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...

MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid V006

Data.gov (United States)

National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid (MOD21A2.006). A new suite of MODIS Land Surface Temperature (LST) and Emissivity...

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...

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...

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%.

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.

Estimation of surface air temperature over central and eastern Eurasia from MODIS land surface temperature

International Nuclear Information System (INIS)

Shen Suhung; Leptoukh, Gregory G

2011-01-01

Surface air temperature (T a ) is a critical variable in the energy and water cycle of the Earth–atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T a from satellite remotely sensed land surface temperature (T s ) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T a and MODIS T s . The relationships between the maximum T a and daytime T s depend significantly on land cover types, but the minimum T a and nighttime T s have little dependence on the land cover types. The largest difference between maximum T a and daytime T s appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T a were estimated from 1 km resolution MODIS T s under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T a were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T a varies from 2.4 °C over closed shrublands to 3.2 °C over grasslands, and the MAE of the estimated minimum T a is about 3.0 °C.

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...

Combining NLCD and MODIS to create a land cover-albedo database for the continental United States

Science.gov (United States)

Wickham, J.; Barnes, Christopher A.; Nash, M.S.; Wade, T.G.

2015-01-01

Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14 years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500 m × 500 m) from the NLCD product (30 m × 30 m), and provides an albedo data record per 500 m × 500 m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥ 50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.

Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

Science.gov (United States)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

2016-12-01

This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

Assessing the Accuracy of MODIS-NDVI Derived Land-Cover Across the Great Lakes Basin

Science.gov (United States)

This research describes the accuracy assessment process for a land-cover dataset developed for the Great Lakes Basin (GLB). This land-cover dataset was developed from the 2007 MODIS Normalized Difference Vegetation Index (NDVI) 16-day composite (MOD13Q) 250 m time-series data. Tr...

Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

Science.gov (United States)

Shen, Suhung; Leptoukh, Gregory G.

2011-01-01

Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

Science.gov (United States)

Pervez, Md Shahriar; Brown, Jesslyn F.

2010-01-01

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

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.

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...

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

Science.gov (United States)

Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

2017-06-01

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

Land cover in Upper Egypt assessed using regional and global land cover products derived from MODIS imagery.

Science.gov (United States)

Fuller, Douglas O; Parenti, Michael S; Gad, Adel M; Beier, John C

2012-01-01

Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of MODIS 250 m NDVI data and Landsat imagery to identify areas that changed from 2001-2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby water bodies. We used two different methods of time series analysis -- principal components (PCA) and harmonic decomposition (HD), applied to the MODIS 250 m NDVI images to derive simple three-class land cover maps and then assessed their accuracy using a set of reference polygons derived from 30 m Landsat 5 and 7 imagery. We analyzed our MODIS 250 m maps against a new MODIS global land cover product (MOD12Q1 collection 5) to assess whether regionally specific mapping approaches are superior to a standard global product. Results showed that the accuracy of the PCA-based product was greater than the accuracy of either the HD or MOD12Q1 products for the years 2001, 2003, and 2008. However, the accuracy of the PCA product was only slightly better than the MOD12Q1 for 2001 and 2003. Overall, the results suggest that our PCA-based approach produces a high level of user and producer accuracies, although the MOD12Q1 product also showed consistently high accuracy. Overlay of 2001-2008 PCA-based maps showed a net increase of 12 129 ha of irrigated vegetation, with the largest increase found from 2006-2008 around the Districts of Edfu and Kom Ombo. This result was unexpected in light of ambitious government plans to develop 336 000 ha of irrigated agriculture around the Toshka Lakes.

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

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.;

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

Downscaling of Aircraft, Landsat, and MODIS-bases Land Surface Temperature Images with Support Vector Machines

Science.gov (United States)

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at s...

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.

CHANGE DETECTION IN LAND-USE AND LAND-COVER DYNAMICS AT A REGIONAL SCALE FROM MODIS TIME-SERIES IMAGERY

Directory of Open Access Journals (Sweden)

Y. Setiawan

2012-07-01

Full Text Available Remote sensing has long been used as a means of detecting and classifying changes on the land. Analysis of multi-year time series of land surface attributes and their seasonal change indicates a complexity of land use land cover change (LULCC. This paper explores the temporal complexity of land change considering temporal vegetation dynamics, in other words, distinguishing the changes regarding to their properties in long-term image analysis. This study is based on the hypothesis that land cover might be dynamics; however, consistent land use has a typical, distinct and repeated temporal pattern of vegetation index inter-annually. Therefore, pixels represent a change when the inter-annual temporal dynamics is changed. We analysed the dynamics pattern of long-term image data of wavelet-filtered MODIS EVI from 2001 to 2007. The change of temporal vegetation dynamics was detected by differentiating distance between two successive annual EVI patterns. Moreover, we defined the type of changes using the clustering method, which were then validated by ground check points and secondary data sets.

Application of MODIS Land Products to Assessment of Land Degradation of Alpine Rangeland in Northern India with Limited Ground-Based Information

Directory of Open Access Journals (Sweden)

Masahiro Tasumi

2014-09-01

Full Text Available Land degradation of alpine rangeland in Dachigam National Park, Northern India, was evaluated in this study using MODerate resolution Imaging Spectroradiometer (MODIS land products. The park has been used by a variety of livestock holders. With increasing numbers of livestock, the managers and users of the park are apprehensive about degradation of the grazing land. However, owing to weak infrastructure for scientific and statistical data collection and sociopolitical restrictions in the region, a lack of quality ground-based weather, vegetation, and livestock statistical data had prevented scientific assessment. Under these circumstances, the present study aimed to assess the rangeland environment and its degradation using MODIS vegetation, snow, and evapotranspiration products as primary input data for assessment. The result of the analysis indicated that soil water content and the timing of snowmelt play an important role in grass production in the area. Additionally, the possibility of land degradation in heavily-grazed rangeland was indicated via a multiple regression analysis at a decadal timescale, whereas weather conditions, such as rainfall and snow cover, primarily explained year-by-year differences in grass production. Although statistical uncertainties remain in the results derived in this study, the satellite-based data and the analyses will promote understanding of the rangeland environment and suggest the potential for unsustainable land management based on statistical probability. This study provides an important initial evaluation of alpine rangeland, for which ground-based information is limited.

Estimating Daily Maximum and Minimum Land Air Surface Temperature Using MODIS Land Surface Temperature Data and Ground Truth Data in Northern Vietnam

Directory of Open Access Journals (Sweden)

Phan Thanh Noi

2016-12-01

Full Text Available This study aims to evaluate quantitatively the land surface temperature (LST derived from MODIS (Moderate Resolution Imaging Spectroradiometer MOD11A1 and MYD11A1 Collection 5 products for daily land air surface temperature (Ta estimation over a mountainous region in northern Vietnam. The main objective is to estimate maximum and minimum Ta (Ta-max and Ta-min using both TERRA and AQUA MODIS LST products (daytime and nighttime and auxiliary data, solving the discontinuity problem of ground measurements. There exist no studies about Vietnam that have integrated both TERRA and AQUA LST of daytime and nighttime for Ta estimation (using four MODIS LST datasets. In addition, to find out which variables are the most effective to describe the differences between LST and Ta, we have tested several popular methods, such as: the Pearson correlation coefficient, stepwise, Bayesian information criterion (BIC, adjusted R-squared and the principal component analysis (PCA of 14 variables (including: LST products (four variables, NDVI, elevation, latitude, longitude, day length in hours, Julian day and four variables of the view zenith angle, and then, we applied nine models for Ta-max estimation and nine models for Ta-min estimation. The results showed that the differences between MODIS LST and ground truth temperature derived from 15 climate stations are time and regional topography dependent. The best results for Ta-max and Ta-min estimation were achieved when we combined both LST daytime and nighttime of TERRA and AQUA and data from the topography analysis.

Combined ASTER and MODIS Emissivity database over Land (CAMEL) Coefficient Monthly Global 0.05Deg V001

Data.gov (United States)

National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined ASTER and MODIS Emissivity database over Land (CAMEL) dataset provides...

Combined ASTER and MODIS Emissivity database over Land (CAMEL) Emissivity Monthly Global 0.05Deg V001

Data.gov (United States)

National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined ASTER and MODIS Emissivity database over Land (CAMEL) dataset provides...

Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

Directory of Open Access Journals (Sweden)

Bo Gao

2014-09-01

Full Text Available Land surface albedo is an essential parameter for monitoring global/regional climate and land surface energy balance. Although many studies have been conducted on global or regional land surface albedo using various remote sensing data over the past few decades, land surface albedo product with a high spatio–temporal resolution is currently very scarce. This paper proposes a method for deriving land surface albedo with a high spatio–temporal resolution (space: 30 m and time: 2–4 days. The proposed method works by combining the land surface reflectance data at 30 m spatial resolution obtained from the charge-coupled devices in the Huanjing-1A and -1B (HJ-1A/B satellites with the Moderate Resolution Imaging Spectroradiometer (MODIS land surface bidirectional reflectance distribution function (BRDF parameters product (MCD43A1, which is at a spatial resolution of 500 m. First, the land surface BRDF parameters for HJ-1A/B land surface reflectance with a spatial–temporal resolutions of 30 m and 2–4 day are calculated on the basis of the prior knowledge from the MODIS BRDF product; then, the calculated high resolution BRDF parameters are integrated over the illuminating/viewing hemisphere to produce the white- and black-sky albedos at 30 m resolution. These results form the basis for the final land surface albedo derivation by accounting for the proportion of direct and diffuse solar radiation arriving at the ground. The albedo retrieved by this novel method is compared with MODIS land surface albedo products, as well as with ground measurements. The results show that the derived land surface albedo during the growing season of 2012 generally achieved a mean absolute accuracy of ±0.044, and a root mean square error of 0.039, confirming the effectiveness of the newly proposed method.

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

PRESENTED 11/01/05 LAND-COVER CHARACTERIZATION AND CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

Science.gov (United States)

Land-Cover (LC) composition and conversions are important factors that affect ecosystem condition and function. The purpose of this research and development effort is to investigate the feasibility of using MODIS derived Normalized Difference Vegetation Index (NDVI) data to deli...

A Generic Approach for Inversion of Surface Reflectance over Land: Overview, Application and Validation Using MODIS and LANDSAT8 Data

Science.gov (United States)

Vermote, E.; Roger, J. C.; Justice, C. O.; Franch, B.; Claverie, M.

2016-01-01

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This technique builds on the extensive dataset acquired by the Terra platform by combining MODIS and MISR to derive an explicit and dynamic map of band ratio's between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. We will present the generic approach and the application to MODIS and LANDSAT data and its validation using the AERONET data.

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

MODIS/Aqua Land Surface Temperature/Emissivity 8-Day L3 Global 0.05Deg CMG V041

Data.gov (United States)

National Aeronautics and Space Administration — The MYD11C2.041 dataset was decommissioned as of March 1, 2018. Users are encouraged to use Version 6 of MODIS/Aqua Land Surface Temperature and Emissivity Daily L3...

Heat waves measured with MODIS land surface temperature data predict changes in avian community structure

Science.gov (United States)

Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Volker C. Radeloff

2011-01-01

Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Specifically, we...

High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

Science.gov (United States)

Jeffrey T. Morisette; Jaime E. Nickeson; Paul Davis; Yujie Wang; Yuhong Tian; Curtis E. Woodcock; Nikolay Shabanov; Matthew Hansen; Warren B. Cohen; Doug R. Oetter; Robert E. Kennedy

2003-01-01

Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These...

Improving Soil Moisture Estimation with a Dual Ensemble Kalman Smoother by Jointly Assimilating AMSR-E Brightness Temperature and MODIS LST

Directory of Open Access Journals (Sweden)

Weijing Chen

2017-03-01

Full Text Available Uncertainties in model parameters can easily result in systematic differences between model states and observations, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this research, a soil moisture assimilation scheme is developed to jointly assimilate AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System brightness temperature (TB and MODIS (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (LST products, which also corrects model bias by simultaneously updating model states and parameters with a dual ensemble Kalman filter (DEnKS. Common Land Model (CoLM and a Radiative Transfer Model (RTM are adopted as model and observation operator, respectively. The assimilation experiment was conducted in Naqu on the Tibet Plateau from 31 May to 27 September 2011. The updated soil temperature at surface obtained by assimilating MODIS LST serving as inputs of RTM is to reduce the differences between the simulated and observed TB, then AMSR-E TB is assimilated to update soil moisture and model parameters. Compared with in situ measurements, the accuracy of soil moisture estimation derived from the assimilation experiment has been tremendously improved at a variety of scales. The updated parameters effectively reduce the states bias of CoLM. The results demonstrate the potential of assimilating AMSR-E TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study indicates that the developed scheme is an effective way to retrieve downscaled soil moisture when assimilating the coarse-scale microwave TB.

Impacts of Land Cover and Seasonal Variation on Maximum Air Temperature Estimation Using MODIS Imagery

Directory of Open Access Journals (Sweden)

Yulin Cai

2017-03-01

Full Text Available Daily maximum surface air temperature (Tamax is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST, a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland and two seasons (i.e., growing season and non-growing season. Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub, suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

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.

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.

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.

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

Detection of land cover change using an Artificial Neural Network on a time-series of MODIS satellite data

CSIR Research Space (South Africa)

Olivier, JC

2007-11-01

Full Text Available An Artificial Neural Network (ANN) is proposed to detect human-induced land cover change using a sliding window through a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite surface reflectance pixel values. Training...

Study of Maowusu Sandy Land Vegetation Coverage Change Based on Modis Ndvi

Science.gov (United States)

Ye, Q.; Liu, H.; Lin, Y.; Han, R.

2018-04-01

This paper selected 2006-2016 MODIS NDVI data with a spatial resolution of 500m and time resolution of 16d, got the 11 years' time series NDVI data of Maowusu sandy land through mosaicking, projection transformation, cutting process in batch. Analysed the spatial and temporal distribution and variation characteristics of vegetation cover in year, season and month time scales by maximum value composite, and unary linear regression analysis. Then, we combined the meteorological data of 33 sites around the sandy area, analysed the response characteristics of vegetation cover change to temperature and precipitation through Pearson correlation coefficient. Studies have shown that: (1) The NDVI value has a stable increase trend, which rate is 0.0075 / a. (2) The vegetation growth have significantly difference in four seasons, the NDVI value of summer > autumn > spring > winter. (3) The NDVI value change trend is conformed to the gauss normal distribution in a year, and it comes to be largest in August, its green season is in April, and yellow season is in the middle of November, the growth period is about 220 d. (4) The vegetation has a decreasing trend from the southeast to the northwest, most part is slightly improved, and Etuokeqianqi improved significantly. (5) The correlation indexes of annual NDVI with temperature and precipitation are -0.2178 and 0.6309, the vegetation growth is mainly affected by precipitation. In this study, a complete vegetation cover analysis and evaluation model for sandy land is established. It has important guiding significance for the sand ecological environment protection.

Distinguishing Land Change from Natural Variability and Uncertainty in Central Mexico with MODIS EVI, TRMM Precipitation, and MODIS LST Data

Directory of Open Access Journals (Sweden)

Zachary Christman

2016-06-01

Full Text Available Precipitation and temperature enact variable influences on vegetation, impacting the type and condition of land cover, as well as the assessment of change over broad landscapes. Separating the influence of vegetative variability independent and discrete land cover change remains a major challenge to landscape change assessments. The heterogeneous Lerma-Chapala-Santiago watershed of central Mexico exemplifies both natural and anthropogenic forces enacting variability and change on the landscape. This study employed a time series of Enhanced Vegetation Index (EVI composites from the Moderate Resolution Imaging Spectoradiometer (MODIS for 2001–2007 and per-pixel multiple linear regressions in order to model changes in EVI as a function of precipitation, temperature, and elevation. Over the seven-year period, 59.1% of the variability in EVI was explained by variability in the independent variables, with highest model performance among changing and heterogeneous land cover types, while intact forest cover demonstrated the greatest resistance to changes in temperature and precipitation. Model results were compared to an independent change uncertainty assessment, and selected regional samples of change confusion and natural variability give insight to common problems afflicting land change analyses.

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...

Analysis of Anomaly in Land Surface Temperature Using MODIS Products

Science.gov (United States)

Yorozu, K.; Kodama, T.; Kim, S.; Tachikawa, Y.; Shiiba, M.

2011-12-01

Atmosphere-land surface interaction plays a dominant role on the hydrologic cycle. Atmospheric phenomena cause variation of land surface state and land surface state can affect on atmosphereic conditions. Widely-known article related in atmospheric-land interaction was published by Koster et al. in 2004. The context of this article is that seasonal anomaly in soil moisture or soil surface temperature can affect summer precipitation generation and other atmospheric processes especially in middle North America, Sahel and south Asia. From not only above example but other previous research works, it is assumed that anomaly of surface state has a key factor. To investigate atmospheric-land surface interaction, it is necessary to analyze anomaly field in land surface state. In this study, soil surface temperature should be focused because it can be globally and continuously observed by satellite launched sensor. To land surface temperature product, MOD11C1 and MYD11C1 products which are kinds of MODIS products are applied. Both of them have 0.05 degree spatial resolution and daily temporal resolution. The difference of them is launched satellite, MOD11C1 is Terra and MYD11C1 is Aqua. MOD11C1 covers the latter of 2000 to present and MYD11C1 covers the early 2002 to present. There are unrealistic values on provided products even if daily product was already calibrated or corrected. For pre-analyzing, daily data is aggregated into 8-days data to remove irregular values for stable analysis. It was found that there are spatial and temporal distribution of 10-years average and standard deviation for each 8-days term. In order to point out extreme anomaly in land surface temperature, standard score for each 8-days term is applied. From the analysis of standard score, it is found there are large anomaly in land surface temperature around north China plain in early April 2005 and around Bangladesh in early May 2009.

Evaluation of the Consistency of MODIS Land Cover Product (MCD12Q1 Based on Chinese 30 m GlobeLand30 Datasets: A Case Study in Anhui Province, China

Directory of Open Access Journals (Sweden)

Dong Liang

2015-11-01

Full Text Available Land cover plays an important role in the climate and biogeochemistry of the Earth system. It is of great significance to produce and evaluate the global land cover (GLC data when applying the data to the practice at a specific spatial scale. The objective of this study is to evaluate and validate the consistency of the Moderate Resolution Imaging Spectroradiometer (MODIS land cover product (MCD12Q1 at a provincial scale (Anhui Province, China based on the Chinese 30 m GLC product (GlobeLand30. A harmonization method is firstly used to reclassify the land cover types between five classification schemes (International Geosphere Biosphere Programme (IGBP global vegetation classification, University of Maryland (UMD, MODIS-derived Leaf Area Index and Fractional Photosynthetically Active Radiation (LAI/FPAR, MODIS-derived Net Primary Production (NPP, and Plant Functional Type (PFT of MCD12Q1 and ten classes of GlobeLand30, based on the knowledge rule (KR and C4.5 decision tree (DT classification algorithm. A total of five harmonized land cover types are derived including woodland, grassland, cropland, wetland and artificial surfaces, and four evaluation indicators are selected including the area consistency, spatial consistency, classification accuracy and landscape diversity in the three sub-regions of Wanbei, Wanzhong and Wannan. The results indicate that the consistency of IGBP is the best among the five schemes of MCD12Q1 according to the correlation coefficient (R. The “woodland” LAI/FPAR is the worst, with a spatial similarity (O of 58.17% due to the misclassification between “woodland” and “others”. The consistency of NPP is the worst among the five schemes as the agreement varied from 1.61% to 56.23% in the three sub-regions. Furthermore, with the biggest difference of diversity indices between LAI/FPAR and GlobeLand30, the consistency of LAI/FPAR is the weakest. This study provides a methodological reference for evaluating the

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.

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.

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.

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

Science.gov (United States)

Li, Yonghong; Angal, Amit; Wu, Aisheng; Geng, Xu; Link, Daniel; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

Science.gov (United States)

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

Directory of Open Access Journals (Sweden)

Gemma Simó

2016-10-01

Full Text Available Land Surface Temperature (LST as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same observation time, for the very heterogeneous Campus of the University of the Balearic Islands (Mallorca, Western Mediterranean, with an area of about 1 km 2 , for a period between 2014 and 2016. Variations of LST between 10 and 20 K are often found at the sub-kilometre scale. In addition, MODIS values are compared to the ground truth for one point in the Campus, as obtained from a four-component net radiometer, and a bias of 3.2 K was found in addition to a Root Mean Square Error (RMSE of 4.2 K. An indication of a more elaborated local measurement strategy in the Campus is given, using an array of radiometers distributed in the area.

Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

Directory of Open Access Journals (Sweden)

F. Alkhaier

2012-07-01

Full Text Available The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Moreover, these measurements can help to include the effect of shallow groundwater on surface energy balance within land surface models and climate studies, which broadens the methods that yield more reliable and informative results. To examine the capacity of MODIS in detecting the effect of shallow groundwater on land surface temperature and the surface energy balance in an area within Al-Balikh River basin in northern Syria, we studied the interrelationship between in-situ measured water table depths and land surface temperatures measured by MODIS. We, also, used the Surface Energy Balance System (SEBS to calculate surface energy fluxes, evaporative fraction and daily evaporation, and inspected their relationships with water table depths. We found out that the daytime temperature increased while the nighttime temperature decreased when the depth of the water table increased. And, when the water table depth increased, net radiation, latent and ground heat fluxes, evaporative fraction and daily evaporation decreased, while sensible heat flux increased. This concords with the findings of a companion paper (Alkhaier et al., 2012. The observed clear relationships were the result of meeting both conditions that were concluded in the companion paper, i.e. high potential evaporation and big contrast in day-night temperature. Moreover, the prevailing conditions in this study area helped SEBS to yield accurate estimates. Under bare soil conditions and under the prevailing weather conditions, we conclude that MODIS is suitable for detecting the effect of shallow groundwater because it has proper imaging times and adequate sensor accuracy; nevertheless, its coarse spatial resolution is disadvantageous.

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

Detecting spatio-temporal changes in agricultural land use in Heilongjiang province, China using MODIS time-series data and a random forest regression model

Science.gov (United States)

Hu, Q.; Friedl, M. A.; Wu, W.

2017-12-01

Accurate and timely information regarding the spatial distribution of crop types and their changes is essential for acreage surveys, yield estimation, water management, and agricultural production decision-making. In recent years, increasing population, dietary shifts and climate change have driven drastic changes in China's agricultural land use. However, no maps are currently available that document the spatial and temporal patterns of these agricultural land use changes. Because of its short revisit period, rich spectral bands and global coverage, MODIS time series data has been shown to have great potential for detecting the seasonal dynamics of different crop types. However, its inherently coarse spatial resolution limits the accuracy with which crops can be identified from MODIS in regions with small fields or complex agricultural landscapes. To evaluate this more carefully and specifically understand the strengths and weaknesses of MODIS data for crop-type mapping, we used MODIS time-series imagery to map the sub-pixel fractional crop area for four major crop types (rice, corn, soybean and wheat) at 500-m spatial resolution for Heilongjiang province, one of the most important grain-production regions in China where recent agricultural land use change has been rapid and pronounced. To do this, a random forest regression (RF-g) model was constructed to estimate the percentage of each sub-pixel crop type in 2006, 2011 and 2016. Crop type maps generated through expert visual interpretation of high spatial resolution images (i.e., Landsat and SPOT data) were used to calibrate the regression model. Five different time series of vegetation indices (155 features) derived from different spectral channels of MODIS land surface reflectance (MOD09A1) data were used as candidate features for the RF-g model. An out-of-bag strategy and backward elimination approach was applied to select the optimal spectra-temporal feature subset for each crop type. The resulting crop maps

An Efficient Approach for Pixel Decomposition to Increase the Spatial Resolution of Land Surface Temperature Images from MODIS Thermal Infrared Band Data

Directory of Open Access Journals (Sweden)

Fei Wang

2014-12-01

Full Text Available Land surface temperature (LST images retrieved from the thermal infrared (TIR band data of Moderate Resolution Imaging Spectroradiometer (MODIS have much lower spatial resolution than the MODIS visible and near-infrared (VNIR band data. The coarse pixel scale of MODIS LST images (1000 m under nadir have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250–500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD. Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI and building index (NDBI, reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER with much higher spatial resolution than MODIS data was on-board the same platform (Terra as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error

An efficient approach for pixel decomposition to increase the spatial resolution of land surface temperature images from MODIS thermal infrared band data.

Science.gov (United States)

Wang, Fei; Qin, Zhihao; Li, Wenjuan; Song, Caiying; Karnieli, Arnon; Zhao, Shuhe

2014-12-25

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250-500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2

A Web Architecture to Geographically Interrogate CHIRPS Rainfall and eMODIS NDVI for Land Use Change

Science.gov (United States)

Burks, Jason E.; Limaye, Ashutosh

2014-01-01

Monitoring of rainfall and vegetation over the continent of Africa is important for assessing the status of crop health and agriculture, along with long-term changes in land use change. These issues can be addressed through examination of long-term precipitation (rainfall) data sets and remote sensing of land surface vegetation and land use types. Two products have been used previously to address these goals: the Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) rainfall data, and multi-day composites of Normalized Difference Vegetation Index (NDVI) from the USGS eMODIS product. Combined, these are very large data sets that require unique tools and architecture to facilitate a variety of data analysis methods or data exploration by the end user community. To address these needs, a web-enabled system has been developed to allow end-users to interrogate CHIRPS rainfall and eMODIS NDVI data over the continent of Africa. The architecture allows end-users to use custom defined geometries, or the use of predefined political boundaries in their interrogation of the data. The massive amount of data interrogated by the system allows the end-users with only a web browser to extract vital information in order to investigate land use change and its causes. The system can be used to generate daily, monthly and yearly averages over a geographical area and range of dates of interest to the user. It also provides analysis of trends in precipitation or vegetation change for times of interest. The data provided back to the end-user is displayed in graphical form and can be exported for use in other, external tools. The development of this tool has significantly decreased the investment and requirements for end-users to use these two important datasets, while also allowing the flexibility to the end-user to limit the search to the area of interest.

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

Quantitative estimation of land surface evapotranspiration in Taiwan based on MODIS data

Directory of Open Access Journals (Sweden)

Che-sheng Zhan

2011-09-01

Full Text Available Land surface evapotranspiration (ET determines the local and regional water-heat balances. Accurate estimation of regional surface ET provides a scientific basis for the formulation and implementation of water conservation programs. This study set up a table of the momentum roughness length and zero-plane displacement related with land cover and an empirical relationship between land surface temperature and air temperature. A revised quantitative remote sensing ET model, the SEBS-Taiwan model, was developed. Based on Moderate Resolution Imaging Spectroradiometer (MODIS data, SEBS-Taiwan was used to simulate and evaluate the typical actual daily ET values in different seasons of 2002 and 2003 in Taiwan. SEBS-Taiwan generally performed well and could accurately simulate the actual daily ET. The simulated daily ET values matched the observed values satisfactorily. The results indicate that the net regional solar radiation, evaporation ratio, and surface ET values for the whole area of Taiwan are larger in summer than in spring, and larger in autumn than in winter. The results also show that the regional average daily ET values of 2002 are a little higher than those of 2003. Through analysis of the ET values from different types of land cover, we found that forest has the largest ET value, while water areas, bare land, and urban areas have the lowest ET values. Generally, the Northern Taiwan area, including Ilan County, Nantou County, and Hualien County, has higher ET values, while other cities, such as Chiayi, Taichung, and Tainan, have lower ET values.

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.

Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types

Czech Academy of Sciences Publication Activity Database

Shi, H.; Li, L.; Eamus, D.; Huete, A.; Cleverly, J.; Tian, X.; Yu, Q.; Wang, S.; Montagnani, L.; Magliulo, V.; Rotenberg, E.; Pavelka, Marian; Carrara, A.

2017-01-01

Roč. 72, Jan (2017), s. 153-164 ISSN 1470-160X R&D Projects: GA MŠk(CZ) LM2015061 Institutional support: RVO:67179843 Keywords : Enhanced vegetation index * Gross primary production * Land cover types * Leaf area index * MODIS * Remote sensing Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 3.898, year: 2016

Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

Directory of Open Access Journals (Sweden)

C. Höpfner

2011-11-01

-annual time scale to NDVI percentiles (50 % of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r²=0.64. In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI values. High-productive vegetation (cropland is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover, as well as prediction methods of land cover change, can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco. It especially offers a quick access when estimating the extent of agricultural lands.

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

Science.gov (United States)

Boyte, Stephen; Wylie, Bruce K.; Rigge, Matthew B.; Dahal, Devendra

2018-01-01

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

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.

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 ...

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

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

Science.gov (United States)

Ran, L.; Cooter, E. J.; Gilliam, R. C.; Foroutan, H.; Kang, D.; Appel, W.; Wong, D. C.; Pleim, J. E.; Benson, V.; Pouliot, G.

2017-12-01

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteorology, climate, and chemical transport. The Environmental Policy Integrated Climate (EPIC) is a cropping model which has long been used in a range of applications related to soil erosion, crop productivity, climate change, and water quality around the world. We have integrated WRF/CMAQ with EPIC using the Fertilizer Emission Scenario Tool for CMAQ (FEST-C) to estimate daily soil N information with fertilization for CMAQ bi-directional ammonia flux modeling. Driven by the weather and N deposition from WRF/CMAQ, FEST-C EPIC simulations are conducted on 22 different agricultural production systems ranging from managed grass lands (e.g. hay and alfalfa) to crop lands (e.g. corn grain and soybean) with rainfed and irrigated information across any defined conterminous United States (U.S.) CMAQ domain and grid resolution. In recent years, this integrated system has been enhanced and applied in many different air quality and ecosystem assessment projects related to land-water-atmosphere interactions. These enhancements have advanced this system to become a valuable tool for integrated assessments of air, land and water quality in light of social drivers and human and ecological outcomes. This presentation will focus on evaluating the sensitivity of precipitation and N deposition in the integrated system to MODIS vegetation input and lightning assimilation and their impacts on agricultural production and fertilization. We will describe the integrated modeling system and evaluate simulated precipitation and N deposition along with other weather information (e.g. temperature, humidity) for 2011 over the conterminous U.S. at 12 km grids from a coupled WRF/CMAQ with MODIS and lightning assimilation

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

An Improved Method For Retrieving Land Surface Albedo Over Rugged Terrain

NARCIS (Netherlands)

Gao, B.; Jia, L.; Menenti, M.

2014-01-01

Land surface albedo is a very important parameter, which can be derived from a bidirectional reflectance distribution function (BRDF) model with angular integration of BRDF in a particular distribution of downward solar irradiance. The Algorithm for MODIS Bidirectional Reflectance Anisotropic of

Towards an improved Land Surface Phenology mapping using a new MODIS product: A case study of Bavarian Forest National Park

Science.gov (United States)

Misra, Gourav; Buras, Allan; Asam, Sarah; Menzel, Annette

2017-04-01

Past work in remote sensing of land surface phenology have mapped vegetation cycles at multiple scales. Much has been discussed and debated about the uncertainties associated with the selection of data, data processing and the eventual conclusions drawn. Several studies do however provide evidence of strong links between different land surface phenology (LSP) metrics with specific ground phenology (GP) (Fisher and Mustard, 2007; Misra et al., 2016). Most importantly the use of high temporal and spatial resolution remote sensing data and ground truth information is critical for such studies. In this study, we use a higher temporal resolution 4 day MODIS NDVI product developed by EURAC (Asam et al., in prep) for the Bavarian Forest National Park during 2002-2015 period and extract various phenological metrics covering different phenophases of vegetation (start of season / sos and end of season / eos). We found the LSP-sos to be more strongly linked to the elevation of the area than LSP-eos which has been cited to be harder to detect (Stöckli et al., 2008). The LSP metrics were also correlated to GP information at 4 different stations covering elevations ranging from approx. 500 to 1500 metres. Results show that among the five dominant species in the area i.e. European ash, Norway spruce, European beech, Norway maple and orchard grass, only particular GP observations for some species show stronger correlations with LSP than others. Spatial variations in the LSP-GP correlations were also observed, with certain areas of the National Park showing positive correlations and others negative. An analysis of temporal trends of LSP also indicates the possibility to detect those areas in the National Park that were affected by extreme events. Further investigations are planned to explain the heterogeneity in the derived LSP metrics using high resolution ground truth data and multivariate statistical analyses. Acknowledgement: This research received funding from the Bavarian

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...

Deriving Vegetation Dynamics of Natural Terrestrial Ecosystems from MODIS NDVI/EVI Data over Turkey.

Science.gov (United States)

Evrendilek, Fatih; Gulbeyaz, Onder

2008-09-01

The 16-day composite MODIS vegetation indices (VIs) at 500-m resolution for the period between 2000 to 2007 were seasonally averaged on the basis of the estimated distribution of 16 potential natural terrestrial ecosystems (NTEs) across Turkey. Graphical and statistical analyses of the time-series VIs for the NTEs spatially disaggregated in terms of biogeoclimate zones and land cover types included descriptive statistics, correlations, discrete Fourier transform (DFT), time-series decomposition, and simple linear regression (SLR) models. Our spatio-temporal analyses revealed that both MODIS VIs, on average, depicted similar seasonal variations for the NTEs, with the NDVI values having higher mean and SD values. The seasonal VIs were most correlated in decreasing order for: barren/sparsely vegetated land > grassland > shrubland/woodland > forest; (sub)nival > warm temperate > alpine > cool temperate > boreal = Mediterranean; and summer > spring > autumn > winter. Most pronounced differences between the MODIS VI responses over Turkey occurred in boreal and Mediterranean climate zones and forests, and in winter (the senescence phase of the growing season). Our results showed the potential of the time-series MODIS VI datasets in the estimation and monitoring of seasonal and interannual ecosystem dynamics over Turkey that needs to be further improved and refined through systematic and extensive field measurements and validations across various biomes.

Highlighting continued uncertainty in global land cover maps for the user community

International Nuclear Information System (INIS)

Fritz, Steffen; See, Linda; McCallum, Ian; Schill, Christian; Obersteiner, Michael; Van der Velde, Marijn; Boettcher, Hannes; Havlík, Petr; Achard, Frédéric

2011-01-01

In the last 10 years a number of new global datasets have been created and new, more sophisticated algorithms have been designed to classify land cover. GlobCover and MODIS v.5 are the most recent global land cover products available, where GlobCover (300 m) has the finest spatial resolution of other comparable products such as MODIS v.5 (500 m) and GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has decreased when comparing these two latest products. This disagreement is also evident spatially when examining maps of cropland and forest disagreement between GLC-2000, MODIS and GlobCover. The analysis highlights the continued uncertainty surrounding these products, with a combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). This letter suggests that data sharing efforts and the provision of more in situ data for training, calibration and validation are very important conditions for improving future global land cover products.

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.

Estimating spatially distributed monthly evapotranspiration rates by linear transformations of MODIS daytime land surface temperature data

Directory of Open Access Journals (Sweden)

J. Szilagyi

2009-05-01

Full Text Available Under simplifying conditions catchment-scale vapor pressure at the drying land surface can be calculated as a function of its watershed-representative temperature (<T_s> by the wet-surface equation (WSE, similar to the wet-bulb equation in meteorology for calculating the dry-bulb thermometer vapor pressure of the Complementary Relationship of evaporation. The corresponding watershed ET rate, , is obtained from the Bowen ratio with the help of air temperature, humidity and percent possible sunshine data. The resulting (<T_s>, pair together with the wet-environment surface temperature (<T_ws> and ET rate (ET_w, obtained by the Priestley-Taylor equation, define a linear transformation on a monthly basis by which spatially distributed ET rates can be estimated as a sole function of MODIS daytime land surface temperature, T_s, values within the watershed. The linear transformation preserves the mean which is highly desirable. <T_ws>, in the lack of significant open water surfaces within the study watershed (Elkhorn, Nebraska, was obtained as the mean of the smallest MODIS T_s values each month. The resulting period-averaged (2000–2007 catchment-scale ET rate of 624 mm/yr is very close to the water-balance derived ET rate of about 617 mm/yr. The latter is a somewhat uncertain value due to the effects of (a observed groundwater depletion of about 1m over the study period caused by extensive irrigation, and; (b the uncertain rate of net regional groundwater supply toward the watershed. The spatially distributed ET rates correspond well with soil/aquifer properties and the resulting land use type (i.e. rangeland versus center-pivot irrigated crops.

Mapping Flooded Rice Paddies Using Time Series of MODIS Imagery in the Krishna River Basin, India

Directory of Open Access Journals (Sweden)

Pardhasaradhi Teluguntla

2015-07-01

Full Text Available Rice is one of the major crops cultivated predominantly in flooded paddies, thus a large amount of water is consumed during its growing season. Accurate paddy rice maps are therefore important inputs for improved estimates of actual evapotranspiration in the agricultural landscape. The main objective of this study was to obtain flooded paddy rice maps using multi-temporal images of Moderate Resolution Imaging Spectroradiometer (MODIS in the Krishna River Basin, India. First, ground-based spectral samples collected by a field spectroradiometer, CROPSCAN, were used to demonstrate unique contrasts between the Normalized Difference Vegetation Index (NDVI and the Land Surface Water Index (LSWI observed during the transplanting season of rice. The contrast between Enhanced Vegetation Index (EVI and Land Surface Water Index (LSWI from MODIS time series data was then used to generate classification decision rules to map flooded rice paddies, for the transplanting seasons of Kharif and Rabi rice crops in the Krishna River Basin. Consistent with ground spectral observations, the relationship of the MODIS EVI vs. LSWI of paddy rice fields showed distinct features from other crops during the transplanting seasons. The MODIS-derived maps were validated against extensive reference data collected from multiple land use field surveys. The accuracy of the paddy rice maps, when determined using field plot data, was approximately 78%. The MODIS-derived rice crop areas were also compared with the areas reported by Department of Agriculture (DOA, Government of India (Government Statistics. The estimated root mean square difference (RMSD of rice area estimated using MODIS and those reported by the Department of Agriculture over 10 districts varied between 3.4% and 6.6% during 10 years of our study period. Some of the major factors responsible for this difference include high noise of the MODIS images during the prolonged monsoon seasons (typically June–October and

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

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

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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.

Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Products over the Corn Belt in the US

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Linglin Zeng

2015-01-01

Full Text Available Air temperature (Ta is a key input in a wide range of agroclimatic applications. Moderate Resolution Imaging Spectroradiometer (MODIS Ts (Land Surface Temperature (LST products are widely used to estimate daily Ta. However, only daytime LST (Ts-day or nighttime LST (Ts-night data have been used to estimate Tmax/Tmin (daily maximum or minimum air temperature, respectively. The relationship between Tmax and Ts-night, and the one between Tmin and Ts-day has not been studied. In this study, both the ability of Ts-night data to estimate Tmax and the ability of Ts-day data to estimate Tmin were tested and studied in the Corn Belt during the growing season (May–September from 2008 to 2012, using MODIS daily LST products from both Terra and Aqua. The results show that using Ts-night for estimating Tmax could result in a higher accuracy than using Ts-day for a similar estimate. Combining Ts-day and Ts-night, the estimation of Tmax was improved by 0.19–1.85, 0.37–1.12 and 0.26–0.93 °C for crops, deciduous forest and developed areas, respectively, when compared with using only Ts-day or Ts-night data. The main factors influencing the Ta estimation errors spatially and temporally were analyzed and discussed, such as satellite overpassing time, air masses, irrigation, etc.

Antarctic Temperature Extremes from MODIS Land Surface Temperatures: New Processing Methods Reveal Data Quality Puzzles

Science.gov (United States)

Grant, G.; Gallaher, D. W.

2017-12-01

New methods for processing massive remotely sensed datasets are used to evaluate Antarctic land surface temperature (LST) extremes. Data from the MODIS/Terra sensor (Collection 6) provides a twice-daily look at Antarctic LSTs over a 17 year period, at a higher spatiotemporal resolution than past studies. Using a data condensation process that creates databases of anomalous values, our processes create statistical images of Antarctic LSTs. In general, the results find few significant trends in extremes; however, they do reveal a puzzling picture of inconsistent cloud detection and possible systemic errors, perhaps due to viewing geometry. Cloud discrimination shows a distinct jump in clear-sky detections starting in 2011, and LSTs around the South Pole exhibit a circular cooling pattern, which may also be related to cloud contamination. Possible root causes are discussed. Ongoing investigations seek to determine whether the results are a natural phenomenon or, as seems likely, the results of sensor degradation or processing artefacts. If the unusual LST patterns or cloud detection discontinuities are natural, they point to new, interesting processes on the Antarctic continent. If the data artefacts are artificial, MODIS LST users should be alerted to the potential issues.

Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

Science.gov (United States)

Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

2017-11-01

Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference ( RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons ( RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

MODIS Data Assimilation in the CROPGRO model for improving soybean yield estimations

Science.gov (United States)

Richetti, J.; Monsivais-Huertero, A.; Ahmad, I.; Judge, J.

2017-12-01

Soybean is one of the main agricultural commodities in the world. Thus, having better estimates of its agricultural production is important. Improving the soybean crop models in Brazil is crucial for better understanding of the soybean market and enhancing decision making, because Brazil is the second largest soybean producer in the world, Parana state is responsible for almost 20% of it, and by itself would be the fourth greatest soybean producer in the world. Data assimilation techniques provide a method to improve spatio-temporal continuity of crops through integration of remotely sensed observations and crop growth models. This study aims to use MODIS EVI to improve DSSAT-CROPGRO soybean yield estimations in the Parana state, southern Brazil. The method uses the Ensemble Kalman filter which assimilates MODIS Terra and Aqua combined products (MOD13Q1 and MYD13Q1) into the CROPGRO model to improve the agricultural production estimates through update of light interception data over time. Expected results will be validated with monitored commercial farms during the period of 2013-2014.

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.

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

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

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

Science.gov (United States)

Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

2014-01-01

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

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.

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

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

Analysis of land degradation processes on a tiger bush plateau in South West Niger using MODIS and LANDSAT TM/ETM+ data

Science.gov (United States)

Fiorillo, Edoardo; Maselli, Fabio; Tarchiani, Vieri; Vignaroli, Patrizio

2017-10-01

Remote sensing digital image analysis has been applied to monitor land clearing and degradation processes on a plateau covered by tiger bush near Niamey in South West Niger, where signs of severe landscape degradation due to fuelwood supply have been observed in the last decades. A MODIS NDVI dataset (2000-2015) and five LANDSAT images (1986-2012) were used to identify spatial and temporal dynamics and to emphasize areas of greater degradation. The study indicates that the land clearing found by previous investigations in the second part of the 20th century is still ongoing, with a decreasing trend of MODIS NDVI values recorded in the period 2000-2015. This trend appeared to be linked to an increase in bare soil areas that was demonstrated by analysis of LANDSAT SAVI images. The investigation also indicated that rates of degradation are stronger in more deteriorated areas like those located nearer Niamey; degradation patterns also tend to increase from the inner areas to the edges of the plateau. These results attest to the urgency to develop effective environmental preservation policies and find alternative solutions for domestic energy supply.

Regional fire monitoring and characterization using global NASA MODIS fire products in dry lands of Central Asia

Science.gov (United States)

Loboda, Tatiana V.; Giglio, Louis; Boschetti, Luigi; Justice, Christopher O.

2012-06-01

Central Asian dry lands are grass- and desert shrub-dominated ecosystems stretching across Northern Eurasia. This region supports a population of more than 100 million which continues to grow at an average rate of 1.5% annually. Dry steppes are the primary grain and cattle growing zone within Central Asia. Degradation of this ecosystem through burning and overgrazing directly impacts economic growth and food supply in the region. Fire is a recurrent disturbance agent in dry lands contributing to soil erosion and air pollution. Here we provide an overview of inter-annual and seasonal fire dynamics in Central Asia obtained from remotely sensed data. We evaluate the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) global fire products within Central Asian dry lands and use these products to characterize fire occurrence between 2001 and 2009. The results show that on average ˜15 million ha of land burns annually across Central Asia with the majority of the area burned in August and September in grasslands. Fire is used as a common crop residue management practice across the region. Nearly 89% of all burning occurs in Kazakhstan, where 5% and 3% of croplands and grasslands, respectively, are burned annually.

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

Science.gov (United States)

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-05-07

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

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...

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.

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...

Application of Modis Data to Assess the Latest Forest Cover Changes of Sri Lanka

Science.gov (United States)

Perera, K.; Herath, S.; Apan, A.; Tateishi, R.

2012-07-01

Assessing forest cover of Sri Lanka is becoming important to lower the pressure on forest lands as well as man-elephant conflicts. Furthermore, the land access to north-east Sri Lanka after the end of 30 years long civil war has increased the need of regularly updated land cover information for proper planning. This study produced an assessment of the forest cover of Sri Lanka using two satellite data based maps within 23 years of time span. For the old forest cover map, the study used one of the first island-wide digital land cover classification produced by the main author in 1988. The old land cover classification was produced at 80 m spatial resolution, using Landsat MSS data. A previously published another study by the author has investigated the application feasibility of MODIS and Landsat MSS imagery for a selected sub-section of Sri Lanka to identify the forest cover changes. Through the light of these two studies, the assessment was conducted to investigate the application possibility of MODIS 250 m over a small island like Sri Lanka. The relation between the definition of forest in the study and spatial resolution of the used satellite data sets were considered since the 2012 map was based on MODIS data. The forest cover map of 1988 was interpolated into 250 m spatial resolution to integrate with the GIS data base. The results demonstrated the advantages as well as disadvantages of MODIS data in a study at this scale. The successful monitoring of forest is largely depending on the possibility to update the field conditions at regular basis. Freely available MODIS data provides a very valuable set of information of relatively large green patches on the ground at relatively real-time basis. Based on the changes of forest cover from 1988 to 2012, the study recommends the use of MODIS data as a resalable method to forest assessment and to identify hotspots to be re-investigated. It's noteworthy to mention the possibility of uncounted small isolated pockets of

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

Science.gov (United States)

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...

Applications of Near Real-Time Image and Fire Products from MODIS

Science.gov (United States)

Schmaltz, J. E.; Ilavajhala, S.; Teague, M.; Ye, G.; Masuoka, E.; Davies, D.; Murphy, K. J.; Michael, K.

2010-12-01

NASA’s MODIS Rapid Response Project (http://rapidfire.sci.gsfc.nasa.gov/) has been providing MODIS fire detections and imagery in near real-time since 2001. The Rapid Response system is part of the Land and Atmospheres Near-real time Capability for EOS (LANCE-MODIS) system. Current capabilities include providing MODIS imagery in true color and false color band combinations, a vegetation index, and temperature - in both uncorrected swath format and geographically corrected subset regions. The geographically-corrected subsets images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. These data are available within a few hours of data acquisition. The images are accessed by large number of user communities to obtain a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (fires, oil spills, floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. In addition, the scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. The MODIS Rapid Response project has also been providing a near real-time data feed on fire locations and MODIS imagery subsets to the Fire Information for Resource Management System (FIRMS) project (http://maps.geog.umd.edu/firms). FIRMS provides timely availability of fire location information, which is essential in preventing and fighting large forest/wild fires. Products are available through a WebGIS for visualizing MODIS hotspots and MCD45 Burned Area images, an email alerting tool to deliver fire data on daily/weekly/near real-time basis, active data downloads in formats such as shape, KML, CSV, WMS, etc., along with MODIS imagery subsets. FIRMS’ user base covers more than 100 countries and territories. A recent user

MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

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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.

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.

Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images

Science.gov (United States)

Hengl, Tomislav; Heuvelink, Gerard B. M.; Perčec Tadić, Melita; Pebesma, Edzer J.

2012-01-01

A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations (159) in Croatia. The input data set contains 57,282 ground measurements of daily temperature for the year 2008. Temperature was modeled as a function of latitude, longitude, distance from the sea, elevation, time, insolation, and the MODIS LST images. The original rasters were first converted to principal components to reduce noise and filter missing pixels in the LST images. The residual were next analyzed for spatio-temporal auto-correlation; sum-metric separable variograms were fitted to account for zonal and geometric space-time anisotropy. The final predictions were generated for time-slices of a 3D space-time cube, constructed in the R environment for statistical computing. The results show that the space-time regression model can explain a significant part of the variation in station-data (84%). MODIS LST 8-day (cloud-free) images are unbiased estimator of the daily temperature, but with relatively low precision (±4.1°C); however their added value is that they systematically improve detection of local changes in land surface temperature due to local meteorological conditions and/or active heat sources (urban areas, land cover classes). The results of 10-fold cross-validation show that use of spatio-temporal regression-kriging and incorporation of time-series of remote sensing images leads to significantly more accurate maps of temperature than if plain spatial techniques were used. The average (global) accuracy of mapping temperature was ±2.4°C. The regression-kriging explained 91% of variability in daily temperatures, compared to 44% for ordinary kriging. Further software advancement—interactive space-time variogram exploration and automated retrieval

Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method

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Xiaokang Kou

2016-01-01

Full Text Available Land surface temperature (LST plays a major role in the study of surface energy balances. Remote sensing techniques provide ways to monitor LST at large scales. However, due to atmospheric influences, significant missing data exist in LST products retrieved from satellite thermal infrared (TIR remotely sensed data. Although passive microwaves (PMWs are able to overcome these atmospheric influences while estimating LST, the data are constrained by low spatial resolution. In this study, to obtain complete and high-quality LST data, the Bayesian Maximum Entropy (BME method was introduced to merge 0.01° and 0.25° LSTs inversed from MODIS and AMSR-E data, respectively. The result showed that the missing LSTs in cloudy pixels were filled completely, and the availability of merged LSTs reaches 100%. Because the depths of LST and soil temperature measurements are different, before validating the merged LST, the station measurements were calibrated with an empirical equation between MODIS LST and 0~5 cm soil temperatures. The results showed that the accuracy of merged LSTs increased with the increasing quantity of utilized data, and as the availability of utilized data increased from 25.2% to 91.4%, the RMSEs of the merged data decreased from 4.53 °C to 2.31 °C. In addition, compared with the filling gap method in which MODIS LST gaps were filled with AMSR-E LST directly, the merged LSTs from the BME method showed better spatial continuity. The different penetration depths of TIR and PMWs may influence fusion performance and still require further studies.

Mapping Crop Cycles in China Using MODIS-EVI Time Series

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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.

Validation of MODIS snow cover images over Austria

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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.

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.

Impact of MODIS SWIR Band Calibration Improvements on Level-3 Atmospheric Products

Science.gov (United States)

Wald, Andrew; Levy, Robert; Angal, Amit; Geng, Xu; Xiong, Jack; Hoffman, Kurt

2016-01-01

The spectral reflectance measured by the MODIS reflective solar bands (RSB) is used for retrieving many atmospheric science products. The accuracy of these products depends on the accuracy of the calibration of the RSB. To this end, the RSB of the MODIS instruments are primarily calibrated on-orbit using regular solar diffuser (SD) observations. For lambda 0.94 microns, the MODIS Characterization Support Team (MCST) developed, in MODIS Collection 6 (C6), a time-dependent correction using observations from pseudo-invariant earth-scene targets. This correction has been implemented in C6 for the Terra MODIS 1.24 micron band over the entire mission, and for the 1.375 micron band in the forward processing. As the instruments continue to operate beyond their design lifetime of six years, a similar correction is planned for other short-wave infrared (SWIR) bands as well. MODIS SWIR bands are used in deriving atmosphere products, including aerosol optical thickness, atmospheric total column water vapor, cloud fraction and cloud optical depth. The SD degradation correction in Terra bands 5 and 26 impact the spectral radiance and therefore the retrieval of these atmosphere products. Here, we describe the corrections to Bands 5 (1.24 microns) and 26 (1.375 microns), and produce three sets (B5, B26 correction on/on, on/off, and off/off) of Terra-MODIS Level 1B (calibrated radiance product) data. By comparing products derived from these corrected and uncorrected Terra MODIS Level 1B (L1B) calibrations, dozens of L3 atmosphere products are surveyed for changes caused by the corrections, and representative results are presented. Aerosol and water vapor products show only small local changes, while some cloud products can change locally by > 10%, which is a large change.

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

Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition

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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.

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

[Winter wheat area estimation with MODIS-NDVI time series based on parcel].

Science.gov (United States)

Li, Le; Zhang, Jin-shui; Zhu, Wen-quan; Hu, Tan-gao; Hou, Dong

2011-05-01

Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

Science.gov (United States)

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Qingsong; Kim, JiHyun; Erb, Angela M.; Gao, Feng; Román, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey R.; Masek, Jeffrey G.; Morisette, Jeffrey T.; Zhang, Xiaoyang; Papuga, Shirley A.

2017-07-01

bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Trend analysis of GIMMS and MODIS NDVI time series for establishing a land degradation neutrality national baseline

Science.gov (United States)

Gichenje, Helene; Godinho, Sergio

2017-04-01

Land degradation is a key global environment and development problem that is recognized as a priority by the international development community. The Sustainable Development Goals (SDGs) were adopted by the global community in 2015, and include a goal related to land degradation and the accompanying target to achieve a land degradation-neutral (LDN) world by 2030. The LDN concept encompasses two joint actions of reducing the rate of degradation and increasing the rate of restoration. Using Kenya as the study area, this study aims to develop and test a spatially explicit methodology for assessing and monitoring the operationalization of a land degradation neutrality scheme at the national level. Time series analysis is applied to Normalized Difference Vegetation Index (NDVI) satellite data records, based on the hypothesis that the resulting NDVI residual trend would enable successful detection of changes in vegetation photosynthetic capacity and thus serve as a proxy for land degradation and regeneration processes. Two NDVI data sets are used to identify the spatial and temporal distribution of degraded and regenerated areas: the long term coarse resolution (8km, 1982-2015) third generation Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g data record; and the shorter-term finer resolution (250m, 2001-2015) Moderate Resolution Imaging Spectroradiometer (MODIS) derived NDVI data record. Climate data (rainfall, temperature and soil moisture) are used to separate areas of human-induced vegetation productivity decline from those driven by climate dynamics. Further, weekly vegetation health (VH) indexes (4km, 1982-2015) developed by National Oceanic and Atmospheric Administration (NOAA), are assessed as indicators for early detection and monitoring of land degradation by estimating vegetation stress (moisture, thermal and combined conditions).

Global Surface Net-Radiation at 5 km from MODIS Terra

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Manish Verma

2016-09-01

Full Text Available Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years from the FLUXNET and Surface Radiation budget network (SURFRAD showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott’s index ranged from 0.74 for boreal to 0.63 for Mediterranean sites. Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W∙m−2 in boreal to 72.0 ± 4.1 W∙m−2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° × 1° but high temporal resolution gridded net-radiation product from the Clouds and Earth’s Radiant Energy System (CERES. Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10 W·m−2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the

Operationalizing a Research Sensor: MODIS to VIIRS

Science.gov (United States)

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

2012-12-01

The National Oceanic and Atmospheric Administration (NOAA) and NASA are jointly acquiring the next-generation civilian environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA. The JPSS satellite will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The primary sensor for the JPSS mission is the Visible/Infrared Imager Radiometer Suite (VIIRS) developed by Raytheon Space and Airborne Systems (SAS). The ground processing system for the JPSS mission is known as the Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS) which are both developed by Raytheon Intelligence and Information Systems (IIS). The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by Raytheon SAS for the NASA Earth Observing System (EOS) as a research instrument to capture data in 36 spectral bands, ranging in wavelength from 0.4 μm to 14.4 μm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). MODIS data provides unprecedented insight into large-scale Earth system science questions related to cloud and aerosol characteristics, surface emissivity and processes occurring in the oceans, on land, and in the lower atmosphere. MODIS has flown on the EOS Terra satellite since 1999 and on the EOS Aqua satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of MODIS-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to MODIS for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager

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

Application of MODIS Products to Infer Possible Relationships Between Basin Land Cover and Coastal Waters Turbidity Using the Magdalena River, Colombia, as a Case Study

Science.gov (United States)

Madrinan, Max Jacobo Moreno; Cordova, Africa Flores; Olivares, Francisco Delgado; Irwin, Dan

2012-01-01

Basin development and consequent change in basin land cover have been often associated with an increased turbidity in coastal waters because of sediment yield and nutrients loading. The later leads to phytoplankton abundance further exacerbating water turbidity. This subsequently affects biological and physical processes in coastal estuaries by interfering with sun light penetration to coral reefs and sea grass, and even affecting public health. Therefore, consistent estimation of land cover changes and turbidity trend lines is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Ground solely methods to estimate land cover change would be unpractical and traditional methods of monitoring in situ water turbidity can be very expensive and time consuming. Accurate monitoring on the status and trends of basin land cover as well as the water quality of the receiving water bodies are required for analysis of relationships between the two variables. Use of remote sensing (RS) technology provides a great benefit for both fields of study, facilitating monitoring of changes in a timely and cost effective manner and covering wide areas with long term measurements. In this study, the Magdalena River basin and fixed geographical locations in the estuarine waters of its delta are used as a case to study the temporal trend lines of both, land cover change and the reflectance of the water turbidity using satellite technology. Land cover data from a combined product between sensors Terra and Aqua (MCD12Q1) from MODIS will be adapted to the conditions in the Magdalena basin to estimate changes in land cover since year 2000 to 2009. Surface reflectance data from a MODIS, Terra (MOD09GQ), band 1, will be used in lieu of in situ water turbidity for the time period between 2000 and present. Results will be compared with available existing data.

Victoria Land, Ross Sea, and Ross Ice Shelf, Antarctica

Science.gov (United States)

2002-01-01

On December 19, 2001, MODIS acquired data that produced this image of Antarctica's Victoria Land, Ross Ice Shelf, and the Ross Sea. The coastline that runs up and down along the left side of the image denotes where Victoria Land (left) meets the Ross Ice Shelf (right). The Ross Ice Shelf is the world's largest floating body of ice, approximately the same size as France. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Fires and Smoke Observed from the Earth Observing System MODIS Instrument: Products, Validation, and Operational Use

Science.gov (United States)

Kaufman, Y. J.; Ichoku, C.; Giglio, L.; Korontzi, S.; Chu, D. A.; Hao, W. M.; Justice, C. O.; Lau, William K. M. (Technical Monitor)

2001-01-01

The MODIS sensor, launched on NASA's Terra satellite at the end of 1999, was designed with 36 spectral channels for a wide array of land, ocean, and atmospheric investigations. MODIS has a unique ability to observe fires, smoke, and burn scars globally. Its main fire detection channels saturate at high brightness temperatures: 500 K at 4 microns and 400 K at 11 microns, which can only be attained in rare circumstances at the I kin fire detection spatial resolution. Thus, unlike other polar orbiting satellite sensors with similar thermal and spatial resolutions, but much lower saturation temperatures (e.g. AVHRR and ATSR), MODIS can distinguish between low intensity ground surface fires and high intensity crown forest fires. Smoke column concentration over land is for the first time being derived from the MOMS solar channels, extending from 0.41 microns to 2.1 microns. The smoke product has been provisionally validated both globally and regionally over southern Africa and central and south America. Burn scars are observed from MODIS even in the presence of smoke, using the 1.2 to 2.1 micron channels. MODIS burned area information is used to estimate pyrogenic emissions. A wide range of these fire and related products and validation are demonstrated for the wild fires that occurred in northwestern United States in the summer of 2000. The MODIS rapid response system and direct broadcast capability is being developed to enable users to obtain and generate data in near real time. It is expected that health and land management organizations will use these systems for monitoring the occurrence of fires and the dispersion of smoke within two to six hours after data acquisition.

The Performances of MODIS-GPP and -ET Products in China and Their Sensitivity to Input Data (FPAR/LAI

Directory of Open Access Journals (Sweden)

Zhengjia Liu

2014-12-01

Full Text Available The aims are to validate and assess the performances of MODIS gross primary production (MODIS-GPP and evapotranspiration (MODIS-ET products in China’s different land cover types and their sensitivity to remote sensing input data. In this study, MODIS-GPP and -ET are evaluated using flux derived/measured data from eight sites of ChinaFLUX. Results show that MODIS-GPP generally underestimates GPP (R2 is 0.58, bias is −6.7 gC/m2/8-day and RMSE is 19.4 gC/m2/8-day at all sites and MODIS-ET overestimates ET (R2 is 0.36, bias is 6 mm/8-day and RMSE is 11 mm/8-day when comparing with derived GPP and measured ET, respectively. For evergreen forests, MODIS-GPP gives a poor performance with R2 varying from 0.03 to 0.44; in contrast, MODIS-ET provides more reliable results. In croplands, MODIS-GPP can explain 80% of GPP variance, but it overestimates flux derived GPP in non-growing season and underestimates flux derived GPP in growing season; similar overestimations also presented in MODIS-ET. For grasslands and mixed forests, MODIS-GPP and -ET perform good estimating accuracy. By designing four experimental groups and taking GPP simulation as an example, we suggest that the maximum light use efficiency of croplands should be optimized, and the differences of meteorological data have little impact on GPP estimation, whereas remote sensing leaf area index/fraction of photo-synthetically active radiation (LAI/FPAR can greatly affect GPP/ET estimations for all land cover types. Thus, accurate remote sensing parameters are important for achieving reliable estimations.

[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.

A Method for Retrieving Daily Land Surface Albedo from Space at 30-m Resolution

Directory of Open Access Journals (Sweden)

Bo Gao

2015-08-01

Full Text Available Land surface albedo data with high spatio-temporal resolution are increasingly important for scientific studies addressing spatially and/or temporally small-scale phenomena, such as urban heat islands and urban land surface energy balance. Our previous study derived albedo data with 2–4-day and 30-m temporal and spatial resolution that have better spatio-temporal resolution than existing albedo data, but do not completely satisfy the requirements for monitoring high-frequency land surface changes at the small scale. Downscaling technology provides a chance to further improve the albedo data spatio-temporal resolution and accuracy. This paper introduces a method that combines downscaling technology for land surface reflectance with an empirical method of deriving land surface albedo. Firstly, downscaling daily MODIS land surface reflectance data (MOD09GA from 500 m to 30 m on the basis of HJ-1A/B BRDF data with 2–4-day and 30-m temporal and spatial resolution is performed: this is the key step in the improved method. Subsequently, the daily 30-m land surface albedo data are derived by an empirical method combining prior knowledge of the MODIS BRDF product and the downscaled daily 30-m reflectance. Validation of albedo data obtained using the proposed method shows that the new method has both improved spatio-temporal resolution and good accuracy (a total absolute accuracy of 0.022 and a total root mean squared error at six sites of 0.028.

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.

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.

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

Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

Science.gov (United States)

Chen, Pei-Yu; Fedosejevs, Gunar; Tiscareño-López, Mario; Arnold, Jeffrey G

2006-08-01

Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

Cross-Calibration of the Oceansat-2 Ocean Colour Monitor (OCM) with Terra and Aqua MODIS

Science.gov (United States)

Angal, Amit; Brinkmann, Jake; Kumar, A. Senthil; Xiong, Xiaoxiong

2016-01-01

The Ocean Colour Monitor (OCM) sensor on-board the Oceansat-2 spacecraft has been operational since its launch in September, 2009. The Oceansat 2 OCM primary design goal is to provide continuity to Oceansat-1 OCM to obtain information regarding various ocean-colour variables. OCM acquires Earth scene measurements in eight multi-spectral bands in the range from 402 to 885 nm. The MODIS sensor on the Terra and Aqua spacecraft has been successfully operating for over a decade collecting measurements of the earth's land, ocean surface and atmosphere. The MODIS spectral bands, designed for land and ocean applications, cover the spectral range from 412 to 869 nm. This study focuses on comparing the radiometric calibration stability of OCM using near-simultaneous TOA measurements with Terra and Aqua MODIS acquired over the Libya 4 target. Same-day scene-pairs from all three sensors (OCM, Terra and Aqua MODIS) between August, 2014 and September, 2015 were chosen for this analysis. On a given day, the OCM overpass is approximately an hour after the Terra overpass and an hour before the Aqua overpass. Due to the orbital differences between Terra and Aqua, MODIS images the Libya 4 site at different scan-angles on a given day. Some of the high-gain ocean bands for MODIS tend to saturate while viewing the bright Libya 4 target, but bands 8-10 (412 nm - 486 nm) provide an unsaturated response and are used for comparison with the spectrally similar OCM bands. All the standard corrections such as bidirectional reflectance factor (BRDF), relative spectral response mismatch, and impact for atmospheric water-vapor are applied to obtain the reflectance differences between OCM and the two MODIS instruments. Furthermore, OCM is used as a transfer radiometer to obtain the calibration differences between Terra and Aqua MODIS reflective solar bands.

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.

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.

An Assessment of Existing Methodologies to Retrieve Snow Cover Fraction from MODIS Data

Directory of Open Access Journals (Sweden)

Théo Masson

2018-04-01

Full Text Available The characterization of snow extent is critical for a wide range of applications. Since 1966, snow maps at different spatial resolutions have been produced using various satellite sensor images. Nowadays, the most widely used products are likely those derived from Moderate-Resolution Imaging Spectroradiometer (MODIS data, which cover the whole Earth at a near-daily frequency. There are a variety of snow mapping methods for MODIS data, based on different methodologies and applied at different spatial resolutions. Up to now, all these products have been tested and evaluated separately. This study aims to compare the methods currently available for retrieving snow from MODIS data. The focus is on fractional snow cover, which represents the snow cover area at the subpixel level. We examine the two main approaches available for generating such products from MODIS data; namely, linear regression of the Normalized Difference Snow Index (NDSI and spectral unmixing (SU. These two approaches have resulted in several methods, such as MOD10A1 (the NSIDC MODIS snow product for NDSI regression, and MODImLAB for SU. The assessment of these approaches was carried out using higher resolution binary snow maps (i.e., showing the presence or absence of snow at spatial resolutions of 10, 20, and 30 m, produced by SPOT 4, SPOT 5, and LANDSAT-8, respectively. Three areas were selected in order to provide landscape diversity: the French Alps (117 dates, the Pyrenees (30 dates, and the Moroccan Atlas (24 dates. This study investigates the impact of reference maps on accuracy assessments, and it is suggested that NDSI-based high spatial resolution reference maps advantage NDSI medium-resolution snow maps. For MODIS snow maps, the results show that applying an NDSI approach to accurate surface reflectance corrected for topographic and atmospheric effects generally outperforms other methods for the global retrieval of snow cover area. The improvements to the newer version

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

models driven by meteorological data. The main impediment to developing such a model is the lack of a MODIS product that provides surface reflectance for the MODIS ocean bands over land.

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

Science.gov (United States)

Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

2011-01-01

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Validation of MODIS Data for localized spatio-temporal evapotranspiration mapping

International Nuclear Information System (INIS)

Nadzri, M I; Hashim, M

2014-01-01

Advancement in satellite remote sensing sensors allows evapo-transpiration (ET) from land surfaces to be derived from selected reflectance and emmitance in visible and thermal infrared wavelengths, such as using Moderate Solution Imaging Spectrometer (MODIS). In this paper, we report the validation of recent MODIS-generated higher-order global terrestrial ET product 16A2. The main focus of this paper is to devise the follow-up calibration for the localised region covering the entire Malaysia peninsular. The validation is carried out locally by dividing the study area into 3 distinct climatological regions based on the influence to monsoons, and using multi-temporal MODIS data acquired in 2000-2009. The results, evidently show the local effects still inherit in the MODIS 16A2 products; with varying R2 within the 3 local climatological regions established (Northwest = 0.49 South = 0.47, and Southwest = 0.52; all with P < 0.001). The accuracy of each region validated is within + RMSE 43mm for monthly ET. With P value in acceptable range, the correction is useable for further usage

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.

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

Land and cryosphere products from Suomi NPP VIIRS: Overview and status.

Science.gov (United States)

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-09-16

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS.

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid SWAT Hydrologic Modeling

Science.gov (United States)

Spruce, J.; Bolten, J. D.; Srinivasan, R.

2017-12-01

This presentation discusses research to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB). Funded by a NASA ROSES Disasters grant, the main objective was to produce updated LULC maps to aid the Mekong River Commission's (MRC's) Soil and Water Assessment Tool (SWAT) hydrologic model. In producing needed LULC maps, temporally processed MODIS monthly NDVI data for 2010 were used as the primary data source for classifying regionally prominent forest and agricultural types. The MODIS NDVI data was derived from processing MOD09 and MYD09 8-day reflectance data with the Time Series Product Tool, a custom software package. Circa 2010 Landsat multispectral data from the dry season were processed into top of atmosphere reflectance mosaics and then classified to derive certain locally common LULC types, such as urban areas and industrial forest plantations. Unsupervised ISODATA clustering was used to derive most LULC classifications. GIS techniques were used to merge MODIS and Landsat classifications into final LULC maps for Sub-Basins (SBs) 1-8 of the LMB. The final LULC maps were produced at 250-meter resolution and delivered to the MRC for use in SWAT modeling for the LMB. A map accuracy assessment was performed for the SB 7 LULC map with 14 classes. This assessment was performed by comparing random locations for sampled LULC types to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data from Google Map/Earth, and other reference data from the MRC (e.g., crop calendars). LULC accuracy assessment results for SB 7 indicated an overall agreement to reference data of 81% at full scheme specificity. However, by grouping 3 deciduous forest classes into 1 class, the overall agreement improved to 87%. The project enabled updated LULC maps, plus more specific rice types were classified compared to the previous LULC maps. The LULC maps from this project should improve the use of SWAT for modeling

Deriving a per-field land use and land cover map in an agricultural mosaic catchment

Science.gov (United States)

Seo, B.; Bogner, C.; Poppenborg, P.; Martin, E.; Hoffmeister, M.; Jun, M.; Koellner, T.; Reineking, B.; Shope, C. L.; Tenhunen, J.

2014-09-01

Detailed data on land use and land cover constitute important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly; however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The data are available at the public repository Pangaea (doi:110.1594/PANGAEA.823677).

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.

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.

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...

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.

Intercomparison of MODIS Albedo Retrievals and In Situ Measurements Across the Global FLUXNET Network

Science.gov (United States)

Cescatti, Alessandro; Marcolla, Barbara; Vannan, Suresh K. Santhana; Pan, Jerry Yun; Roman, Miguel O.; Yang, Xiaoyuan; Ciais, Philippe; Cook, Robert B.; Law, Beverly E.; Matteucci, Girogio;

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

An assessment of the land surface emissivity in the 8 - 12 micrometer window determined from ASTER and MODIS data

Science.gov (United States)

Schmugge, T.; Hulley, G.; Hook, S.

2009-04-01

The land surface emissivity is often overlooked when considering surface properties that effect the energy balance. However, knowledge of the emissivity in the window region is important for determining the longwave radiation balance and its subsequent effect on surface temperature. The net longwave radiation (NLR) is strongly affected by the difference between the temperature of the emitting surface and the sky brightness temperature, this difference will be the greatest in the window region. Outside the window region any changes in the emitted radiation by emissivity variability are mostly compensated for by changes in the reflected sky brightness. The emissivity variability is typically greatest in arid regions where the exposed soil and rock surfaces display the widest range of emissivity. For example, the dune regions of North Africa have emissivities of 0.7 or less in the 8 to 9 micrometer wavelength band due to the quartz sands of the region, which can produce changes in NLR of more than 10 w/m*m compared to assuming a constant emissivity. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite result from using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions here the variation in emissivity is large, both spatially and spectrally. The multispectral thermal infrared data obtained from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer and MODerate resolution Imaging Spectrometer (MODIS) sensors on NASA's Terra satellite have been shown to be of good quality and provide a unique new tool for studying the emissivity of the land surface. ASTER has 5 channels in the 8 to 12 micrometer waveband with 90 m spatial resolution, when the data are combined with the Temperature Emissivity Separation (TES) algorithm the surface emissivity over this wavelength region

Promotion of inclusive land governance to improve women's land ...

International Development Research Centre (IDRC) Digital Library (Canada)

The general objective of this action research project is to help increase women's access to and control over land and their involvement in decision-making for responsible, sustainable land governance, in the context of large-scale land acquisition in Senegal. Its objectives are to establish the conditions to improve women's ...

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

Improvements of a COMS Land Surface Temperature Retrieval Algorithm Based on the Temperature Lapse Rate and Water Vapor/Aerosol Effect

Directory of Open Access Journals (Sweden)

A-Ra Cho

2015-02-01

Full Text Available The National Meteorological Satellite Center in Korea retrieves land surface temperature (LST by applying the split-window LST algorithm (CSW_v1.0 to Communication, Ocean, and Meteorological Satellite (COMS data. Considerable errors were detected under conditions of high water vapor content or temperature lapse rates during validation with Moderate Resolution Imaging Spectroradiometer (MODIS LST because of the too simplified LST algorithm. In this study, six types of LST retrieval equations (CSW_v2.0 were developed to upgrade the CSW_v1.0. These methods were developed by classifying “dry,” “normal,” and “wet” cases for day and night and considering the relative sizes of brightness temperature difference (BTD values. Similar to CSW_v1.0, the LST retrieved by CSW_v2.0 had a correlation coefficient of 0.99 with the prescribed LST and a slightly larger bias of −0.03 K from 0.00K; the root mean square error (RMSE improved from 1.41 K to 1.39 K. In general, CSW_v2.0 improved the retrieval accuracy compared to CSW_v1.0, especially when the lapse rate was high (mid-day and dawn and the water vapor content was high. The spatial distributions of LST retrieved by CSW_v2.0 were found to be similar to the MODIS LST independently of the season, day/night, and geographic locations. The validation using one year’s MODIS LST data showed that CSW_v2.0 improved the retrieval accuracy of LST in terms of correlations (from 0.988 to 0.989, bias (from −1.009 K to 0.292 K, and RMSEs (from 2.613 K to 2.237 K.

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.

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

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...

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling.

Science.gov (United States)

Zhou, Fuqun; Zhang, Aining

2016-10-25

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2-3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests' features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.

Evaluation of the data of vegetable covering using fraction images and multitemporal vegetation index, derived of orbital data of moderate resolution of the sensor MODIS

International Nuclear Information System (INIS)

Murillo Mejia, Mario Humberto

2006-01-01

The objective was to evaluate the data obtained by sensor MODIS onboard the EOS terra satellite land cover units. The study area is the republic of Colombia in South America. The methodology consisted of analyzing the multitemporal (vegetation, soil and shade-water) fraction images and vegetation indices (NDVI) apply the lineal spectral mixture model to products derived from derived images by sensor MODIS data obtained in years 2001 and 2003. The mosaics of the original and the transformed vegetation (soil and shade-water) bands were generated for the whole study area using SPRING 4. 0 software, developed by INPE then these mosaics were segmented, classified, mapped, and edited to obtain a moderate resolution land cover map. The results derived from MODIS analysis were compared with Landsat ETM+ data acquire for a single test site. The results of the project showed the usefulness of MODIS images for large-scale land cover mapping and monitoring studies

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.

Comparison and Validation of Long Time Serial Global GEOV1 and Regional Australian MODIS Fractional Vegetation Cover Products Over the Australian Continent

Directory of Open Access Journals (Sweden)

Yanling Ding

2015-05-01

Full Text Available Fractional vegetation cover (FVC is one of the most critical parameters in monitoring vegetation status. Comprehensive assessment of the FVC products is critical for their improvement and use in land surface models. This study investigates the performances of two major long time serial FVC products: GEOV1 and Australian MODIS. The spatial and temporal consistencies of these products were compared during the 2000–2012 period over the main biome types across the Australian continent. Their accuracies were validated by 443 FVC in-situ measurements during the 2011–2012 period. Our results show that there are strong correlations between the GEOV1 and Australian MODIS FVC products over the main Australian continent while they exhibit large differences and uncertainties in the coastal regions covered by dense forests. GEOV1 and Australian MODIS describe similar seasonal variations over the main biome types with differences in magnitude, while Australian MODIS exhibit unstable temporal variations over grasslands and shifted seasonal variations over evergreen broadleaf forests. The GEOV1 and Australian MODIS products overestimate FVC values over the biome types with high vegetation density and underestimate FVC in sparsely vegetated areas and grasslands. Overall, the GEOV1 and Australian MODIS FVC products agree with in-situ FVC values with a RMSE around 0.10 over the Australian continent.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation.

Science.gov (United States)

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger

2003-01-01

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...

LAND-COVER CHARACTERIZATION AND CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

Science.gov (United States)

The purpose of this research and development effort is to investigate the feasibility of using MODIS derived Normalized Difference Vegetation Index (NDVI) data to delineate areas of LC change on an annual basis and identify the outcome of LC conversions (i.e., new steady state). ...

MODIS Land Surface Temperature time series reconstruction with Open Source GIS: A new quality of temperature based ecological indicators in complex terrain (Invited)

Science.gov (United States)

Neteler, M.

2009-12-01

In complex terrain like the Central European Alps, meteorological stations and ground surveys are usually sparsely and/or irregularly distributed and often favor agricultural areas. The application of traditional geospatial interpolation methods in complex terrain remains challenging and difficult to optimize. An alternative data source is remote sensing: high temporal resolution satellite data are continuously gaining interest since these data are intrinsically spatialized: continuous field of observations is obtained with this tool instead of point data. The increasing data availability suggests using these time series as surrogate to certain measures from meteorological stations, especially for temperature and related derivatives. The Terra and Aqua satellites with the Moderate Resolution Imaging Spectroradiometer (MODIS) provide four Earth coverages per day at various resolutions. We analyzed 8 years (2000 to 2008) of daily land surface temperature (LST) data from MODIS in an area located in the Southern European Alps. A method was developed to reconstruct incomplete maps (cloud coverage, invalid pixels) based on image statistics and on a model that includes additional GIS layers. The original LST map resolution of 1000m could be improved to 200m in this process which renders the resulting LST maps applicable at regional scales. We propose the use of these reconstructed daily LST time series as surrogate to meteorological observations especially in the area of epidemiological modeling where data are typically aggregated to decadal indicators. From these daily LST map series, derivable indicators include: 1) temperatures minima, means and maxima for annual/monthly/decadal periods; 2) unusual hot summers;3) the calculation of growing degree days, and 4) spring temperature increase or autumnal temperature decrease. Since more than 8 years of MODIS LST data are available today, even preliminary gradients can be extracted to assess multi-annual temperature trends

Present Situation and Problems of Land Improvement District as an Operation and Maintenance Organization of Land Improvement Facilities

OpenAIRE

長堀, 金造; 赤江, 剛夫; 大田, 征六

1994-01-01

Land improvement districts originally started as organizations after World War II: They are in charge of construction and operation of irrigation and drainage facilities, Development of agricultural land, reclamation from sea water, reclamation by filling, Recovery from disaster, exchange and consolidation of agricultural land and so on. As the Main construction projects were completed, the purpose of land improvement districts Has shifted from facilities construction to operation and mainten...

The use of a multilayer perceptron for detecting new human settlements from a time series of MODIS images

CSIR Research Space (South Africa)

Salmon, BP

2011-12-01

Full Text Available This paper presents a novel land cover change detection method that employs a sliding window over hyper-temporal multi-spectral images acquired from the 7 bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance...

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

Energy Technology Data Exchange (ETDEWEB)

Maclaurin, Galen [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sengupta, Manajit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Xie, Yu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gilroy, Nicholas [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-12-01

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance) broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the

Analysis of MODIS 250 m Time Series Product for LULC Classification and Retrieval of Crop Biophysical Parameter

Science.gov (United States)

Verma, A. K.; Garg, P. K.; Prasad, K. S. H.; Dadhwal, V. K.

2016-12-01

Agriculture is a backbone of Indian economy, providing livelihood to about 70% of the population. The primary objective of this research is to investigate the general applicability of time-series MODIS 250m Normalized difference vegetation index (NDVI) and Enhanced vegetation index (EVI) data for various Land use/Land cover (LULC) classification. The other objective is the retrieval of crop biophysical parameter using MODIS 250m resolution data. The Uttar Pradesh state of India is selected for this research work. A field study of 38 farms was conducted during entire crop season of the year 2015 to evaluate the applicability of MODIS 8-day, 250m resolution composite images for assessment of crop condition. The spectroradiometer is used for ground reflectance and the AccuPAR LP-80 Ceptometer is used to measure the agricultural crops Leaf Area Index (LAI). The AccuPAR measures Photosynthetically Active Radiation (PAR) and can invert these readings to give LAI for plant canopy. Ground-based canopy reflectance and LAI were used to calibrate a radiative transfer model to create look-up table (LUT) that was used to simulate LAI. The seasonal trend of MODIS-derived LAI was used to find crop parameter by adjusting the LAI simulated from climate-based crop yield model. Cloud free MODIS images of 250m resolution (16 day composite period) were downloaded using LP-DAAC website over a period of 12 months (Jan to Dec 2015). MODIS both the VI products were found to have sufficient spectral, spatial and temporal resolution to detect unique signatures for each class (water, fallow land, urban, dense vegetation, orchard, sugarcane and other crops). Ground truth data were collected using JUNO GPS. Multi-temporal VI signatures for vegetation classes were consistent with its general phenological characteristic and were spectrally separable at some point during the growing season. The MODIS NDVI and EVI multi-temporal images tracked similar seasonal responses for all croplands and were

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.

MODIS-based global terrestrial estimates of gross primary productivity and evapotranspiration

Science.gov (United States)

Ryu, Y.; Baldocchi, D. D.; Kobayashi, H.; Li, J.; van Ingen, C.; Agarwal, D.; Jackson, K.; Humphrey, M.

2010-12-01

We propose a novel approach to quantify gross primary productivity (GPP) and evapotranspiration (ET) at global scale (5 km resolution with 8-day interval). The MODIS-based, process-oriented approach couples photosynthesis, evaporation, two-leaf energy balance and nitrogen, which are different from the previous satellite-based approaches. We couple information from MODIS with flux towers to assess the drivers and parameters of GPP and ET. Incoming shortwave radiation components (direct and diffuse PAR, NIR) under all sky condition are modeled using a Monte-Carlo based atmospheric radiative transfer model. The MODIS Level 2 Atmospheric products are gridded and overlaid with MODIS Land products to produce spatially compatible forcing variables. GPP is modeled using a two-leaf model (sunlit and shaded leaf) and the maximum carboxylation rate is estimated using albedo-Nitrogen-leaf trait relations. The GPP is used to calculate canopy conductance via Ball-Berry model. Then, we apply Penman-Monteith equation to calculate evapotranspiration. The process-oriented approach allows us to investigate the main drivers of GPP and ET at global scale. Finally we explore the spatial and temporal variability of GPP and ET at global scale.

Comparisons of Brightness Temperatures of Landsat-7/ETM+ and Terra/MODIS around Hotien Oasis in the Taklimakan Desert

International Nuclear Information System (INIS)

Oguro, Y; Ito, S; Tsuchiya, K

2011-01-01

The brightness temperature (BT) of Taklimakan Desert retrieved from the data of Landsat-7/ETM+ band 6 and Terra/MODIS band 31 and 32 indicates the following features: (1) good linear relationship between the BT of ETM+ and that of MODIS, (2) the observation time adjusted BT of ETM+ is almost equal to that of MODIS, (3) the BT of Terra/MODIS band 31 is slightly higher than that of band 32 over a reservoir while opposite feature is recognized over desert area, (4) the statistical analysis of 225 sample data of ETM+ in one pixel of MODIS for different land covers indicates that the standard deviation and range of BT of ETM+ corresponding to one pixel of MODIS are 0.45 degree C, 2.25 degree C for a flat area of desert, while respective values of the oasis farmland and shading side of rocky hill amount to 2.88 degree C, 14.04 degree C, and 2.80 degree C, 16.04 degree C.

Comparison of feature extraction methods within a spatio-temporal land cover change detection framework

CSIR Research Space (South Africa)

Kleynhans, W

2011-07-01

Full Text Available OF FEATURE EXTRACTION METHODS WITHIN A SPATIO-TEMPORAL LAND COVER CHANGE DETECTION FRAMEWORK ??W. Kleynhans,, ??B.P. Salmon, ?J.C. Olivier, ?K.J. Wessels, ?F. van den Bergh ? Electrical, Electronic and Computer Engi- neering University of Pretoria, South... Bergh, and K. Steenkamp, ?Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data,? IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 381?385, Apr. 2010. ...

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.

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

Science.gov (United States)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2011-01-01

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series

DEFF Research Database (Denmark)

Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo

2015-01-01

for recultivation hinges on incomplete knowledge about the spatial patterns of fallow and abandoned farmland, especially at broad geographic scales. Our goals were to develop a methodology to map active and fallow land using MODIS Normalized Differenced Vegetation Index (NDVI) time series and to provide the first...

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.

MODIS-Derived 1.64 micron white-sky albedo on a global, 1-minute equal angle grid (Collection 004 and 005)

Data.gov (United States)

National Aeronautics and Space Administration — The Filled Land Surface Albedo Product is a global data set of spatially complete albedo maps. It was derived from the MODIS MOD43B3 Land product and includes both...

Analysis of Accuracy of Modis BRDF Product (MCD43 C6) Based on Misr Land Surface Brf Product - a Case Study of the Central Part of Northeast Asia

Science.gov (United States)

Li, J.; Chen, S.; Qin, W.; Murefu, M.; Wang, Y.; Yu, Y.; Zhen, Z.

2018-04-01

EOS/MODIS land surface Bi-directional Reflectance Distribution Function (BRDF) product (MCD43), with the latest version C6, is one of the most important operational BRDF products with global coverage. The core sub-product MCD43A1 stores 3 parameters of the RossThick-LiSparseR semi-empirical kernel-driven BRDF model. It is important for confident use of the product to evaluate the accuracy of bi-directional reflectance factor (BRF) predicted by MCD43A1 BRDF model (mBRF). A typical region in the central part of Northeast Asia is selected as the study area. The performance of MCD43A1 BRDF model is analyzed in various observation geometries and phenological phases, using Multi-angle Imaging SpectroRadiometer (MISR) land-surface reflectance factor product (MILS_BRF) as the reference data. In addition, MODIS products MCD12Q1 and MOD/MYD10A1 are used to evaluate the impacts of land cover types and snow covers on the model accuracy, respectively. The results show an overall excellent performance of MCD43A1 in representing the anisotropic reflectance of land surface, with root mean square error (RMSE) of 0.0262 and correlation coefficient (R) of 0.9537, for all available comparable samples of MILS_BRF and mBRF pairs. The model accuracy varies in different months, which is related to the phenological phases of the study area. The accuracy for pixels labelled as `snow' by MCD43 is obviously low, with RMSE/R of 0.0903/0.8401. Ephemeral snowfall events further decrease the accuracy, with RMSE/R of 0.1001/0.7715. These results provide meaningful information to MCD43 users, especially those, whose study regions are subject to phenological cycles as well as snow cover and change.

Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images

NARCIS (Netherlands)

Hengl, T.; Heuvelink, G.B.M.; Percec Tadic, M.; Pebesma, E.J.

2012-01-01

A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations

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.

A comparative between CRISP-DM and SEMMA through the construction of a MODIS repository for studies of land use and cover change

Directory of Open Access Journals (Sweden)

Herman Jair Gómez Palacios

2017-06-01

Full Text Available Among the most popular methodologies for development of data mining projects are CRISP-DM and SEMMA, This research paper explains the reason why it was decided to compare them from a specific case study. Therefore, this document describes in detail each phase, task and activity proposed by each methodology, applying it in the construction of a MODIS repository for studies of land use and cover change. In addition to the obvious differences between the methodologies, there were found other differences in the activities proposed by each model that are crucial in non-typical studies of data mining. At the same time, this research determines safely the advantages and disadvantages of each model for this type of case studies. When the MODIS product repository construction process was completed, it was found that the additional time used by CRISP-DM in the first phase was composed in the following phases, since the planning, definition of mining goals, and generation of contingency plans, allow developing the proposed phases without inconvenience. It was also demonstrated that CRISP-DM is presented as a true methodology in comparison with SEMMA, because it describes in detail each phase and task through its official documentation and concrete examples of its application.

Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

KAUST Repository

Zampieri, Matteo

2012-02-01

Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions and the ecosystem dynamics. In regional-scale climate applications land surface models (LSMs) are commonly coupled to atmospheric models to close the surface energy, mass and carbon balance. LSMs in these applications are used to resolve the momentum, heat, water and carbon vertical fluxes, accounting for the effect of vegetation, soil type and other surface parameters, while lack of adequate resolution prevents using them to resolve horizontal sub-grid processes. Specifically, LSMs resolve the large-scale runoff production associated with infiltration excess and sub-grid groundwater convergence, but they neglect the effect from loosing streams to groundwater. Through the analysis of observed data of soil moisture obtained from the Oklahoma Mesoscale Network stations and land surface temperature derived from MODIS we provide evidence that the regional scale soil moisture and surface temperature patterns are affected by the rivers. This is demonstrated on the basis of simulations from a land surface model (i.e., Community Land Model - CLM, version 3.5). We show that the model cannot reproduce the features of the observed soil moisture and temperature spatial patterns that are related to the underlying mechanism of reinfiltration of river water to groundwater. Therefore, we implement a simple parameterization of this process in CLM showing the ability to reproduce the soil moisture and surface temperature spatial variabilities that relate to the river distribution at regional scale. The CLM with this new parameterization is used to evaluate impacts of the improved representation of river-groundwater interactions on the simulated water cycle parameters and the surface energy budget at the regional scale. © 2011 Elsevier B.V.

Near real time detection of deforestation in the Brazilian Amazon using MODIS imagery

Directory of Open Access Journals (Sweden)

Egídio Arai

2007-06-01

Full Text Available The objective of this paper is to provide near real time information about deforestation detection (DETER in the entire Brazilian Amazon using MODIS high temporal resolution images. It is part of the operational deforestation monitoring project to estimate the annual deforestation rate in the Brazilian Amazon (PRODES. A rapid deforestation detection method was designed to support land use policies in this region. In order to evaluate the proposed method a test site was selected covering a Landsat ETM+ scene (227/68 located in Mato Grosso State. For this purpose a multitemporal series of MODIS surface reflectance images (MOD09 and the corresponding ETM+ images from June to October 2002 were analyzed. It was found that small deforested areas (lower than 15 ha were detected by MODIS images with lower accuracy when compared with ETM+ images. As the deforested areas increase MODIS and ETM+ results tend to converge. This procedure showed to be adequate to operationally detect and monitor deforested areas and has been used since 2004 as part of a government plan to control the Amazon deforestation.

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

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

Science.gov (United States)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

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.

Mapping of Daily Mean Air Temperature in Agricultural Regions Using Daytime and Nighttime Land Surface Temperatures Derived from TERRA and AQUA MODIS Data

Directory of Open Access Journals (Sweden)

Ran Huang

2015-07-01

Full Text Available Air temperature is one of the most important factors in crop growth monitoring and simulation. In the present study, we estimated and mapped daily mean air temperature using daytime and nighttime land surface temperatures (LSTs derived from TERRA and AQUA MODIS data. Linear regression models were calibrated using LSTs from 2003 to 2011 and validated using LST data from 2012 to 2013, combined with meteorological station data. The results show that these models can provide a robust estimation of measured daily mean air temperature and that models that only accounted for meteorological data from rural regions performed best. Daily mean air temperature maps were generated from each of four MODIS LST products and merged using different strategies that combined the four MODIS products in different orders when data from one product was unavailable for a pixel. The annual average spatial coverage increased from 20.28% to 55.46% in 2012 and 28.31% to 44.92% in 2013.The root-mean-square and mean absolute errors (RMSE and MAE for the optimal image merging strategy were 2.41 and 1.84, respectively. Compared with the least-effective strategy, the RMSE and MAE decreased by 17.2% and 17.8%, respectively. The interpolation algorithm uses the available pixels from images with consecutive dates in a sliding-window mode. The most appropriate window size was selected based on the absolute spatial bias in the study area. With an optimal window size of 33 × 33 pixels, this approach increased data coverage by up to 76.99% in 2012 and 89.67% in 2013.

Stratifying Tropical Fires by Land Cover: Insights into Amazonian Fires, Aerosol Loading, and Regional Deforestation

Science.gov (United States)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

This study analyzes changes in the number of fires detected on forest, grass, and transition lands during the 2002-2009 biomass burning seasons using fire detection data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the total number of detected fires correlates well with MODIS mean aerosol optical depth (AOD) from year to year, in accord with other studies. However, we also show that the ratio of forest to savanna fires varies substantially from year to year. Forest fires have trended downward, on average, since the beginning of 2006 despite a modest increase in 2007. Our study suggests that high particulate matter loading detected in 2007 was likely due to a large number of savanna/agricultural fires that year. Finally, we illustrate that the correlation between annual Brazilian deforestation estimates and MODIS fires is considerably higher when fires are stratified by MODIS-derived land cover classifications.

ANALYSIS OF ACCURACY OF MODIS BRDF PRODUCT (MCD43 C6 BASED ON MISR LAND SURFACE BRF PRODUCT – A CASE STUDY OF THE CENTRAL PART OF NORTHEAST ASIA

Directory of Open Access Journals (Sweden)

J. Li

2018-04-01

Full Text Available EOS/MODIS land surface Bi-directional Reflectance Distribution Function (BRDF product (MCD43, with the latest version C6, is one of the most important operational BRDF products with global coverage. The core sub-product MCD43A1 stores 3 parameters of the RossThick-LiSparseR semi-empirical kernel-driven BRDF model. It is important for confident use of the product to evaluate the accuracy of bi-directional reflectance factor (BRF predicted by MCD43A1 BRDF model (mBRF. A typical region in the central part of Northeast Asia is selected as the study area. The performance of MCD43A1 BRDF model is analyzed in various observation geometries and phenological phases, using Multi-angle Imaging SpectroRadiometer (MISR land-surface reflectance factor product (MILS_BRF as the reference data. In addition, MODIS products MCD12Q1 and MOD/MYD10A1 are used to evaluate the impacts of land cover types and snow covers on the model accuracy, respectively. The results show an overall excellent performance of MCD43A1 in representing the anisotropic reflectance of land surface, with root mean square error (RMSE of 0.0262 and correlation coefficient (R of 0.9537, for all available comparable samples of MILS_BRF and mBRF pairs. The model accuracy varies in different months, which is related to the phenological phases of the study area. The accuracy for pixels labelled as ‘snow’ by MCD43 is obviously low, with RMSE/R of 0.0903/0.8401. Ephemeral snowfall events further decrease the accuracy, with RMSE/R of 0.1001/0.7715. These results provide meaningful information to MCD43 users, especially those, whose study regions are subject to phenological cycles as well as snow cover and change.

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

A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET

Science.gov (United States)

Velpuri, Naga M.; Senay, Gabriel B.; Singh, Ramesh K.; Bohms, Stefanie; Verdin, James P.

2013-01-01

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research

Comparison of two split-window methods for retrieving land surface temperature from MODIS data

Science.gov (United States)

Zhao, Shaohua; Qin, Qiming; Yang, Yonghui; Xiong, Yujiu; Qiu, Guoyu

2009-08-01

Land surface temperature (LST) is a key parameter in environment and earth science study, especially for monitoring drought. The objective of this work is a comparison of two split-window methods: Mao method and Sobrino method, for retrieving LST using MODIS (Moderate-resolution Imaging Spectroradiometer) data in North China Plain. The results show that the max, min and mean errors of Mao method are 1.33K, 1.54K and 0.13K lower than the standard LST product respectively; while those of Sobrino method are 0.73K, 1.46K and 1.50K higher than the standard respectively. Validation of the two methods using LST product based on weather stations shows a good agreement between the standard and Sobrino method, with RMSE of 1.17K, whereas RMSE of Mao method is 1.85K. Finally, the study introduces the Sobmao method, which is based on Sobrino method but simplifies the estimation of atmospheric water vapour content using Mao method. The Sobmao method has almost the same accuracy with Sobrino method. With high accuracy and simplification of water vapour content estimation, the Sobmao method is recommendable in LST inversion for good application in Ningxia region, the northwest China, with mean error of 0.33K and the RMSE value of 0.91K.

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.

Crop Condition Assessment with Adjusted NDVI Using the Uncropped Arable Land Ratio

Directory of Open Access Journals (Sweden)

Miao Zhang

2014-06-01

Full Text Available Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield prediction. A normalized difference vegetation index (NDVI-based method is employed to evaluate crop condition by inter-annual comparisons of both spatial variability (using NDVI images and seasonal dynamics (based on crop condition profiles. Since this type of method will generate false information if there are changes in crop rotation, cropping area or crop phenology, information on cropped/uncropped arable land is integrated to improve the accuracy of crop condition monitoring. The study proposes a new method to retrieve adjusted NDVI for cropped arable land during the growing season of winter crops by integrating 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS reflectance data at 250-m resolution with a cropped and uncropped arable land map derived from the multi-temporal China Environmental Satellite (Huan Jing Satellite charge-coupled device (HJ-1 CCD images at 30-m resolution. Using the land map’s data on cropped and uncropped arable land, a pixel-based uncropped arable land ratio (UALR at 250-m resolution was generated. Next, the UALR-adjusted NDVI was produced by assuming that the MODIS reflectance value for each pixel is a linear mixed signal composed of the proportional reflectance of cropped and uncropped arable land. When UALR-adjusted NDVI data are used for crop condition assessment, results are expected to be more accurate, because: (i pixels with only uncropped arable land are not included in the assessment; and (ii the adjusted NDVI corrects for interannual variation in cropping area. On the provincial level, crop growing profiles based on the two kinds of NDVI data illustrate the difference between the regular and the adjusted NDVI, with the difference depending on the total area of uncropped arable land in the region. The results suggested that the proposed method can be used to improve the assessment of

Use of LST images from MODIS/AQUA sensor as an indication of frost occurrence in RS

Directory of Open Access Journals (Sweden)

Débora de S. Simões

2015-10-01

Full Text Available ABSTRACTAlthough frost occurrence causes severe losses in agriculture, especially in the south of Brazil, the data of minimum air temperature (Tmin currently available for monitoring and predicting frosts show insufficient spatial distribution. This study aimed to evaluate the MDY11A1 (LST – Land Surface Temperature product, from the MODIS sensor on board the AQUA satellite as an estimator of frost occurrence in the southeast of the state of Rio Grande do Sul, Brazil. LST images from the nighttime overpass of the MODIS/AQUA sensor for the months of June, July and August from 2006 to 2012, and data from three conventional weather stations of the National Institute of Meteorology (INMET were used. Consistency was observed between Tmin data measured in weather stations and LST data obtained from the MODIS sensor. According to the results, LSTs below 3 ºC recorded by the MODIS/AQUA sensor are an indication of a favorable scenario to frost occurrence.

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

A data assimilation framework for constraining upscaled cropland carbon flux seasonality and biometry with MODIS

Directory of Open Access Journals (Sweden)

O. Sus

2013-04-01

Full Text Available Agroecosystem models are strongly dependent on information on land management patterns for regional applications. Land management practices play a major role in determining global yield variability, and add an anthropogenic signal to the observed seasonality of atmospheric CO2 concentrations. However, there is still little knowledge on spatial and temporal variability of important farmland activities such as crop sowing dates, and thus these remain rather crudely approximated within carbon cycle studies. In this study, we present a framework allowing for spatio-temporally resolved simulation of cropland carbon fluxes under observational constraints on land management and canopy greenness. We apply data assimilation methodology in order to explicitly account for information on sowing dates and model leaf area index. MODIS 250 m vegetation index data were assimilated both in batch-calibration for sowing date estimation and sequentially for improved model state estimation, using the ensemble Kalman filter (EnKF, into a crop carbon mass balance model (SPAc. In doing so, we are able to quantify the multiannual (2000–2006 regional carbon flux and biometry seasonality of maize–soybean crop rotations surrounding the Bondville Ameriflux eddy covariance site, averaged over 104 pixel locations within the wider area. (1 Validation at the Bondville site shows that growing season C cycling is simulated accurately with MODIS-derived sowing dates, and we expect that this framework allows for accurate simulations of C cycling at locations for which ground-truth data are not available. Thus, this framework enables modellers to simulate current (i.e. last 10 yr carbon cycling of major agricultural regions. Averaged over the 104 field patches analysed, relative spatial variability for biometry and net ecosystem exchange ranges from ∼7% to ∼18%. The annual sign of net biome productivity is not significantly different from carbon neutrality. (2 Moreover

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.

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

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

Science.gov (United States)

Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.

2009-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data

Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index Land Reflectance Global Binned Data

Data.gov (United States)

National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

Science.gov (United States)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

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.

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.

High-sensitivity C-reactive protein does not improve the differential diagnosis of HNF1A-MODY and familial young-onset type 2 diabetes: A grey zone analysis.

Science.gov (United States)

Bellanné-Chantelot, C; Coste, J; Ciangura, C; Fonfrède, M; Saint-Martin, C; Bouché, C; Sonnet, E; Valéro, R; Lévy, D-J; Dubois-Laforgue, D; Timsit, J

2016-02-01

Low plasma levels of high-sensitivity C-reactive protein (hs-CRP) have been suggested to differentiate hepatocyte nuclear factor 1 alpha-maturity-onset diabetes of the young (HNF1A-MODY) from type 2 diabetes (T2D). Yet, differential diagnosis of HNF1A-MODY and familial young-onset type 2 diabetes (F-YT2D) remains a difficult challenge. Thus, this study assessed the added value of hs-CRP to distinguish between the two conditions. This prospective multicentre study included 143 HNF1A-MODY patients, 310 patients with a clinical history suggestive of HNF1A-MODY, but not confirmed genetically (F-YT2D), and 215 patients with T2D. The ability of models, including clinical characteristics and hs-CRP to predict HNF1A-MODY was analyzed, using the area of the receiver operating characteristic (AUROC) curve, and a grey zone approach was used to evaluate these models in clinical practice. Median hs-CRP values were lower in HNF1A-MODY (0.25mg/L) than in F-YT2D (1.14mg/L) and T2D (1.70mg/L) patients. Clinical parameters were sufficient to differentiate HNF1A-MODY from classical T2D (AUROC: 0.99). AUROC analyses to distinguish HNF1A-MODY from F-YT2D were 0.82 for clinical features and 0.87 after including hs-CRP. For the grey zone analysis, the lower boundary was set to missMODY with F-YT2D, 65% of patients were classified in between these categories - in the zone of diagnostic uncertainty - even after adding hs-CRP to clinical parameters. hs-CRP does not improve the differential diagnosis of HNF1A-MODY and F-YT2D. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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

MODIS Time Series to Detect Anthropogenic Interventions and Degradation Processes in Tropical Pasture

Directory of Open Access Journals (Sweden)

Daniel Alves Aguiar

2017-01-01

Full Text Available The unavoidable diet change in emerging countries, projected for the coming years, will significantly increase the global consumption of animal protein. It is expected that Brazilian livestock production, responsible for close to 15% of global production, be prepared to answer to the increasing demand of beef. Consequently, the evaluation of pasture quality at regional scale is important to inform public policies towards a rational land use strategy directed to improve livestock productivity in the country. Our hypothesis is that MODIS images can be used to evaluate the processes of degradation, restoration and renovation of tropical pastures. To test this hypothesis, two field campaigns were performed covering a route of approximately 40,000 km through nine Brazilian states. To characterize the sampled pastures, biophysical parameters were measured and observations about the pastures, the adopted management and the landscape were collected. Each sampled pasture was evaluated using a time series of MODIS EVI2 images from 2000–2012, according to a new protocol based on seven phenological metrics, 14 Boolean criteria and two numerical criteria. The theoretical basis of this protocol was derived from interviews with producers and livestock experts during a third field campaign. The analysis of the MODIS EVI2 time series provided valuable historical information on the type of intervention and on the biological degradation process of the sampled pastures. Of the 782 pastures sampled, 26.6% experienced some type of intervention, 19.1% were under biological degradation, and 54.3% presented neither intervention nor trend of biomass decrease during the period analyzed.

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

Impact of Land-Use and Land-Cover Change on urban air quality in representative cities of China

Science.gov (United States)

Sun, L.; Wei, J.; Duan, D. H.; Guo, Y. M.; Yang, D. X.; Jia, C.; Mi, X. T.

2016-05-01

The atmospheric particulate pollution in China is getting worse. Land-Use and Land-Cover Change (LUCC) is a key factor that affects atmospheric particulate pollution. Understanding the response of particulate pollution to LUCC is necessary for environmental protection. Eight representative cities in China, Qingdao, Jinan, Zhengzhou, Xi'an, Lanzhou, Zhangye, Jiuquan, and Urumqi were selected to analyze the relationship between particulate pollution and LUCC. The MODIS (MODerate-resolution Imaging Spectroradiometer) aerosol product (MOD04) was used to estimate atmospheric particulate pollution for nearly 10 years, from 2001 to 2010. Six land-use types, water, woodland, grassland, cultivated land, urban, and unused land, were obtained from the MODIS land cover product (MOD12), where the LUCC of each category was estimated. The response of particulate pollution to LUCC was analyzed from the above mentioned two types of data. Moreover, the impacts of time-lag and urban type changes on particulate pollution were also considered. Analysis results showed that due to natural factors, or human activities such as urban sprawl or deforestation, etc., the response of particulate pollution to LUCC shows obvious differences in different areas. The correlation between particulate pollution and LUCC is lower in coastal areas but higher in inland areas. The dominant factor affecting urban air quality in LUCC changes from ocean, to woodland, to urban land, and eventually into grassland or unused land when moving from the coast to inland China.

Change and persistence in land surface phenologies of the Don and Dnieper river basins

Energy Technology Data Exchange (ETDEWEB)

Kovalskyy, V; Henebry, G M, E-mail: geoffrey.henebry@sdstate.ed [Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, 1021 Medary Avenue, Wecota Hall 506B, Brookings, SD 57007-3510 (United States)

2009-10-15

The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins-Don and Dnieper-using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated growing degree-days (GDDI NDVI). Three land cover super-classes-forest lands, agricultural lands, and shrub lands-constitute 96% of the land area within the basins. All three in both basins exhibit unidirectional increases in AVHRR GDDI NDVI between the Soviet and post-Soviet epochs. During the MODIS era (2001-2007), different socio-economic trajectories in Ukraine and Russia appear to have led to divergences in the LSPs of the agricultural lands in the two basins. Interannual variation in the shrub lands of the Don river basin has increased since 2000. This is due in part to the better signal-to-noise ratio of the MODIS sensor, but may also be due to a regional drought affecting the Don basin more than the Dnieper basin.

Change and persistence in land surface phenologies of the Don and Dnieper river basins

International Nuclear Information System (INIS)

Kovalskyy, V; Henebry, G M

2009-01-01

The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins-Don and Dnieper-using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated growing degree-days (GDDI NDVI). Three land cover super-classes-forest lands, agricultural lands, and shrub lands-constitute 96% of the land area within the basins. All three in both basins exhibit unidirectional increases in AVHRR GDDI NDVI between the Soviet and post-Soviet epochs. During the MODIS era (2001-2007), different socio-economic trajectories in Ukraine and Russia appear to have led to divergences in the LSPs of the agricultural lands in the two basins. Interannual variation in the shrub lands of the Don river basin has increased since 2000. This is due in part to the better signal-to-noise ratio of the MODIS sensor, but may also be due to a regional drought affecting the Don basin more than the Dnieper basin.

Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

Science.gov (United States)

Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

2014-01-01

Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

Improving the mapping of crop types in the Midwestern U.S. by fusing Landsat and MODIS satellite data

Science.gov (United States)

Zhu, Likai; Radeloff, Volker C.; Ives, Anthony R.

2017-06-01

Mapping crop types is of great importance for assessing agricultural production, land-use patterns, and the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat's sensors images are optimized for cropland monitoring. However, accurate mapping of crop types requires frequent cloud-free images during the growing season, which are often not available, and this raises the question of whether Landsat data can be combined with data from other satellites. Here, our goal is to evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one or two images from all cloud-free Landsat observations available for the Arlington Agricultural Research Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used each combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Both the original Landsat and STARFM-predicted images were then classified with a support vector machine (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two original Landsat images of each combination only, 2) classifying the one or two original Landsat images plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images together with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as the input of STARFM did not significantly improve the STARFM predictions compared to using only one, and predictions using Landsat images between July and August as input were most accurate. Including all STARFM-predicted images together with the Landsat images significantly increased average classification error by 4% points (from 21% to 25%) compared to using only Landsat

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.

[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.

The Role of Suomi NPP VIIRS Data in Land Science and Applications.

Science.gov (United States)

Justice, C. O.; Csiszar, I. A.; Roman, M. O.; Vermote, E.

2014-12-01

The current Suomi-NPP mission was designed as a bridging mission to the Joint Polar Satellite System (JPSS) next-generation, operational satellites. The VIIRS instrument on-board Suomi-NPP provides continuity with NASA's Earth Observing System Moderate-resolution Imaging Spectroradiometer (MODIS) observations and a much-needed replacement of the long-serving, operational NOAA Advanced Very High Resolution Radiometer (AVHRR) system, to meet the expanding needs of Earth Science and Applications of Societal Benefit. Post-launch evaluation has proven the instrument to be excellent for land observations and capable of providing measurement continuity with MODIS. This provides a critical contribution to the scientific study of global change. Several regions of the World are undergoing rapid land transformations, driven by economic development and population growth. In addition, changes in climate conditions are resulting in ecosystem responses and changes in land cover and land use. Long-term, systematic observations of the global land surface at coarse resolution enable detection, monitoring and characterization of such changes to the land surface. A suite of Land environmental data records (EDRs) from the VIIRS, are being developed by NOAA to meet operational data needs, primarily for the National Weather Service (e.g., Albedo, Land Surface Temperature, Fractional Vegetation Cover, Surface Type, Snow and Ice Monitoring). Scientists funded by NOAA and NASA, have been evaluating and validating these products. Based on these evaluations, NASA is embarking on a program to develop enhanced and additional products to provide continuity with MODIS to meet the needs of the global change science community. In addition, and as with MODIS, data from the VIIRS can be used as input to a number of practical applications of societal benefit and the associated decision support systems. For example, progress with VIIRS data is being made in the areas of fire and agricultural monitoring

Biomass Burning Aerosol Absorption Measurements with MODIS Using the Critical Reflectance Method

Science.gov (United States)

Zhu, Li; Martins, Vanderlei J.; Remer, Lorraine A.

2010-01-01

This research uses the critical reflectance technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical reflectance technique is then applied to Moderate Resolution Imaging Spectrometer (MODIS) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean MODIS retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the MODIS retrievals as well. The ensemble average of MODIS-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical reflectance technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from MODIS data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate.

Monitoring and Evaluation of Cultivated Land Irrigation Guarantee Capability with Remote Sensing

Science.gov (United States)

Zhang, C., Sr.; Huang, J.; Li, L.; Wang, H.; Zhu, D.

2015-12-01

Abstract: Cultivated Land Quality Grade monitoring and evaluation is an important way to improve the land production capability and ensure the country food safety. Irrigation guarantee capability is one of important aspects in the cultivated land quality monitoring and evaluation. In the current cultivated land quality monitoring processing based on field survey, the irrigation rate need much human resources investment in long investigation process. This study choses Beijing-Tianjin-Hebei as study region, taking the 1 km × 1 km grid size of cultivated land unit with a winter wheat-summer maize double cropping system as study object. A new irrigation capacity evaluation index based on the ratio of the annual irrigation requirement retrieved from MODIS data and the actual quantity of irrigation was proposed. With the years of monitoring results the irrigation guarantee capability of study area was evaluated comprehensively. The change trend of the irrigation guarantee capability index (IGCI) with the agricultural drought disaster area in rural statistical yearbook of Beijing-Tianjin-Hebei area was generally consistent. The average of IGCI value, the probability of irrigation-guaranteed year and the weighted average which controlled by the irrigation demand index were used and compared in this paper. The experiment results indicate that the classification result from the present method was close to that from irrigation probability in the gradation on agriculture land quality in 2012, with overlap of 73% similar units. The method of monitoring and evaluation of cultivated land IGCI proposed in this paper has a potential in cultivated land quality level monitoring and evaluation in China. Key words: remote sensing, evapotranspiration, MODIS cultivated land quality, irrigation guarantee capability Authors: Chao Zhang, Jianxi Huang, Li Li, Hongshuo Wang, Dehai Zhu China Agricultural University zhangchaobj@gmail.com

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

Science.gov (United States)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

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.

Potential Long-Term Records of Surface Albedo at Fine Spatiotemporal Resolution from Landsat/Sentinle-2A Surface Reflectance and MODIS/VIIRS BRDF

Science.gov (United States)

Li, Z.; Schaaf, C.; Shuai, Y.; Liu, Y.; Sun, Q.; Erb, A.; Wang, Z.

2016-12-01

The land surface albedo products at fine spatial resolutions are generated by coupling surface reflectance (SR) from Landsat (30 m) or Sentinel-2A (20 m) with concurrent surface anisotropy information (the Bidirectional Reflectance Distribution Function - BRDF) at coarser spatial resolutions from sequential multi-angular observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) or its successor, the Visible Infrared Imaging Radiometer Suite (VIIRS). We assess the comparability of four types of fine-resolution albedo products (black-sky and white-sky albedos over the shortwave broad band) generated by coupling, (1) Landsat-8 Optical Land Imager (OLI) SR with MODIS BRDF; (2) OLI SR with VIIRS BRDF; (3) Sentinel-2A MultiSpectral Instrument (MSI) SR with MODIS BRDF; and (4) MSI SR with VIIRS BRDF. We evaluate the accuracy of these four types of fine-resolution albedo products using ground tower measurements of surface albedo over six SURFace RADiation Network (SURFRAD) sites in the United States. For comparison with the ground measurements, we estimate the actual (blue-sky) albedo values at the six sites by using the satellite-based retrievals of black-sky and white-sky albedos and taking into account the proportion of direct and diffuse solar radiation from the ground measurements at the sites. The coupling of the OLI and MSI SR with MODIS BRDF has already been shown to provide accurate fine-resolution albedo values. With demonstration of a high agreement in BRDF products from MODIS and VIIRS, we expect to see consistency between all four types of fine-resolution albedo products. This assurance of consistency between the couplings of both OLI and MSI with both MODIS and VIIRS guarantees the production of long-term records of surface albedo at fine spatial resolutions and an increased temporal resolution. Such products will be critical in studying land surface changes and associated surface energy balance over the dynamic and heterogeneous landscapes

Assessment of MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6) for directional reflectance retrieval

Science.gov (United States)

Che, X.; Feng, M.; Sexton, J. O.; Channan, S.; Yang, Y.; Song, J.

2017-12-01

Reflection of solar radiation from Earth's surface is the basis for retrieving many higher-level terrestrial attributes such as vegetation indices and albedo. However, reflectance varies with the illumination and viewing geometry of observation (Bi-directional Reflectance Distribution Function (BRDF)) even with constant surface properties, and correcting for these artifacts increases precision of comparisons of images and time series acquired from satellites with different illumination and observation geometries. The operational MODIS processing inverts MODIS BRDF/Albedo Model Parameters (MCD43A1) to retrieve directional reflectance at any solar and view angles, and recently the MCD43A1 (Collection 6) was updated and distributed. We quantified the ability of MCD43A1 Collection 6 for retrieving directional reflectance compared to Collection 5 and tested whether changes in the land surface change over a 16-day composite period affect time series of directional reflectance. Correcting the Terra MODIS daily Surface Reflectance (MOD09GA) to the illumination and view geometries of coincidental Aqua MODIS daily Surface Reflectance (MYD09GA), MCD43A4 Collection 6 and Landsat-5 TM imagery show that the BRDF-corrected results using MCD43A1 Collection 6 hold a higher consistency with higher R2 (0.63 0.955), the slopes close to unity (0.718 0.955) and the lower RMSD (0.422 3.142) and MAE (0.282 1.735) reduced by about 10% than Collection 5. A simple parameter calibration to evaluate the variability of the roughness (R) and the volumetric (V) BRDF parameters for MCD43A1 Collection 6 shows that the assumption of stable land surface characteristic over 16-days composite period, used for BRDF parameters inversion, is plausible in spite of small improvement of directional reflectance and BRDF parameters time series. The larger fluctuations for the MCD43A1 Collection 6 do not have a discernable impact on the reflectance time series. All of these results shows that MCD43A1 Collection

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.

Combining Sustainable Land Management Technologies to Combat Land Degradation and Improve Rural Livelihoods in Semi-arid Lands in Kenya

Science.gov (United States)

Mganga, K. Z.; Musimba, N. K. R.; Nyariki, D. M.

2015-12-01

Drylands occupy more than 80 % of Kenya's total land mass and contribute immensely to the national economy and society through agriculture, livestock production, tourism, and wild product harvesting. Dryland ecosystems are areas of high climate variability making them vulnerable to the threats of land degradation. Consequently, agropastoralists inhabiting these ecosystems develop mechanisms and technologies to cope with the impacts of climate variability. This study is aimed to; (1) determine what agropastoralists inhabiting a semi-arid ecosystem in Kenya attribute to be the causes and indicators of land degradation, (2) document sustainable land management (SLM) technologies being undertaken to combat land degradation, and (3) identify the factors that influence the choice of these SLM technologies. Vegetation change from preferred indigenous forage grass species to woody vegetation was cited as the main indicator of land degradation. Land degradation was attributed to recurrent droughts and low amounts of rainfall, overgrazing, and unsustainable harvesting of trees for fuelwood production. However, despite the challenges posed by climate variability and recurrent droughts, the local community is engaging in simple SLM technologies including grass reseeding, rainwater harvesting and soil conservation, and dryland agroforestry as a holistic approach combating land degradation and improving their rural livelihoods. The choice of these SLM technologies was mainly driven by their additional benefits to combating land degradation. In conclusion, promoting such simple SLM technologies can help reverse the land degradation trend, improve agricultural production, food security including access to food, and subsequently improve livelihoods of communities inhabiting dryland ecosystems.

Combining Sustainable Land Management Technologies to Combat Land Degradation and Improve Rural Livelihoods in Semi-arid Lands in Kenya.

Science.gov (United States)

Mganga, K Z; Musimba, N K R; Nyariki, D M

2015-12-01

Drylands occupy more than 80% of Kenya's total land mass and contribute immensely to the national economy and society through agriculture, livestock production, tourism, and wild product harvesting. Dryland ecosystems are areas of high climate variability making them vulnerable to the threats of land degradation. Consequently, agropastoralists inhabiting these ecosystems develop mechanisms and technologies to cope with the impacts of climate variability. This study is aimed to; (1) determine what agropastoralists inhabiting a semi-arid ecosystem in Kenya attribute to be the causes and indicators of land degradation, (2) document sustainable land management (SLM) technologies being undertaken to combat land degradation, and (3) identify the factors that influence the choice of these SLM technologies. Vegetation change from preferred indigenous forage grass species to woody vegetation was cited as the main indicator of land degradation. Land degradation was attributed to recurrent droughts and low amounts of rainfall, overgrazing, and unsustainable harvesting of trees for fuelwood production. However, despite the challenges posed by climate variability and recurrent droughts, the local community is engaging in simple SLM technologies including grass reseeding, rainwater harvesting and soil conservation, and dryland agroforestry as a holistic approach combating land degradation and improving their rural livelihoods. The choice of these SLM technologies was mainly driven by their additional benefits to combating land degradation. In conclusion, promoting such simple SLM technologies can help reverse the land degradation trend, improve agricultural production, food security including access to food, and subsequently improve livelihoods of communities inhabiting dryland ecosystems.

An Improved Method for Producing High Spatial-Resolution NDVI Time Series Datasets with Multi-Temporal MODIS NDVI Data and Landsat TM/ETM+ Images

Directory of Open Access Journals (Sweden)

Yuhan Rao

2015-06-01

Full Text Available Due to technical limitations, it is impossible to have high resolution in both spatial and temporal dimensions for current NDVI datasets. Therefore, several methods are developed to produce high resolution (spatial and temporal NDVI time-series datasets, which face some limitations including high computation loads and unreasonable assumptions. In this study, an unmixing-based method, NDVI Linear Mixing Growth Model (NDVI-LMGM, is proposed to achieve the goal of accurately and efficiently blending MODIS NDVI time-series data and multi-temporal Landsat TM/ETM+ images. This method firstly unmixes the NDVI temporal changes in MODIS time-series to different land cover types and then uses unmixed NDVI temporal changes to predict Landsat-like NDVI dataset. The test over a forest site shows high accuracy (average difference: −0.0070; average absolute difference: 0.0228; and average absolute relative difference: 4.02% and computation efficiency of NDVI-LMGM (31 seconds using a personal computer. Experiments over more complex landscape and long-term time-series demonstrated that NDVI-LMGM performs well in each stage of vegetation growing season and is robust in regions with contrasting spatial and spatial variations. Comparisons between NDVI-LMGM and current methods (i.e., Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM, Enhanced STARFM (ESTARFM and Weighted Linear Model (WLM show that NDVI-LMGM is more accurate and efficient than current methods. The proposed method will benefit land surface process research, which requires a dense NDVI time-series dataset with high spatial resolution.

FORMS OF DEVELOPMENT AND LAND TENURE AS IMPROVEMENT TOOLS OF land use planning IN UKRAINE

Directory of Open Access Journals (Sweden)

Tretyak A.M.

2016-05-01

Full Text Available Transformations which take place now in the the economy of Ukraine, and in particular in agriculture considerably exacerbated organizational and legal problems and organizational and territorial forms of local agricultural enterprises, protection of land ownership rights. Transformation of land relations violated the the traditional forms of organization of agricultural production, reduced the efficiency of capital investmenst in improvement of using and protection of land. Therefore, to improve the efficiency of agricultural land use in conditions of formation of market economy, general urgent of time is an in-depth analysis of the types and forms of land use which have found their consolidation at the legislative level. Land management is carried out throughout the country. It enveloped lands irrespective of unequivocal purpose, ownership and the character of using. But goals and objectives of land management, it’s content may be different. An important feature of land management are and it’s types. The current Land Code of Ukraineas the the Law of Ukraine "On Land Management" don’t contain legislative provisions on division of land management for certain types. Meanwhile, it should be noted, that normative and legal acts on land management of the Soviet period (Fundamentals of land legislation of the USSR and the United Republics 1968. Land codes 1978., 1990, 1992 there are two separate types of it - intereconomic (Modern terminology of A.M. Tretyak - territorial and internaleconomic. Modern practice of the actions in the field of land management as evidenced by about the existence of another and a third type of land management – separational. Each of them is characterized by a specific purpose, carried out at different levels. It would therefore be appropriate, hat separate species of land management und their consolidation and in legislation level. Given that the process of implementation of land management for the object of land

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....

ANALYSIS OF ACCURACY OF MODIS BRDF PRODUCT (MCD43 C6) BASED ON MISR LAND SURFACE BRF PRODUCT – A CASE STUDY OF THE CENTRAL PART OF NORTHEAST ASIA

OpenAIRE

Li, J.; Chen, S.; Qin, W.; Murefu, M.; Wang, Y.; Yu, Y.; Zhen, Z.

2018-01-01

EOS/MODIS land surface Bi-directional Reflectance Distribution Function (BRDF) product (MCD43), with the latest version C6, is one of the most important operational BRDF products with global coverage. The core sub-product MCD43A1 stores 3 parameters of the RossThick-LiSparseR semi-empirical kernel-driven BRDF model. It is important for confident use of the product to evaluate the accuracy of bi-directional reflectance factor (BRF) predicted by MCD43A1 BRDF model (mBRF). A typical region in th...

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.

Improving Post-Hurricane Katrina Forest Management with MODIS Time Series Products

Science.gov (United States)

Lewis, Mark David; Spruce, Joseph; Evans, David; Anderson, Daniel

2012-01-01

Hurricane damage to forests can be severe, causing millions of dollars of timber damage and loss. To help mitigate loss, state agencies require information on location, intensity, and extent of damaged forests. NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data products offers a potential means for state agencies to monitor hurricane-induced forest damage and recovery across a broad region. In response, a project was conducted to produce and assess 250 meter forest disturbance and recovery maps for areas in southern Mississippi impacted by Hurricane Katrina. The products and capabilities from the project were compiled to aid work of the Mississippi Institute for Forest Inventory (MIFI). A series of NDVI change detection products were computed to assess hurricane induced damage and recovery. Hurricane-induced forest damage maps were derived by computing percent change between MODIS MOD13 16-day composited NDVI pre-hurricane "baseline" products (2003 and 2004) and post-hurricane NDVI products (2005). Recovery products were then computed in which post storm 2006, 2007, 2008 and 2009 NDVI data was each singularly compared to the historical baseline NDVI. All percent NDVI change considered the 16-day composite period of August 29 to September 13 for each year in the study. This provided percent change in the maximum NDVI for the 2 week period just after the hurricane event and for each subsequent anniversary through 2009, resulting in forest disturbance products for 2005 and recovery products for the following 4 years. These disturbance and recovery products were produced for the Mississippi Institute for Forest Inventory's (MIFI) Southeast Inventory District and also for the entire hurricane impact zone. MIFI forest inventory products were used as ground truth information for the project. Each NDVI percent change product was classified into 6 categories of forest disturbance intensity. Stand age

Inferences of all-sky solar irradiance using Terra and Aqua MODIS satellite data

DEFF Research Database (Denmark)

Houborg, Rasmus Møller; Søgaard, Henrik; Emmerich, W.

2007-01-01

-sky solar irradiance components, which links a physically based clear-sky model with a neural network version of a rigorous radiative transfer model. The scheme exploits the improved cloud characterization and retrieval capabilities of the MODerate resolution Imaging Spectroradiometer (MODIS) onboard...... contrasting climates and cloud environments. Information on the atmospheric state was provided by MODIS data products and verifications against AErosol RObotic NETwork (AERONET) data demonstrated usefulness of MODIS aerosol optical depth and total precipitable water vapour retrievals for the delineation...... and become unusable above approximately 60° latitude. However, in principle, the scheme can be applied anywhere on the globe, and a synergistic use of MODIS and geostationary satellite datasets may be envisaged for some applications....

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.

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.

A 3D approach to reconstruct continuous optical images using lidar and MODIS

Directory of Open Access Journals (Sweden)

HuaGuo Huang

2015-06-01

Full Text Available Background Monitoring forest health and biomass for changes over time in the global environment requires the provision of continuous satellite images. However, optical images of land surfaces are generally contaminated when clouds are present or rain occurs. Methods To estimate the actual reflectance of land surfaces masked by clouds and potential rain, 3D simulations by the RAPID radiative transfer model were proposed and conducted on a forest farm dominated by birch and larch in Genhe City, DaXing’AnLing Mountain in Inner Mongolia, China. The canopy height model (CHM from lidar data were used to extract individual tree structures (location, height, crown width. Field measurements related tree height to diameter of breast height (DBH, lowest branch height and leaf area index (LAI. Series of Landsat images were used to classify tree species and land cover. MODIS LAI products were used to estimate the LAI of individual trees. Combining all these input variables to drive RAPID, high-resolution optical remote sensing images were simulated and validated with available satellite images. Results Evaluations on spatial texture, spectral values and directional reflectance were conducted to show comparable results. Conclusions The study provides a proof-of-concept approach to link lidar and MODIS data in the parameterization of RAPID models for high temporal and spatial resolutions of image reconstruction in forest dominated areas.

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...

MODIS-derived daily PAR simulation from cloud-free images and its validation

Energy Technology Data Exchange (ETDEWEB)

Chen, Liangfu; Gu, Xingfa; Tian, Guoliang [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China); The Center for National Spaceborne Demonstration, Beijing 100101 (China); Gao, Yanhua [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China); Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101 (China); Yang, Lei [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China); Jilin University, Changchun 130026 (China); Liu, Qinhuo [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China)

2008-06-15

In this paper, a MODIS-derived daily PAR (photosynthetically active radiation) simulation model from cloud-free image over land surface has been developed based on Bird and Riordan's model. In this model, the total downwelling spectral surface irradiance is divided into two parts: one is beam irradiance, and another is diffuse irradiance. The attenuation of solar beam irradiance comprises scattering by the gas mixture, absorption by ozone, the gas mixture and water vapor, and scattering and absorption by aerosols. The diffuse irradiance is scattered out of the direct beam and towards the surface. The multiple ground-air interactions have been taken into account in the diffuse irradiance model. The parameters needed in this model are atmospheric water vapor content, aerosol optical thickness and spectral albedo ranging from 400 nm to 700 nm. They are all retrieved from MODIS data. Then, the instantaneous photosynthetically available radiation (IPAR) is integrated by using a weighted sum at each of the visible MODIS wavebands. Finally, a daily PAR is derived by integration of IPAR. In order to validate the MODIS-derived PAR model, we compared the field PAR measurements in 2003 and 2004 against the simulated PAR. The measurements were made at the Qianyanzhou ecological experimental station, Chinese Ecosystem Research Network. A total of 54 days of cloud-free MODIS L1B level images were used for the PAR simulation. Our results show that the simulated PAR is consistent with field measurements, where the correlation coefficient of linear regression between calculated PAR and measured PAR is 0.93396. However, there were some uncertainties in the comparison of 1 km pixel PAR with the tower flux stand measurement. (author)

Identifying the Impact of Natural Hazards on Food Security in Africa: Crop Monitoring Using MODIS NDVI Time-Series

Science.gov (United States)

Freund, J. T.; Husak, G.; Funk, C.; Brown, M. E.; Galu, G.

2005-12-01

Most developing countries rely primarily on the successful cultivation of staple crops to ensure food security. Climatic hazards like drought and flooding often negatively impact economically vulnerable economies such as those in Eastern Africa. Effective tracking of food production is required in this area. Production is typically quantified as the simple product of a planted area and its corresponding crop yield. To date, crop yields have been estimated with reasonable accuracy using grid-cell techniques and a Water Requirement Satisfaction Index (WRSI), which draw from remotely sensed data. However, planted area and hence production estimation remains an arduous manual technique fraught with inevitable inaccuracies. In this study we present ongoing efforts to use MODIS NDVI time-series data as a surrogate for greenness, exploiting phenological contrast between cropland and other land cover types. In regions with small field sizes, variations in land cover can impose uncertainty in food production figures, resulting in a lack of consensus in the donor community as to the amount and type of food aid required during an emergency. To concentrate on this issue, statistical methods were employed to produce sub-pixel estimation, addressing the challenges in a monitoring system for use in subsistence-farmed areas. We will discuss two key results. Firstly, we established an inter-annual evaluation of crop health in primary agricultural areas in Kenya. These estimates will greatly improve our ability to anticipate and prevent famine in risk-prone regions through the FEWS NET early warning system. A primary goal is to build capacity in high-risk areas through the transfer of these results to local entities in the form of an operational tool. The low cost and accessibility of MODIS data lends itself well to this objective. Monitoring of crop health will be instituted for use on a yearly basis, and will draw on MODIS data analysis, ground sampling and valuable local

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

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.

Developing MODIS-based cloud climatologies to aid species distribution modeling and conservation activities

Directory of Open Access Journals (Sweden)

Michael William Douglas

2016-10-01

Full Text Available WorldClim (Hijmans et al. 2005 has been the de-facto source of basic climatological analyses for most species distribution modeling research and conservation science applications because of its global coverage and fine (<1 km spatial resolution.  However, it has been recognized since its development that there are limitations in data-poor regions, especially with regard to the precipitation analyses.  Here we describe procedures to develop a satellite-based daytime cloudiness climatology that better reflects the variations in vegetation cover in many regions of the globe than do the WorldClim precipitation products.  Moderate Resolution Imaging Spectroradiometer (MODIS imagery from the National Aeronautics and Space Administration (NASA Terra and Aqua sun-synchronous satellites have recently been used to develop multi-year climatologies of cloudiness.  Several procedures exist for developing such climatologies.  We first discuss a simple procedure that uses brightness thresholds to identify clouds.  We compare these results with those from a more complex procedure: the MODIS Cloud Mask product, recently averaged into climatological products by Wilson and Jetz (2016.  We discuss advantages and limitations of both approaches.  We also speculate on further work that will be needed to improve the usefulness of these MODIS-based climatologies of cloudiness. Despite limitations of current MODIS-based climatology products, they have the potential to greatly improve our understanding of the distribution of biota across the globe.  We show examples from oceanic islands and arid coastlines in the subtropics and tropics where the MODIS products should be of special value in predicting the observed vegetation cover.  Some important applications of reliable climatologies based on MODIS imagery products will include 1 helping to restore long-degraded cloud-impacted environments; 2 improving estimations of the spatial distribution of cloud

Land Surface Phenologies of the Northern Great Plains: Possible Futures Arising From Land and Climate Change

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Henebry, G. M.; Wimberly, M. C.; Senay, G.; Wang, A.; Chang, J.; Wright, C. R.; Hansen, M. C.

2008-12-01

Land cover change across the Northern Great Plains of North America over the past three decades has been driven by changes in agricultural management (conservation tillage; irrigation), government incentives (Conservation Reserve Program; subsidies to grain-based ethanol), crop varieties (cold-hardy soybean), and market dynamics (increasing world demand). Climate change across the Northern Great Plains over the past three decades has been evident in trends toward earlier warmth in the spring and a longer frost-free season. Together these land and climate changes induce shifts in local and regional land surface phenologies (LSPs). Any significant shift in LSP may correspond to a significant shift in evapotranspiration, with consequences for regional hydrometeorology. We explored possible future scenarios involving land use and climate change in six steps. First, we defined the nominal draw areas of current and future biorefineries in North Dakota, South Dakota, Nebraska, Minnesota, and Iowa and masked those land cover types within the draw areas that were unlikely to change to agricultural use (open water, settlements, forests, etc.). Second, we estimated the proportion of corn and soybean remaining within the masked draw areas using MODIS-derived crop maps. Third, in each draw area, we modified LSPs to simulate crop changes for a control and two treatment scenarios. In the control, we used LSP profiles identified from MODIS Collection 5 NBAR data. In one treatment, we increased the proportion of tallgrass LSPs in the draw areas to represent widespread cultivation of a perennial cellulosic crop, like switchgrass. In a second treatment, we increased the proportion of corn LSPs in the draw areas to represent increased corn cultivation. Fourth, we characterized the seasonal progression of the thermal regime associated with the LSP profiles using MODIS Land Surface Temperature (LST) products. Fifth, we modeled the LSP profile as a quadratic function of accumulated

Assessment of MODIS sun-sensor geometry variations effect on observed NDVI using MSG SEVIRI geostationary data

DEFF Research Database (Denmark)

Fensholt, R.; Sandholt, I.; Proud, Simon Richard

2010-01-01

The quality of Earth observation (EO) based vegetation monitoring has improved during recent years, which can be attributed to the enhanced sensor design of new satellites such as MODIS (Moderate Resolution Imaging Spectroradiometer) on Terra and Aqua. It is however expected that sun-sensor geome......The quality of Earth observation (EO) based vegetation monitoring has improved during recent years, which can be attributed to the enhanced sensor design of new satellites such as MODIS (Moderate Resolution Imaging Spectroradiometer) on Terra and Aqua. It is however expected that sun......-sensor geometry variations will have a more visible impact on the Normalized Difference Vegetation Index (NDVI) from MODIS compared to earlier data sources, since noise related to atmosphere and sensor calibration is substantially reduced in the MODIS data stream. For this reason, the effect of varying MODIS......, including a red and NIR band, and the high temporal resolution (15 min) of data, enabling MSG data to be used as a reference for estimating MODIS surface reflectance and NDVI variations caused by varying sun-sensor geometry. The study was performed on data covering West Africa for periods of lowest possible...

Cloud vector mapping using MODIS 09 Climate Modeling Grid (CMG) for the year 2010 and 2011

International Nuclear Information System (INIS)

Jah, Asjad Asif; Farrukh, Yousaf Bin; Ali, Rao Muhammad Saeed

2013-01-01

An alternate use for MODIS images was sought by mapping cloud movement directions and dissipation time during the 2010 and 2011 floods. MODIS Level-02 daily CMG (Climate Modelling Grid) land-cover images were downloaded and subsequently rectified and clipped to the study area. These images were then put together to observe the direction of cloud movement and vectorize the observed paths. Initial findings suggest that usually cloud does not have a prolonged coverage period over the northern humid region of the country and dissipates within less than 24-hours. Additionally, this led to the development of a robust methodology for cloud motion analysis using FOSS and market leading GIS utilities

Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data

Science.gov (United States)

Robin, Jessica; Dubayah, Ralph; Sparrow, Elena; Levine, Elissa

2008-03-01

This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region. Six quadratic regression models with NDVI as a function of accumulated growing degree days (AGDD) were developed from 2001 through 2004 AVHRR and MODIS NDVI data sets for urban, mixed, and forested land covers. Model parameters determined NDVI values for start of the observational period as well as peak and length of the growing season. NDVI values for start of the growing season were determined from the model equations and field observations of SOS made by GLOBE students and researchers at University of Alaska Fairbanks. AGDD was computed from daily air temperature. AVHRR and MODIS models were significantly different from one another with differences in the start of the observational season as well as start, peak, and length of the growing season. Furthermore, AGDD for SOS was significantly lower during the 1990s than the 1980s. NDVI values at SOS did not detect this change. There are limitations with using NDVI to monitor phenological changes in these regions because of snow, the large extent of conifers, and clouds, which restrict the composite period. In addition, differing processing and spectral characteristics restrict continuity between AVHRR and MODIS NDVI data sets.

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.

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

greater than seven meters and were located over five kilometers from shore. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and cyclonic bay-wide circulation transports these nutrients to a northern Bay bloom incubation region. Both of these case studies illustrate the utility of improved MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

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.

[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.

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.

Accuracy of the Temperature-Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions

DEFF Research Database (Denmark)

Garcia, Monica; Fernández, N.; Villagarcía, L.

2014-01-01

surface fluxes using MODIS data; and (ii) provide insights about the factors most affecting the accuracy of results. Factors considered included the type of climatic control on evapotranspiration, λE, (i.e. water-limited vs. energy-limited), the quality of Tair estimates, the heterogeneity of land cover...

Advances in land modeling of KIAPS based on the Noah Land Surface Model

Science.gov (United States)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico

Science.gov (United States)

Jarchow, Christopher J.; Didan, Kamel; Barreto-Muñoz, Armando; Glenn, Edward P.

2018-01-01

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area. PMID:29757265

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%.

[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.

[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.

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.

Land–biosphere–atmosphere interactions over the Tibetan plateau from MODIS observations

International Nuclear Information System (INIS)

Jin, Menglin S; Mullens, Terrence J

2012-01-01

Eleven years (2000–10) of monthly observations from the National Aeronautics and Space Administration (NASA) Terra Moderate-resolution Imaging Spectroradiometer (MODIS) show the diurnal, seasonal, and inter-annual variations of skin temperature over the Tibetan plateau (75–100°E, 27–45°N) at 0.05° × 0.05° resolution. A slight warming trend is observed during this period of time, although the relatively short duration of the observation makes such a trend uncertain. More importantly, using the most recent climatology of land skin temperature, spatially high correlation coefficients are found among normalized difference vegetation index (NDVI), water vapor and cloud relations, indicating that the land surface, vegetation and atmosphere influence one another. Such a quantitative understanding of these relationships at high spatial resolution would be helpful for modeling the biosphere–atmosphere–land surface interaction processes over the Tibetan plateau. (letter)

Securing Land Tenure, Improving Food Security and Reducing ...

International Development Research Centre (IDRC) Digital Library (Canada)

Securing Land Tenure, Improving Food Security and Reducing Poverty in Rural ... land tenure regimes as obstacles to food security, economic integration and ... its 2017 call for proposals to establish Cyber Policy Centres in the Global South.

Land Use and Change

Science.gov (United States)

Irwin, Daniel E.

2004-01-01

The overall purpose of this training session is to familiarize Central American project cooperators with the remote sensing and image processing research that is being conducted by the NASA research team and to acquaint them with the data products being produced in the areas of Land Cover and Land Use Change and carbon modeling under the NASA SERVIR project. The training session, therefore, will be both informative and practical in nature. Specifically, the course will focus on the physics of remote sensing, various satellite and airborne sensors (Landsat, MODIS, IKONOS, Star-3i), processing techniques, and commercial off the shelf image processing software.

Protocol for Validation of the Land Surface Reflectance Fundamental Climate Data Record using AERONET: Application to the Global MODIS and VIIRS Data Records

Science.gov (United States)

Roger, J. C.; Vermote, E.; Holben, B. N.

2014-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and a key parameter in the understanding of the land-surface-climate processes. It is essential that a careful validation of its uncertainties is performed on a global and continuous basis. One approach is the direct comparison of this product with ground measurements but that approach presents several issues related to scale, the episodic nature of ground measurements and the global representativeness. An alternative is to compare the surface reflectance product to reference reflectance determined from Top of atmosphere reflectance corrected using accurate radiative transfer code and very detailed measurements of the atmosphere obtained over the AERONET sites (Vermote and al, 2014, RSE) which allows to test for a large range of aerosol characteristics; formers being important inputs for atmospheric corrections. However, the application of this method necessitates the definition of a very detailed protocol for the use of AERONET data especially as far as size distribution and absorption are concerned, so that alternative validation methods or protocols could be compared. This paper describes the protocol we have been working on based on our experience with the AERONET data and its application to the MODIS and VIIRS record.

Аccounting and methodological aspects of capital expenditure for land improvement

Directory of Open Access Journals (Sweden)

J.P. Melnychuk

2016-07-01

Full Text Available The article highlights the process of reflection in accounting the capital costs for land improvement. The main legislation governing this issue is covered. Also the article has agreed the key issues that ensure in accounting for capital expenditures for farmland improving. The survey has benefited such general scientific methods as: induction and deduction, dialectic, historical and systematic methods and specific methods of accounting. Due to the land reform the ownership of the land was changed. Lands which were owned by farms have been privatized and have received a particular owner. Now privatized lands constitute a significant part of farmland. The land managers require quality accounting information about composition and state of the land and improvements that occur to make an effective management. The numerous changes in legislation generate controversies in their interpretation and, consequently, it results in appearance of the discrepancies in the conduct of cost accounting for capital land improvement which will effect on the amount of net profit in future. The article reflects the economic substance of the process and fundamentally describes the implementation method of accounting for capital expenditure for land in accordance with the applicable law.

Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Imagery

Science.gov (United States)

Monitoring the locations and distributions of land-cover change is important for establishing linkages between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be perfor...

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

Science.gov (United States)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

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

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

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

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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

Regional-scale assessment of soil salinity in the Red River Valley using multi-year MODIS EVI and NDVI.

Science.gov (United States)

Lobell, D B; Lesch, S M; Corwin, D L; Ulmer, M G; Anderson, K A; Potts, D J; Doolittle, J A; Matos, M R; Baltes, M J

2010-01-01

The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10-10(5) km(2)) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.

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.

Forest fire danger index based on modifying Nesterov Index, fuel, and anthropogenic activities using MODIS TERRA, AQUA and TRMM satellite datasets

Science.gov (United States)

Suresh Babu, K. V.; Roy, Arijit; Ramachandra Prasad, P.

2016-05-01

Forest fire has been regarded as one of the major causes of degradation of Himalayan forests in Uttarakhand. Forest fires occur annually in more than 50% of forests in Uttarakhand state, mostly due to anthropogenic activities and spreads due to moisture conditions and type of forest fuels. Empirical drought indices such as Keetch-Byram drought index, the Nesterov index, Modified Nesterov index, the Zhdanko index which belongs to the cumulative type and the Angstrom Index which belongs to the daily type have been used throughout the world to assess the potential fire danger. In this study, the forest fire danger index has been developed from slightly modified Nesterov index, fuel and anthropogenic activities. Datasets such as MODIS TERRA Land Surface Temperature and emissivity (MOD11A1), MODIS AQUA Atmospheric profile product (MYD07) have been used to determine the dew point temperature and land surface temperature. Precipitation coefficient has been computed from Tropical Rainfall measuring Mission (TRMM) product (3B42RT). Nesterov index has been slightly modified according to the Indian context and computed using land surface temperature, dew point temperature and precipitation coefficient. Fuel type danger index has been derived from forest type map of ISRO based on historical fire location information and disturbance danger index has been derived from disturbance map of ISRO. Finally, forest fire danger index has been developed from the above mentioned indices and MODIS Thermal anomaly product (MOD14) has been used for validating the forest fire danger index.

Environmental handling in the Japan: Project of improvement of lands

International Nuclear Information System (INIS)

Tascon Carvajal, R.

1993-01-01

Some administrative aspects, politicians and strategies are described continued by the Japan to protect the environment in the agrarian sector. It is analyzed the project of improvement of lands, their objectives and functions and the operative mark inside which is unwrapped, their procedures for the implementation as sampling and planning, definitive design and construction. Equally the projects of improvement of lands of reduced reach are discussed, in what concerns to irrigation and drainage, consolidation of lands, prevention of disasters and development of the community. The perspectives of the projects of development of lands of long reach are mentioned inside a general strategy of productivity, sustainability, justness and improvement of the level of life

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...

MODIS Hotspot Validation over Thailand

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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.

Estimating Daily Global Evapotranspiration Using Penman–Monteith Equation and Remotely Sensed Land Surface Temperature

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Roozbeh Raoufi

2017-11-01

Full Text Available Daily evapotranspiration (ET is modeled globally for the period 2000–2013 based on the Penman–Monteith equation with radiation and vapor pressures derived using remotely sensed Land Surface Temperature (LST from the MODerate resolution Imaging Spectroradiometer (MODIS on the Aqua and Terra satellites. The ET for a given land area is based on four surface conditions: wet/dry and vegetated/non-vegetated. For each, the ET resistance terms are based on land cover, leaf area index (LAI and literature values. The vegetated/non-vegetated fractions of the land surface are estimated using land cover, LAI, a simplified version of the Beer–Lambert law for describing light transition through vegetation and newly derived light extension coefficients for each MODIS land cover type. The wet/dry fractions of the land surface are nonlinear functions of LST derived humidity calibrated using in-situ ET measurements. Results are compared to in-situ measurements (average of the root mean squared errors and mean absolute errors for 39 sites are 0.81 mm day−1 and 0.59 mm day−1, respectively and the MODIS ET product, MOD16, (mean bias during 2001–2013 is −0.2 mm day−1. Although the mean global difference between MOD16 and ET estimates is only 0.2 mm day−1, local temperature derived vapor pressures are the likely contributor to differences, especially in energy and water limited regions. The intended application for the presented model is simulating ET based on long-term climate forecasts (e.g., using only minimum, maximum and mean daily or monthly temperatures.

Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale

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Louis Kouadio

2014-10-01

Full Text Available Crop yield forecasting plays a vital role in coping with the challenges of the impacts of climate change on agriculture. Improvements in the timeliness and accuracy of yield forecasting by incorporating near real-time remote sensing data and the use of sophisticated statistical methods can improve our capacity to respond effectively to these challenges. The objectives of this study were (i to investigate the use of derived vegetation indices for the yield forecasting of spring wheat (Triticum aestivum L. from the Moderate resolution Imaging Spectroradiometer (MODIS at the ecodistrict scale across Western Canada with the Integrated Canadian Crop Yield Forecaster (ICCYF; and (ii to compare the ICCYF-model based forecasts and their accuracy across two spatial scales-the ecodistrict and Census Agricultural Region (CAR, namely in CAR with previously reported ICCYF weak performance. Ecodistricts are areas with distinct climate, soil, landscape and ecological aspects, whereas CARs are census-based/statistically-delineated areas. Agroclimate variables combined respectively with MODIS-NDVI and MODIS-EVI indices were used as inputs for the in-season yield forecasting of spring wheat during the 2000–2010 period. Regression models were built based on a procedure of a leave-one-year-out. The results showed that both agroclimate + MODIS-NDVI and agroclimate + MODIS-EVI performed equally well predicting spring wheat yield at the ECD scale. The mean absolute error percentages (MAPE of the models selected from both the two data sets ranged from 2% to 33% over the study period. The model efficiency index (MEI varied between −1.1 and 0.99 and −1.8 and 0.99, respectively for the agroclimate + MODIS-NDVI and agroclimate + MODIS-EVI data sets. Moreover, significant improvement in forecasting skill (with decreasing MAPE of 40% and 5 times increasing MEI, on average was obtained at the finer, ecodistrict spatial scale, compared to the coarser CAR scale. Forecast

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

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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.

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

Detection of geothermal anomalies in Tengchong, Yunnan Province, China from MODIS multi-temporal night LST imagery

Science.gov (United States)

Li, H.; Kusky, T. M.; Peng, S.; Zhu, M.

2012-12-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using multi-temporal MODIS LST (Land Surface Temperature). The monthly night MODIS LST data from Mar. 2000 to Mar. 2011 of the study area were collected and analyzed. The 132 month average LST map was derived and three geothermal anomalies were identified. The findings of this study agree well with the results from relative geothermal gradient measurements. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect geothermal anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters

Science.gov (United States)

Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max

2017-12-01

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM

High-frequency remote monitoring of large lakes with MODIS 500 m imagery

Science.gov (United States)

McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

2012-01-01

Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on Aqua/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using MODIS 500 m data and compared MODIS utility to Landsat-based methods. MODIS images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface reflectance. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to reflect seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.

Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

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Tao Yu

2018-02-01

Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

Retrieving near-global aerosol loading over land and ocean from AVHRR

Science.gov (United States)

Hsu, N. C.; Lee, J.; Sayer, A. M.; Carletta, N.; Chen, S.-H.; Tucker, C. J.; Holben, B. N.; Tsay, S.-C.

2017-09-01

The spaceborne advanced very high resolution radiometer (AVHRR) sensor data record is approaching 40 years, providing a crucial asset for studying long-term trends of aerosol properties regionally and globally. However, due to limitations of its channels' information content, aerosol optical depth (AOD) data from AVHRR over land are still largely lacking. In this paper, we describe a new physics-based algorithm to retrieve aerosol loading over both land and ocean from AVHRR for the first time. The over-land algorithm is an extension of our Sea-viewing Wide Field-of-view Sensor and Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue algorithm, while a simplified version of our Satellite Ocean Aerosol Retrieval algorithm is used over ocean. We compare retrieved AVHRR AOD with that from MODIS on a daily and seasonal basis and find, in general, good agreement between the two. For the satellites with equatorial crossing times within 2 h of solar noon, the spatial coverage of the AVHRR aerosol product is comparable to that of MODIS, except over very bright arid regions (such as the Sahara), where the underlying surface reflectance at 630 nm reaches the critical surface reflectance. Based upon comparisons of the AVHRR AOD against Aerosol Robotic Network data, preliminary results indicate that the expected error confidence interval envelope is around ±(0.03 + 15%) over ocean and ±(0.05 + 25%) over land for this first version of the AVHRR aerosol products. Consequently, these new AVHRR aerosol products can contribute important building blocks for constructing a consistent long-term data record for climate studies.

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.

ESTIMATING PM2.5 IN THE BEIJING-TIANJIN-HEBEI REGION USING MODIS AOD PRODUCTS FROM 2014 TO 2015

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Y. Li

2016-06-01

Full Text Available Fine particulate matter with a diameter less than 2.5 μm (PM2.5 has harmful impacts on regional climate, economic development and public health. The high PM2.5 concentrations in China’s urban areas are mainly caused by the combustion of coal and gasoline, industrial pollution and unknown/uncertain sources. The Beijing-Tianjin-Hebei (BTH region with a land area of 218,000 km2, which contains 13 cities, is the biggest urbanized region in northern China. The huge population (110 million, 8% of the China’s population, local heavy industries and vehicle emissions have resulted in severe air pollution. Traditional models have used 10 km Moderate-resolution Imaging Spectroradiometer (MODIS Aerosol Optical Depth (AOD products and proved the statistical relationship between AOD and PM2.5. In 2014, the 3 km MODIS AOD product was released which made PM2.5 estimations with a higher resolution became possible. This study presents an estimation on PM2.5 distributions in the BTH region from September 2014 to August 2015 by combining the MODIS satellite data, ground measurements of PM2.5, meteorological parameters and social-economic factors based on the geographically weighted regression model. The results demonstrated that the 10 km AOD product provided results with a slightly higher accuracy although the 3 km AOD product could provide more information about the spatial variations of PM2.5 estimations. Additionally, compared with the global regression, the geographically weighed model was able to improve the estimation results.

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.

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.

Combining vegetation index and model inversion methods for theextraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data

DEFF Research Database (Denmark)

Houborg, Rasmus Møller; Søgaard, Henrik; Bøgh, Eva

2007-01-01

for the inversion of a canopy reflectance model using Terra and Aqua MODIS multi-spectral, multi-temporal, and multi-angle reflectance observations to aid the determination of vegetation-specific physiological and structural canopy parameters. Land cover and site-specific inversion modeling was applied...

Observation of Mountain Lee Waves with MODIS NIR Column Water Vapor

Science.gov (United States)

Lyapustin, A.; Alexander, M. J.; Ott, L.; Molod, A.; Holben, B.; Susskind, J.; Wang, Y.

2014-01-01

Mountain lee waves have been previously observed in data from the Moderate Resolution Imaging Spectroradiometer (MODIS) "water vapor" 6.7 micrometers channel which has a typical peak sensitivity at 550 hPa in the free troposphere. This paper reports the first observation of mountain waves generated by the Appalachian Mountains in the MODIS total column water vapor (CWV) product derived from near-infrared (NIR) (0.94 micrometers) measurements, which indicate perturbations very close to the surface. The CWV waves are usually observed during spring and late fall or some summer days with low to moderate CWV (below is approx. 2 cm). The observed lee waves display wavelengths from3-4 to 15kmwith an amplitude of variation often comparable to is approx. 50-70% of the total CWV. Since the bulk of atmospheric water vapor is confined to the boundary layer, this indicates that the impact of thesewaves extends deep into the boundary layer, and these may be the lowest level signatures of mountain lee waves presently detected by remote sensing over the land.

Analysis of Post-Fire Vegetation Recovery in the Mediterranean Basin using MODIS Derived Vegetation Indices

Science.gov (United States)

Hawtree, Daniel; San Miguel, Jesus; Sedano, Fernando; Kempeneers, Pieter

2010-05-01

The Mediterranean basin region is highly susceptible to wildfire, with approximately 60,000 individual fires and half a million ha of natural vegetation burnt per year. Of particular concern in this region is the impact of repeated wildfires on the ability of natural lands to return to a pre-fire state, and of the possibility of desertification of semi-arid areas. Given these concerns, understanding the temporal patterns of vegetation recovery is important for the management of environmental resources in the region. A valuable tool for evaluating these recovery patterns are vegetation indices derived from remote sensing data. Previous research on post-fire vegetation recovery conducted in this region has found significant variability in recovery times across different study sites. It is unclear what the primary variables are affecting the differences in the rates of recovery, and if any geographic patterns of behavior exist across the Mediterranean basin. This research has primarily been conducted using indices derived from Landsat imagery. However, no extensive analysis of vegetation regeneration for large regions has been published, and assessment of vegetation recovery on the basis of medium-spatial resolution imagery such as that of MODIS has not yet been analyzed. This study examines the temporal pattern of vegetation recovery in a number of fire sites in the Mediterranean basin, using data derived from MODIS 16 -day composite vegetation indices. The intent is to develop a more complete picture of the temporal sequence of vegetation recovery, and to evaluate what additional factors impact variations in the recovery sequence. In addition, this study evaluates the utility of using MODIS derived vegetation indices for regeneration studies, and compares the findings to earlier studies which rely on Landsat data. Wildfires occurring between the years 2000 and 2004 were considered as potential study sites for this research. Using the EFFIS dataset, all wildfires

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL

Science.gov (United States)

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far

Role of MODIS Vegetation Phenology Products in the U.S. for Warn Early Warning System for Forest Threats

Science.gov (United States)

Spruce, Joseph; Hargrove, William; Norman, Steve; Gasser, Gerald; Smoot, James; Kuper, Philip

2012-01-01

U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic damage agents disturb, damage, kill, and/or threaten these forests. Regionally extensive forest disturbances can also threaten human life and property, bio-diversity and water supplies. timely regional forest disturbance monitoring products are needed to aid forest health management work at finer scales. daily MODIS data provide a means to monitor regional forest disturbances on a weekly basis, leveraging vegetation phenology. In response, the USFS and NASA began collaborating in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat Early Warning System (EWS).

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.

Identification of HNF1A-MODY and HNF4A-MODY in Irish families: phenotypic characteristics and therapeutic implications.

Science.gov (United States)

Kyithar, M P; Bacon, S; Pannu, K K; Rizvi, S R; Colclough, K; Ellard, S; Byrne, M M

2011-12-01

The prevalence of hepatocyte nuclear factor (HNF)-1A and HNF4A mutations, and the clinical implications following the genetic diagnosis of maturity-onset diabetes of the young (MODY) in the Irish population, remain unknown. The aim of this study was to establish the occurrence of HNF1A and HNF4A mutations in subjects classified clinically as MODY to identify novel mutations, and to determine the phenotypic features and response to therapy. A total of 36 unrelated index cases with a clinical diagnosis of MODY were analyzed for HNF1A/HNF4A mutations. OGTT was performed to determine the degree of glucose tolerance and insulin secretory response. Also, 38 relatives underwent OGTT and were tested for the relevant known mutations. HNF1A-/HNF4A-MODY subjects were compared with nine HNF1A mutation-negative relatives and 20 type 2 diabetic (T2DM) patients. Seven different HNF1A mutations were identified in 11/36 (30.5%) index cases, two of which were novel (S352fsdelG and F426X), as well as two novel HNF4A mutations (M1? and R290C; 6%). Family screening revealed 20 subjects with HNF1A and seven with HNF4A mutations. Only 51.6% of HNF1A mutation carriers were diagnosed with diabetes by age 25 years; 11 of the mutation carriers were overweight and four were obese. Insulin secretory response to glucose was significantly lower in HNF1A-MODY subjects than in T2DM patients and HNF1A mutation-negative relatives (P=0.01). Therapeutic changes occurred in 48% of mutation carriers following genetic diagnosis. There was an HNF1A-MODY pick-up rate of 30.5% and an HNF4A-MODY pick-up rate of 6% in Irish MODY families. Genetically confirmed MODY has significant therapeutic implications. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Improving snow cover mapping in forests through the use of a canopy reflectance model

International Nuclear Information System (INIS)

Klein, A.G.; Hall, D.K.; Riggs, G.A.

1998-01-01

MODIS, the moderate resolution imaging spectro radiometer, will be launched in 1998 as part of the first earth observing system (EOS) platform. Global maps of land surface properties, including snow cover, will be created from MODIS imagery. The MODIS snow-cover mapping algorithm that will be used to produce daily maps of global snow cover extent at 500 m resolution is currently under development. With the exception of cloud cover, the largest limitation to producing a global daily snow cover product using MODIS is the presence of a forest canopy. A Landsat Thematic Mapper (TM) time-series of the southern Boreal Ecosystem–Atmosphere Study (BOREAS) study area in Prince Albert National Park, Saskatchewan, was used to evaluate the performance of the current MODIS snow-cover mapping algorithm in varying forest types. A snow reflectance model was used in conjunction with a canopy reflectance model (GeoSAIL) to model the reflectance of a snow-covered forest stand. Using these coupled models, the effects of varying forest type, canopy density, snow grain size and solar illumination geometry on the performance of the MODIS snow-cover mapping algorithm were investigated. Using both the TM images and the reflectance models, two changes to the current MODIS snow-cover mapping algorithm are proposed that will improve the algorithm's classification accuracy in forested areas. The improvements include using the normalized difference snow index and normalized difference vegetation index in combination to discriminate better between snow-covered and snow-free forests. A minimum albedo threshold of 10% in the visible wavelengths is also proposed. This will prevent dense forests with very low visible albedos from being classified incorrectly as snow. These two changes increase the amount of snow mapped in forests on snow-covered TM scenes, and decrease the area incorrectly identified as snow on non-snow-covered TM scenes. (author)

A Consistent EPIC Visible Channel Calibration Using VIIRS and MODIS as a Reference.

Science.gov (United States)

Haney, C.; Doelling, D. R.; Minnis, P.; Bhatt, R.; Scarino, B. R.; Gopalan, A.

2017-12-01

The Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite constantly images the sunlit disk of Earth from the Lagrange-1 (L1) point in 10 spectral channels spanning the UV, VIS, and NIR spectrums. Recently, the DSCOVR EPIC team has publicly released version 2 dataset, which has implemented improved navigation, stray-light correction, and flat-fielding of the CCD array. The EPIC 2-year data record must be well-calibrated for consistent cloud, aerosol, trace gas, land use and other retrievals. Because EPIC lacks onboard calibrators, the observations made by EPIC channels must be calibrated vicariously using the coincident measurements from radiometrically stable instruments that have onboard calibration systems. MODIS and VIIRS are best-suited instruments for this task as they contain similar spectral bands that are well-calibrated onboard using solar diffusers and lunar tracking. We have previously calibrated the EPIC version 1 dataset by using EPIC and VIIRS angularly matched radiance pairs over both all-sky ocean and deep convective clouds (DCC). We noted that the EPIC image required navigations adjustments, and that the EPIC stray-light correction provided an offset term closer to zero based on the linear regression of the EPIC and VIIRS ray-matched radiance pairs. We will evaluate the EPIC version 2 navigation and stray-light improvements using the same techniques. In addition, we will monitor the EPIC channel calibration over the two years for any temporal degradation or anomalous behavior. These two calibration methods will be further validated using desert and DCC invariant Earth targets. The radiometric characterization of the selected invariant targets is performed using multiple years of MODIS and VIIRS measurements. Results of these studies will be shown at the conference.

A Simple Technique for Creating Regional Composites of Sea Surface Temperature from MODIS for Use in Operational Mesoscale NWP

Science.gov (United States)

Knievel, Jason C.; Rife, Daran L.; Grim, Joseph A.; Hahmann, Andrea N.; Hacker, Joshua P.; Ge, Ming; Fisher, Henry H.

2010-01-01

This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the 61.08C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this

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.

An assessment on the MODIS quality data over the Iberian Peninsula (Southern Europe)

Science.gov (United States)

Huesca, Margarita; Merino-de-Miguel, Silvia; Cicuéndez, Víctor; Litago, Javier; Palacios-Orueta, Alicia

2014-05-01

pixels that belong to long gaps to stratify the study area. Finally, the mean annual pattern was used to assess the generic intra-annual evolution of the number of low quality dates and log gaps within the classes that showed the worst pixel quality conditions. The intra-annual evolution was evaluated in order to select those periods of the year when each quality parameter was dominant. Results showed that the most significant quality flags in the study area were clouds, cloud shadows, pixels adjacent to cloud and aerosols; in both the spatial and temporal frequency terms. Besides, developed maps provided a useful tool in the selection of the best method to improve the quality of the MODIS time series (e.g. spatial and temporal interpolation, function fitting, pixel removal, etc). References: David P Roy, Jordan S Borak, Sadashiva Devadiga, Robert E Wolfe, Min Zheng, Jacques Descloitres. 2002. The MODIS Land product quality assessment approach. Remote Sensing of Environment, Volume 83, Issues 1-2, Pages 62-76.

Relation of MODIS EVI and LAI across time, vegetation types and hydrological regimes

Science.gov (United States)

Alexandridis, Thomas; Ovakoglou, George

2015-04-01

Estimation of the Leaf Area Index (LAI) of a landscape is considered important to describe the ecosystems activity and is used as an important input parameter in hydrological and biogeochemical models related to water and carbon cycle, desertification risk, etc. The measurement of LAI in the field is a laborious and costly process and is mainly done by indirect methods, such as hemispherical photographs that are processed by specialized software. For this reason there have been several attempts to estimate LAI with multispectral satellite images, using theoretical biomass development models, or empirical equations using vegetation indices and land cover maps. The aim of this work is to study the relation of MODIS EVI and LAI across time, vegetation type, and hydrological regime. This was achieved by studying 120 maps of EVI and LAI which cover a hydrological year and five hydrologically diverse areas: river Nestos in Greece, Queimados catchment in Brazil, Rijnland catchment in The Netherlands, river Tamega in Portugal, and river Umbeluzi in Mozambique. The following Terra MODIS composite datasets were downloaded for the hydrological year 2012-2013: MOD13A2 "Vegetation Indices" and MCD15A2 "LAI and FPAR", as well as the equivalent quality information layers (QA). All the pixels that fall in a vegetation land cover (according to the MERIS GLOBCOVER map) were sampled for the analysis, with the exception of those that fell at the border between two vegetation or other land cover categories, to avoid the influence of mixed pixels. Using linear regression analysis, the relationship between EVI and LAI was identified per date, vegetation type and study area. Results show that vegetation type has the highest influence in the variation of the relationship between EVI and LAI in each study area. The coefficient of determination (R2) is high and statistically significant (ranging from 0.41 to 0.83 in 90% of the cases). When plotting the EVI factor from the regression equation

Do Surface Energy Fluxes Reveal Land Use/Land Cover Change in South Florida?: A Remote Sensing Perspective

Science.gov (United States)

Kandel, H. P.; Melesse, A. M.

2017-12-01

Series of changes on land use/ land cover in South Florida resulting from drainage and development activities during early to mid-20th followed by restoration measures since late-20th century have had prominent impacts on hydrologic regime and energy fluxes in the region. Previous results from numerical modeling and MODIS-based analysis have shown a shift in dominance of heat fluxes: from latent to sensible along the axes of urbanization, and an opposite along the axes of restoration. This study implements a slightly modified version of surface energy balance algorithm (SEBAL) on cloud-masked Landsat imageries archived over the period of 30-years combined with ground-meteorological data for South Florida using spatial analysis model in ArcGIS and calculates energy flux components: sensible heat flux, latent heat flux, and ground heat flux. The study finally computes variation of Bowen's ratio (BR) and daily evapotranspiration (ET) rate over various land covers for different years. Coexistences are apparent between increased BR and increased intensity of urbanization, and between increased daily ET rates and improved best management practices in agricultural areas. An increase in mean urban BR from 1.67 in 1984 to 3.06 in 2010 show plausible link of BR with urban encroachment of open lands, and expulsion of additional heat by increased population/automobiles/factories/air conditioning units. Likewise, increase in mean agricultural daily ET rates from 0.21 mm/day to 3.60 mm/day between 1984 to 2010 probably shows the effects of improved moisture conditions on the northern farm lands as the results of restoration practices. Once new observed data become available to corroborate these results, remote sensing methods-owing to their greater spatial and temporal details-can be used as assessment measures both for the progress of restoration evaluation and for the extent detection of human-induced climate change.

The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes.

Science.gov (United States)

Shields, B M; McDonald, T J; Ellard, S; Campbell, M J; Hyde, C; Hattersley, A T

2012-05-01

Diagnosing MODY is difficult. To date, selection for molecular genetic testing for MODY has used discrete cut-offs of limited clinical characteristics with varying sensitivity and specificity. We aimed to use multiple, weighted, clinical criteria to determine an individual's probability of having MODY, as a crucial tool for rational genetic testing. We developed prediction models using logistic regression on data from 1,191 patients with MODY (n = 594), type 1 diabetes (n = 278) and type 2 diabetes (n = 319). Model performance was assessed by receiver operating characteristic (ROC) curves, cross-validation and validation in a further 350 patients. The models defined an overall probability of MODY using a weighted combination of the most discriminative characteristics. For MODY, compared with type 1 diabetes, these were: lower HbA(1c), parent with diabetes, female sex and older age at diagnosis. MODY was discriminated from type 2 diabetes by: lower BMI, younger age at diagnosis, female sex, lower HbA(1c), parent with diabetes, and not being treated with oral hypoglycaemic agents or insulin. Both models showed excellent discrimination (c-statistic = 0.95 and 0.98, respectively), low rates of cross-validated misclassification (9.2% and 5.3%), and good performance on the external test dataset (c-statistic = 0.95 and 0.94). Using the optimal cut-offs, the probability models improved the sensitivity (91% vs 72%) and specificity (94% vs 91%) for identifying MODY compared with standard criteria of diagnosis MODY. This allows an improved and more rational approach to determine who should have molecular genetic testing.

Evaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid lands

KAUST Repository

Rosas, Jorge

2014-12-01

Satellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.

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...

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.

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.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

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Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

MODIS-derived EVI, NDVI and WDRVI time series to estimate phenological metrics in French deciduous forests

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Testa, S.; Soudani, K.; Boschetti, L.; Borgogno Mondino, E.

2018-02-01

Monitoring forest phenology allows us to study the effects of climate change on vegetated land surfaces. Daily and composite time series (TS) of several vegetation indices (VIs) from MODerate resolution Imaging Spectroradiometer (MODIS) data have been widely used in scientific works for phenological studies since the beginning of the MODIS mission. The objective of this work was to use MODIS data to find the best VI/TS combination to estimate start-of-season (SOS) and end-of-season (EOS) dates across 50 temperate deciduous forests. Our research used as inputs 2001-2012 daily reflectance from MOD09GQ/MOD09GA products and 16-day composite VIs from the MOD13Q1 dataset. The 50 pixels centered on the 50 forest plots were extracted from the above-mentioned MODIS imagery; we then generated 5 different types of TS (1 daily from MOD09 and 4 composite from MOD13Q1) and used all of them to implement 6 VIs, obtaining 30 VI/TS combinations. SOS and EOS estimates were determined for each pixel/year and each VI/TS combination. SOS/EOS estimations were then validated against ground phenological observations. Results showed that, in our test areas, composite TS, if actual acquisition date is considered, performed mostly better than daily TS. EVI, WDRVI0.20 and NDVI were more suitable to SOS estimation, while WDRVI0.05 and EVI were more convenient in estimating early and advanced EOS, respectively.

Evaluation of spatio-temporal variability of Hamburg Aerosol Climatology against aerosol datasets from MODIS and CALIOP

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V. Pappas

2013-08-01

Full Text Available The new global aerosol climatology named HAC (Hamburg Aerosol Climatology is compared against MODIS (Collection 5, 2000–2007 and CALIOP (Level 2-version 3, 2006–2011 retrievals. The comparison of aerosol optical depth (AOD from HAC against MODIS shows larger HAC AOD values over regions with higher aerosol loads and smaller HAC AOD values than MODIS for regions with lower loads. The HAC data are found to be more reliable over land and for low AOD values. The largest differences between HAC and MODIS occur from March to August for the Northern Hemisphere and from September to February for the Southern Hemisphere. In addition, both the spectral variability and vertical distribution of the HAC AOD are examined at selected AERONET (1998–2007 sites, representative of main aerosol types (pollutants, sea salt, biomass and dust. Based on comparisons against spectral AOD values from AERONET, the mean absolute percentage error in HAC AOD data is 25% at ultraviolet wavelengths (400 nm, 6–12% at visible and 18% at near-infrared (1000 nm. For the same AERONET sites, the HAC AOD vertical distribution is compared against CALIOP space lidar data. On a daily average basis, HAD AOD is less by 9% in the lowest 3 km than CALIOP values, especially for sites with biomass burning smoke, desert dust and sea salt spray. Above the boundary layer, the HAC AOD vertical distribution is reliable.

Land ECVs from QA4ECV using an optimal estimation framework

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Muller, Jan-Peter; Kharbouche, Said; Lewis, Philip; Danne, Olaf; Blessing, Simon; Giering, Ralf; Gobron, Nadine; Lanconelli, Christian; Govaerts, Yves; Schulz, Joerg; Doutriaux-Boucher, Marie; Lattanzio, Alessio; Aoun, Youva

2017-04-01

In the ESA-DUE GlobAlbedo project (http://www.GlobAlbedo.org), a 15 year record of land surface albedo was generated from the European VEGETATION & MERIS sensors using optimal estimation. This was based on 3 broadbands (0.4-0.7, 0.7-3, 0.4-3µm) and fused data at level-2 after converting from spectral narrowband to these 3 broadbands with surface BRFs. A 10 year long record of land surface albedo climatology was generated from Collection 5 of the MODIS BRDF product for these same broadbands. This was employed as an a priori estimate for an optimal estimation based retrieval of land surface albedo when there were insufficient samples from the European sensors. This so-called MODIS prior was derived at 1km from the 500m MOD43A1,2 BRDF inputs every 8 days using the QA bits and the method described in the GlobAlbedo ATBD which is available from the website (http://www.globalbedo.org/docs/GlobAlbedo_Albedo_ATBD_V4.12.pdf). In the ESA-STSE WACMOS-ET project, FastOpt generated fapar & LAI based on this GlobAlbedo BRDF with associated per pixel uncertainty using the TIP framework. In the successor EU-FP7-QA4ECV* project, we have developed a 33 year record (1981-2014) of Earth surface spectral and broadband albedo (i.e. including the ocean and sea-ice) using optimal estimation for the land and where available, relevant sensors for "instantaneous" retrievals over the poles (Kharbouche & Muller, this conference). This requires the longest possible land surface spectral and broadband BRDF record that can only be supplied by a 16 year of MODIS Collection 6 BRDFs at 500m but produced on a daily basis. The CEMS Big Data computer at RAL was used to generate 7 spectral bands and 3 broadband BRDF with and without snow and snow_only. We will discuss the progress made since the start of the QA4ECV project on the production of a new fused land surface BRDF/albedo spectral and broadband CDR product based on four European sensors: MERIS, (A)ATSR(2), VEGETATION, PROBA-V and two US sensors

Land, Cryosphere, and Nighttime Environmental Products from Suomi NPP VIIRS: Overview and Status

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Roman, Miguel O.; Justice, Chris; Csiszar, Ivan

2014-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-orbiting Partnership (S-NPP: http://npp.gsfc.nasa.gov/). VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provide observation continuity with NASA's Earth Observing System's (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA and NOAA funded scientists have been working to evaluate the instrument performance and derived products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the former National Polar-orbiting Environmental Satellite System (NPOESS). The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs and providing MODIS data product continuity. This paper will present to-date findings of the NASA Science Team's evaluation of the VIIRS Land and Cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization (http://viirsland.gsfc.nasa.gov/index.html). The paper will also discuss new capabilities being developed at NASA's Land Product Evaluation and Test Element (http://landweb.nascom.nasa.gov/NPP_QA/); including downstream data and products derived from the VIIRS Day/Night Band (DNB).

Adaptive Landing Gear: Optimum Control Strategy and Potential for Improvement

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Grzegorz Mikułowski

2009-01-01

Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.

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

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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.

Towards a systematic nationwide screening strategy for MODY.

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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.

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

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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

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

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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.

Application of the Support Vector Regression Method for Turbidity Assessment with MODIS on a Shallow Coral Reef Lagoon (Voh-Koné-Pouembout, New Caledonia

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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.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

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Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map

Trajectory analysis of land use and land cover maps to improve spatial-temporal patterns, and impact assessment on groundwater recharge

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Zomlot, Z.; Verbeiren, B.; Huysmans, M.; Batelaan, O.

2017-11-01

Land use/land cover (LULC) change is a consequence of human-induced global environmental change. It is also considered one of the major factors affecting groundwater recharge. Uncertainties and inconsistencies in LULC maps are one of the difficulties that LULC timeseries analysis face and which have a significant effect on hydrological impact analysis. Therefore, an accuracy assessment approach of LULC timeseries is needed for a more reliable hydrological analysis and prediction. The objective of this paper is to assess the impact of land use uncertainty and to improve the accuracy of a timeseries of CORINE (coordination of information on the environment) land cover maps by using a new approach of identifying spatial-temporal LULC change trajectories as a pre-processing tool. This ensures consistency of model input when dealing with land-use dynamics and as such improves the accuracy of land use maps and consequently groundwater recharge estimation. As a case study the impact of consistent land use changes from 1990 until 2013 on groundwater recharge for the Flanders-Brussels region is assessed. The change trajectory analysis successfully assigned a rational trajectory to 99% of all pixels. The methodology is shown to be powerful in correcting interpretation inconsistencies and overestimation errors in CORINE land cover maps. The overall kappa (cell-by-cell map comparison) improved from 0.6 to 0.8 and from 0.2 to 0.7 for forest and pasture land use classes respectively. The study shows that the inconsistencies in the land use maps introduce uncertainty in groundwater recharge estimation in a range of 10-30%. The analysis showed that during the period of 1990-2013 the LULC changes were mainly driven by urban expansion. The results show that the resolution at which the spatial analysis is performed is important; the recharge differences using original and corrected CORINE land cover maps increase considerably with increasing spatial resolution. This study indicates

Assessment of MODIS On-Orbit Calibration Using a Deep Convective Cloud Technique

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Mu, Qiaozhen; Wu, Aisheng; Chang, Tiejun; Angal, Amit; Link, Daniel; Xiong, Xiaoxiong; Doelling, David R.; Bhatt, Rajendra

2016-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensors onboard Terra and Aqua satellites are calibrated on-orbit with a solar diffuser (SD) for the reflective solar bands (RSB). The MODIS sensors are operating beyond their designed lifetime and hence present a major challenge to maintain the calibration accuracy. The degradation of the onboard SD is tracked by a solar diffuser stability monitor (SDSM) over a wavelength range from 0.41 to 0.94 micrometers. Therefore, any degradation of the SD beyond 0.94 micrometers cannot be captured by the SDSM. The uncharacterized degradation at wavelengths beyond this limit could adversely affect the Level 1B (L1B) product. To reduce the calibration uncertainties caused by the SD degradation, invariant Earth-scene targets are used to monitor and calibrate the MODIS L1B product. The use of deep convective clouds (DCCs) is one such method and particularly significant for the short-wave infrared (SWIR) bands in assessing their long-term calibration stability. In this study, we use the DCC technique to assess the performance of the Terra and Aqua MODIS Collection-6 L1B for RSB 1 3- 7, and 26, with spectral coverage from 0.47 to 2.13 micrometers. Results show relatively stable trends in Terra and Aqua MODIS reflectance for most bands. Careful attention needs to be paid to Aqua band 1, Terra bands 3 and 26 as their trends are larger than 1% during the study time period. We check the feasibility of using the DCC technique to assess the stability in MODIS bands 17-19. The assessment test on response versus scan angle (RVS) calibration shows substantial trend difference for Aqua band 1between different angles of incidence (AOIs). The DCC technique can be used to improve the RVS calibration in the future.

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

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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.

Land degradation and improvement trends over Iberia in the last three decades

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Gouveia, Célia M.; Páscoa, Patrícia; Russo, Ana; Trigo, Ricardo

2017-04-01

Land degradation and desertification are recognised as an important environmental and social problem in arid and semiarid regions, particularly within a climate change context. In the last three decades the entire Mediterranean basin has been affected by more frequent droughts, covering large sectors and often lasting several months. Simultaneously, the stress imposed by land management practices, such as land abandonment and intensification, highlights the need of a continuous monitoring and early detection of degradation. The Normalized Difference Vegetation Index (NDVI) from GIMMS dataset was used as an indicator of land degradation or improvement over Iberia between 1982 and 2012. The precipitation influence on NDVI was previously removed and the negative/positive trends of the obtained residuals were presumed to indicate land degradation/improvement. Overall the Iberian Peninsula is dominated by widespread land improvement with only a few hot spots of land degradation located in central and southern sectors and also in east Mediterranean and Atlantic coasts. Less than 20% of the area presenting land degradation is located within regions where land cover changes were observed, being the new land cover types associated with transitional woodland-shrub, permanent and annual crops and permanently irrigated land areas. Although being a very small fraction, the pixels of land degradation are mainly located on a semi-arid region. The monotonic changes and trend shifts present in the NDVI dataset were also assessed. The major shifts in vegetation trends and the corresponding year of occurrence were associated with the main disturbances observed in Iberia, namely the major wildfires' seasons in Portugal, and also to land abandonment and to new agricultural practices that resulted from the construction of new dams. The results obtained provide a new outlook of the real nature of degradation or improvement of vegetation in Iberia in the last three decades

Global Scale Attribution of Anthropogenic and Natural Dust Sources and their Emission Rates Based on MODIS Deep Blue Aerosol Products

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Ginoux, Paul; Prospero, Joseph M.; Gill, Thomas E.; Hsu, N. Christina; Zhao, Ming

2012-01-01

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. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products

Science.gov (United States)

Ginoux, Paul; Prospero, Joseph M.; Gill, Thomas E.; Hsu, N. Christina; Zhao, Ming

2012-09-01

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. Here we present a global-scale high-resolution (0.1°) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

Building Daily 30-meter Spatial Resolution Maps of Surface Water Bodies from MODIS Data Using a Novel Technique for Transferring Information Across Space and Time

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Khandelwal, A.; Karpatne, A.; Kumar, V.

2017-12-01

In this paper, we present novel methods for producing surface water maps at 30 meter spatial resolution at a daily temporal resolution. These new methods will make use of the MODIS spectral data from Terra (available daily since 2000) to produce daily maps at 250 meter and 500 meter resolution, and then refine them using the relative elevation ordering of pixels at 30 meter resolution. The key component of these methods is the use of elevation structure (relative elevation ordering) of a water body. Elevation structure is not explicitly available at desired resolution for most water bodies in the world and hence it will be estimated using our previous work that uses the history of imperfect labels. In this paper, we will present a new technique that uses elevation structure (unlike existing pixel based methods) to enforce temporal consistency in surface water extents (lake area on nearby dates is likely to be very similar). This will greatly improve the quality of the MODIS scale land/water labels since daily MODIS data can have a large amount of missing (or poor quality) data due to clouds and other factors. The quality of these maps will be further improved using elevation based resolution refinement approach that will make use of elevation structure estimated at Landsat scale. With the assumption that elevation structure does not change over time, it provides a very effective way to transfer information between datasets even when they are not observed concurrently. In this work, we will derive elevation structure at Landsat scale from monthly water extent maps spanning 1984-2015, publicly available through a joint effort of Google Earth Engine and the European Commission's Joint Research Centre (JRC). This elevation structure will then be used to refine spatial resolution of Modis scale maps from 2000 onwards. We will present the analysis of these methods on a large and diverse set of water bodies across the world.

Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images.

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Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

2015-05-12

As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems.

Monitoring Farmland Loss Caused by Urbanization in Beijing from Modis Time Series Using Hierarchical Hidden Markov Model

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Yuan, Y.; Meng, Y.; Chen, Y. X.; Jiang, C.; Yue, A. Z.

2018-04-01

In this study, we proposed a method to map urban encroachment onto farmland using satellite image time series (SITS) based on the hierarchical hidden Markov model (HHMM). In this method, the farmland change process is decomposed into three hierarchical levels, i.e., the land cover level, the vegetation phenology level, and the SITS level. Then a three-level HHMM is constructed to model the multi-level semantic structure of farmland change process. Once the HHMM is established, a change from farmland to built-up could be detected by inferring the underlying state sequence that is most likely to generate the input time series. The performance of the method is evaluated on MODIS time series in Beijing. Results on both simulated and real datasets demonstrate that our method improves the change detection accuracy compared with the HMM-based method.

Mapping of land cover in Northern California with simulated HyspIRI images

Science.gov (United States)

Clark, M. L.; Kilham, N. E.

2014-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (i.e., full range) of the spectrum have shown improved capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a full-range hyperspectral and thermal satellite being considered for development by NASA (hyspiri.jpl.nasa.gov). A hyperspectral satellite, such as HyspIRI, will provide detailed spectral and temporal information at global scales that could greatly improve our ability to map land cover with greater class detail and spatial and temporal accuracy than possible with conventional multispectral satellites. The broad goal of our research is to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping across a range of environmental and anthropogenic gradients in California. In this study, we mapped FAO Land Cover Classification System (LCCS) classes over 30,000 km2 in Northern California using multi-temporal HyspIRI imagery simulated from the AVIRIS airborne sensor. The Random Forests classification was applied to predictor variables derived from the multi-temporal hyperspectral data and accuracies were compared to that from Landsat 8 OLI. Results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different forest life-form types, such as mixed conifer and broadleaf forests and open- and closed-canopy forests.

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring.

Science.gov (United States)

Skakun, Sergii; Justice, Christopher O; Vermote, Eric; Roger, Jean-Claude

2018-01-01

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for

Large-sized seaweed monitoring based on MODIS

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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.

PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

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Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...

Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

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Forman, Bart; Reichle, Rofl; Rodell, Matt

2011-01-01

Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

Global cloud database from VIRS and MODIS for CERES

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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.

Mapping the global depth to bedrock for land surface modelling

Science.gov (United States)

Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

2017-12-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

Assessment of MODIS RSB Detector Uniformity Using Deep Convective Clouds

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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.

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.

Normalization of NDVI from Different Sensor System using MODIS Products as Reference

International Nuclear Information System (INIS)

Wenxia, Gan; Liangpei, Zhang; Wei, Gong; Huanfeng, Shen

2014-01-01

Medium Resolution NDVI(Normalized Difference Vegetation Index) from different sensor systems such as Landsat, SPOT, ASTER, CBERS and HJ-1A/1B satellites provide detailed spatial information for studies of ecosystems, vegetation biophysics, and land cover. Limitation of sensor designs, cloud contamination, and sensor failure highlighted the need to normalize and integrate NDVI from multiple sensor system in order to create a consistent, long-term NDVI data set. In this paper, we used a reference-based method for NDVI normalization. And present an application of this approach which covert Landsat ETM+ NDVI calculated by digital number (NDVI DN ) to NDVI calculated by surface reflectance (NDVI SR ) using MODIS products as reference, and different cluster was treated differently. Result shows that this approach can produce NDVI with highly agreement to NDVI calculated by surface reflectance from physical approaches based on 6S (Second Simulation of the satellite Signal in the Solar Spectrum). Although some variability exists, the cluster specified reference based approach shows considerable potential for NDVI normalization. Therefore, NDVI products in MODIS era from different sources can be combined for time-series analysis, biophysical parameter retrievals, and other downstream analysis

On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates

Science.gov (United States)

Singh, Ramesh K.; Senay, Gabriel B.; Velpuri, Naga Manohar; Bohms, Stefanie; Verdin, James P.

2014-01-01

 Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.

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.

Exploring the differences in cloud properties observed by the Terra and Aqua MODIS Sensors

Directory of Open Access Journals (Sweden)

N. Meskhidze

2009-05-01

Full Text Available The aerosol-cloud interaction in different parts of the globe is examined here using multi-year statistics of remotely sensed data from two MODIS sensors aboard NASA's Terra (morning and Aqua (afternoon satellites. Simultaneous retrievals of aerosol loadings and cloud properties by the MODIS sensor allowed us to explore morning-to-afternoon variation of liquid cloud fraction (CF and optical thickness (COT for clean, moderately polluted and heavily polluted clouds in different seasons. Data analysis for seven-years of MODIS retrievals revealed strong temporal and spatial patterns in morning-to-afternoon variation of cloud fraction and optical thickness over different parts of the global oceans and the land. For the vast areas of stratocumulus cloud regions, the data shows that the days with elevated aerosol abundance were also associated with enhanced afternoon reduction of CF and COT pointing to the possible reduction of the indirect climate forcing. A positive correlation between aerosol optical depth and morning-to-afternoon variation of trade wind cumulus cloud cover was also found over the northern Indian Ocean, though no clear relationship between the concentration of Indo-Asian haze and morning-to-afternoon variation of COT was established. Over the Amazon region during wet conditions, aerosols are associated with an enhanced convective process in which morning shallow warm clouds are organized into afternoon deep convection with greater ice cloud coverage. Analysis presented here demonstrates that the new technique for exploring morning-to-afternoon variability in cloud properties by using the differences in data products from the two daily MODIS overpasses is capable of capturing some of the major features of diurnal variations in cloud properties and can be used for better understanding of aerosol radiative effects.

An improvement of satellite-based algorithm for gross primary production estimation optimized over Korea

Science.gov (United States)

Pi, Kyoung-Jin; Han, Kyung-Soo; Kim, In-Hwan; Kim, Sang-Il; Lee, Min-Ji

2011-11-01

Monitoring the global gross primary production (GPP) is relevant to understanding the global carbon cycle and evaluating the effects of interannual climate variation on food and fiber production. GPP, the flux of carbon into ecosystems via photosynthetic assimilation, is an important variable in the global carbon cycle and a key process in land surface-atmosphere interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) is one of the primary global monitoring sensors. MODIS GPP has some of the problems that have been proven in several studies. Therefore this study was to solve the regional mismatch that occurs when using the MODIS GPP global product over Korea. To solve this problem, we estimated each of the GPP component variables separately to improve the GPP estimates. We compared our GPP estimates with validation GPP data to assess their accuracy. For all sites, the correlation was close with high significance (R2 = 0.8164, RMSE = 0.6126 g.C.m-2.d-1, bias = -0.0271 g.C.m-2.d-1). We also compared our results to those of other models. The component variables tended to be either over- or under-estimated when compared to those in other studies over the Korean peninsula, although the estimated GPP was better. The results of this study will likely improve carbon cycle modeling by capturing finer patterns with an integrated method of remote sensing. Keywords: VEGETATION, Gross Primary Production, MODIS.

THE EFFECT OF LAND USE CHANGE ON LAND SURFACE TEMPERATURE IN THE NETHERLANDS

Directory of Open Access Journals (Sweden)

S. Youneszadeh

2015-12-01

Full Text Available The Netherlands is a small country with a relatively large population which experienced a rapid rate of land use changes from 2000 to 2008 years due to the industrialization and population increase. Land use change is especially related to the urban expansion and open agriculture reduction due to the enhanced economic growth. This research reports an investigation into the application of remote sensing and geographical information system (GIS in combination with statistical methods to provide a quantitative information on the effect of land use change on the land surface temperature. In this study, remote sensing techniques were used to retrieve the land surface temperature (LST by using the MODIS Terra (MOD11A2 Satellite imagery product. As land use change alters the thermal environment, the land surface temperature (LST could be a proper change indicator to show the thermal changes in relation with land use changes. The Geographical information system was further applied to extract the mean yearly land surface temperature (LST for each land use type and each province in the 2003, 2006 and 2008 years, by using the zonal statistic techniques. The results show that, the inland water and offshore area has the highest night land surface temperature (LST. Furthermore, the Zued (South-Holland province has the highest night LST value in the 2003, 2006 and 2008 years. The result of this research will be helpful tool for urban planners and environmental scientists by providing the critical information about the land surface temperature.

Linking field observations, Landsat and MODIS data to estimate agricultural change in European Russia.

Science.gov (United States)

de Beurs, K. M.; Ioffe, G.

2011-12-01

Agricultural reform has been one of the most important anthropogenic change processes in European Russia that has been unfolding since the formal collapse of the Soviet Union at the end of 1991. Widespread land abandonment is perhaps the most vivid side effect of the reform, even visible in synoptic imagery. Currently, Russia is transitioning into a country with an internal "archipelago" of islands of productive agriculture around cities embedded in a matrix of unproductive, abandoned lands. This heterogeneous spatial pattern is mainly driven by depopulation of the least favorable parts of the countryside, where "least favorable" is a function of fertility, remoteness, and their interaction. In this work we provide a satellite, GIS and field based overview of the current agricultural developments in Russia and look beyond the unstable period immediately following the collapse of the Soviet Union. We apply Landsat images in one of Russia's oblasts to create a detailed land cover map. We then use a logistic model to link the Landsat land cover map with the inter-annual variability in key phenological parameters calculated from MODIS to derive the percent of cropland per 500m MODIS pixel. By evaluating the phenological characteristics of the MODIS curves for each year we determine whether a pixel was actually cropped or left fallow. A comparison of satellite-estimated cropped areas with regional statistics (by rayon) revealed that the satellite estimates are highly correlated with the regional statistics for both arable lands and successfully cropped areas. We use the crop maps to determine the number of times a particular area was cropped between 2002 and 2009 by summing all the years with crops per pixel. This variable provides a good indication about the intensification and de-intensification of the Russian croplands over the last decade. We have visited several rural areas in Russia and we link the satellite data with information acquired through field interviews

A Method for Improving Hotspot Directional Signatures in BRDF Models Used for MODIS

Science.gov (United States)

Jiao, Ziti; Schaaf, Crystal B.; Dong, Yadong; Roman, Miguel; Hill, Michael J.; Chen, Jing M.; Wang, Zhuosen; Zhang, Hu; Saenz, Edward; Poudyal, Rajesh;

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

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

Successful maintenance on sulphonylurea therapy and low diabetes complication rates in a HNF1A-MODY cohort.

Science.gov (United States)

Bacon, S; Kyithar, M P; Rizvi, S R; Donnelly, E; McCarthy, A; Burke, M; Colclough, K; Ellard, S; Byrne, M M

2016-07-01

HNF1A gene mutations are the most common cause of maturity-onset diabetes of the young (MODY) in the UK. Persons with HNF1A-MODY display sensitivity to sulphonylurea therapy; however, the long-term efficacy is not established. There is limited literature as to the prevalence of micro- and macrovascular complications in this unique cohort. The aim of this study was to determine the natural progression and clinical management of HNF1A-MODY diabetes in a dedicated MODY clinic. Sixty patients with HNF1A-MODY and a cohort of 60 BMI-, age-, ethnicity- and diabetes duration-matched patients with Type 1 diabetes mellitus participated in the study. All patients were phenotyped in detail. Clinical follow-up of the HNF1A-MODY cohort occurred on a bi-annual basis. Following a genetic diagnosis of MODY, the majority of the cohort treated with sulphonylurea therapy remained insulin independent at 84-month follow-up (80%). The HbA1c in the HNF1A-MODY group treated with sulphonylurea therapy alone improved significantly over the study period [from 49 (44-63) mmol/mol, 6.6 (6.2-7.9)% to 41 (31-50) mmol/mol, 5.9 (5-6.7)%; P = 0.003]. The rate of retinopathy was significantly lower than that noted in the Type 1 diabetes mellitus group (13.6 vs. 50%; P = 0.0001).There was also a lower rate of microalbuminuria and cardiovascular disease in the HNF1A-MODY group compared with the Type 1 diabetes mellitus group. This study demonstrates that the majority of patients with HNF1A-MODY can be maintained successfully on sulphonylurea therapy with good glycaemic control. We note a significantly lower rate of micro- and macrovascular complications than reported previously. The use of appropriate therapy at early stages of the disorder may decrease the incidence of complications. © 2015 Diabetes UK.

Improving Estimation of Evapotranspiration under Water-Limited Conditions Based on SEBS and MODIS Data in Arid Regions

Directory of Open Access Journals (Sweden)

Chunlin Huang

2015-12-01

Full Text Available This study proposes a method for improving the estimation of surface turbulent fluxes in surface energy balance system (SEBS model under water stress conditions using MODIS data. The normalized difference water index (NDWI as an indicator of water stress is integrated into SEBS. To investigate the feasibility of the new approach, the desert-oasis region in the middle reaches of the Heihe River Basin (HRB is selected as the study area. The proposed model is calibrated with meteorological and flux data over 2008–2011 at the Yingke station and is verified with data from 16 stations of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER project in 2012. The results show that soil moisture significantly affects evapotranspiration (ET under water stress conditions in the study area. Adding the NDWI in SEBS can significantly improve the estimations of surface turbulent fluxes in water-limited regions, especially for spare vegetation cover area. The daily ET maps generated by the new model also show improvements in drylands with low ET values. This study demonstrates that integrating the NDWI into SEBS as an indicator of water stress is an effective way to improve the assessment of the regional ET in semi-arid and arid regions.

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

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Ichoku, Charles; Kaufman, Yoram; Remer, Lorraine; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Kleidman, Richard; Lau, William K. M. (Technical Monitor)

2001-01-01

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial

Automatic and improved radiometric correction of Landsat imagery using reference values from MODIS surface reflectance images

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Pons, X.; Pesquer, L.; Cristóbal, J.; González-Guerrero, O.

2014-12-01

Radiometric correction is a prerequisite for generating high-quality scientific data, making it possible to discriminate between product artefacts and real changes in Earth processes as well as accurately produce land cover maps and detect changes. This work contributes to the automatic generation of surface reflectance products for Landsat satellite series. Surface reflectances are generated by a new approach developed from a previous simplified radiometric (atmospheric + topographic) correction model. The proposed model keeps the core of the old model (incidence angles and cast-shadows through a digital elevation model [DEM], Earth-Sun distance, etc.) and adds new characteristics to enhance and automatize ground reflectance retrieval. The new model includes the following new features: (1) A fitting model based on reference values from pseudoinvariant areas that have been automatically extracted from existing reflectance products (Terra MODIS MOD09GA) that were selected also automatically by applying quality criteria that include a geostatistical pattern model. This guarantees the consistency of the internal and external series, making it unnecessary to provide extra atmospheric data for the acquisition date and time, dark objects or dense vegetation. (2) A spatial model for atmospheric optical depth that uses detailed DEM and MODTRAN simulations. (3) It is designed so that large time-series of images can be processed automatically to produce consistent Landsat surface reflectance time-series. (4) The approach can handle most images, acquired now or in the past, regardless of the processing system, with the exception of those with extremely high cloud coverage. The new methodology has been successfully applied to a series of near 300 images of the same area including MSS, TM and ETM+ imagery as well as to different formats and processing systems (LPGS and NLAPS from the USGS; CEOS from ESA) for different degrees of cloud coverage (up to 60%) and SLC

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

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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.

Heterozygous ABCC8 mutations are a cause of MODY.

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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.

Near Real-time Operational Use of eMODIS Expedited NDVI for Monitoring Applications and Famine Early Warning

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Rowland, J.; Budde, M. E.

2010-12-01

The Famine Early Warning Systems Network (FEWS NET) has requirements for near real-time monitoring of vegetation conditions for food security applications. Accurate and timely assessments of crop conditions are an important element of food security decision making. FEWS NET scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center are utilizing a new Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset for operational monitoring of crop and pasture conditions in parts of the world where food availability is highly dependent on subsistence agriculture and animal husbandry. The expedited MODIS, or eMODIS, production system processes NDVI data using MODIS surface reflectance provided by the Land Atmosphere Near-real-time Capability for EOS (LANCE). Benefits of this production system include customized compositing schedules, near real-time data availability, and minimized re-sampling. FEWS NET has implemented a 10-day compositing scheme every five days to accommodate the need for timely information on vegetation conditions. The data are currently being processed at 250-meter spatial resolution for Central America, Hispaniola, and Africa. Data are further enhanced by the application of a temporal smoothing filter which helps remove contamination due to clouds and other atmospheric effects. The results of this near real-time monitoring capability have been the timely provision of NDVI and NDVI anomaly maps for each of the FEWS NET monitoring regions and the availability of a consistently processed dataset to aid crop assessment missions and to facilitate customized analyses of crop production, drought, and agro-pastoral conditions.

Identification of circulating microRNAs in HNF1A-MODY carriers.

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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.

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

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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.

Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

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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.

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

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

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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;

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

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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

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).

A snow cover climatology for the Pyrenees from MODIS snow products

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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

LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

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Monitoring the locations and spatial distributions of land-cover changes and patterns is important for establishing links between policy decisions, regulatory actions and resulting landuse activities. The monitoring of change patterns across the landscape can also supply valuable...

Land surface skin temperature climatology: benefitting from the strengths of satellite observations

International Nuclear Information System (INIS)

Jin Menglin; Dickinson, Robert E

2010-01-01

Surface skin temperature observations (T skin ), as obtained by satellite remote sensing, provide useful climatological information of high spatial resolution and global coverage that enhances the traditional ground observations of surface air temperature (T air ) and so, reveal new information about land surface characteristics. This letter analyzes nine years of moderate-resolution imaging spectroradiometer (MODIS) skin temperature observations to present monthly skin temperature diurnal, seasonal, and inter-annual variations at a 0.05 deg. latitude/longitude grid over the global land surface and combines these measurements with other MODIS-based variables in an effort to understand the physical mechanisms responsible for T skin variations. In particular, skin temperature variations are found to be closely related to vegetation cover, clouds, and water vapor, but to differ from 2 m surface T air in terms of both physical meaning and magnitude. Therefore, the two temperatures (T skin and T air ) are complementary in their contribution of valuable information to the study of climate change.

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

MODIS on-orbit thermal emissive bands lifetime performance

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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.

A genetic diagnosis of maturity-onset diabetes of the young (MODY): experiences of patients and family members.

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Bosma, A R; Rigter, T; Weinreich, S S; Cornel, M C; Henneman, L

2015-10-01

Genetic testing for maturity-onset diabetes of the young (MODY) facilitates a correct diagnosis, enabling treatment optimization and allowing monitoring of asymptomatic family members. To date, the majority of people with MODY remain undiagnosed. To identify patients' needs and areas for improving care, this study explores the experiences of patients and family members who have been genetically tested for MODY. Fourteen semi-structured interviews with patients and the parents of patients, and symptomatic and asymptomatic family members were conducted. Atlas.ti was used for thematic analysis. Most people with MODY were initially misdiagnosed with Type 1 or Type 2 diabetes; they had been seeking for the correct diagnosis for a long time. Reasons for having a genetic test included reassurance, removing the uncertainty of developing diabetes (in asymptomatic family members) and informing relatives. Reasons against testing were the fear of genetic discrimination and not having symptoms. Often a positive genetic test result did not come as a surprise. Both patients and family members were satisfied with the decision to get tested because it enabled them to adjust their lifestyle and treatment accordingly. All participants experienced a lack of knowledge of MODY among healthcare professionals, in their social environment and in patient organizations. Additionally, problems with the reimbursement of medical expenses were reported. Patients and family members are generally positive about genetic testing for MODY. More education of healthcare professionals and attention on the part of diabetes organizations is needed to increase awareness and optimize care and support for people with MODY. © 2015 The Authors. Diabetic Medicine © 2015 Diabetes UK.

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

Evaluation of Enhanced High Resolution MODIS/AMSR-E SSTs and the Impact on Regional Weather Forecast

Science.gov (United States)

Schiferl, Luke D.; Fuell, Kevin K.; Case, Jonathan L.; Jedlovec, Gary J.

2010-01-01

Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) instruments as well as the Operational Sea Surface Temperature and Sea Ice Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs

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

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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.

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.

Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods

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Chao Yang

2017-11-01

Full Text Available Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D Terrain model, which was created using an image fusion digital elevation model (DEM, to select training samples (ROIs, and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.

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.

An Improved Rotation Forest for Multi-Feature Remote-Sensing Imagery Classification

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Yingchang Xiu

2017-11-01

Full Text Available Multi-feature, especially multi-temporal, remote-sensing data have the potential to improve land cover classification accuracy. However, sometimes it is difficult to utilize all the features efficiently. To enhance classification performance based on multi-feature imagery, an improved rotation forest, combining Principal Component Analysis (PCA and a boosting naïve Bayesian tree (NBTree, is proposed. First, feature extraction was carried out with PCA. The feature set was randomly split into several disjoint subsets; then, PCA was applied to each subset, and new training data for linear extracted features based on original training data were obtained. These steps were repeated several times. Second, based on the new training data, a boosting naïve Bayesian tree was constructed as the base classifier, which aims to achieve lower prediction error than a decision tree in the original rotation forest. At the classification phase, the improved rotation forest has two-layer voting. It first obtains several predictions through weighted voting in a boosting naïve Bayesian tree; then, the first-layer vote predicts by majority to obtain the final result. To examine the classification performance, the improved rotation forest was applied to multi-feature remote-sensing images, including MODIS Enhanced Vegetation Index (EVI imagery time series, MODIS Surface Reflectance products and ancillary data in Shandong Province for 2013. The EVI imagery time series was preprocessed using harmonic analysis of time series (HANTS to reduce the noise effects. The overall accuracy of the final classification result was 89.17%, and the Kappa coefficient was 0.71, which outperforms the original rotation forest and other classifier ensemble results, as well as the NASA land cover product. However, this new algorithm requires more computational time, meaning the efficiency needs to be further improved. Generally, the improved rotation forest has a potential advantage in

Sensitivity analysis of the Commonly Used Drought Indices on the different land use Types - Case Study over Turkey

Science.gov (United States)

Ersoy, E. N.; Hüsami Afşar, M.; Bulut, B.; Onen, A.; Yilmaz, M. T.

2017-12-01

Droughts are climatic phenomenon that may impact large and small regions alike for long or short time periods and influence society in terms of industrial, agricultural, domestic and many more aspects. The characteristics of the droughts are commonly investigated using indices like Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI). On the other hand, these indices may not necessarily yield similar performance over different vegetation types. The aim is to analyze the sensitivity of drought indices (SPI, SPEI, PDSI) to vegetation types over different climatic regions in Turkey. Here the magnitude of the drought severity is measured using MODIS NDVI data, while the vegetation type (e.g., non-irrigated arable lands, vineyards, fruit trees and berry plantations, olive groves, pastures, land principally occupied by agriculture) information is obtained using CORINE land cover classification. This study has compared the drought characteristics and vegetation conditions on different land use types using remotely sensed datasets (e.g., CORINE land use data, MODIS NDVI), and commonly used drought indices between 2000 and 2016 using gauge based precipitation and temperature measurements.

High-sensitivity CRP discriminates HNF1A-MODY from other subtypes of diabetes.

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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.

Spatio-temporal Characteristics of Land Use Land Cover Change Driven by Large Scale Land Transactions in Cambodia

Science.gov (United States)

Ghosh, A.; Smith, J. C.; Hijmans, R. J.

2017-12-01

Since mid-1990s, the Cambodian government granted nearly 300 `Economic Land Concessions' (ELCs), occupying approximately 2.3 million ha to foreign and domestic organizations (primarily agribusinesses). The majority of Cambodian ELC deals have been issued in areas of both relatively low population density and low agricultural productivity, dominated by smallholder production. These regions often contain highly biodiverse areas, thereby increasing the ecological cost associated with land clearing for extractive purposes. These large-scale land transactions have also resulted in substantial and rapid changes in land-use patterns and agriculture practices by smallholder farmers. In this study, we investigated the spatio-temporal characteristics of land use change associated with large-scale land transactions across Cambodia using multi-temporal multi-reolution remote sensing data. We identified major regions of deforestation during the last two decades using Landsat archive, global forest change data (2000-2014) and georeferenced database of ELC deals. We then mapped the deforestation and land clearing within ELC boundaries as well as areas bordering or near ELCs to quantify the impact of ELCs on local communities. Using time-series from MODIS Vegetation Indices products for the study period, we also estimated the time period over which any particular ELC deal initiated its proposed activity. We found evidence of similar patterns of land use change outside the boundaries of ELC deals which may be associated with i) illegal land encroachments by ELCs and/or ii) new agricultural practices adopted by local farmers near ELC boundaries. We also detected significant time gaps between ELC deal granting dates and initiation of land clearing for ELC purposes. Interestingly, we also found that not all designated areas for ELCs were put into effect indicating the possible proliferation of speculative land deals. This study demonstrates the potential of remote sensing techniques

Evaluating the impact of improvements to the FLAMBE smoke source model on forecasts of aerosol distribution from NAAPS

Science.gov (United States)

Hyer, E. J.; Reid, J. S.

2006-12-01

As more forecast models aim to include aerosol and chemical species, there is a need for source functions for biomass burning emissions that are accurate, robust, and operable in real-time. NAAPS is a global aerosol forecast model running every six hours and forecasting distributions of biomass burning, industrial sulfate, dust, and sea salt aerosols. This model is run operationally by the U.S. Navy as an aid to planning. The smoke emissions used as input to the model are calculated from the data collected by the FLAMBE system, driven by near-real-time active fire data from GOES WF_ABBA and MODIS Rapid Response. The smoke source function uses land cover data to predict properties of detected fires based on literature data from experimental burns. This scheme is very sensitive to the choice of land cover data sets. In areas of rapid land cover change, the use of static land cover data can produce artifactual changes in emissions unrelated to real changes in fire patterns. In South America, this change may be as large as 40% over five years. We demonstrate the impact of a modified land cover scheme on FLAMBE emissions and NAAPS forecasts, including a fire size algorithm developed using MODIS burned area data. We also describe the effects of corrections to emissions estimates for cloud and satellite coverage. We outline areas where existing data sources are incomplete and improvements are required to achieve accurate modeling of biomass burning emissions in real time.

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.

Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

Science.gov (United States)

Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

2006-01-01

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

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.

Genetically Targeted Dipeptidyl Peptidase-4 Inhibitor Use in a Patient with a Novel Mutation of MODY type 4

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Christian Mangrum

2015-01-01

Full Text Available Maturity onset diabetes of the young (MODY is a rare form of diabetes mellitus typically seen in young adults that results from pancreatic beta-cell dysfunction. MODY4 is a rare subtype caused by a PDX1 mutation. In this case, we present a nonobese 26-year-old male with polyuria and polydipsia. Lab work showed a blood glucose of 511 mg/dL, no ketones or antibodies (insulin, islet cell, and glutamic acid decarboxylase [GAD], C-peptide of 1.6 ng/mL, and A1c 9.3%. Genetic analysis revealed a novel nonsense mutation in the PDX1 gene, consistent with MODY type 4. Given this patient's particular genetic mutation affecting the incretin pathway, sitagliptin was substituted for glyburide, which led to significant improvement in glycemic control. Our case report identifies a unique mutation in a rare form of MODY and outlines management of ensuing diabetes through targeting its inherent genetic mutation.

Land cover mapping of North and Central America—Global Land Cover 2000

Science.gov (United States)

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data.

Science.gov (United States)

Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru

2017-09-15

Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q 10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q 10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessing soil erosion using USLE model and MODIS data in the Guangdong, China

Science.gov (United States)

Gao, Feng; Wang, Yunpeng; Yang, Jingxue

2017-07-01

In this study, soil erosion in the Guangdong, China during 2012 was quantitatively assessed using Universal Soil Loss Equation (USLE). The parameters of the model were calculated using GIS and MODIS data. The spatial distribution of the average annual soil loss on grid basis was mapped. The estimated average annual soil erosion in Guangdong in 2012 is about 2294.47t/ (km2.a). Four high sensitive area of soil erosion in Guangdong in 2012 was found. The key factors of these four high sensitive areas of soil erosion were significantly contributed to the land cover types, rainfall and Economic development and human activities.

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.

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.

[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.

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

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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.

Photosynthetic Efficiency of Northern Forest Ecosystems Using a MODIS-Derived Photochemical Reflectance Index (PRI)

Science.gov (United States)

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

2016-01-01

This study evaluates a direct remote sensing approach from space for the determination of ecosystem photosynthetic light use efficiency (LUE), through measurement of vegetation reflectance changes expressed with the Photochemical Reflectance Index (PRI). The PRI is a normalized difference index based on spectral changes at a physiologically active wavelength (approximately 531 nanometers) as compared to a reference waveband, and is only available from a very few satellites. These include the two Moderate-Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites each of which have a narrow (10-nanometer) ocean band centered at 531 nanometers. We examined several PRI variations computed with candidate reference bands, since MODIS lacks the traditional 570-nanometer reference band. The PRI computed using MODIS land band 1 (620-670 nanometers) gave the best performance for daily LUE estimation. Through rigorous statistical analyses over a large image collection (n equals 420), the success of relating in situ daily tower-derived LUE to MODIS observations for northern forests was strongly influenced by satellite viewing geometry. LUE was calculated from CO2 fluxes (moles per moles of carbon absorbed quanta) measured at instrumented Canadian Carbon Program flux towers in four Canadian forests: a mature fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed deciduous/coniferous forest site in Ontario. All aspects of the viewing geometry had significant effects on the MODIS-PRI, including the view zenith angle (VZA), the view azimuth angle, and the displacement of the view azimuth relative to the solar principal plane, in addition to illumination related variables.Nevertheless, we show that forward scatter sector views (VZA, 16 degrees-45 degrees) provided the strongest relationships to daily LUE, especially those collected in the early afternoon by Aqua (r squared = 0.83, RMSE (root mean square error) equals 0

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

Remote Sensing Time Series to Evaluate Direct Land Use Change of Recent Expanded Sugarcane Crop in Brazil

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Marcio Pupin Mello

2012-04-01

Full Text Available The use of biofuels to mitigate global carbon emissions is highly dependent on direct and indirect land use changes (LUC. The direct LUC (dLUC can be accurately evaluated using remote sensing images. In this work we evaluated the dLUC of about 4 million hectares of sugarcane expanded from 2005 to 2010 in the South-central region of Brazil. This region has a favorable climate for rain-fed sugarcane, a great potential for agriculture expansion without deforestation, and is currently responsible for almost 90% of Brazilian’s sugarcane production. An available thematic map of sugarcane along with MODIS and Landast images, acquired from 2000 to 2009, were used to evaluate the land use prior to the conversion to sugarcane. A systematic sampling procedure was adopted and the land use identification prior to sugarcane, for each sample, was performed using a web tool developed to visualize both the MODIS time series and the multitemporal Landsat images. Considering 2000 as reference year, it was observed that sugarcane expanded: 69.7% on pasture land; 25.0% on annual crops; 0.6% on forest; while 3.4% was sugarcane land under crop rotation. The results clearly show that the dLUC of recent sugarcane expansion has occurred on more than 99% of either pasture or agriculture land.

Maturity-onset diabetes of the young (MODY): how many cases are we missing?

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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.

MODIS Near real-time (NRT) data for fire applications

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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

Quality Assessment of S-NPP VIIRS Land Surface Temperature Product

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Yuling Liu

2015-09-01

Full Text Available The VIIRS Land Surface Temperature (LST Environmental Data Record (EDR has reached validated (V1 stage maturity in December 2014. This study compares VIIRS v1 LST with the ground in situ observations and with heritage LST product from MODIS Aqua and AATSR. Comparisons against U.S. SURFRAD ground observations indicate a similar accuracy among VIIRS, MODIS and AATSR LST, in which VIIRS LST presents an overall accuracy of −0.41 K and precision of 2.35 K. The result over arid regions in Africa suggests that VIIRS and MODIS underestimate the LST about 1.57 K and 2.97 K, respectively. The cross comparison indicates an overall close LST estimation between VIIRS and MODIS. In addition, a statistical method is used to quantify the VIIRS LST retrieval uncertainty taking into account the uncertainty from the surface type input. Some issues have been found as follows: (1 Cloud contamination, particularly the cloud detection error over a snow/ice surface, shows significant impacts on LST validation; (2 Performance of the VIIRS LST algorithm is strongly dependent on a correct classification of the surface type; (3 The VIIRS LST quality can be degraded when significant brightness temperature difference between the two split window channels is observed; (4 Surface type dependent algorithm exhibits deficiency in correcting the large emissivity variations within a surface type.

Monitoring of suspended sediment variation using Landsat and MODIS in the Saemangeum coastal area of Korea.

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Min, Jee-Eun; Ryu, Joo-Hyung; Lee, Seok; Son, Seunghyun

2012-02-01

Suspended sediment concentration (SS) is an important indicator of marine environmental changes due to natural causes such as tides, tidal currents, and river discharges, as well as human activities such as construction in coastal regions. In the Saemangeum area on the west coast of Korea, construction of a huge tidal dyke for land reclamation has strongly influenced the coastal environment. This study used remotely sensed data to analyze the SS changes in coastal waters caused by the dyke construction. Landsat and MODIS satellite images were used for the spatial analysis of finer patterns and for the detailed temporal analysis, respectively. Forty Landsat scenes and 105 monthly composite MODIS images observed during 1985-2010 were employed, and four field campaigns (from 2005 to 2006) were performed to verify the image-derived SS. The results of the satellite data analyses showed that the seawater was clear before the dyke construction, with SS values lower than 20 g/m(3). These values increased continuously as the dyke construction progressed. The maximum SS values appeared just before completion of the fourth dyke. Values decreased to below 5 g/m(3) after dyke construction. These changes indicated tidal current modification. Some eddies and plumes were observed in the images generated from Landsat data. Landsat and MODIS can reveal that coastal water turbidity was greatly reduced after completion of the construction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

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Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model

Usability Study to Assess the IGBP Land Cover Classification for Singapore

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Nanki Sidhu

2017-10-01

Full Text Available Our research focuses on assessing the usability of the International Geosphere Biosphere Programme (IGBP classification scheme provided in the MODIS MCD12Q1-1 dataset for assessing the land cover of the city-state, Singapore. We conducted a user study with responses from 33 users by providing them with Google Earth images from different parts of Singapore, asking survey-takers to classify these images according to their understanding by the IGBP definitions provided. We also conducted interviews with experts from major governmental agencies working with satellite imagery, which highlighted the need for a detailed land classification for Singapore. In addition to the qualitative analysis of the IGBP land classification scheme, we carried out a validation of the MCD12Q1-1 remote sensing product against SPOT-5 imagery for our study area. The user study revealed that survey-takers were able to correctly classify urban areas, as well as densely forested areas. Misclassifications between Cropland and Mixed Forest classes were highest and were attributed by users to the broad terminology of the IGBP of the two land cover class definitions. For the accuracy assessment, we obtained validation points using weighted and unweighted stratified sampling. The overall classification accuracy for all 17 IGBP land classes is 62%. Upon selecting only the four most occurring IGBP land classes in Singapore, the classification accuracy improved to 71%. Validation of the MCD12Q1-1 against ground truth for Singapore revealed less-common land classes that may be of importance in a global context but are sources of error when the same product is applied at a smaller scale. Combining the user study with the accuracy assessment gives a comprehensive overview of the challenges associated with using global-level land cover data to derive localized land cover information specifically for smaller land masses like Singapore.

An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data

CSIR Research Space (South Africa)

Kleynhans, W

2011-07-01

Full Text Available Human settlement expansion is one of the most pervasive forms of land cover change in the Gauteng province of South Africa. A method for detecting new settlement developments in areas that are typically covered by natural vegetation using 500m MODIS...

Validação do balanço de radiação obtido a partir de dados MODIS/TERRA na Amazônia com medidas de superfície do LBA Validation of net radiation obtained from MODIS/TERRA data in Amazonia with LBA surface measurements

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Gabriel de Oliveira

2013-09-01

Full Text Available Este estudo tem como objetivo estimar os componentes do balanço de radiação em duas regiões do estado de Rondônia (sudoeste da Amazônia brasileira, a partir de dados do Moderate Resolution Imaging Spectroradiometer (MODIS/TERRA por intermédio do modelo Surface Energy Balance Algorithms for Land (SEBAL, e validar os resultados com informações adquiridas por torres micrometeorológicas do projeto LBA sob as condições de pastagem (Fazenda Nossa Senhora Aparecida e floresta (Reserva Biológica do Jaru. A implementação do modelo SEBAL foi realizada diretamente sobre os dados MODIS e incluiu etapas envolvendo o cômputo de índices de vegetação, albedo e transmitância atmosférica. A comparação das estimativas geradas a partir de dados MODIS com as observações resultou em erros relativos para a condição de pastagem variando entre 0,2 e 19,2%, e para a condição de floresta variando entre 0,8 e 15,6%. A integração de dados em diferentes escalas constituiu uma proposição útil para a estimativa e espacialização dos fluxos de radiação na região amazônica, o que pode contribuir para a melhor compreensão da interação entre a floresta tropical e a atmosfera e gerar informações de entrada necessárias aos modelos de superfície acoplados aos modelos de circulação geral da atmosfera.This study aims to estimate the components of net radiation in two regions located in the state of Rondônia (southwest of the Brazilian Amazon, using Moderate Resolution Imaging Spectroradiometer (MODIS/TERRA data based on Surface Energy Balance Algorithms for Land (SEBAL model, and to validate the results with information acquired by the micrometeorological towers of LBA under the conditions of pasture (Fazenda Nossa Senhora Aparecida and forest (Reserva Biológica do Jaru. Implementation of SEBAL model was performed directly on the MODIS data and included steps involving the computation of vegetation indices, albedo and atmospheric

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

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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

Aspectos más recientes en relación con la diabetes mellitus tipo MODY Most recent aspects about type MODY diabetes mellitus

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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

Influence of land urbanization on carbon sequestration of urban vegetation: A temporal cooperativity analysis in Guangzhou as an example.

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