -1.5% compared with usual care. GCK-MODY received no therapy. Main outcome measures were costs and quality-adjusted life years (QALYs) based on lifetime risk of complications and treatments, expressed as the incremental cost-effectiveness ratio (ICER) (USD/QALY). RESULTS The testing policy yielded an average gain of 0.012 QALYs and resulted in an ICER of 205,000 USD. Sensitivity analysis showed that if the MODY prevalence was 6%, the ICER would be ~50,000 USD. If MODY prevalence was >30%, the testing policy was cost saving. Reducing genetic testing costs to 700 USD also resulted in an ICER of ~50,000 USD. CONCLUSIONS Our simulated model suggests that a policy of testing for MODY in selected populations is cost-effective for the U.S. based on contemporary ICER thresholds. Higher prevalence of MODY in the tested population or decreased testing costs would enhance cost-effectiveness. Our results make a compelling argument for routine coverage of genetic testing in patients with high clinical suspicion of MODY.

  7. Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.

    Directory of Open Access Journals (Sweden)

    Amélie Bonnefond

    Full Text Available BACKGROUND: Maturity-onset of the young (MODY is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X. Here, we aimed to use whole-exome sequencing (WES in a four-generation MODY-X family to identify a new susceptibility gene for MODY. METHODOLOGY: WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. PRINCIPAL FINDINGS: By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130 present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11 co-segregated with diabetes in the family (with a LOD-score of 3.68. No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. CONCLUSIONS/SIGNIFICANCE: Beyond neonatal diabetes mellitus (NDM, KCNJ11 is also a MODY gene ('MODY13', confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS. Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.

  8. Comparing Stream Discharge, Dissolved Organic Carbon, and Selected MODIS Indices in Freshwater Basins

    Science.gov (United States)

    Shaver, W. T.; Wollheim, W. M.

    2009-12-01

    In a preliminary study of the Ipswich Basin in Massachusetts, a good correlation was found to exist between the MODIS (Moderate Resolution Imaging Spectroradiometer) Enhanced Vegetation Index and stream dissolved organic carbon (DOC). Further study was warranted to determine the utility of MODIS indices in predicting temporal stream DOC. Stream discharge rates and DOC data were obtained from the USGS National Water Quality Assessment Program (NAWQA) database. Twelve NAWQA monitoring sites were selected for evaluation based on the criteria of having drainage basin sizes less than 600 km2 with relatively continuous, long-term DOC and discharge data. MODIS indices were selected based on their connections with terrestrial DOC and were obtained for each site's catchment area. These included the Normalized Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Daily Photosynthesis (PSN) and the Leaf Area Index (LAI). Regression analysis was used to evaluate the relationships between DOC, discharge and MODIS products. Data analysis revealed several important trends. Sites with strong positive correlation coefficients (r values ranging from 0.462 to 0.831) between DOC and discharge displayed weak correlations with all of the MODIS indices (r values ranging from 0 to 0.322). For sites where the DOC/discharge correlation was weak or negative, MODIS indices were moderately correlated, with r values ranging from 0.35 to 0.647, all of which were significant at less than 1 percent. Some sites that had weak positive correlations with MODIS indices displayed a lag time, that is, the MODIS index rose and fell shortly before the DOC concentration rose and fell. Shifting the MODIS data forward in time by roughly one month significantly increased the DOC/MODIS r values by about 10%. NDVI and EVI displayed the strongest correlations with temporal DOC variability (r values ranging from 0.471 to 0.647), and therefore these indices are the most promising for being incorporated

  9. Crop Dominance Mapping with IRS-P6 and MODIS 250-m Time Series Data

    Directory of Open Access Journals (Sweden)

    Murali Krishna Gumma

    2014-04-01

    Full Text Available This paper describes an approach to accurately separate out and quantify crop dominance areas in the major command area in the Krishna River Basin. Classification was performed using IRS-P6 (Indian Remote Sensing Satellite, series P6 and MODIS eight-day time series remote sensing images with a spatial resolution of 23.6 m, 250 m for the year 2005. Temporal variations in the NDVI (Normalized Difference Vegetation Index pattern obtained in crop dominance classes enables a demarcation between long duration crops and short duration crops. The NDVI pattern was found to be more consistent in long duration crops than in short duration crops due to the continuity of the water supply. Surface water availability, on the other hand, was dependent on canal water release, which affected the time of crop sowing and growth stages, which was, in turn, reflected in the NDVI pattern. The identified crop-wise classes were tested and verified using ground-truth data and state-level census data. The accuracy assessment was performed based on ground-truth data through the error matrix method, with accuracies from 67% to 100% for individual crop dominance classes, with an overall accuracy of 79% for all classes. The derived major crop land areas were highly correlated with the sub-national statistics with R2 values of 87% at the mandal (sub-district level for 2005–2006. These results suggest that the methods, approaches, algorithms and datasets used in this study are ideal for rapid, accurate and large-scale mapping of paddy rice, as well as for generating their statistics over large areas. This study demonstrates that IRS-P6 23.6-m one-time data fusion with MODIS 250-m time series data is very useful for identifying crop type, the source of irrigation water and, in the case of surface water irrigation, the way in which it is applied. The results from this study have assisted in improving surface water and groundwater irrigated areas of the command area and also

  10. Verification, improvement and application of aerosol optical depths in China Part 1: Inter-comparison of NPP-VIIRS and Aqua-MODIS

    Science.gov (United States)

    Wei, Jing; Sun, Lin; Huang, Bo; Bilal, Muhammad; Zhang, Zhaoyang; Wang, Lunche

    2018-02-01

    The objective of this study is to evaluate typical aerosol optical depth (AOD) products in China, which experienced seriously increasing atmospheric particulate pollution. For this, the Aqua-MODerate resolution Imaging Spectroradiometer (MODIS) AOD products (MYD04) at 10 km spatial resolution and Visible Infrared Imaging Radiometer Suite (VIIRS) Environmental Data Record (EDR) AOD product at 6 km resolution for different Quality Flags (QF) are obtained for validation against AErosol RObotic NETwork (AERONET) AOD measurements during 2013-2016. Results show that VIIRS EDR similarly Dark Target (DT) and MODIS DT algorithms perform worse with only 45.36% and 45.59% of the retrievals (QF = 3) falling within the Expected Error (EE, ±(0.05 + 15%)) compared to the Deep Blue (DB) algorithm (69.25%, QF ≥ 2). The DT retrievals perform poorly over the Beijing-Tianjin-Hebei (BTH) and Yangtze-River-Delta (YRD) regions, which significantly overestimate the AOD observations, but the performance is better over the Pearl-River-Delta (PRD) region than DB retrievals, which seriously under-estimate the AOD loadings. It is not surprising that the DT algorithm performs better over vegetated areas, while the DB algorithm performs better over bright areas mainly depends on the accuracy of surface reflectance estimation over different land use types. In general, the sensitivity of aerosol to apparent reflectance reduces by about 34% with an increasing surface reflectance by 0.01. Moreover, VIIRS EDR and MODIS DT algorithms perform overall better in the winter as 64.53% and 72.22% of the retrievals are within the EE but with less retrievals. However, the DB algorithm performs worst (57.17%) in summer mainly affected by the vegetation growth but there are overall high accuracies with more than 62% of the collections falling within the EE in other three seasons. Results suggest that the quality assurance process can help improve the overall data quality for MYD04 DB retrievals, but it is

  11. True Colour Classification of Natural Waters with Medium-Spectral Resolution Satellites: SeaWiFS, MODIS, MERIS and OLCI

    Directory of Open Access Journals (Sweden)

    Hendrik J. van der Woerd

    2015-10-01

    Full Text Available The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne “ocean colour” instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10 of narrow (≈10 nm bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α. Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

  12. Applications of MODIS Fluorescence Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity in Coastal and Estuarine Waters

    Science.gov (United States)

    Fischer, A.; Ryan, J. P.; Moreno-Madriñán, M. J.

    2012-12-01

    Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS), calibration updates, improved aerosol retrievals, and new aerosol models have led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean-color. This has opened the way for studying coastal ocean phenomena and processes at finer spatial scales. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and increases in local concentrations of phytoplankton, which could result in harmful algal blooms. In two case studies we present improved and validated MODIS coastal observations of fluorescence line height (FLH) to: (1) assess trends in water quality for Tampa Bay, Florida; and (2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California, as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and imagery from Tampa Bay, we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout this large, optically complex estuarine system. A systematic analysis of sampling sites throughout the bay illustrates that the correlations between FLH and in situ chlorophyll-a are influenced by water quality parameters of total nitrogen, total phosphorous, turbidity and biological oxygen demand. Sites that correlated well with satellite imagery were in depths

  13. Technical note: A new day- and night-time Meteosat Second Generation Cirrus Detection Algorithm MeCiDA

    Directory of Open Access Journals (Sweden)

    W. Krebs

    2007-12-01

    Full Text Available A new cirrus detection algorithm for the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI aboard the geostationary Meteosat Second Generation (MSG, MeCiDA, is presented. The algorithm uses the seven infrared channels of SEVIRI and thus provides a consistent scheme for cirrus detection at day and night. MeCiDA combines morphological and multi-spectral threshold tests and detects optically thick and thin ice clouds. The thresholds were determined by a comprehensive theoretical study using radiative transfer simulations for various atmospheric situations as well as by manually evaluating actual satellite observations. The cirrus detection has been optimized for mid- and high latitudes but it could be adapted to other regions as well. The retrieved cirrus masks have been validated by comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS Cirrus Reflection Flag. To study possible seasonal variations in the performance of the algorithm, one scene per month of the year 2004 was randomly selected and compared with the MODIS flag. 81% of the pixels were classified identically by both algorithms. In a comparison of monthly mean values for Europe and the North-Atlantic MeCiDA detected 29.3% cirrus coverage, while the MODIS SWIR cirrus coverage was 38.1%. A lower detection efficiency is to be expected for MeCiDA, as the spatial resolution of MODIS is considerably better and as we used only the thermal infrared channels in contrast to the MODIS algorithm which uses infrared and visible radiances. The advantage of MeCiDA compared to retrievals for polar orbiting instruments or previous geostationary satellites is that it permits the derivation of quantitative data every 15 min, 24 h a day. This high temporal resolution allows the study of diurnal variations and life cycle aspects. MeCiDA is fast enough for near real-time applications.

  14. Parallel algorithms

    CERN Document Server

    Casanova, Henri; Robert, Yves

    2008-01-01

    ""…The authors of the present book, who have extensive credentials in both research and instruction in the area of parallelism, present a sound, principled treatment of parallel algorithms. … This book is very well written and extremely well designed from an instructional point of view. … The authors have created an instructive and fascinating text. The book will serve researchers as well as instructors who need a solid, readable text for a course on parallelism in computing. Indeed, for anyone who wants an understandable text from which to acquire a current, rigorous, and broad vi

  15. Algorithm 865

    DEFF Research Database (Denmark)

    Gustavson, Fred G.; Reid, John K.; Wasniewski, Jerzy

    2007-01-01

    We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and for solving corresponding sets of linear equations. They exploit cache memory by using the block hybrid format proposed by the authors in a companion article. The matrix is packed into n(n + 1)/2 real...... variables, and the speed is usually better than that of the LAPACK algorithm that uses full storage (n2 variables). Included are subroutines for rearranging a matrix whose upper or lower-triangular part is packed by columns to this format and for the inverse rearrangement. Also included is a kernel...

  16. The Zoning of Forest Fire Potential of Gulestan Province Forests Using Granular Computing and MODIS Images

    Directory of Open Access Journals (Sweden)

    A. Jalilzadeh Shadlouei

    2013-09-01

    Full Text Available There are many vegetation in Iran. This is because of extent of Iran and its width. One of these vegetation is forest vegetation most prevalent in Northern provinces named Guilan, Mazandaran, Gulestan, Ardebil as well as East Azerbaijan. These forests are always threatened by natural forest fires so much so that there have been reports of tens of fires in recent years. Forest fires are one of the major environmental as well as economic, social and security concerns in the world causing much damages. According to climatology, forest fires are one of the important factors in the formation and dispersion of vegetation. Also, regarding the environment, forest fires cause the emission of considerable amounts of greenhouse gases, smoke and dust into the atmosphere which in turn causes the earth temperature to rise up and are unhealthy to humans, animals and vegetation. In agriculture droughts are the usual side effects of these fires. The causes of forest fires could be categorized as either Human or Natural Causes. Naturally, it is impossible to completely contain forest fires; however, areas with high potentials of fire could be designated and analysed to decrease the risk of fires. The zoning of forest fire potential is a multi-criteria problem always accompanied by inherent uncertainty like other multi-criteria problems. So far, various methods and algorithm for zoning hazardous areas via Remote Sensing (RS and Geospatial Information System (GIS have been offered. This paper aims at zoning forest fire potential of Gulestan Province of Iran forests utilizing Remote Sensing, Geospatial Information System, meteorological data, MODIS images and granular computing method. Granular computing is part of granular mathematical and one way of solving multi-criteria problems such forest fire potential zoning supervised by one expert or some experts , and it offers rules for classification with the least inconsistencies. On the basis of the experts’ opinion

  17. Relation of MODIS EVI and LAI across time, vegetation types and hydrological regimes

    Science.gov (United States)

    Alexandridis, Thomas; Ovakoglou, George

    2015-04-01

    across time, there is an evident temporal change in all test sites. The sensitivity of EVI to LAI is smaller in periods of high biomass production. The range of fluctuation is different across sites, and is related to biomass quantity and type. Higher fluctuation is noted in the winter season in Tamega, possibly due to cloud infected pixels that the QA and compositing algorithms did not successfully detect. Finally, there was no significant difference in the R2 and EVI factor when including in the analyses pixels indicated as "low and marginal quality" by the QA layers, thus suggesting that the use of low quality pixels can be justified when good quality pixels are not enough. Future work will study the transferability of these relations across scales and sensors. This study is supported by the Research Committee of Aristotle University of Thessaloniki project "Improvement of the estimation of Leaf Area Index (LAI) at basin scale using satellite images". MODIS data are provided by USGS.

  18. Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

    Science.gov (United States)

    Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

    2016-04-01

    (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

  19. MODIS Near real-time (NRT) data for fire applications

    Science.gov (United States)

    Wong, M.; Davies, D.; Ilavajhala, S.; Molinario, G.; Justice, C.; Latham, J.; Martucci, A.; Murphy, K. J.

    2011-12-01

    This paper describes the lessons learned from the development of the Fire Information for Resource Management System (FIRMS) prototype and its transition to an operational system, the Global Fire Information Management System (GFIMS), at the United Nations Food and Agriculture Organization (FAO) in August 2010. These systems provide active fire data from the MODIS sensor, on board NASA's Terra and Aqua Earth Observing Satellites, to users at no cost, in near-real time and in easy-to-use formats. The FIRMS prototype evolved from simply providing daily active fire text files via FTP, to include services such as providing fire data in various data formats, an interactive WebGIS allowing users to view and query the data and an email alert service enabling users to receive emails of near real-time fire data of their chosen area of interest. FIRMS was designed to remove obstacles to the uptake and use of fire data by addressing issues often associated with satellite data: cost, timeliness of delivery, limited data formats and the need for technical expertise to process and analyze the data. We also illustrate how the MODIS active fire data are routinely used for firefighting and conservation monitoring. We present results from a user survey, completed by approximately 345 people from 65 countries, and provide case studies highlighting how the provision of MODIS active fire data have made an impact on conservation and firefighting, especially in remote areas where it is difficult to have on-the-ground surveillance. We highlight the gaps in current capabilities, both with users and the data. A major obstacle still for some users is having low or no internet connectivity and a possible solution is through the use of cell phone technologies such as SMS text messaging of fire locations and information. GFIMS, and its precursor, FIRMS, were developed by the University of Maryland with funding from NASA's Applied Sciences Program. With GFIMS established at FAO as an operational

  20. Validation of near infrared satellite based algorithms to relative atmospheric water vapour content over land

    International Nuclear Information System (INIS)

    Serpolla, A.; Bonafoni, S.; Basili, P.; Biondi, R.; Arino, O.

    2009-01-01

    This paper presents the validation results of ENVISAT MERIS and TERRA MODIS retrieval algorithms for atmospheric Water Vapour Content (WVC) estimation in clear sky condition on land. The MERIS algorithms exploits the radiance ratio of the absorbing channel at 900 nm with the almost absorption-free reference at 890 nm, while the MODIS one is based on the ratio of measurements centred at near 0.905, 0.936, and 0.94 μm with atmospheric window reflectance at 0.865 and 1.24 μm. The first test was performed in the Mediterranean area using WVC provided from both ECMWF and AERONET. As a second step, the performances of the algorithms were tested exploiting WVC computed from radio sounding (RAOBs)in the North East Australia. The different comparisons with respect to reference WVC values showed an overestimation of WVC by MODIS (root mean square error percentage greater than 20%) and an acceptable performance of MERIS algorithms (root mean square error percentage around 10%) [it

  1. Maturity-Onset Diabetes of the Young (MODY): Making the Right Diagnosis to Optimize Treatment.

    Science.gov (United States)

    Amed, Shazhan; Oram, Richard

    2016-10-01

    Maturity onset diabetes of the young (MODY) is a rare but increasingly recognized cause of diabetes in young people. It is a monogenic disorder that typically presents at MODY are caused by mutations in glucokinase and hepatic nuclear factor 1 alpha or 4 alpha genes and account for almost 80% of cases of MODY. MODY is commonly misdiagnosed as type 1 or type 2 diabetes and, as a result, patients are often inappropriately managed with insulin when they can be more effectively managed with oral sulfonylureas. Therefore, making the right diagnosis is critical for effective treatment as well as for genetic counselling and, more important, for patients' quality of life. In this review, we aim to raise awareness about MODY among diabetes clinicians by describing key clinical and laboratory features of the most common forms of MODY, outlining features that might help to differentiate MODY from type 1 and type 2 diabetes and providing information about clinical tests and tools that might assist in identifying patients who are most likely to benefit from molecular genetic testing. Copyright © 2016 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

  2. To test, or not to test: time for a MODY calculator?

    Science.gov (United States)

    Njølstad, P R; Molven, A

    2012-05-01

    To test, or not to test, that is often the question in diabetes genetics. This is why the paper of Shields et al in the current issue of Diabetologia is so warmly welcomed. MODY is the most common form of monogenic diabetes. Nevertheless, the optimal way of identifying MODY families still poses a challenge both for researchers and clinicians. Hattersley's group in Exeter, UK, have developed an easy-to-use MODY prediction model that can help to identify cases appropriate for genetic testing. By answering eight simple questions on the internet ( www.diabetesgenes.org/content/mody-probability-calculator ), the doctor receives a positive predictive value in return: the probability that the patient has MODY. Thus, the classical binary (yes/no) assessment provided by clinical diagnostic criteria has been substituted by a more rational, quantitative estimate. The model appears to discriminate well between MODY and type 1 and type 2 diabetes when diabetes is diagnosed before the age of 35 years. However, the performance of the MODY probability calculator should now be validated in other settings than where it was developed-and, as always, there is room for some improvements and modifications.

  3. Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data

    Directory of Open Access Journals (Sweden)

    Hu Zhang

    2015-06-01

    Full Text Available Bidirectional reflectance distribution function (BRDF archetypes extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS BRDF/Albedo product over the global Earth Observing System Land Validation Core Sites can be used to simplify BRDF models. The present study attempts to evaluate the representativeness of BRDF archetypes for surface reflectance anisotropy. Five-year forward-modeled MODIS multi-angular reflectance (MCD-ref and aditional actual MODIS multi-angular observations (MCD-obs in four growing periods in 2008 over three tiles were taken as validation data. First, BRDF archetypes in the principal plane were qualitatively compared with the time-series MODIS BRDF product of randomly sampled pixels. Secondly, BRDF archetypes were used to fit MCD-ref, and the average root-mean-squared errors (RMSEs over each tile were examined for these five years. Finally, both BRDF archetypes and the MODIS BRDF were used to fit MCD-obs, and the histograms of the fit-RMSEs were compared. The consistency of the directional reflectance between the BRDF archetypes and MODIS BRDFs in nadir-view, hotspot and entire viewing hemisphere at 30° and 50° solar geometries were also examined. The results confirm that BRDF archetypes are representative of surface reflectance anisotropy for available snow-free MODIS data.

  4. Comparing MODIS Net Primary Production Estimates with Terrestrial National Forest Inventory Data in Austria

    Directory of Open Access Journals (Sweden)

    Mathias Neumann

    2015-04-01

    Full Text Available The mission of this study is to compare Net Primary Productivity (NPP estimates using (i forest inventory data and (ii spatio-temporally continuous MODIS (MODerate resolution Imaging Spectroradiometer remote sensing data for Austria. While forest inventories assess the change in forest growth based on repeated individual tree measurements (DBH, height etc., the MODIS NPP estimates are based on ecophysiological processes such as photosynthesis, respiration and carbon allocation. We obtained repeated national forest inventory data from Austria, calculated a “ground-based” NPP estimate and compared the results with “space-based” MODIS NPP estimates using different daily climate data. The MODIS NPP estimates using local Austrian climate data exhibited better compliance with the forest inventory driven NPP estimates than the MODIS NPP predictions using global climate data sets. Stand density plays a key role in addressing the differences between MODIS driven NPP estimates versus terrestrial driven inventory NPP estimates. After addressing stand density, both results are comparable across different scales. As forest management changes stand density, these findings suggest that management issues are important in understanding the observed discrepancies between MODIS and terrestrial NPP.

  5. Searching for Maturity-Onset Diabetes of the Young (MODY): When and What for?

    Science.gov (United States)

    Timsit, José; Saint-Martin, Cécile; Dubois-Laforgue, Danièle; Bellanné-Chantelot, Christine

    2016-10-01

    Maturity-onset diabetes of the young (MODY) is a group of monogenic diseases that results in primary defects in insulin secretion and dominantly inherited forms of nonautoimmune diabetes. Although many genes may be associated with monogenic diabetes, heterozygous mutations in 6 of them are responsible for the majority of cases of MODY. Glucokinase (GCK)-MODY is due to mutations in the glucokinase gene, 3 MODY subtypes are associated with mutations in the hepatocyte nuclear factor (HNF) transcription factors, and 2 others with mutations in ABCC8 and KCNJ11, which encode the subunits of the ATP-dependent potassium channel in pancreatic beta cells. GCK-MODY and HNF1A-MODY are the most common subtypes. The clinical presentation of MODY subtypes has been reported to differ according to the gene involved, and the diagnosis of MODY may be considered in various clinical circumstances. However, except in patients with GCK-MODY whose phenotype is very homogeneous, in most cases the penetrance and expressivity of a given molecular abnormality vary greatly among patients and, conversely, alterations in various genes may lead to similar phenotypes. Moreover, differential diagnosis among more common forms of diabetes may be difficult, particularly with type 2 diabetes. Thus, careful assessment of the personal and family histories of patients with diabetes is mandatory to select those in whom genetic screening is worthwhile. The diagnosis of monogenic diabetes has many consequences in terms of prognosis, therapeutics and family screening. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

  6. Validation and empirical correction of MODIS AOT and AE over ocean

    Directory of Open Access Journals (Sweden)

    N. A. J. Schutgens

    2013-09-01

    Full Text Available We present a validation study of Collection 5 MODIS level 2 Aqua and Terra AOT (aerosol optical thickness and AE (Ångström exponent over ocean by comparison to coastal and island AERONET (AErosol RObotic NETwork sites for the years 2003–2009. We show that MODIS (MODerate-resolution Imaging Spectroradiometer AOT exhibits significant biases due to wind speed and cloudiness of the observed scene, while MODIS AE, although overall unbiased, exhibits less spatial contrast on global scales than the AERONET observations. The same behaviour can be seen when MODIS AOT is compared against Maritime Aerosol Network (MAN data, suggesting that the spatial coverage of our datasets does not preclude global conclusions. Thus, we develop empirical correction formulae for MODIS AOT and AE that significantly improve agreement of MODIS and AERONET observations. We show these correction formulae to be robust. Finally, we study random errors in the corrected MODIS AOT and AE and show that they mainly depend on AOT itself, although small contributions are present due to wind speed and cloud fraction in AOT random errors and due to AE and cloud fraction in AE random errors. Our analysis yields significantly higher random AOT errors than the official MODIS error estimate (0.03 + 0.05 τ, while random AE errors are smaller than might be expected. This new dataset of bias-corrected MODIS AOT and AE over ocean is intended for aerosol model validation and assimilation studies, but also has consequences as a stand-alone observational product. For instance, the corrected dataset suggests that much less fine mode aerosol is transported across the Pacific and Atlantic oceans.

  7. Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

    Science.gov (United States)

    Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Perez Garcia-Pando, Carlos

    2017-01-01

    A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

  8. Application of the Support Vector Regression Method for Turbidity Assessment with MODIS on a Shallow Coral Reef Lagoon (Voh-Koné-Pouembout, New Caledonia

    Directory of Open Access Journals (Sweden)

    Guillaume Wattelez

    2017-09-01

    Full Text Available Particle transport by erosion from ultramafic lands in pristine tropical lagoons is a crucial problem, especially for the benthic and pelagic biodiversity associated with coral reefs. Satellite imagery is useful for assessing particle transport from land to sea. However, in the oligotrophic and shallow waters of tropical lagoons, the bottom reflection of downwelling light usually hampers the use of classical optical algorithms. In order to address this issue, a Support Vector Regression (SVR model was developed and tested. The proposed application concerns the lagoon of New Caledonia—the second longest continuous coral reef in the world—which is frequently exposed to river plumes from ultramafic watersheds. The SVR model is based on a large training sample of in-situ turbidity values representative of the annual variability in the Voh-Koné-Pouembout lagoon (Western Coast of New Caledonia during the 2014–2015 period and on coincident satellite reflectance values from MODerate Resolution Imaging Spectroradiometer (MODIS. It was trained with reflectance and two other explanatory parameters—bathymetry and bottom colour. This approach significantly improved the model’s capacity for retrieving the in-situ turbidity range from MODIS images, as compared with algorithms dedicated to deep oligotrophic or turbid waters, which were shown to be inadequate. This SVR model is applicable to the whole shallow lagoon waters from the Western Coast of New Caledonia and it is now ready to be tested over other oligotrophic shallow lagoon waters worldwide.

  9. Circulating CD36 is reduced in HNF1A-MODY carriers.

    Science.gov (United States)

    Bacon, Siobhan; Kyithar, Ma P; Schmid, Jasmin; Costa Pozza, Andre; Handberg, Aase; Byrne, Maria M

    2013-01-01

    Premature atherosclerosis is a significant cause of morbidity and mortality in type 2 diabetes mellitus. Maturity onset diabetes of the young (MODY) accounts for approximately 2% of all diabetes, with mutations in the transcription factor; hepatocyte nuclear factor 1 alpha (HNF1A) accounting for the majority of MODY cases. There is somewhat limited data available on the prevalence of macrovascular disease in HNF1A-MODY carriers with diabetes. Marked insulin resistance and the associated dyslipidaemia are not clinical features of HNF1A-MODY carriers. The scavenger protein CD36 has been shown to play a substantial role in the pathogenesis of atherosclerosis, largely through its interaction with oxidised LDL. Higher levels of monocyte CD36 and plasma CD36(sCD36) are seen to cluster with insulin resistance and diabetes. The aim of this study was to determine levels of sCD36 in participants with HNF1A-MODY diabetes and to compare them with unaffected normoglycaemic family members and participants with type 2 diabetes mellitus. We recruited 37 participants with HNF1A-MODY diabetes and compared levels of sCD36 with BMI-matched participants with type 2 diabetes mellitus and normoglycaemic HNF1A-MODY negative family controls. Levels of sCD36 were correlated with phenotypic and biochemical parameters. HNF1A-MODY participants were lean, normotensive, with higher HDL and lower triglyceride levels when compared to controls and participants with type 2 diabetes mellitus. sCD36 was also significantly lower in HNF1A-MODY participants when compared to both the normoglycaemic family controls and to lean participants with type 2 diabetes mellitus. In conclusion, sCD36 is significantly lower in lean participants with HNF1A-MODY diabetes when compared to weight-matched normoglycaemic familial HNF1A-MODY negative controls and to lean participants with type 2 diabetes mellitus. Lower levels of this pro-atherogenic marker may result from the higher HDL component in the lipid profile of

  10. MODY3 in the child with type 2 diabetes mellitus phenotype: case report

    Directory of Open Access Journals (Sweden)

    Tamara Leonidovna Kuraeva

    2013-06-01

    Full Text Available MODY is a heterogeneous group of diseases that stem from certain genetic mutations and are characterized by beta-cell dysfunction, early clinical onset (before the age of 25 and autosomal dominant inheritance. Nowadays many studies address atypical variants of diabetes mellitus (DM and consequential problems in differential diagnosis. Though generally patients with MODY have normal body weight, the ongoing spread of obesity will probably produce comorbid forms and thus alter clinical picture. We present a case of DM in a 13-year-old patient that characterizes development of MODY3 in type 2 DM-like phenotype.

  11. Circulating CD36 is reduced in HNF1A-MODY carriers.

    Directory of Open Access Journals (Sweden)

    Siobhan Bacon

    Full Text Available INTRODUCTION: Premature atherosclerosis is a significant cause of morbidity and mortality in type 2 diabetes mellitus. Maturity onset diabetes of the young (MODY accounts for approximately 2% of all diabetes, with mutations in the transcription factor; hepatocyte nuclear factor 1 alpha (HNF1A accounting for the majority of MODY cases. There is somewhat limited data available on the prevalence of macrovascular disease in HNF1A-MODY carriers with diabetes. Marked insulin resistance and the associated dyslipidaemia are not clinical features of HNF1A-MODY carriers. The scavenger protein CD36 has been shown to play a substantial role in the pathogenesis of atherosclerosis, largely through its interaction with oxidised LDL. Higher levels of monocyte CD36 and plasma CD36(sCD36 are seen to cluster with insulin resistance and diabetes. The aim of this study was to determine levels of sCD36 in participants with HNF1A-MODY diabetes and to compare them with unaffected normoglycaemic family members and participants with type 2 diabetes mellitus. METHODS: We recruited 37 participants with HNF1A-MODY diabetes and compared levels of sCD36 with BMI-matched participants with type 2 diabetes mellitus and normoglycaemic HNF1A-MODY negative family controls. Levels of sCD36 were correlated with phenotypic and biochemical parameters. RESULTS: HNF1A-MODY participants were lean, normotensive, with higher HDL and lower triglyceride levels when compared to controls and participants with type 2 diabetes mellitus. sCD36 was also significantly lower in HNF1A-MODY participants when compared to both the normoglycaemic family controls and to lean participants with type 2 diabetes mellitus. CONCLUSION: In conclusion, sCD36 is significantly lower in lean participants with HNF1A-MODY diabetes when compared to weight-matched normoglycaemic familial HNF1A-MODY negative controls and to lean participants with type 2 diabetes mellitus. Lower levels of this pro-atherogenic marker may

  12. Multilayered Clouds Identification and Retrieval for CERES Using MODIS

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

    2006-01-01

    Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

  13. Aspectos más recientes en relación con la diabetes mellitus tipo MODY Most recent aspects about type MODY diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Ana Ibis Conesa González

    2012-08-01

    Full Text Available Antecedentes: la mejor comprensión fisiopatológica de la diabetes mellitus permite identificar diferentes tipos, entre ellos una variante monogénica denominada por sus siglas en inglés MODY (Maturity-Onset Diabetes of the Young. Objetivos: describir los aspectos fisiopatológicos, clínicos, diagnósticos y terapéuticos de los diferentes subtipos MODY. Desarrollo: los pacientes con diabetes tipo MODY presentan un comportamiento similar a la diabetes mellitus del adulto. Se caracteriza por una alteración genética autosómica dominante inherente y primaria a un defecto en la secreción de insulina. Hasta el momento actual se aceptan 9 subtipos de MODY. Los subtipos 1, 3, 4, 5 y 6 afectan a genes que codifican a factores nucleares de trascripción, y el subtipo 2 al gen que codifica a la enzima glucoquinasa. Se caracterizan clínicamente por cuadros que oscilan entre hiperglucemias permanentes, leves o moderadas, con buen pronóstico clínico, y pocas complicaciones, hasta cuadros de hiperglucemias mantenidas acompañadas de complicaciones crónicas precoces y graves. Conclusiones: las personas que padecen diabetes tipo MODY no son tan infrecuentes como se piensa. La correcta y temprana identificación de la enfermedad permitirá una acción terapéutica más racional y adecuada para brindar la posibilidad de mejor calidad de vida de estas personas.Background: a better physiopathological understanding of diabetes mellitus allows identifying its different types such as a monogenic variant called MODY (maturity-onset diabetes of the young. Objectives: to describe the physiopathological, clinical, diagnostic and therapeutic aspects of the different subtypes in MODY diabetes. Development: the patients with MODY diabetes behave similarly to those suffering diabetes mellitus in adults. It is characterized by inherited dominant autosomal genetic alteration which is primary to a defect in insulin secretion. Up to the present, 9 subtypes are accepted