Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

Science.gov (United States)

Spruce, Joseph P.; Hargrove, William; Gasser, Gerald; Smoot, James; Kuper, Philip D.

2012-01-01

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product

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

Application of New MODIS-Based Aerosol Index for Air Pollution Severity Assessment and Mapping in Upper Northern Thailand

Directory of Open Access Journals (Sweden)

Chat Phayungwiwatthanakoon

2014-06-01

Full Text Available This paper reports capability of a newly-proposed index called the aerosol prediction index (API in the determination and mapping of near-ground PM10 concentrations (at spatial resolution of 500 x 500 m during the 2009 and 2010 burning seasons in upper northern Thailand. API is a normalized index defined based on the difference in the observed reflectance data at two spectral bands of the MODIS instrument aboard NASA�s Terra satellite; Band 3 (blue and Band 7 (mid-infrared. Initial analysis suggested that API had strong correlation with the corresponding MODIS-AOD and AERONET-AOD with coefficient of determination (R2 about 0.62 in both cases, and also with the reference PM10 data with R2 of 0.66. In terms of predictive performance, it exhibited low bias at low PM10 condition and achieved impressive prediction accuracy with relative error of 10.78 %. The near-ground PM10 concentration map yielded from the proposed index was proved very useful in the comprehensive assessment of aerosol pollution situation over entire area at fine spatial detail. This task could not be fulfilled from sole use of the ground-based measured data or standard MODIS-AOD product. These findings indicate that API should be a promising tool for the regular monitoring of air pollution severity over the concerned area.

Monitoring 2009 Forest Disturbance Across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

Science.gov (United States)

Spruce, J.; Hargrove, W. W.; Gasser, G.; Smoot, J. C.; Kuper, P.

2009-01-01

This case study shows the promise of computing current season forest disturbance detection products at regional to CONUS scales. Use of the eMODIS expedited product enabled a NRT CONUS forest disturbance detection product, a requirement for an eventual, operational forest threat EWS. The 2009 classification product from this study can be used to quantify the areal extent of forest disturbance across CONUS, although a quantitative accuracy assessment still needs to be completed. However, the results would not include disturbances that occurred after July 27, such as the Station Fire. While not shown here, the project also produced maximum NDVI products for the June 10-July 27 period of each year of the 2000-2009 time frame. These products could be applied to compute forest change products on an annual basis. GIS could then be used to assess disturbance persistence. Such follow-on work could lead to attribution of year in which a disturbance occurred. These products (e.g., Figures 6 and 7) may also be useful for assessing forest change associated with climate change, such as carbon losses from bark beetle-induced forest mortality in the Western United States. Other MODIS phenological products are being assessed for aiding forest monitoring needs of the EWS, including cumulative NDVI products (Figure 10).

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...

Assessing the Impact of Climate Variability on Cropland Productivity in the Canadian Prairies Using Time Series MODIS FAPAR

Directory of Open Access Journals (Sweden)

Taifeng Dong

2016-03-01

Full Text Available Cropland productivity is impacted by climate. Knowledge on spatial-temporal patterns of the impacts at the regional scale is extremely important for improving crop management under limiting climatic factors. The aim of this study was to investigate the effects of climate variability on cropland productivity in the Canadian Prairies between 2000 and 2013 based on time series of MODIS (Moderate Resolution Imaging Spectroradiometer FAPAR (Fraction of Absorbed Photosynthetically Active Radiation product. Key phenological metrics, including the start (SOS and end of growing season (EOS, and the cumulative FAPAR (CFAPAR during the growing season (between SOS and EOS, were extracted and calculated from the FAPAR time series with the Parametric Double Hyperbolic Tangent (PDHT method. The Mann-Kendall test was employed to assess the trends of cropland productivity and climatic variables, and partial correlation analysis was conducted to explore the potential links between climate variability and cropland productivity. An assessment using crop yield statistical data showed that CFAPAR can be taken as a surrogate of cropland productivity in the Canadian Prairies. Cropland productivity showed an increasing trend in most areas of Canadian Prairies, in general, during the period from 2000 to 2013. Interannual variability in cropland productivity on the Canadian Prairies was influenced positively by rainfall variation and negatively by mean air temperature.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Assessing the Impact of Climate Variability on Cropland Productivity in the Canadian Prairies Using Time Series MODIS FAPAR

OpenAIRE

Taifeng Dong; Jiangui Liu; Jiali Shang; Budong Qian; Ted Huffman; Yinsuo Zhang; Catherine Champagne; Bahram Daneshfar

2016-01-01

Cropland productivity is impacted by climate. Knowledge on spatial-temporal patterns of the impacts at the regional scale is extremely important for improving crop management under limiting climatic factors. The aim of this study was to investigate the effects of climate variability on cropland productivity in the Canadian Prairies between 2000 and 2013 based on time series of MODIS (Moderate Resolution Imaging Spectroradiometer) FAPAR (Fraction of Absorbed Photosynthetically Active Radiation...

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

Science.gov (United States)

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

2014-01-01

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

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.

Fuel type characterization based on coarse resolution MODIS satellite data

Directory of Open Access Journals (Sweden)

Lanorte A

2007-01-01

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

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

An ontological system based on MODIS images to assess ecosystem functioning of Natura 2000 habitats: A case study for Quercus pyrenaica forests

Science.gov (United States)

Pérez-Luque, A. J.; Pérez-Pérez, R.; Bonet-García, F. J.; Magaña, P. J.

2015-05-01

The implementation of the Natura 2000 network requires methods to assess the conservation status of habitats. This paper shows a methodological approach that combines the use of (satellite) Earth observation with ontologies to monitor Natura 2000 habitats and assess their functioning. We have created an ontological system called Savia that can describe both the ecosystem functioning and the behaviour of abiotic factors in a Natura 2000 habitat. This system is able to automatically download images from MODIS products, create indicators and compute temporal trends for them. We have developed an ontology that takes into account the different concepts and relations about indicators and temporal trends, and the spatio-temporal components of the datasets. All the information generated from datasets and MODIS images, is stored into a knowledge base according to the ontology. Users can formulate complex questions using a SPARQL end-point. This system has been tested and validated in a case study that uses Quercus pyrenaica Willd. forests as a target habitat in Sierra Nevada (Spain), a Natura 2000 site. We assess ecosystem functioning using NDVI. The selected abiotic factor is snow cover. Savia provides useful data regarding these two variables and reflects relationships between them.

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2014-12-01

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

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

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

NARCIS (Netherlands)

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

2016-01-01

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

A snow cover climatology for the Pyrenees from MODIS snow products

Science.gov (United States)

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

2015-05-01

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

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.

Evaluation of eco-physiological indicators in Northeast Asia dryland regions based on MODIS products and ecological models

Science.gov (United States)

Kang, W.

2017-12-01

Ecosystem carbon-energy-water circles have significant effect on function and structure and vice verse. Based on these circles mechanism, some eco-physiological indicators, like Transpiration (T), gross primary productivity (GPP), light use efficiency (LUE) and water use efficiency (WUE), are commonly applied to assess terrestrial ecosystem function and structure dynamics. The ecosystem weakened function and simple structure in Northeast dryland regions resulted from land degradation or desertification, which could be demonstrated by above-mentioned indicators. In this study, based on MODIS atmosphere (MYD07, MYD04, MYD06 data) and land products (MYD13A2 NDVI, MYD11A1 LST, MYD15A2 LAI and land cover data), we first retrieved transpiration and LUE via Penman-Monteith Model and modified Vegetation Photosynthesis Model (VPM), respectively; and then evaluated dynamics of these eco-physiological indicators (Tair, VPD, T, LUE, GPP and WUE) and some hotspots were found for next land degradation assessment. The results showed: (1) LUE and WUE are lower in barren or sparsely vegetated area and grasslands than in forest and croplands. (2) Whereas, all indicators presented higher variability in grassland area, particularly in east Mongolia. (3) GPP and transpiration have larger variability than other indicators due to fraction of absorbed Photosynthetically active radiation (FPAR). These eco-physiological indicators are expected to continue to change under future climate change and to help to assess land degradation from ecosystem energy-water-carbon perspectives.

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.

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

Directory of Open Access Journals (Sweden)

Guangming Shi

2017-11-01

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

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

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.

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

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.

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

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

NASA's MODIS/VIIRS Land Surface Temperature and Emissivity Products: Asssessment of Accuracy, Continuity and Science Uses

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

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

2014-05-01

Satellite remote sensing may provide land surface processes observations at high temporal frequency over long periods of time. However, many influences have a bearing on the spectral properties which may be derived from multi-spectral data. The MODIS (Moderate Resolution Imaging Spectroradiometer) Land Science Team provides quality assessment (QA) data. QA is key information for the correct interpretation of remote sensing products since we need to discrimite between real changes on the Earth surface and satellite product artefacts (Roy et al., 2002). The present work focuses on evaluating the quality of the MOD09A1 (Surface Reflectance 8-Day L3 Global 500m) product over the Iberian Peninsula during the period 2000-2008. The quality was estimated in terms of identifying the most important noise sources that might distort the data as well as identifying the areas and seasons where they were dominant. The specific objectives were: (i) to select the most relevant QA parameters based on their frequency over the study area, (ii) to analyze the spatial distribution of the QA parameters and stratify the territory based on this information, and (iii) to analyze the temporal distribution of the QA parameters. The quality data founded within the MOD09A1 product provides information: (i) at the pixel level, (ii) per reflectance band and (iii) for the whole file. In particular, QA is stored in two different layers or bands, one related to each band and based on sensor characteristics and image acquisition (named 'Surface Reflectance Data' QA layer), and the other one related to each pixel and based on external conditions (named 'Surface Reflectance Data State' QA layer). The present work focuses only on this second one. The QA parameters were analyzed in terms of the number of dates where we found low quality pixels, and of the presence of long gaps (four or more consecutive low quality dates). The next step consisted of using the number of low quality dates and the 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.

MODIS/Terra Gross Primary Productivity 8-Day L4 Global 1km SIN Grid V055

Data.gov (United States)

National Aeronautics and Space Administration — The Terra/MODIS Gross Primary Productivity (GPP) product (MOD17A2) is a cumulative composite of GPP values based on the radiation-use efficiency concept that is...

MODIS Snow and Sea Ice Products

Science.gov (United States)

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

2004-01-01

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

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.

Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence

Science.gov (United States)

Gentine, P.; Alemohammad, S. H.

2018-04-01

Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.

Primary Productivity, NASA Aqua MODIS, 4.4 km, Global, EXPERIMENTAL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Primary Productivity is calculated from NASA Aqua MODIS Chl a SST data. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for scientific evaluation by professional...

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.

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.

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

Science.gov (United States)

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

2017-12-01

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

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

additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

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

Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe

Science.gov (United States)

Funk, Chris; Budde, Michael E.

2009-01-01

For thirty years, simple crop water balance models have been used by the early warning community to monitor agricultural drought. These models estimate and accumulate actual crop evapotranspiration, evaluating environmental conditions based on crop water requirements. Unlike seasonal rainfall totals, these models take into account the phenology of the crop, emphasizing conditions during the peak grain filling phase of crop growth. In this paper we describe an analogous metric of crop performance based on time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) imagery. A special temporal filter is used to screen for cloud contamination. Regional NDVI time series are then composited for cultivated areas, and adjusted temporally according to the timing of the rainy season. This adjustment standardizes the NDVI response vis-??-vis the expected phenological response of maize. A national time series index is then created by taking the cropped-area weighted average of the regional series. This national time series provides an effective summary of vegetation response in agricultural areas, and allows for the identification of NDVI green-up during grain filling. Onset-adjusted NDVI values following the grain filling period are well correlated with U.S. Department of Agriculture production figures, possess desirable linear characteristics, and perform better than more common indices such as maximum seasonal NDVI or seasonally averaged NDVI. Thus, just as appropriately calibrated crop water balance models can provide more information than seasonal rainfall totals, the appropriate agro-phenological filtering of NDVI can improve the utility and accuracy of space-based agricultural monitoring.

Assessment of MODIS RSB Detector Uniformity Using Deep Convective Clouds

Science.gov (United States)

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

2016-01-01

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

Large-sized seaweed monitoring based on MODIS

Science.gov (United States)

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

2009-10-01

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

Assessment of biases in MODIS surface reflectance due to Lambertian approximation

Energy Technology Data Exchange (ETDEWEB)

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

2010-08-01

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

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 ...

Snow Cover Monitoring Using MODIS Data in Liaoning Province, Northeastern China

Directory of Open Access Journals (Sweden)

Yu Lu

2010-03-01

Full Text Available This paper presents the results of snow cover monitoring studies in Liaoning Province, northeastern China, using MODIS data. Snow cover plays an important role in both the regional water balance and soil moisture properties during the early spring in northeastern China. In addition, heavy snowfalls commonly trigger hazards such as flooding, caused by rapid snow melt, or crop failure, resulting from fluctuations in soil temperature associated with changes in the snow cover. The latter is a function of both regional, or global, climatic changes, as well as fluctuations in the albedo resulting from variations in the Snow Covered Area (SCA. These impacts are crucial to human activities, especially to those living in middle-latitude areas such as Liaoning Province. Thus, SCA monitoring is currently an important tool in studies of global climate change, particularly because satellite remote sensing data provide timely and efficient snow cover information for large areas. In this study, MODIS L1B data, MODIS Daily Snow Products (MOD10A1 and MODIS 8-day Snow Products (MOD10A2 were used to monitor the SCA of Liaoning Province over the winter months of November–April, 2006–2008. The effects of cloud masking and forest masking on the snow monitoring results were also assessed. The results show that the SCA percentage derived from MODIS L1B data is relatively consistent, but slightly higher than that obtained from MODIS Snow Products. In situ data from 25 snow stations were used to assess the accuracy of snow cover monitoring from the SCA compared to the results from MODIS Snow Products. The studies found that the SCA results were more reliable than MODIS Snow Products in the study area.

Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing

Directory of Open Access Journals (Sweden)

Wei Chen

2017-05-01

Full Text Available The newly released MODIS Collection 6 aerosol products have been widely used to evaluate fine particulate matter with a 10 km Dark Target aerosol optic depth (DT AOD product, a new 3 km DT AOD product and an enhanced Deep Blue (DB AOD product. However, the representativeness of MODIS AOD products under different air quality conditions remains unclear. In this study, we obtained all three types of MODIS Terra AOD from 2001 to 2015 and Aqua AOD from 2003 to 2015 for the Beijing region to study the performance of the different AOD products (Collection 6 under different air quality situations. The validation of three MODIS AOD products suggests that DB AOD has the highest accuracy with an expected error (EE envelope (containing at least 67% of the matchups on a scatter plot of 0.05 + 0.15τ, followed by 10 km DT AOD (0.08 + 0.2τ and 3 km DT AOD (0.35 + 0.15τ, specifically for Beijing. Near-surface PM2.5 concentrations during the passage of MODIS from 2013 to 2015 were also obtained to categorize air quality as unpolluted, moderately, and heavily polluted, as well as to analyze the performance of the different AOD products under different air quality conditions. Very few MODIS 3 km DT retrievals appeared on heavily polluted days, making it almost impossible to play an effective role in air quality applications in Beijing. While the DB AOD allowed for considerable retrievals under all air quality conditions, it had a coarse spatial resolution. These results demonstrate that the MODIS 3 km DT AOD product may not be the appropriate proxy to be used in the satellite retrieval of surface PM2.5, especially for those areas with frequent haze-fog events like Beijing.

ASTER cloud coverage reassessment using MODIS cloud mask products

Science.gov (United States)

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

2010-10-01

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

Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

Science.gov (United States)

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

2013-01-01

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

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

OpenAIRE

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

2016-01-01

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

Global NOAA CoastWatch Chlorophyll Frontal Product from MODIS/Aqua (NCEI Accession 0110333)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — MODIS/Aqua chlorophyll frontal products: the NOAA Okeanos operational production system produces near real-time chlorophyll frontal products (magnitude and...

Evaluation of MODIS NPP and GPP products across multiple biomes.

Science.gov (United States)

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

2006-01-01

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

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

Science.gov (United States)

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

2005-04-01

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

Deriving Snow Cover Metrics for Alaska from MODIS

Directory of Open Access Journals (Sweden)

Chuck Lindsay

2015-09-01

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

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...

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.

Validation of MODIS integrated water vapor product against reference GPS data at the Iberian Peninsula

Science.gov (United States)

Vaquero-Martínez, Javier; Antón, Manuel; Ortiz de Galisteo, José Pablo; Cachorro, Victoria E.; Costa, Maria João; Román, Roberto; Bennouna, Yasmine S.

2017-12-01

In this work, the water vapor product from MODIS (MODerate-resolution Imaging Spectroradiometer) instrument, on-board Aqua and Terra satellites, is compared against GPS water vapor data from 21 stations in the Iberian Peninsula as reference. GPS water vapor data is obtained from ground-based receiver stations which measure the delay caused by water vapor in the GPS microwave signals. The study period extends from 2007 until 2012. Regression analysis in every GPS station show that MODIS overestimates low integrated water vapor (IWV) data and tends to underestimate high IWV data. R2 shows a fair agreement, between 0.38 and 0.71. Inter-quartile range (IQR) in every station is around 30-45%. The dependence on several parameters was also analyzed. IWV dependence showed that low IWV are highly overestimated by MODIS, with high IQR (low precision), sharply decreasing as IWV increases. Regarding dependence on solar zenith angle (SZA), performance of MODIS IWV data decreases between 50° and 90°, while night-time MODIS data (infrared) are quite stable. The seasonal cycles of IWV and SZA cause a seasonal dependence on MODIS performance. In summer and winter, MODIS IWV tends to overestimate the reference IWV value, while in spring and autumn the tendency is to underestimate. Low IWV from coastal stations is highly overestimated (∼60%) and quite imprecise (IQR around 60%). On the contrary, high IWV data show very little dependence along seasons. Cloud-fraction (CF) dependence was also studied, showing that clouds display a negligible impact on IWV over/underestimation. However, IQR increases with CF, except in night-time satellite values, which are quite stable.

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

African Journals Online (AJOL)

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

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

The MODIS (Collection V005) BRDF/albedo product: Assessment of spatial representativeness over forested landscapes

Energy Technology Data Exchange (ETDEWEB)

Roman, Miguel O. [NASA Goddard Space Flight Center; Schaaf, Crystal [Boston University; Woodcock, Curtis E. [Boston University; Strahler, Alan [Boston University; Yang, Xiaoyuan [Boston University; Braswell, Rob H. [Complex Systems Research Center, Durham, NH; Curtis, Peter [Ohio State University, The, Columbus; Davis, Kenneth J. [Pennsylvania State University; Dragoni, Danilo [Indiana University; Goulden, Michael L. [University of California, Irvine; Gu, Lianhong [ORNL; Hollinger, David Y [ORNL; Meyers, Tilden P. [NOAA, Oak Ridge, TN; Wilson, Tim B. [NOAA; Munger, J. William [Harvard University; Wofsy, Steve [Harvard University; Privette, Jeffrey L. [NOAA; Richardson, Andrew D. [Harvard University

2009-11-01

A new methodology for establishing the spatial representativeness of tower albedo measurements that are routinely used in validation of satellite retrievals from global land surface albedo and reflectance anisotropy products is presented. This method brings together knowledge of the intrinsic biophysical properties of a measurement site, and the surrounding landscape to produce a number of geostatistical attributes that describe the overall variability, spatial extent, strength of the spatial correlation, and spatial structure of surface albedo patterns at separate seasonal periods throughout the year. Variogram functions extracted from Enhanced Thematic Mapper Plus (ETM+) retrievals of surface albedo using multiple spatial and temporal thresholds were used to assess the degree to which a given point (tower) measurement is able to capture the intrinsic variability of the immediate landscape extending to a satellite pixel. A validation scheme was implemented over a wide range of forested landscapes, looking at both deciduous and coniferous sites, from tropical to boreal ecosystems. The experiment focused on comparisons between tower measurements of surface albedo acquired at local solar noon and matching retrievals from the MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V005) Bidirectional Reflectance Distribution Function (BRDF)/albedo algorithm. Assessments over a select group of field stations with comparable landscape features and daily retrieval scenarios further demonstrate the ability of this technique to identify measurement sites that contain the intrinsic spatial and seasonal features of surface albedo over sufficiently large enough footprints for use in modeling and remote sensing studies. This approach, therefore, improves our understanding of product uncertainty both in terms of the representativeness of the field data and its relationship to the larger satellite pixel.

Primary Productivity, NASA Aqua MODIS and GOES Imager, 0.1 degrees, Global, EXPERIMENTAL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Primary Productivity is calculated from NASA Aqua MODIS Chl a and NOAA GOES Imager SST data. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for scientific...

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.

MODIS 3km Aerosol Product: Algorithm and Global Perspective

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

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

2004-12-01

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

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

Directory of Open Access Journals (Sweden)

Jesslyn F. Brown

2015-12-01

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

MODIS NDVI Change Detection Techniques and Products Used in the Near Real Time ForWarn System for Detecting, Monitoring, and Analyzing Regional Forest Disturbances

Science.gov (United States)

Spruce, Joseph P.; Hargrove, William; Gasser, Jerry; Smoot, James; Kuper, Philip D.

2014-01-01

This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Early Warning System (EWS) for near real time (NRT) recognition and tracking of regionally evident forest disturbances throughout the conterminous US (CONUS). The latter has provided NRT forest change products to the forest health protection community since 2010, using temporally processed MODIS Aqua and Terra NDVI time series data to currently compute and post 6 different forest change products for CONUS every 8 days. Multiple change products are required to improve detectability and to more fully assess the nature of apparent disturbances. Each type of forest change product reports per pixel percent change in NDVI for a given 24 day interval, comparing current versus a given historical baseline NDVI. EMODIS 7 day expedited MODIS MOD13 data are used to obtain current and historical NDVIs, respectively. Historical NDVI data is processed with Time Series Product Tool (TSPT); and 2) the Phenological Parameters Estimation Tool (PPET) software. While each change products employ maximum value compositing (MVC) of NDVI, the design of specific products primarily differs in terms of the historical baseline. The three main change products use either 1, 3, or all previous years of MVC NDVI as a baseline. Another product uses an Adaptive Length Compositing (ALC) version of MVC to derive an alternative current NDVI that is the freshest quality NDVI as opposed to merely the MVC NDVI across a 24 day time frame. The ALC approach can improve detection speed by 8 to 16 days. ForWarn also includes 2 change products that improve detectability of forest disturbances in lieu of climatic fluctuations, especially in the spring and fall. One compares current MVC NDVI to the zonal maximum under the curve NDVI per pheno-region cluster class, considering all previous years in the MODIS record. The other compares current maximum NDVI to the mean of maximum NDVI for all previous MODIS years.

Monitoring NEON terrestrial sites phenology with daily MODIS BRDF/albedo product and landsat data

Science.gov (United States)

The MODerate resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) and albedo products (MCD43) have already been in production for more than a decade. The standard product makes use of a linear “kernel-driven” RossThick-LiSparse Reciprocal (RTLSR) BRDF m...

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.

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.

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

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...

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

Science.gov (United States)

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

2007-01-01

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

Machine learning-based Landsat-MODIS data fusion approach for 8-day 30m evapotranspiration monitoring

Science.gov (United States)

Im, J.; Ke, Y.; Park, S.

2016-12-01

Continuous monitoring of evapotranspiration (ET) is important for understanding of hydrological cycles and energy flux dynamics. At regional and local scales, routine ET estimation is a critical for efficient water management, drought impact assessment and ecosystem health monitoring, etc. Remote sensing has long been recognized to be able to provide ET monitoring over large areas. However, no single satellite could provide temporally continuous ET at relatively high spatial resolution due to the trade-off between the spatial and temporal resolution of current satellite sensors. Landsat-series satellites provide optical and thermal imagery at 30-100m resolution, whereas the 16-day revisit cycle hinders the observation of ET dynamics; MODIS provides sources of ET estimation at daily basis, but the 500-1000m ground sampling distance is too coarse for field level applications. In this study, we present a machine learning and STARFM based method for Landsat/MODIS ET fusion. The approach first downscales MODIS 8-day 1km ET (MOD16A2) to 30m based on eleven Landsat-derived indicators such as NDVI, EVI, NDWI etc on the cloud-free Landsat-available days using Random Forest approach. For the days when Landsat data are not available, downscaled ET is synthesized by MODIS and Landsat data fusion with STARFM and STI-FM approaches. The models are evaluated using in situ flux tower measurements at US-ARM and US-Twt AmeriFlux sites the United States. Results show that the downscaled 30m ET have good agreement with MODIS ET (RMSE=0.42-3.4mm/8days, rRMSE=3.2%-26%) and the downscaled ET have higher accuracy than MODIS ET when compared to in-situ measurements.

Quantitative Evaluation of MODIS Fire Radiative Power Measurement for Global Smoke Emissions Assessment

Science.gov (United States)

Ichoku, Charles; Ellison, Luke

2011-01-01

Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the MODIS sensors aboard the polar orbiting Terra and Aqua satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has steadily gained increasing recognition as an important parameter for facilitating the development of various scientific studies and applications relating to the quantitative characterization of biomass burning and their emissions. To establish the scientific integrity of the FRP as a stable quantity that can be measured consistently across a variety of sensors and platforms, with the potential of being utilized to develop a unified long-term climate data record of fire activity and impacts, it needs to be thoroughly evaluated, calibrated, and validated. Therefore, we are conducting a detailed analysis of the FRP products from MODIS to evaluate the uncertainties associated with them, such as those due to the effects of satellite variable observation geometry and other factors, in order to establish their error budget for use in diverse scientific research and applications. In this presentation, we will show recent results of the MODIS FRP uncertainty analysis and error mitigation solutions, and demonstrate

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

Directory of Open Access Journals (Sweden)

P. Glantz

2012-07-01

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

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

Data.gov (United States)

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

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

Data.gov (United States)

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

Assessment of Global Carbon Dioxide Concentration Using MODIS and GOSAT Data

Directory of Open Access Journals (Sweden)

Hiroshi Tani

2012-11-01

Full Text Available Carbon dioxide (CO2 is the most important greenhouse gas (GHG in the atmosphere and is the greatest contributor to global warming. CO2 concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is difficult to monitor CO2 concentrations on regional or global scales for a long time. The use of the remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR or Moderate Resolution Imaging Spectroradiometer (MODIS data can overcome these problems, particularly in areas with low densities of CO2 concentration watch stations. A model based on temperature (MOD11C3, vegetation cover (MOD13C2 and MOD15A2 and productivity (MOD17A2 of MODIS (which we have named the TVP model was developed in the current study to assess CO2 concentrations on a global scale. We assumed that CO2 concentration from the Thermal And Near infrared Sensor for carbon Observation (TANSO aboard the Greenhouse gases Observing SATellite (GOSAT are the true values and we used these values to check the TVP model accuracy. The results indicate that the accuracy of the TVP model is different in different continents: the greatest Pearson’s correlation coefficient (R2 was 0.75 in Eurasia (RMSE = 1.16 and South America (RMSE = 1.17; the lowest R2 was 0.57 in Australia (RMSE = 0.73. Compared with the TANSO-observed CO2 concentration (XCO2, we found that the accuracy throughout the World is between −2.56~3.14 ppm. Potential sources of TVP model uncertainties were also analyzed and identified.

Assessment of global carbon dioxide concentration using MODIS and GOSAT data.

Science.gov (United States)

Guo, Meng; Wang, Xiufeng; Li, Jing; Yi, Kunpeng; Zhong, Guosheng; Tani, Hiroshi

2012-11-26

Carbon dioxide (CO(2)) is the most important greenhouse gas (GHG) in the atmosphere and is the greatest contributor to global warming. CO(2) concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is difficult to monitor CO(2) concentrations on regional or global scales for a long time. The use of the remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) or Moderate Resolution Imaging Spectroradiometer (MODIS) data can overcome these problems, particularly in areas with low densities of CO(2) concentration watch stations. A model based on temperature (MOD11C3), vegetation cover (MOD13C2 and MOD15A2) and productivity (MOD17A2) of MODIS (which we have named the TVP model) was developed in the current study to assess CO(2) concentrations on a global scale. We assumed that CO(2) concentration from the Thermal And Near infrared Sensor for carbon Observation (TANSO) aboard the Greenhouse gases Observing SATellite (GOSAT) are the true values and we used these values to check the TVP model accuracy. The results indicate that the accuracy of the TVP model is different in different continents: the greatest Pearson's correlation coefficient (R2) was 0.75 in Eurasia (RMSE = 1.16) and South America (RMSE = 1.17); the lowest R2 was 0.57 in Australia (RMSE = 0.73). Compared with the TANSO-observed CO(2) concentration (XCO(2)), we found that the accuracy throughout the World is between -2.56~3.14 ppm. Potential sources of TVP model uncertainties were also analyzed and identified.

Comparing Stream Discharge, Dissolved Organic Carbon, and Selected MODIS Indices in Freshwater Basins

Science.gov (United States)

Shaver, W. T.; Wollheim, W. M.

2009-12-01

In a preliminary study of the Ipswich Basin in Massachusetts, a good correlation was found to exist between the MODIS (Moderate Resolution Imaging Spectroradiometer) Enhanced Vegetation Index and stream dissolved organic carbon (DOC). Further study was warranted to determine the utility of MODIS indices in predicting temporal stream DOC. Stream discharge rates and DOC data were obtained from the USGS National Water Quality Assessment Program (NAWQA) database. Twelve NAWQA monitoring sites were selected for evaluation based on the criteria of having drainage basin sizes less than 600 km2 with relatively continuous, long-term DOC and discharge data. MODIS indices were selected based on their connections with terrestrial DOC and were obtained for each site's catchment area. These included the Normalized Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Daily Photosynthesis (PSN) and the Leaf Area Index (LAI). Regression analysis was used to evaluate the relationships between DOC, discharge and MODIS products. Data analysis revealed several important trends. Sites with strong positive correlation coefficients (r values ranging from 0.462 to 0.831) between DOC and discharge displayed weak correlations with all of the MODIS indices (r values ranging from 0 to 0.322). For sites where the DOC/discharge correlation was weak or negative, MODIS indices were moderately correlated, with r values ranging from 0.35 to 0.647, all of which were significant at less than 1 percent. Some sites that had weak positive correlations with MODIS indices displayed a lag time, that is, the MODIS index rose and fell shortly before the DOC concentration rose and fell. Shifting the MODIS data forward in time by roughly one month significantly increased the DOC/MODIS r values by about 10%. NDVI and EVI displayed the strongest correlations with temporal DOC variability (r values ranging from 0.471 to 0.647), and therefore these indices are the most promising for being incorporated

A method for daily global solar radiation estimation from two instantaneous values using MODIS atmospheric products

International Nuclear Information System (INIS)

Xu, Xiaojun; Du, Huaqiang; Zhou, Guomo; Mao, Fangjie; Li, Pingheng; Fan, Weiliang; Zhu, Dien

2016-01-01

Accurate information on the temporal and spatial distributions of solar radiation is very important in many scientific fields. In this study, instantaneous solar irradiances on a horizontal surface at 10:30 and 13:30 local time (LT) were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric data products with relatively high spatial resolution using a solar radiation model. These solar irradiances were combined to derive half-hourly averages of solar irradiance (HASI) and daily global solar radiation (GSR) on a horizontal surface using linear interpolation, piecewise linear regression, and quadratic polynomial regression. Compared with field observations, the HASI were estimated accurately when the total cloud fraction (TCF) was 0.6. Overall, the daily GSR estimated in this study was better than that estimated by the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis of NASA. The daily GSR estimated in this study was underestimated, whereas it was overestimated by MERRA. The combination of the daily GSR estimates of this study and MERRA offers a simple and feasible technique for reducing uncertainty in daily GSR estimates. - Highlights: • Daily GSR is integrated from two observations from the MODIS products. • Daily GSR from the MODIS products is underestimated. • Biases were attributed primarily to variations in the total cloud percent. • Combining daily GSR estimates from the MODIS and the MERRA increases accuracy.

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).

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.

Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

Science.gov (United States)

Gacal, G. F. B.; Lagrosas, N.

2017-12-01

Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds

MODIS/Aqua Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V005

Data.gov (United States)

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

MODIS/Aqua Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km V005

Data.gov (United States)

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

MODIS/Terra Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km V005

Data.gov (United States)

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

MODIS/Terra Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V005

Data.gov (United States)

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

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.

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

Directory of Open Access Journals (Sweden)

Patrick H. Freeborn

2014-02-01

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

Validation of quasi-invariant ice cloud radiative quantities with MODIS satellite-based cloud property retrievals

International Nuclear Information System (INIS)

Ding, Jiachen; Yang, Ping; Kattawar, George W.; King, Michael D.; Platnick, Steven; Meyer, Kerry G.

2017-01-01

Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If τ(1–ϖ) and τ(1–ϖg) are conserved where τ is optical thickness, ϖ the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection 5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1–ϖg) factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1–ϖ)/(1–ϖg)]"1"/"2, also tend to be similar. - Highlights: • Similarity relations are theoretically analyzed and validated. • Similarity relations are verified with the MODIS Level 2 Collection 5 and 6 ice cloud property products. • The product of ice cloud optical thickness and (1–ϖg) is approximately invariant. • The similarity parameter derived from the MODIS ice cloud effective radius retrieval tends to be invariant.

A Big Data Approach for Situation-Aware estimation, correction and prediction of aerosol effects, based on MODIS Joint Atmosphere product (collection 6) time series data

Science.gov (United States)

Singh, A. K.; Toshniwal, D.

2017-12-01

The MODIS Joint Atmosphere product, MODATML2 and MYDATML2 L2/3 provided by LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center) re-sampled from medium resolution MODIS Terra /Aqua Satellites data at 5km scale, contains Cloud Reflectance, Cloud Top Temperature, Water Vapor, Aerosol Optical Depth/Thickness, Humidity data. These re-sampled data, when used for deriving climatic effects of aerosols (particularly in case of cooling effect) still exposes limitations in presence of uncertainty measures in atmospheric artifacts such as aerosol, cloud, cirrus cloud etc. The effect of uncertainty measures in these artifacts imposes an important challenge for estimation of aerosol effects, adequately affecting precise regional weather modeling and predictions: Forecasting and recommendation applications developed largely depend on these short-term local conditions (e.g. City/Locality based recommendations to citizens/farmers based on local weather models). Our approach inculcates artificial intelligence technique for representing heterogeneous data(satellite data along with air quality data from local weather stations (i.e. in situ data)) to learn, correct and predict aerosol effects in the presence of cloud and other atmospheric artifacts, defusing Spatio-temporal correlations and regressions. The Big Data process pipeline consisting correlation and regression techniques developed on Apache Spark platform can easily scale for large data sets including many tiles (scenes) and over widened time-scale. Keywords: Climatic Effects of Aerosols, Situation-Aware, Big Data, Apache Spark, MODIS Terra /Aqua, Time Series

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

Directory of Open Access Journals (Sweden)

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.

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

DEFF Research Database (Denmark)

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

2012-01-01

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

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

Science.gov (United States)

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

2014-12-01

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

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

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...

Spatio-temporal dynamics of phytoplankton and primary production in Lake Tanganyika using a MODIS based bio-optical time series

DEFF Research Database (Denmark)

Bergamino, N; Horion, Stéphanie; Stenuite, S

2010-01-01

dynamics throughout the lake. In the present work, daily MODIS-AQUA satellite measurements were used to estimate chlorophyll-a concentrations and the diffuse attenuation coefficient (K490) for surface waters. The spatial regionalisation of Lake Tanganyika, based on Empirical Orthogonal Functions...

Assessing woody vegetation trends in Sahelian drylands using MODIS based seasonal metrics

DEFF Research Database (Denmark)

Brandt, Martin Stefan; Hiernaux, Pierre; Rasmussen, Kjeld

2016-01-01

Woody plants play a major role for the resilience of drylands and in peoples' livelihoods. However, due to their scattered distribution, quantifying and monitoring woody cover over space and time is challenging. We develop a phenology driven model and train/validate MODIS (MCD43A4, 500 m) derived...

MODIS/Aqua Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V005

Data.gov (United States)

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

MODIS/Terra Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V005

Data.gov (United States)

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

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.

[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.

MODIS/Aqua Near Real Time (NRT) Thermal Anomalies/Fire 5-Min L2 Swath 1km

Data.gov (United States)

National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

MODIS/Terra Near Real Time (NRT) Thermal Anomalies/Fire 5-Min L2 Swath 1km

Data.gov (United States)

National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

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

Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

Science.gov (United States)

Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

2010-01-01

Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

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.

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.

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

Can MODIS detect trends in aerosol optical depth over land?

Science.gov (United States)

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

2018-02-01

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

Accuracy assessment of the vegetation continuous field tree cover product using 3954 ground plots in the southwestern USA

Science.gov (United States)

M. A. White; J. D. Shaw; R. D. Ramsey

2005-01-01

An accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field (VCF) tree cover product using two independent ground-based tree cover databases was conducted. Ground data included 1176 Forest Inventory and Analysis (FIA) plots for Arizona and 2778 Southwest Regional GAP (SWReGAP) plots for Utah and western Colorado....

A Phenology-Based Classification of Time-Series MODIS Data for Rice Crop Monitoring in Mekong Delta, Vietnam

Directory of Open Access Journals (Sweden)

Nguyen-Thanh Son

2013-12-01

Full Text Available Rice crop monitoring is an important activity for crop management. This study aimed to develop a phenology-based classification approach for the assessment of rice cropping systems in Mekong Delta, Vietnam, using Moderate Resolution Imaging Spectroradiometer (MODIS data. The data were processed from December 2000, to December 2012, using empirical mode decomposition (EMD in three main steps: (1 data pre-processing to construct the smooth MODIS enhanced vegetation index (EVI time-series data; (2 rice crop classification; and (3 accuracy assessment. The comparisons between the classification maps and the ground reference data indicated overall accuracies and Kappa coefficients, respectively, of 81.4% and 0.75 for 2002, 80.6% and 0.74 for 2006 and 85.5% and 0.81 for 2012. The results by comparisons between MODIS-derived rice area and rice area statistics were slightly overestimated, with a relative error in area (REA from 0.9–15.9%. There was, however, a close correlation between the two datasets (R2 ≥ 0.89. From 2001 to 2012, the areas of triple-cropped rice increased approximately 31.6%, while those of the single-cropped rain-fed rice, double-cropped irrigated rice and double-cropped rain-fed rice decreased roughly −5.0%, −19.2% and −7.4%, respectively. This study demonstrates the validity of such an approach for rice-crop monitoring with MODIS data and could be transferable to other regions.

MODIS/Aqua Near Real Time (NRT) Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km

Data.gov (United States)

National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

MODIS/Terra Near Real Time (NRT) Coarse Thermal Anomalies/Fire 5-Min L2 Swath 5km

Data.gov (United States)

National Aeronautics and Space Administration — MODIS Near Real Time (NRT) Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on...

Validation of the MODIS Collection 6 MCD64 Global Burned Area Product

Science.gov (United States)

Boschetti, L.; Roy, D. P.; Giglio, L.; Stehman, S. V.; Humber, M. L.; Sathyachandran, S. K.; Zubkova, M.; Melchiorre, A.; Huang, H.; Huo, L. Z.

2017-12-01

The research, policy and management applications of satellite products place a high priority on rigorously assessing their accuracy. A number of NASA, ESA and EU funded global and continental burned area products have been developed using coarse spatial resolution satellite data, and have the potential to become part of a long-term fire Essential Climate Variable. These products have usually been validated by comparison with reference burned area maps derived by visual interpretation of Landsat or similar spatial resolution data selected on an ad hoc basis. More optimally, a design-based validation method should be adopted, characterized by the selection of reference data via probability sampling. Design based techniques have been used for annual land cover and land cover change product validation, but have not been widely used for burned area products, or for other products that are highly variable in time and space (e.g. snow, floods, other non-permanent phenomena). This has been due to the challenge of designing an appropriate sampling strategy, and to the cost and limited availability of independent reference data. This paper describes the validation procedure adopted for the latest Collection 6 version of the MODIS Global Burned Area product (MCD64, Giglio et al, 2009). We used a tri-dimensional sampling grid that allows for probability sampling of Landsat data in time and in space (Boschetti et al, 2016). To sample the globe in the spatial domain with non-overlapping sampling units, the Thiessen Scene Area (TSA) tessellation of the Landsat WRS path/rows is used. The TSA grid is then combined with the 16-day Landsat acquisition calendar to provide tri-dimensonal elements (voxels). This allows the implementation of a sampling design where not only the location but also the time interval of the reference data is explicitly drawn through stratified random sampling. The novel sampling approach was used for the selection of a reference dataset consisting of 700

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

Science.gov (United States)

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.

Validation of MODIS snow cover images over Austria

Directory of Open Access Journals (Sweden)

J. Parajka

2006-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

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

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

Directory of Open Access Journals (Sweden)

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.

Debris Likelihood, based on GhostNet, NASA Aqua MODIS, and GOES Imager, EXPERIMENTAL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Debris Likelihood Index (Estimated) is calculated from GhostNet, NASA Aqua MODIS Chl a and NOAA GOES Imager SST data. THIS IS AN EXPERIMENTAL PRODUCT: intended...

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

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...

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....

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

Directory of Open Access Journals (Sweden)

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

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Science.gov (United States)

Spruce, Joseph P.; Hargrove, William W.; Gasser, Gerald

2013-01-01

computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

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

Science.gov (United States)

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

2016-01-01

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

Statistical Analysis of SSMIS Sea Ice Concentration Threshold at the Arctic Sea Ice Edge during Summer Based on MODIS and Ship-Based Observational Data.

Science.gov (United States)

Ji, Qing; Li, Fei; Pang, Xiaoping; Luo, Cong

2018-04-05

The threshold of sea ice concentration (SIC) is the basis for accurately calculating sea ice extent based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the sea ice edge used in previous studies and released sea ice products has not always been consistent. To explore the representable value of the PM SIC threshold corresponding on average to the position of the Arctic sea ice edge during summer in recent years, we extracted sea ice edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) sea ice product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and sea ice ship-based observation points (1 km) during the fifth (CHINARE-2012) and sixth (CHINARE-2014) Chinese National Arctic Research Expeditions, and made an overlay and comparison analysis with PM SIC derived from Special Sensor Microwave Imager Sounder (SSMIS, with a spatial resolution of 25 km) in the summer of 2012 and 2014. Results showed that the average SSMIS SIC threshold at the Arctic sea ice edge based on ice-water boundary lines extracted from MOD29 was 33%, which was higher than that of the commonly used 15% discriminant threshold. The average SIC threshold at sea ice edge based on ice-water boundary lines extracted by visual interpretation from four scenes of the MODIS image was 35% when compared to the average value of 36% from the MOD29 extracted ice edge pixels for the same days. The average SIC of 31% at the sea ice edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for sea ice extent calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of sea ice under the rapidly changing Arctic.

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.

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

MODIS on-orbit thermal emissive bands lifetime performance

Science.gov (United States)

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

2016-05-01

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

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

[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.

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

Science.gov (United States)

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

A New Approach to Evaluate MODIS Annual NPP Product (MOD17A3) Using Forest Field Data from Turkey

Energy Technology Data Exchange (ETDEWEB)

Gulbeyaz, Onder; Bond-Lamberty, Benjamin; Akyurek, Zuhal; West, Tristram O.

2018-04-18

In this study we present the first evaluation of the MODIS (MODerate resolution Imaging Spectroradiometer) annual Net Primary Product (NPP) for Turkey's forest ecosystems using field measurements. Due to lack of country scale field measurements (i.e. flux tower for forest ecosystems), tree DBH (Diameter at Breast Height) dataset provided by Ministry of Forest and Water Affair (MFWA) of Turkey is used to calculate NPP of Turkey’s forest ecosystems. The lack of a reliable NPP dataset leads the researchers to use global NPP models such as MODIS annual NPP product. The MODIS MOD17A3 product of vegetation net primary production (NPP) is one of the most highly used data sources for studies of global carbon 25 cycle. However, it is still necessary to test its predictions in multiple biomes, especially for heterogeneous areas in terms of its accuracy and potential bias. Here, we studied a new approach to evaluate coarse scale NPP estimates from the MODIS NPP- MOD17A3 data product, using 2008-2013 field measurements of tree growth throughout Turkey. There different methods were used to calculate field NPP, including standardized growth coefficients (MC), growth coefficients from North America (JC) and annual expected increment (AEI). The average NPP values for all the country is calculated as 2.06 kgC m-2(5years)-1 (0.412 kgC m-2 year-1) (SD = 1.15 kgC m-2 (5years)-1) from MOD17A3, 0.90 kgC m-2(5years)-1 (0.18 kgC m-2 year-1) (SD = 0.57 kgC m-2(5years)-1) with MC, 0.63 kgC m-2(5years)-1 (0.126 kgC m-2 year-1) (SD = 0.37 kgC m-2(5years)-1) with JC and 0.58 kgC m-2 year-1 (SD = 0.29 kgC m-2(5years)-1) with AEI for the studied plots. We found that the MODIS NPP product has a clear relation with both the NPP estimates obtained by using MC (R36 2 = 0.34, RMSE=1.51 kgC m-2(5years)-1) and JC (R37 2 = 0.32, RMSE = 1.73 kgC m-2(5years)-1). In addition to that, the relation between MOD17A3 product and AEI-derived NPP is relatively strong (R39 2 = 0.48, RMSE = 0.26 kgC m-2 year

Development of a High Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance with MODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China

Directory of Open Access Journals (Sweden)

Dongqin You

2015-05-01

Full Text Available A land-cover-based linear BRDF (bi-directional reflectance distribution function unmixing (LLBU algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI reflectance with the moderate resolution imaging spectroradiometer (MODIS daily reflectance product to derive the BRDF/albedo of the two sensors simultaneously in the foci experimental area (FEA of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER, which was carried out in the Heihe River basin, China. For each land cover type, an archetypal BRDF, which characterizes the shape of its anisotropic reflectance, is extracted by linearly unmixing from the MODIS reflectance with the assistance of a high-resolution classification map. The isotropic coefficients accounting for the differences within a class are derived from the CASI reflectance. The BRDF is finally determined by the archetypal BRDF and the corresponding isotropic coefficients. Direct comparisons of the cropland archetypal BRDF and CASI albedo with in situ measurements show good agreement. An indirect validation which compares retrieved BRDF/albedo with that of the MCD43A1 standard product issued by NASA and aggregated CASI albedo also suggests reasonable reliability. LLBU has potential to retrieve the high spatial resolution BRDF/albedo product for airborne and spaceborne sensors which have inadequate angular samplings. In addition, it can shorten the timescale for coarse spatial resolution product like MODIS.

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

Science.gov (United States)

Levitan, Nathaniel; Gross, Barry

2016-10-01

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

Production of Arctic Sea-ice Albedo by fusion of MISR and MODIS data

Science.gov (United States)

Kharbouche, Said; Muller, Jan-Peter

2017-04-01

We have combined data from the NASA MISR and MODIS spectro-radiometers to create a cloud-free albedo dataset specifically for sea-ice. The MISR (Multi-Angular Spectro-Radiometer) instrument on board Terra satellite has a unique ability to create high-quality Bidirectional Reflectance (BRF) over a 7 minute time interval per single overpass, thanks to its 9 cameras of different view angles (±70°,±60°,±45°,±26°). However, as MISR is limited to narrow spectral bands (443nm, 555nm, 670nm, 865nm), which is not sufficient to mask cloud effectively and robustly, we have used the sea-ice mask MOD09 product (Collection 6) from MODIS (Moderate resolution Imaging Spectoradiometer) instrument, which is also on board Terra satellite and acquiring data simultaneously. Only We have created a new and consistent sea-ice (for Arctic) albedo product that is daily, from 1st March to 22nd September for each and every year between 2000 to 2016 at two spatial grids, 1km x 1km and 5km x 5km in polar stereographic projection. Their analysis is described in a separate report [1]. References [1] Muller & Kharbouche, Variation of Arctic's Sea-ice Albedo between 2000 and 2016 by fusion of MISR and MODIS data. This conference. Acknowledgements This work was supported by www.QA4ECV.eu, a project of European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 607405. We thank our colleagues at JPL and NASA LaRC for processing these data, especially Sebastian Val and Steve Protack.

Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

Science.gov (United States)

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

2011-01-01

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

Using MODIS NDVI products for vegetation state monitoring on the oil production territory in Western Siberia

OpenAIRE

Kovalev, Anton; Tokareva, Olga Sergeevna

2016-01-01

Article describes the results of using remote sensing data for vegetation state monitoring on the oil field territories in Western Siberia. We used MODIS data product providing the normalized difference vegetation index (NDVI) values. Average NDVI values of each studied area were calculated for the period from 2010 to 2015 with one year interval for June, July and August. Analysis was carried out via an open tool of geographic information system QGIS used for spatial analysis and calculation ...

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

Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA

Science.gov (United States)

Gu, Yingxin; Wylie, Bruce K.; Bliss, Norman B.

2013-01-01

This study assessed and described a relationship between satellite-derived growing season averaged Normalized Difference Vegetation Index (NDVI) and annual productivity for grasslands within the Greater Platte River Basin (GPRB) of the United States. We compared growing season averaged NDVI (GSN) with Soil Survey Geographic (SSURGO) database rangeland productivity and flux tower Gross Primary Productivity (GPP) for grassland areas. The GSN was calculated for each of nine years (2000–2008) using the 7-day composite 250-m eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. Strong correlations exist between the nine-year mean GSN (MGSN) and SSURGO annual productivity for grasslands (R2 = 0.74 for approximately 8000 pixels randomly selected from eight homogeneous regions within the GPRB; R2 = 0.96 for the 14 cluster-averaged points). Results also reveal a strong correlation between GSN and flux tower growing season averaged GPP (R2 = 0.71). Finally, we developed an empirical equation to estimate grassland productivity based on the MGSN. Spatially explicit estimates of grassland productivity over the GPRB were generated, which improved the regional consistency of SSURGO grassland productivity data and can help scientists and land managers to better understand the actual biophysical and ecological characteristics of grassland systems in the GPRB. This final estimated grassland production map can also be used as an input for biogeochemical, ecological, and climate change models.

Inventory of Agricultural Land Area of Egypt Using Modis Data

International Nuclear Information System (INIS)

Hereher, M.E.

2009-01-01

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

MODIS NDVI Response Following Fires in Siberia

Science.gov (United States)

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

2003-01-01

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

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...

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

Science.gov (United States)

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

2012-12-01

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

OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km V003

Data.gov (United States)

National Aeronautics and Space Administration — The OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km (OMMYDCLD) is a Level-2 orbital product that combines cloud parameters retrieved by the...

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

Directory of Open Access Journals (Sweden)

Meng Bao-Ping

2017-01-01

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

Assessment of the abnormal growth of floating macrophytes in Winam Gulf (Kenya) by using MODIS imagery time series

Science.gov (United States)

Fusilli, L.; Collins, M. O.; Laneve, G.; Palombo, A.; Pignatti, S.; Santini, F.

2013-02-01

The objective of this research study is to assess the capability of time-series of MODIS imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the abnormal growth of the floating macrophytes in order to support monitoring and management action of Lake Victoria water resources. The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the high infestation of water hyacinth with significant socio-economic impact on riparian populations. In this paper, we describe an approach based on the time-series of MODIS to derive the temporal behaviour, the abundance and distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria) and its possible links to the concentrations of the main water constituencies. To this end, we consider the NDVI values computed from the MODIS imagery time-series from 2000 to 2009 to identify the floating macrophytes cover and an appropriate bio-optical model to retrieve, by means of an inverse procedure, the concentrations of chlorophyll a, coloured dissolved organic matter and total suspended solid. The maps of the floating vegetation based on the NDVI values allow us to assess the spatial and temporal dynamics of the weeds with high time resolution. A floating vegetation index (FVI) has been introduced for describing the weeds pollution level. The results of the analysis show a consistent temporal relation between the water constituent concentrations within the Winam Gulf and the FVI, especially in the proximity of the greatest proliferation of floating vegetation in the last 10 years that occurred between the second half of 2006 and the first half of 2007.The adopted approach will be useful to implement an automatic system for monitoring and predicting the floating macrophytes proliferation in Lake Victoria.

A Critical Examination of Spatial Biases Between MODIS and MISR Aerosol Products - Application for Potential AERONET Deployment

Science.gov (United States)

Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; Eck, T. F.; Holben, B. N.; Kahn, R. A.

2011-01-01

AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while side-stepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a km1 file.

Remote Sensing of Ecosystem Light Use Efficiency Using MODIS

Science.gov (United States)

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

2009-12-01

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

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.

Snow and Ice Climatology of the Western United States and Alaska from MODIS

Science.gov (United States)

Rittger, K. E.; Painter, T. H.; Mattmann, C. A.; Seidel, F. C.; Burgess, A.; Brodzik, M.

2013-12-01

The climate and hydroclimate of the Western US and Alaska are tightly coupled to their snow and ice cover. The Western US depends on mountain snowmelt for the majority of its water supply to agriculture, industrial and urban use, hydroelectric generation, and recreation, all driven by increasing population and demand. Alaskan snow and glacier cover modulate regional climate and, as with the Western US, dominate water supply and hydroelectric generation in much of the state. Projections of climate change in the Western US and Alaska suggest that the most pronounced impacts will include reductions of mountain snow and ice cover, earlier runoff, and a greater fraction of rain instead of snow. We establish a snow and ice climatology of the Western US and Alaska using physically based MODIS Snow Covered Area and Grain size model (MODSCAG) for fractional snow cover, the MODIS Dust Radiative Forcing in Snow model (MODDRFS) for radiative forcing by light absorbing impurities in snow, and the MODIS Permanent Ice model (MODICE) for annual minimum exposed snow. MODSCAG and MODDRFS use EOS MOD09GA historical reflectance data (2000-2012) to provide daily and 8-day composites and near real time products since the beginning of 2013, themselves ultimately composited to 8-day products. The compositing method considers sensor-viewing geometry, solar illumination, clouds, cloud shadows, aerosols and noisy detectors in order to select the best pixel for an 8-day period. The MODICE annual minimum exposed snow and ice product uses the daily time series of fractional snow and ice from MODSCAG to generate annual maps. With this project we have established an ongoing, national-scale, consistent and replicable approach to assessing current and projected climate impacts and climate-related risk in the context of other stressors. We analyze the products in the Northwest, Southwest, and Alaska/Arctic regions of the National Climate Assessment for the last decade, the nation's hottest on record

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

Science.gov (United States)

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

2006-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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.

Assessing MODIS GPP in Non-Forested Biomes in Water Limited Areas Using EC Tower Data

Directory of Open Access Journals (Sweden)

Flor Álvarez-Taboada

2015-03-01

Full Text Available Although shrublands, savannas and grasslands account for 37% of the world’s terrestrial area, not many studies have analysed the role of these ecosystems in the global carbon cycle at a regional scale. The MODIS Gross Primary Production (GPP product is used here to help bridge this gap. In this study, the agreement between the MODIS GPP product (GPPm and the GPP Eddy Covariance tower data (GPPec was tested for six different sites in temperate and dry climatic regions (three grasslands, two shrublands and one evergreen forest. Results of this study show that for the non-forest sites in water-limited areas, GPPm is well correlated with GPPec at annual scales (r2 = 0.77, n = 12; SEE = 149.26 g C∙m−2∙year−1, although it tends to overestimate GPP and it is less accurate in the sites with permanent water restrictions. The use of biome-specific models based on precipitation measurements at a finer spatial resolution than the Data Assimilation Office (DAO values can increase the accuracy of these estimations. The seasonal dynamics and the beginning and end of the growing season were well captured by GPPm for the sites where (i the productivity was low throughout the year or (ii the changes in the flux trend were abrupt, usually due to the restrictions in water availability. The agreement between GPPec and GPPm in non-forested sites was lower on a weekly basis than at an annual scale (0.44 ≤ r2 ≤ 0.49, but these results were improved by including meteorological data at a finer spatial scale, and soil water content and temperature measurements in the model developed to predict GPPec (0.52 ≤ r2 ≤ 0.65.

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

Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring.

Science.gov (United States)

David P. Turner; William D. Ritts; Warren B. Cohen; Thomas K. Maeirsperger; Stith T. Gower; Al A. Kirschbaum; Steve W. Runnings; Maosheng Zhaos; Steven C. Wofsy; Allison L. Dunn; Beverly E. Law; John L. Campbell; Walter C. Oechel; Hyo Jung Kwon; Tilden P. Meyers; Eric E. Small; Shirley A. Kurc; John A. Gamon

2005-01-01

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling...

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.

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

Science.gov (United States)

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

2018-02-01

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

Retrieval of canopy moisture content for dynamic fire risk assessment using simulated MODIS bands

Science.gov (United States)

Maffei, Carmine; Leone, Antonio P.; Meoli, Giuseppe; Calabrò, Gaetano; Menenti, Massimo

2007-10-01

Forest fires are one of the major environmental hazards in Mediterranean Europe. Biomass burning reduces carbon fixation in terrestrial vegetation, while soil erosion increases in burned areas. For these reasons, more sophisticated prevention tools are needed by local authorities to forecast fire danger, allowing a sound allocation of intervention resources. Various factors contribute to the quantification of fire hazard, and among them vegetation moisture is the one that dictates vegetation susceptibility to fire ignition and propagation. Many authors have demonstrated the role of remote sensing in the assessment of vegetation equivalent water thickness (EWT), which is defined as the weight of liquid water per unit of leaf surface. However, fire models rely on the fuel moisture content (FMC) as a measure of vegetation moisture. FMC is defined as the ratio of the weight of the liquid water in a leaf over the weight of dry matter, and its retrieval from remote sensing measurements might be problematic, since it is calculated from two biophysical properties that independently affect vegetation reflectance spectrum. The aim of this research is to evaluate the potential of the Moderate Resolution Imaging Spectrometer (MODIS) in retrieving both EWT and FMC from top of the canopy reflectance. The PROSPECT radiative transfer code was used to simulate leaf reflectance and transmittance as a function of leaf properties, and the SAILH model was adopted to simulate the top of the canopy reflectance. A number of moisture spectral indexes have been calculated, based on MODIS bands, and their performance in predicting EWT and FMC has been evaluated. Results showed that traditional moisture spectral indexes can accurately predict EWT but not FMC. However, it has been found that it is possible to take advantage of the multiple MODIS short-wave infrared (SWIR) channels to improve the retrieval accuracy of FMC (r2 = 0.73). The effects of canopy structural properties on MODIS

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

Science.gov (United States)

Veraverbeke, Sander; Sedano, Fernando; Hook, Simon J.; Randerson, James T.; Jin, Yufang; Rogers, Brendan

2013-01-01

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

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

Science.gov (United States)

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

2010-01-01

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

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.

An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

Science.gov (United States)

Spruce, Joseph P.; Sader, Steve; Smoot, James

2012-01-01

This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

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.

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.

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

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

Directory of Open Access Journals (Sweden)

Marc Zebisch

2013-03-01

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

Gross primary production dynamics assessment of a mediterranean holm oak forest by remote sensing time series analysis

Science.gov (United States)

Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia

2014-05-01

Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross

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.

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.

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

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.

Assessing Digital Student Productions, a Design-Based Research Study on the Development of a Criteria-Based Assessment Tool for Students’ Digital Multimodal Productions

DEFF Research Database (Denmark)

Hoffmeyer, Mikkeline; Jensen, Jesper Juellund; Olsen, Marie Veisegaard

2017-01-01

Digital multimodal production is becoming increasingly important as a 21st century skill and as a learning condition in school (K-12). Moreover, there is a growing attention to the significance of criteria-based assessment for learning. Nevertheless, assessment of students’ digital multimodal...... productions is often vague or lacking. Therefore, the research project aims at developing a tool to support assessment of student’s digital multimodal productions through a design-based research method. This paper presents a proposal for issues to be considered through a prototyping phase, based on interviews...

A high-resolution open biomass burning emission inventory based on statistical data and MODIS observations in mainland China

Science.gov (United States)

Xu, Y.; Fan, M.; Huang, Z.; Zheng, J.; Chen, L.

2017-12-01

Open biomass burning which has adverse effects on air quality and human health is an important source of gas and particulate matter (PM) in China. Current emission estimations of open biomass burning are generally based on single source (alternative to statistical data and satellite-derived data) and thus contain large uncertainty due to the limitation of data. In this study, to quantify the 2015-based amount of open biomass burning, we established a new estimation method for open biomass burning activity levels by combining the bottom-up statistical data and top-down MODIS observations. And three sub-category sources which used different activity data were considered. For open crop residue burning, the "best estimate" of activity data was obtained by averaging the statistical data from China statistical yearbooks and satellite observations from MODIS burned area product MCD64A1 weighted by their uncertainties. For the forest and grassland fires, their activity levels were represented by the combination of statistical data and MODIS active fire product MCD14ML. Using the fire radiative power (FRP) which is considered as a better indicator of active fire level as the spatial allocation surrogate, coarse gridded emissions were reallocated into 3km ×3km grids to get a high-resolution emission inventory. Our results showed that emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC and OC in mainland China were 6607, 427, 84, 79, 1262, 1198, 1222, 159 and 686 Gg/yr, respectively. Among all provinces of China, Henan, Shandong and Heilongjiang were the top three contributors to the total emissions. In this study, the developed open biomass burning emission inventory with a high-resolution could support air quality modeling and policy-making for pollution control.

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

Science.gov (United States)

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

2003-01-01

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

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.

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.

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

Science.gov (United States)

Adolph, Alden C.; Albert, Mary R.; Hall, Dorothy K.

2018-03-01

As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of -0.4 °C, spanning a range of temperatures from -35 to -5 °C (RMSE = 1.6 °C and mean bias = -0.7 °C prior to cloud masking). For our study area and time series, MODIS surface temperature products agree with skin surface

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...

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...

Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

Estimating crop net primary production using inventory data and MODIS-derived parameters

Energy Technology Data Exchange (ETDEWEB)

Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

2013-06-03

National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

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

Science.gov (United States)

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.

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.

Circulating ghrelin level is higher in HNF1A-MODY and GCK-MODY than in polygenic forms of diabetes mellitus.

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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.

Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

Science.gov (United States)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

2015-12-01

Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD Retrievals Against Ground Sunphotometer Observations Over East Asia

Science.gov (United States)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-01-01

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51% of VIIRS Environmental Data Record (EDR) AOD, 37% of GOCI AOD, 33% of VIIRS Intermediate Product (IP) AOD, 26% of Terra MODIS C6 3km AOD, and 16% of Aqua MODIS C6 3km AOD fell within the reference expected error (EE) envelope (+/-0.05/+/- 0.15 AOD). Comparing against AERONET AOD over the JapanSouth Korea region, 64% of EDR, 37% of IP, 61% of GOCI, 39% of Terra MODIS, and 56% of Aqua MODIS C6 3km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3km products had positive biases.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

Science.gov (United States)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-02-01

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra MODIS C6 3 km AOD, and 16 % of Aqua MODIS C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra MODIS, and 56 % of Aqua MODIS C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.

A MODIS-Based Robust Satellite Technique (RST for Timely Detection of Oil Spilled Areas

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Teodosio Lacava

2017-02-01

Full Text Available Natural crude-oil seepages, together with the oil released into seawater as a consequence of oil exploration/production/transportation activities, and operational discharges from tankers (i.e., oil dumped during cleaning actions represent the main sources of sea oil pollution. Satellite remote sensing can be a useful tool for the management of such types of marine hazards, namely oil spills, mainly owing to the synoptic view and the good trade-off between spatial and temporal resolution, depending on the specific platform/sensor system used. In this paper, an innovative satellite-based technique for oil spill detection, based on the general robust satellite technique (RST approach, is presented. It exploits the multi-temporal analysis of data acquired in the visible channels of the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua satellite in order to automatically and quickly detect the presence of oil spills on the sea surface, with an attempt to minimize “false detections” caused by spurious effects associated with, for instance, cloud edges, sun/satellite geometries, sea currents, etc. The oil spill event that occurred in June 2007 off the south coast of Cyprus in the Mediterranean Sea has been considered as a test case. The resulting data, the reliability of which has been evaluated by both carrying out a confutation analysis and comparing them with those provided by the application of another independent MODIS-based method, showcase the potential of RST in identifying the presence of oil with a high level of accuracy.

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.

Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

Science.gov (United States)

Ranson, K. J.; Montesano, P. M.; Nelson, R.

2011-01-01

The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

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.

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

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JESSICA PANISSET

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

Spatio-temporal variability of the phytoplankton biomass in the Levantine basin between 2002 and 2015 using MODIS products

OpenAIRE

Roy El Hourany; Ali Fadel; Elissar Gemayel; Marie Abboud-Abi Saab; Ghaleb Faour

2017-01-01

The Levantine basin in the Eastern Mediterranean Sea is subject to spatial and seasonal variations in primary production and physical-chemical properties both on a short and long-term basis. In this study, the monthly means of daily MODIS product images were averaged between 2002 and 2015, and used to characterize the phytoplankton blooms in different bioregions of the Levantine basin. The selected products were the sea surface temperature (SST), the chlorophyll-a concentration (Chl-a), the d...

Comparison of NDVIs from GOCI and MODIS Data towards Improved Assessment of Crop Temporal Dynamics in the Case of Paddy Rice

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Jong-Min Yeom

2015-09-01

Full Text Available The monitoring of crop development can benefit from the increased frequency of observation provided by modern geostationary satellites. This paper describes a four-year testing period from 2010 to 2014, during which satellite images from the world's first Geostationary Ocean Color Imager (GOCI were used for spectral analyses of paddy rice in South Korea. A vegetation index was calculated from GOCI data based on the bidirectional reflectance distribution function (BRDF-adjusted reflectance, which was then used to visually analyze the seasonal crop dynamics. These vegetation indices were then compared with those calculated using the Moderate-resolution Imaging Spectroradiometer (MODIS-normalized difference vegetation index (NDVI based on Nadir BRDF-adjusted reflectance. The results show clear advantages of GOCI, which provided four times better temporal resolution than the combined MODIS sensors, interpreting subtle characteristics of the vegetation development. Particularly in the rainy season, when data acquisition under clear weather conditions was very limited, it was possible to find cloudless pixels within the study sites by compiling GOCI images obtained from eight acquisition periods per day, from which the vegetation index could be calculated. In this study, ground spectral measurements from CROPSCAN were also compared with satellite-based vegetation products, despite their different index magnitude, according to systematic discrepancy, showing a similar crop development pattern to the GOCI products. Consequently, we conclude that the very high temporal resolution of GOCI is very beneficial for monitoring crop development, and has potential for providing improved information on phenology.

Land cover mapping of Greater Mesoamerica using MODIS data

Science.gov (United States)

Giri, Chandra; Jenkins, Clinton N.

2005-01-01

A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

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

Science.gov (United States)

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

2013-04-01

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

Remote sensing of aerosols by synergy of caliop and modis

OpenAIRE

Kudo Rei; Nishizawa Tomoaki; Higurashi Akiko; Oikawa Eiji

2018-01-01

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

Assessment of the Short-Term Radiometric Stability between Terra MODIS and Landsat 7 ETM+ Sensors

Science.gov (United States)

Choi, Taeyoung; Xiong, Xiaxiong; Chander, G.; Angal, Amit

2009-01-01

Constellation satellites, Terra MODIS flies approximately 30 minutes behind L7 ETM+ in the same orbit. The orbit of L7 is repetitive, circular, sunsynchronous, and near polar at a nominal altitude of 705 km (438 miles) at the Equator. The spacecraft crosses the Equator from north to south on a descending node between 10:00 AM and 10:15 AM. Circling the Earth at 7.5 km/sec, each orbit takes nearly 99 minutes. The spacecraft completes just over 14 orbits per day, covering the entire Earth between 81 degrees north and south latitude every 16 days. The longest continuous imaging swath that L7 sensor can collect is for a 14-minute subinterval contact period which is equivalent to 35 full WRS-2 scenes. On the other hand, Terra can provide the entire corresponding orbit with wider swath at any given ETM+ collection without contact time limitation. There are six spectral matching band pairs between MODIS (bands 3, 4, 1, 2, 6, 7) and ETM+ (bands 1, 2, 3, 4, 5, 7) sensor. MODIS has narrower spectral responses than ETM+ in all the bands. A short-term radiometric stability was evaluated using continuous ETM+ scenes within the contact period and the corresponding half orbit MODIS scenes. The near simultaneous earth observations (SNO) were limited by the smaller swath size of ETM+ (187 km) as compared to MODIS (2330 km). Two sets of continuous granules for MODIS and ETM+ were selected and mosaiced based on pixel geolocation information for non cloudy pixels over the North American continent. The Top-of- Atmosphere (TOA) reflectances were computed for the spectrally matching bands between ETM+ and MODIS over the regions of interest (ROI). The matching pixel pairs were aggregated from a finer to a coarser pixel resolution and the TOA reflectance values covering a wide dynamic range of the sensors were compared and analyzed. Considering the uncertainties of the absolute calibration of the both sensors, radiometric stability was verified for the band pairs. The Railroad Valley Playa, Nada (RVPN

Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data

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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.

A Methodology to Assess the Impact of Optical and Electronic Crosstalk in a New Generation of Sensors Using Heritage Sensors

Science.gov (United States)

Oudrari, Hassan; Schwarting, Thomas; Chiang, Kwo-Fu; McIntire, Jeff; Pan, Chunhui; Xiong, Xiaoxiong; Butler, James

2010-01-01

Electronic and optical crosstalk are radiometric challenges that often exist in the focal plane design in many sensors Such as MODIS. A methodology is described to assess the impact due to optical and electronic crosstalk on the measured radiance, and thereafter, the retrieval of geophysical products using MODIS Level I data sets. Based on a postulated set of electronic and optical crosstalk coefficients, and a set of MODIS scenes, we have simulated a system signal contamination on any detector on a focal plane when another detector on that focal plane is stimulated with a geophysical signal. The original MODIS scenes and the crosstalk impacted scenes can be used with validated geophysical algorithms to derive the final data products. Products contaminated with crosstalk are then compared to those without contamination to assess the impact magnitude and location, and will allow us to separate Out-Of-Band (OOB) leaks from hand-to-hand optical crosstalk, and identify potential failures to meet climate research requirements.

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

Data.gov (United States)

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

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

Directory of Open Access Journals (Sweden)

A. C. Adolph

2018-03-01

Full Text Available As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of −0.4 °C, spanning a range of temperatures from −35 to −5 °C (RMSE  =  1.6 °C and mean bias  =  −0.7 °C prior to cloud masking. For our study area and time series

UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

OpenAIRE

Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

2018-01-01

Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire dis...

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

Science.gov (United States)

Wang, Jiao; Deng, Zhiqiang

2017-06-01

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

Preliminary Research on Grassland Fine-classification Based on MODIS

International Nuclear Information System (INIS)

Hu, Z W; Zhang, S; Yu, X Y; Wang, X S

2014-01-01

Grassland ecosystem is important for climatic regulation, maintaining the soil and water. Research on the grassland monitoring method could provide effective reference for grassland resource investigation. In this study, we used the vegetation index method for grassland classification. There are several types of climate in China. Therefore, we need to use China's Main Climate Zone Maps and divide the study region into four climate zones. Based on grassland classification system of the first nation-wide grass resource survey in China, we established a new grassland classification system which is only suitable for this research. We used MODIS images as the basic data resources, and use the expert classifier method to perform grassland classification. Based on the 1:1,000,000 Grassland Resource Map of China, we obtained the basic distribution of all the grassland types and selected 20 samples evenly distributed in each type, then used NDVI/EVI product to summarize different spectral features of different grassland types. Finally, we introduced other classification auxiliary data, such as elevation, accumulate temperature (AT), humidity index (HI) and rainfall. China's nation-wide grassland classification map is resulted by merging the grassland in different climate zone. The overall classification accuracy is 60.4%. The result indicated that expert classifier is proper for national wide grassland classification, but the classification accuracy need to be improved

Assessment of MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6 for Directional Reflectance Retrieval

Directory of Open Access Journals (Sweden)

Xianghong Che

2017-11-01

Full Text Available Measurements of solar radiation reflected from Earth’s surface are the basis for calculating albedo, vegetation indices, and other terrestrial attributes. However, the “bi-directional” geometry of illumination and viewing (i.e., the Bi-directional Reflectance Distribution Function (BRDF impacts reflectance and all variables derived or estimated based on these data. The recently released MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6 dataset enables retrieval of directional reflectance at arbitrary solar and viewing angles, potentially increasing precision and comparability of data collected under different illumination and observation geometries. We quantified the ability of MCD43A1 Collection 6 for retrieving directional reflectance and compared the daily Collection 6 retrievals to those of MCD43A1 Collection 5, which are retrieved on an eight-day basis. Correcting MODIS-based estimates of surface reflectance from the illumination and viewing geometry of the Terra satellite (MOD09GA to that of the MODIS Aqua (MYD09GA overpass, as well as MCD43A4 Collection 6 and Landsat-5 TM images show that the BRDF correction of MCD43A1 Collection 6 results in greater consistency among datasets, with higher R2 (0.63–0.955, regression slopes closer to unity (0.718–0.955, lower root mean squared difference (RMSD (0.422–3.142, and lower mean absolute error (MAE (0.282–1.735 compared to the Collection 5 data. Smaller levels of noise (observed as high-frequency variability within the time series in MCD43A1 Collection 6 in comparison to Collection 5 corroborates the improvement of BRDF parameters time series. These results corroborates that the daily MCD43A1 Collection 6 product represents the anisotropy of surface features and results in more precise directional reflectance derivation at any solar and viewing geometry than did the previous Collection 5.

OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km V003 (OMMYDCLD) at GES DISC

Data.gov (United States)

National Aeronautics and Space Administration — The OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km (OMMYDCLD) is a Level-2 orbital product that combines cloud parameters retrieved by the...

GCK-MODY in the US National Monogenic Diabetes Registry: frequently misdiagnosed and unnecessarily treated.

Science.gov (United States)

Carmody, David; Naylor, Rochelle N; Bell, Charles D; Berry, Shivani; Montgomery, Jazzmyne T; Tadie, Elizabeth C; Hwang, Jessica L; Greeley, Siri Atma W; Philipson, Louis H

2016-10-01

GCK-MODY leads to mildly elevated blood glucose typically not requiring therapy. It has been described in all ethnicities, but mainly in Caucasian Europeans. Here we describe our US cohort of GCK-MODY. We examined the rates of detection of heterozygous mutations in the GCK gene in individuals referred to the US Monogenic Diabetes Registry with a phenotype consistent with GCK-MODY. We also assessed referral patterns, treatment and demography, including ethnicity, of the cohort. Deleterious heterozygous GCK mutations were found in 54.7 % of Registry probands selected for GCK sequencing for this study. Forty-nine percent were previously unnecessarily treated with glucose-lowering agents, causing hypoglycemia and other adverse effects in some of the subjects. The proportion of probands found to have a GCK mutation through research-based testing was similar across each ethnic group. However, together African-American, Latino and Asian subjects represented only 20.5 % of screened probands and 17.2 % of those with GCK-MODY, despite higher overall diabetes prevalence in these groups. Our data show that a high detection rate of GCK-MODY is possible based on clinical phenotype and that prior to genetic diagnosis, a large percentage are inappropriately treated with glucose-lowering therapies. We also find low minority representation in our Registry, which may be due to disparities in diagnostic diabetes genetic testing and is an area needing further investigation.

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

Science.gov (United States)

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

2006-12-01

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

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...

Glucokinase MODY and implications for treatment goals of common forms of diabetes.

Science.gov (United States)

Ajjan, Ramzi A; Owen, Katharine R

2014-12-01

Treatment goals in diabetes concentrate on reducing the risk of vascular complications, largely through setting targets for glycated haemoglobin (HbA1c). These targets are based on epidemiological studies of complication development, but so far have not adequately addressed the adverse effects associated with lowering HbA1c towards the normal range. Glucokinase (GCK) mutations cause a monogenic form of hyperglycaemia (GCK-MODY) characterised by fasting hyperglycaemia with low postprandial glucose excursions and a marginally elevated HbA1c. Minimal levels of vascular complications (comparable with nondiabetic individuals) are observed in GCK-MODY, leading to the hypothesis that GCK-MODY may represent a useful paradigm for assessing treatment goals in all forms of diabetes. In this review, we discuss the evidence behind this concept, suggest ways of translating this hypothesis into clinical practice and address some of the caveats of such an approach.

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

Science.gov (United States)

Platnick, Steven E.

2011-01-01

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

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

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

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a

Type 2 diabetes mellitus in children and adolescents is still a rare disease in Germany: a population-based assessment of the prevalence of type 2 diabetes and MODY in patients aged 0-20 years.

Science.gov (United States)

Neu, Andreas; Feldhahn, Lutz; Ehehalt, Stefan; Hub, Regine; Ranke, Michael B

2009-11-01

To assess the prevalence of type 2 diabetes mellitus (T2DM) and maturity onset diabetes of the young (MODY) in children and adolescents aged 0-20 yr in Baden-Württemberg (BW), Germany, and to compare our results with those from other European countries. Our study involved every children's hospital (n = 31), each diabetologist in private practice (n = 122), and every internal medicine unit (n = 164) in BW. A written questionnaire and a telephone survey were used to identify children with T2DM and MODY who had been examined at any of these institutions between 2004 and 2005. Population data were drawn from the national census of 1987 and the subsequent annual updates. The prevalence of T2DM for the age range from 0 to 20 yr is 2.30/100 000, whereas the prevalence of MODY in the same age range is 2.39/100 000. The median age of patients with T2DM was 15.8 yr, and 13.9 yr for MODY patients. The majority of patients with either T2DM or MODY were treated in children's hospitals and by consultant diabetologists. A molecular genetic analysis was done to substantiate the clinical diagnosis in less than half of the recruits (14.3% of T2DM and 44.8% of MODY patients). The prevalence of T2DM and MODY is considerably lower than the prevalence of type 1 diabetes. Type 2 diabetes thus continues to be a rare disease in children and adolescents in Germany, as is also the case in other European countries.

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

. In this paper, the algorithms of these approaches are described, their performance is demonstrated, and their impact on L1B products is discussed. In general, the shorter wavelength bands have experienced a larger on-orbit RVS change, which, in general, are mirror side and detector dependent. The on-orbit RVS change due to the degradation of band 8 can be as large as 35 percent for Terra MODIS and 20 percent for Aqua MODIS. Vital to maintaining the accuracy of the MODIS L1B products is an accurate characterization of the on-orbit RVS change. The derived time-independent RVS, implemented in C6, makes an important improvement to the quality of the MODIS L1B products.

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.

Intima-media thickness and endothelial dysfunction in GCK and HNF1A-MODY patients.

Science.gov (United States)

Szopa, Magdalena; Osmenda, Grzegorz; Wilk, Grzegorz; Matejko, Bartłomiej; Skupien, Jan; Zapala, Barbara; Młynarski, Wojciech; Guzik, Tomasz; Malecki, Maciej T

2015-03-01

Mutations in the glucokinase (GCK) gene, along with hepatocyte nuclear factor 1A (HNF1A) gene mutations, are the most frequent cause of maturity-onset diabetes of the young (MODY). GCK-MODY patients are typically characterized by a moderate fasting hyperglycemia; however, little is known about atherosclerosis and intermediate-related phenotypes in these subjects. To examine carotid artery intima-media thickness (IMT) and endothelial function assessed by brachial artery flow-mediated dilatation (FMD) in GCK gene mutations carriers and HNF1A-MODY. A total of 64 subjects with GCK gene mutations, and 52 HNF1A gene mutation carriers as well as 53 nondiabetic controls were examined. IMT and FMD were assessed by ultrasonography. Appropriate statistical tests were performed to assess differences between the groups, and multivariate linear regression was done for the association with IMT and FMD. The clinical characteristics of all groups were similar with the mean age at examination of 35.1, 41.1, and 39.5 years for GCK, HNF1A and the control group respectively. The highest mean IMT value was in the HNF1A-MODY group: 7.0±1.4 mm, whereas it reached 6.3±1.4 mm in GCK mutation carriers and 6.3±1.3 mm in controls (P=0.008). After adjustment for possible clinical and biochemical cofounders, IMT remained higher in HNF1A-MODY patients as compared with GCK-MODY patients (P=0.02) and controls (P=0.0003). FMD was significantly lower in HNF1A (9.9±4.6%) and GCK-MODY (11.1±4.6%) patients in comparison with controls (13.9±4.7%; P=0.0001). After adjustment, FMD remained lower in HNF1A-MODY (P=0.0005) and GCK-MODY patients (P=0.01) as compared with controls. Both examined MODY groups demonstrated evidence of endothelial dysfunction. In addition, HNF1-MODY patients seem to be more prone to an early atherosclerotic phenotype. © 2015 European Society of Endocrinology.

Deriving Aerosol Characteristics Over the Ocean from MODIS: Are We There Yet?

Science.gov (United States)

Remer, L. A.; Tanre, D.

2006-12-01

The MODerate resolution Imaging Spectroradiometer (MODIS) has been successfully retrieving aerosol characteristics over the ocean since shortly after the launch of the Terra satellite at the end of 1999. With its wide spectral range (0.47 to 2.13 μm) MODIS is able to derive spectral aerosol optical depth and information on the size of the aerosol particles. The products were quickly validated, the validation confirmed, and the products are now in wide use across the scientific community. The MODIS aerosol products over ocean are an outstanding success story, but are we done? As the years progress and we gain experience in using the products, evaluating them and nudging even greater information from them, we discover new challenges. Firstly, we continue to find issues affecting the integrity of the products we now produce. We need to find methods to reduce the uncertainty introduced by clouds that go beyond the classical concept of cloud masking and cloud contamination. Some of these novel cloud effects on aerosol retrieval include 3D scattering of light from cloud sides. Another issue that needs resolution is the uncertainty introduced by nonspherical particle shapes. Secondly, when MODIS was new we were excited to have spectral optical depth and particle size information. Now we find that aerosol characterization is still incomplete. We need more information. Are we there yet? Well, no, but we can see the future. To meet these new challenges we will need information beyond the spectral radiances that MODIS measures. We can see the future of satellite derivation of aerosol characteristics, and it looks more and more like a multi-sensor future.

Spatial Rice Yield Estimation Based on MODIS and Sentinel-1 SAR Data and ORYZA Crop Growth Model

Directory of Open Access Journals (Sweden)

Tri D. Setiyono

2018-02-01

Full Text Available Crop insurance is a viable solution to reduce the vulnerability of smallholder farmers to risks from pest and disease outbreaks, extreme weather events, and market shocks that threaten their household food and income security. In developing and emerging countries, the implementation of area yield-based insurance, the form of crop insurance preferred by clients and industry, is constrained by the limited availability of detailed historical yield records. Remote-sensing technology can help to fill this gap by providing an unbiased and replicable source of the needed data. This study is dedicated to demonstrating and validating the methodology of remote sensing and crop growth model-based rice yield estimation with the intention of historical yield data generation for application in crop insurance. The developed system combines MODIS and SAR-based remote-sensing data to generate spatially explicit inputs for rice using a crop growth model. MODIS reflectance data were used to generate multitemporal LAI maps using the inverted Radiative Transfer Model (RTM. SAR data were used to generate rice area maps using MAPScape-RICE to mask LAI map products for further processing, including smoothing with logistic function and running yield simulation using the ORYZA crop growth model facilitated by the Rice Yield Estimation System (Rice-YES. Results from this study indicate that the approach of assimilating MODIS and SAR data into a crop growth model can generate well-adjusted yield estimates that adequately describe spatial yield distribution in the study area while reliably replicating official yield data with root mean square error, RMSE, of 0.30 and 0.46 t ha−1 (normalized root mean square error, NRMSE of 5% and 8% for the 2016 spring and summer seasons, respectively, in the Red River Delta of Vietnam, as evaluated at district level aggregation. The information from remote-sensing technology was also useful for identifying geographic locations with

THE ANALYSIS OF MOISTURE DEFICIT BASED ON MODIS AND LANDSAT SATELLITE IMAGES. CASE STUDY: THE OLTENIA PLAIN

Directory of Open Access Journals (Sweden)

ONȚEL IRINA

2014-03-01

Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.

Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites

Directory of Open Access Journals (Sweden)

Stephan Paul

2015-04-01

Full Text Available The opacity of clouds is the main problem for optical and thermal space-borne sensors, like the Moderate-Resolution Imaging Spectroradiometer (MODIS. Especially during polar nighttime, the low thermal contrast between clouds and the underlying snow/ice results in deficiencies of the MODIS cloud mask and affected products. There are different approaches to retrieve information about frequently cloud-covered areas, which often operate with large amounts of days aggregated into single composites for a long period of time. These approaches are well suited for static-nature, slow changing surface features (e.g., fast-ice extent. However, this is not applicable to fast-changing features, like sea-ice polynyas. Therefore, we developed a spatial feature reconstruction to derive information for cloud-covered sea-ice areas based on the surrounding days weighted directly proportional with their temporal proximity to the initial day of interest. Its performance is tested based on manually-screened and artificially cloud-covered case studies of MODIS-derived polynya area data for the polynya in the Brunt Ice Shelf region of Antarctica. On average, we are able to completely restore the artificially cloud-covered test areas with a spatial correlation of 0.83 and a mean absolute spatial deviation of 21%.

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

Data.gov (United States)

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

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.

Developing a Random Forest Algorithm for MODIS Global Burned Area Classification

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Rubén Ramo

2017-11-01

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

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.

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

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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.

Estimating atmospheric visibility using synergy of MODIS data and ground-based observations

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Komeilian, H.; Mohyeddin Bateni, S.; Xu, T.; Nielson, J.

2015-05-01

Dust events are intricate climatic processes, which can have adverse effects on human health, safety, and the environment. In this study, two data mining approaches, namely, back-propagation artificial neural network (BP ANN) and supporting vector regression (SVR), were used to estimate atmospheric visibility through the synergistic use of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B (L1B) data and ground-based observations at fourteen stations in the province of Khuzestan (southwestern Iran), during 2009-2010. Reflectance and brightness temperature in different bands (from MODIS) along with in situ meteorological data were input to the models to estimate atmospheric visibility. The results show that both models can accurately estimate atmospheric visibility. The visibility estimates from the BP ANN network had a root-mean-square error (RMSE) and Pearson's correlation coefficient (R) of 0.67 and 0.69, respectively. The corresponding RMSE and R from the SVR model were 0.59 and 0.71, implying that the SVR approach outperforms the BP ANN.

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.

Assessing variability and long-term trends in burned area by merging multiple satellite fire products

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L. Giglio

2010-03-01

Full Text Available Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM Visible and Infrared Scanner (VIRS and the Along-Track Scanning Radiometer (ATSR allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3 estimates of trace gas and aerosol emissions.

MODIS-Based Products for Operational Decision Support Systems, Phase I

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National Aeronautics and Space Administration — SMH Consulting proposes to develop a web-based decision support system to assist in Rapid Assessment, Monitoring, and Management (RAMM-DSS) on a regional scale. SMH...

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.

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

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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

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

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

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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

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.

Noise Characterization and Performance of MODIS Thermal Emissive Bands

Science.gov (United States)

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

2016-01-01

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

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

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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.

MODIS Science Algorithms and Data Systems Lessons Learned

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

2009-01-01

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

Assessment of Burned Area and Atmospheric Gases from Multi- temporal MODIS Images (2000- 2017) in Nainital District, Uttarakhand

Science.gov (United States)

Aggarwal, R.; K V, S. B.; Dhakate, P. M.

2017-12-01

Recent times have observed a significant rate of deforestation and forest degradation. One of the major causes of forest degradation is forest fires. Forest fires though have shaped the current forest ecosystem but also have continued to degrade the system by causing loss of flora and fauna. In addition to that, forest fire leads to emission of carbon and other trace gases which contributes to global warming. The hill states in India, particularly Uttarakhand witnesses annual forest fires; which are primarily anthropogenic caused, occurring from March to June. Nainital one of the thirteen districts in Uttarakhand, has been selected as the study site. The region has diverse endemic species of vegetation, ranging from Alpine in North to moist deciduous in South. The increasing forest fire incidents in the region and limited studies on the subject, calls for landscape assessment of the complex Human Environment System (HES). It is in this context, that a greater need for monitoring forest fire incidents has been felt. Remote Sensing and GIS which are robust tool, provides continuous information of an area at various spatial and temporal resolutions. The goal of this study is to map burned area, burned severity and estimate atmospheric gas emissions in forested areas of Nainital by utilizing cloud free MODIS images from 2000- 2017. Multiple spectral indices were generated from pre and post burn dataset of MODIS to conclude the most sensitive band combination. Inter- comparison of results obtained from different spectral indices and the global MODIS MCD45A1 was carried out using linear regression analysis. Additionally, burned area estimation from satellite was compared to figures reported by forest department. There were considerable differences amongst the two which could be primarily due to differences in spatial resolution, and timings of forest fire occurrence and image acquisition. Further, estimation of various atmospheric gases was carried out based on the IPCC

The Research on the Spectral Characteristics of Sea Fog Based on Caliop and Modis Data

Science.gov (United States)

Wan, J.; Su, J.; Liu, S.; Sheng, H.

2018-04-01

In view of that difficulty of distinguish between sea fog and low cloud by optical remote sensing mean, the research on spectral characteristics of sea fog is focused and carried out. The satellite laser radar CALIOP data and the high spectral MODIS data were obtained from May to December 2017, and the scattering coefficient and the vertical height information were extracted from the atmospheric attenuation of the lower star to extract the sea fog sample points, and the spectral response curve based on MODIS was formed to analyse the spectral response characteristics of the sea fog, thus providing a theoretical basis for the monitoring of sea fog with optical remote sensing image.

THE RESEARCH ON THE SPECTRAL CHARACTERISTICS OF SEA FOG BASED ON CALIOP AND MODIS DATA

Directory of Open Access Journals (Sweden)

J. Wan

2018-04-01

Full Text Available In view of that difficulty of distinguish between sea fog and low cloud by optical remote sensing mean, the research on spectral characteristics of sea fog is focused and carried out。The satellite laser radar CALIOP data and the high spectral MODIS data were obtained from May to December 2017, and the scattering coefficient and the vertical height information were extracted from the atmospheric attenuation of the lower star to extract the sea fog sample points, and the spectral response curve based on MODIS was formed to analyse the spectral response characteristics of the sea fog, thus providing a theoretical basis for the monitoring of sea fog with optical remote sensing image.

Model Development for MODIS Thermal Band Electronic Crosstalk

Science.gov (United States)

Chang, Tiejun; Wu, Aisheng; Geng, Xu; Li, Yonghonh; Brinkman, Jake; Keller, Graziela; Xiong, Xiaoxiong

2016-01-01

MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 m. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands developed substantial issues that cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 m and band 29 at 8.5 m increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk effect is evident in the near-monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. The development of an alternative approach is very helpful for independent verification.In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically to correct the Earth brightness temperature measurements. In the model development, the detectors nonlinear response is considered. The impact of the electronic crosstalk is assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detectors nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector non-linearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic cross talk can be implemented empirically from the processed bias at different brightness temperature. The implementation

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.

MODIS observations of cyanobacterial risks in a eutrophic lake: Implications for long-term safety evaluation in drinking-water source.

Science.gov (United States)

Duan, Hongtao; Tao, Min; Loiselle, Steven Arthur; Zhao, Wei; Cao, Zhigang; Ma, Ronghua; Tang, Xiaoxian

2017-10-01

The occurrence and related risks from cyanobacterial blooms have increased world-wide over the past 40 years. Information on the abundance and distribution of cyanobacteria is fundamental to support risk assessment and management activities. In the present study, an approach based on Empirical Orthogonal Function (EOF) analysis was used to estimate the concentrations of chlorophyll a (Chla) and the cyanobacterial biomarker pigment phycocyanin (PC) using data from the MODerate resolution Imaging Spectroradiometer (MODIS) in Lake Chaohu (China's fifth largest freshwater lake). The approach was developed and tested using fourteen years (2000-2014) of MODIS images, which showed significant spatial and temporal variability of the PC:Chla ratio, an indicator of cyanobacterial dominance. The results had unbiased RMS uncertainties of MODIS Chla and PC products were then used for cyanobacterial risk mapping with a decision tree classification model. The resulting Water Quality Decision Matrix (WQDM) was designed to assist authorities in the identification of possible intake areas, as well as specific months when higher frequency monitoring and more intense water treatment would be required if the location of the present intake area remained the same. Remote sensing cyanobacterial risk mapping provides a new tool for reservoir and lake management programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.125 degrees, East US

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures photosynthetically available radiation that may be used to mode primary productivity. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for...

Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.125 degrees, West US

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures photosynthetically available radiation that may be used to mode primary productivity. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for...

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

Science.gov (United States)

Peddle, D. R.; Hall, F.

2009-12-01

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

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

Science.gov (United States)

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

2008-05-01

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

Global cloud database from VIRS and MODIS for CERES

Science.gov (United States)

Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

2003-04-01

The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

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.

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

Directory of Open Access Journals (Sweden)

Laura Ulsig

2017-01-01

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

Cost-effectiveness of MODY genetic testing: translating genomic advances into practical health applications.

Science.gov (United States)

Naylor, Rochelle N; John, Priya M; Winn, Aaron N; Carmody, David; Greeley, Siri Atma W; Philipson, Louis H; Bell, Graeme I; Huang, Elbert S

2014-01-01

OBJECTIVE To evaluate the cost-effectiveness of a genetic testing policy for HNF1A-, HNF4A-, and GCK-MODY in a hypothetical cohort of type 2 diabetic patients 25-40 years old with a MODY prevalence of 2%. RESEARCH DESIGN AND METHODS We used a simulation model of type 2 diabetes complications based on UK Prospective Diabetes Study data, modified to account for the natural history of disease by genetic subtype to compare a policy of genetic testing at diabetes diagnosis versus a policy of no testing. Under the screening policy, successful sulfonylurea treatment of HNF1A-MODY and HNF4A-MODY was modeled to produce a glycosylated hemoglobin reduction of -1.5% compared with usual care. GCK-MODY received no therapy. Main outcome measures were costs and quality-adjusted life years (QALYs) based on lifetime risk of complications and treatments, expressed as the incremental cost-effectiveness ratio (ICER) (USD/QALY). RESULTS The testing policy yielded an average gain of 0.012 QALYs and resulted in an ICER of 205,000 USD. Sensitivity analysis showed that if the MODY prevalence was 6%, the ICER would be ~50,000 USD. If MODY prevalence was >30%, the testing policy was cost saving. Reducing genetic testing costs to 700 USD also resulted in an ICER of ~50,000 USD. CONCLUSIONS Our simulated model suggests that a policy of testing for MODY in selected populations is cost-effective for the U.S. based on contemporary ICER thresholds. Higher prevalence of MODY in the tested population or decreased testing costs would enhance cost-effectiveness. Our results make a compelling argument for routine coverage of genetic testing in patients with high clinical suspicion of MODY.

INVESTIGATION THE BEHAVIOR OF MODIS OCEAN COLOR PRODUCTS UNDER THE 2008 RED TIDE IN THE EASTERN PERSIAN GULF

Directory of Open Access Journals (Sweden)

M. Ghanea

2015-12-01

software package. The Strait of Hormuz was selected as the study area in the eastern part of the PG. Images including high cloud coverage (>50% over the study area were filtered out. The classification maps of the above products were shown during RT and normal periods. Monthly variations of mentioned products were calculated for the dates before, during, and after RT appearance. The results were demonstrated as time-series diagrams. All the above calculations and presentations were performed in Matlab 7 software package. The results show that MODIS Chl-a, nFLH, and kd490 increased during the 2008 RT. Based on the feedback of these parameters under RT conditions, hybrid ocean color index (HOCI is defined. HOCI is able to display better water variations during RT outbreak. High values of HOCI show RT affected areas.

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...

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.

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.

Characterizing and estimating noise in InSAR and InSAR time series with MODIS

Science.gov (United States)

Barnhart, William D.; Lohman, Rowena B.

2013-01-01

InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

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....

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

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Science.gov (United States)

Zhang, Ping; Imhoff, Marc L.; Wolfe, Robert E.; Bounoua, Lahouari

2010-01-01

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship with development intensity, size, and ecological setting for more than 3000 urban settlements globally. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby nonurban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to ensure objective intercomparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass shrubs biomes; and only a weak UHI or sometimes an urban heat sink (UHS) in cities in arid and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) with the difference in vegetation density between urban and rural zones represented by the MODIS normalized difference vegetation index (NDVI). Globally averaged, the daytime UHI amplitude for all settlements is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers compared with 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude, with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variance is explained by ISA for urban settlements within forests at mid to high latitudes. This

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.;

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.

Assessment of NPP VIIRS Ocean Color Data Products: Hope and Risk

Science.gov (United States)

Turpie, Kevin R.; Meister, Gerhard; Eplee, Gene; Barnes, Robert A.; Franz, Bryan; Patt, Frederick S.; Robinson, Wayne d.; McClain, Charles R.

2010-01-01

For several years, the NASA/Goddard Space Flight Center (GSFC) NPP VIIRS Ocean Science Team (VOST) provided substantial scientific input to the NPP project regarding the use of Visible Infrared Imaging Radiometer Suite (VIIRS) to create science quality ocean color data products. This work has culminated into an assessment of the NPP project and the VIIRS instrument's capability to produce science quality Ocean Color data products. The VOST concluded that many characteristics were similar to earlier instruments, including SeaWiFS or MODIS Aqua. Though instrument performance and calibration risks do exist, it was concluded that programmatic and algorithm issues dominate concerns. Keywords: NPP, VIIRS, Ocean Color, satellite remote sensing, climate data record.

Remote sensing of aerosols by synergy of caliop and modis

Directory of Open Access Journals (Sweden)

Kudo Rei

2018-01-01

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

Remote sensing of aerosols by synergy of caliop and modis

Science.gov (United States)

Kudo, Rei; Nishizawa, Tomoaki; Higurashi, Akiko; Oikawa, Eiji

2018-04-01

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

The comparison of MODIS-Aqua (C5 and CALIOP (V2 & V3 aerosol optical depth

Directory of Open Access Journals (Sweden)

J. Redemann

2012-03-01

Full Text Available We assess the consistency between instantaneously collocated level-2 aerosol optical depth (AOD retrievals from MODIS-Aqua (C5 and CALIOP (Version 2 & 3, comparing the standard MODIS AOD (MYD04_L2 data to the AOD calculated from CALIOP aerosol extinction profiles for both the previous release (V2 and the latest release (V3 of CALIOP data. Based on data collected in January 2007, we investigate the most useful criteria for screening the MODIS and CALIOP retrievals to achieve the best agreement between the two data sets. Applying these criteria to eight months of data (Jan, Apr, Jul, Oct 2007 and 2009, we find an order of magnitude increase for the CALIOP V3 data density (by comparison to V2, that is generally accompanied by equal or better agreement with MODIS AOD. Differences in global, monthly mean, over-ocean AOD (532 nm between CALIOP and MODIS range between 0.03 and 0.04 for CALIOP V3, with CALIOP generally biased low, when all available data from both sensors are considered. Root-mean-squares (RMS differences in instantaneously collocated AOD retrievals by the two instruments are reduced from values ranging between 0.14 and 0.19 using the unscreened V3 data to values ranging from 0.09 to 0.1 for the screened data. A restriction to scenes with cloud fractions less than 1% (as defined in the MODIS aerosol retrievals generally results in improved correlation (R²>0.5, except for the month of July when correlations remain relatively lower. Regional assessments show hot spots in disagreement between the two sensors in Asian outflow during April and off the coast of South Africa in July.

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...

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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.

Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.05 degrees, Global, Science Quality

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures photosynthetically available radiation that may be used to mode primary productivity. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for...

Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.125 degrees, Gulf of Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures photosynthetically available radiation that may be used to mode primary productivity. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for...

Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

Science.gov (United States)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

2017-08-01

Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

Cross-comparison of the IRS-P6 AWiFS sensor with the L5 TM, L7 ETM+, & Terra MODIS sensors

Science.gov (United States)

Chander, G.; Xiong, X.; Angal, A.; Choi, T.; Malla, R.

2009-01-01

As scientists and decision makers increasingly rely on multiple Earth-observing satellites to address urgent global issues, it is imperative that they can rely on the accuracy of Earth-observing data products. This paper focuses on the crosscomparison of the Indian Remote Sensing (IRS-P6) Advanced Wide Field Sensor (AWiFS) with the Landsat 5 (L5) Thematic Mapper (TM), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The cross-comparison was performed using image statistics based on large common areas observed by the sensors within 30 minutes. Because of the limited availability of simultaneous observations between the AWiFS and the Landsat and MODIS sensors, only a few images were analyzed. These initial results are presented. Regression curves and coefficients of determination for the top-of-atmosphere (TOA) trends from these sensors were generated to quantify the uncertainty in these relationships and to provide an assessment of the calibration differences between these sensors. ?? 2009 SPIE.

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.

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

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

Science.gov (United States)

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

2015-08-01

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

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.

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

DEFF Research Database (Denmark)

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

2014-01-01

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

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

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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.

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.

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

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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.

Improved VIIRS and MODIS SST Imagery

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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 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.

Object-Based Assessment of Satellite Precipitation Products

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Jingjing Li

2016-06-01

Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US

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Andrew E. Suyker

2013-11-01

Full Text Available Remote sensing techniques that provide synoptic and repetitive observations over large geographic areas have become increasingly important in studying the role of agriculture in global carbon cycles. However, it is still challenging to model crop yields based on remotely sensed data due to the variation in radiation use efficiency (RUE across crop types and the effects of spatial heterogeneity. In this paper, we propose a production efficiency model-based method to estimate corn and soybean yields with MODerate Resolution Imaging Spectroradiometer (MODIS data by explicitly handling the following two issues: (1 field-measured RUE values for corn and soybean are applied to relatively pure pixels instead of the biome-wide RUE value prescribed in the MODIS vegetation productivity product (MOD17; and (2 contributions to productivity from vegetation other than crops in mixed pixels are deducted at the level of MODIS resolution. Our estimated yields statistically correlate with the national survey data for rainfed counties in the Midwestern US with low errors for both corn (R2 = 0.77; RMSE = 0.89 MT/ha and soybeans (R2 = 0.66; RMSE = 0.38 MT/ha. Because the proposed algorithm does not require any retrospective analysis that constructs empirical relationships between the reported yields and remotely sensed data, it could monitor crop yields over large areas.

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.

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.

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.

[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.

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

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

2017-07-01

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

Extreme thermal episodes analyzed with MODIS products during the boreal winter (2000-2016

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J. Gomis-Cebolla

2016-06-01

Full Text Available The beginning of the XXI century is characterized by the intensification of the existing global warming situation and for a series of drastic global meteorological events. Particularly, during the winter season a series of extreme temperature episodes affecting large areas of the northern hemisphere have been produced. In this paper, these episodes are studied by analyzing the thermal anomalies spatial distribution and temporal evolution in the period 2001-2016 from Land Surface Temperature (LST products obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS sensor. The study regions considered in this investigation are eight of the northern hemisphere. The results obtained for the heating and cooling episodes do not reveal an important discrepancy, however, an increase in the area affected by heating versus cooling is observed.

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia

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de Oliveira, Gabriel; Brunsell, Nathaniel A.; Moraes, Elisabete C.; Bertani, Gabriel; dos Santos, Thiago V.; Shimabukuro, Yosio E.; Aragão, Luiz E. O. C.

2016-01-01

In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001–December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance. PMID:27347957

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia.

Science.gov (United States)

de Oliveira, Gabriel; Brunsell, Nathaniel A; Moraes, Elisabete C; Bertani, Gabriel; Dos Santos, Thiago V; Shimabukuro, Yosio E; Aragão, Luiz E O C

2016-06-24

In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001-December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance.

N-MODY: A Code for Collisionless N-body Simulations in Modified Newtonian Dynamics

Science.gov (United States)

Londrillo, Pasquale; Nipoti, Carlo

2011-02-01

N-MODY is a parallel particle-mesh code for collisionless N-body simulations in modified Newtonian dynamics (MOND). N-MODY is based on a numerical potential solver in spherical coordinates that solves the non-linear MOND field equation, and is ideally suited to simulate isolated stellar systems. N-MODY can be used also to compute the MOND potential of arbitrary static density distributions. A few applications of N-MODY indicate that some astrophysically relevant dynamical processes are profoundly different in MOND and in Newtonian gravity with dark matter.

Remotely sensed MODIS wetland components for assessing the variability of methane emissions in Indian tropical/subtropical wetlands

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Bansal, Sangeeta; Katyal, Deeksha; Saluja, Ridhi; Chakraborty, Monojit; Garg, J. K.

2018-02-01

Temperature and area fluctuations in wetlands greatly influence its various physico-chemical characteristics, nutrients dynamic, rates of biomass generation and decomposition, floral and faunal composition which in turn influence methane (CH4) emission rates. In view of this, the present study attempts to up-scale point CH4 flux from the wetlands of Uttar Pradesh (UP) by modifying two-factor empirical process based CH4 emission model for tropical wetlands by incorporating MODIS derived wetland components viz. wetland areal extent and corresponding temperature factors (Ft). This study further focuses on the utility of remotely sensed temperature response of CH4 emission in terms of Ft. Ft is generated using MODIS land surface temperature products and provides an important semi-empirical input for up-scaling CH4 emissions in wetlands. Results reveal that annual mean Ft values for UP wetlands vary from 0.69 (2010-2011) to 0.71(2011-2012). The total estimated area-wise CH4 emissions from the wetlands of UP varies from 66.47 Gg yr-1with wetland areal extent and Ft value of 2564.04 km2 and 0.69 respectively in 2010-2011 to 88.39 Gg yr-1with wetland areal extent and Ft value of 2720.16 km2 and 0.71 respectively in 2011-2012. Temporal analysis of estimated CH4 emissions showed that in monsoon season estimated CH4 emissions are more sensitive to wetland areal extent while in summer season sensitivity of estimated CH4 emissions is chiefly controlled by augmented methanogenic activities at high wetland surface temperatures.

Estimating Coastal Turbidity using MODIS 250 m Band Observations

Science.gov (United States)

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

2004-01-01

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

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

Science.gov (United States)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

Science.gov (United States)

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

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

Searching for Maturity-Onset Diabetes of the Young (MODY): When and What for?

Science.gov (United States)

Timsit, José; Saint-Martin, Cécile; Dubois-Laforgue, Danièle; Bellanné-Chantelot, Christine

2016-10-01

Maturity-onset diabetes of the young (MODY) is a group of monogenic diseases that results in primary defects in insulin secretion and dominantly inherited forms of nonautoimmune diabetes. Although many genes may be associated with monogenic diabetes, heterozygous mutations in 6 of them are responsible for the majority of cases of MODY. Glucokinase (GCK)-MODY is due to mutations in the glucokinase gene, 3 MODY subtypes are associated with mutations in the hepatocyte nuclear factor (HNF) transcription factors, and 2 others with mutations in ABCC8 and KCNJ11, which encode the subunits of the ATP-dependent potassium channel in pancreatic beta cells. GCK-MODY and HNF1A-MODY are the most common subtypes. The clinical presentation of MODY subtypes has been reported to differ according to the gene involved, and the diagnosis of MODY may be considered in various clinical circumstances. However, except in patients with GCK-MODY whose phenotype is very homogeneous, in most cases the penetrance and expressivity of a given molecular abnormality vary greatly among patients and, conversely, alterations in various genes may lead to similar phenotypes. Moreover, differential diagnosis among more common forms of diabetes may be difficult, particularly with type 2 diabetes. Thus, careful assessment of the personal and family histories of patients with diabetes is mandatory to select those in whom genetic screening is worthwhile. The diagnosis of monogenic diabetes has many consequences in terms of prognosis, therapeutics and family screening. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

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

GHRSST Level 2P USA NASA MODIS Terra SST:1

Data.gov (United States)

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

GHRSST Level 2P USA NASA MODIS Aqua SST:1

Data.gov (United States)

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

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...

[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.

Weekday AOD smaller than weekend AOD in eastern China on the basis of the MODIS AOD product

Science.gov (United States)

Song, Jingjing; Xia, Xiangao; Zhang, Xiaoling; Che, Huizheng; Li, Xiaojing

2018-05-01

A weekly cycle of surface particulate matter (PM) characterized by smaller values during weekends and larger values during weekdays was reported in eastern China. Whether column-integrated aerosol optical depth (AOD) showed similar weekly cycling as that of PM was debated. The weekly variation of AOD in eastern China was further studied by using the latest MODIS aerosol product (collection 6) with a fine spatial resolution (0.1°) from 2002 to 2015. We used three statistical methods to determine whether the weekly cycle of AOD was significant. AOD during weekdays (Wednesday to Friday) was lower than that during weekends. The maximum and minimum AOD was generally observed on Monday and Wednesday, respectively. This weekly pattern of AOD was in good agreement with previous results based on satellite aerosol products with a coarse spatial resolution, but it was in contrast to that of PM. Further analysis of the AOD weekly variability in 19 provincial cities suggested that AOD during weekdays was smaller than that during weekends in urban regions. Potential causes for the different weekly cycle of PM and AOD in eastern China were discussed.

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.

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

PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part

Surface BRDF estimation from an aircraft compared to MODIS and ground estimates at the Southern Great Plains site

Energy Technology Data Exchange (ETDEWEB)

Knobelspiesse, Kirk D.; Cairns, Brian; Schmid, Beat; Roman, Miguel O.; Schaaf, Crystal B.

2008-10-21

The surface spectral albedo is an important component of climate models since it determines the amount of incident solar radiation that is absorbed by the ground. The albedo can be highly heterogeneous, both in space and time, and thus adequate measurement and modeling is challenging. One source of measurements that constrain the surface albedo are satellite instruments that observe the Earth, such as the Moderate Resolution Imaging Spectroradiometer (MODIS). Satellites estimate the surface bidirectional reflectance distribution function (BRDF) by correcting top of the atmosphere (TOA) radiances for atmospheric effects and accumulating observations at a variety of viewing geometries. The BRDF can then be used to determine the albedo that is required in climate modeling. Other measurements that provide a more direct constraint on surface albedo are those made by upward and downward looking radiometers at the ground. One product in particular, the Best Estimate Radiation Flux (BEFLUX) value added product of the Department of Energy’s Atmospheric Radiation Measurement (ARM) Program at the Southern Great Plains Central Facility (SGP CF) in central Oklahoma, has been used to evaluate the quality of the albedo products derived from MODIS BRDF estimates. These comparisons have highlighted discrepancies between the energy absorbed at the surface that is calculated from the BEFLUX products and that is predicted from the MODIS BRDF product. This paper attempts to investigate these discrepancies by using data from an airborne scanning radiometer, the Research Scanning Polarimeter (RSP) that was flown at low altitude in the vicinity of the SGP CF site during the Aerosol Lidar Validation Experiment (ALIVE) in September of 2005. The RSP is a polarimeter that scans in the direction of the aircraft ground track, and can thus estimate the BRDF in a period of seconds, rather than the days required by MODIS to accumulate enough viewing angles. Atmospheric correction is aided by the

Comparison of Gross Primary Productivity Derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

Directory of Open Access Journals (Sweden)

Junbang Wang

2014-03-01

Full Text Available Gross primary production (GPP plays an important role in the net ecosystem exchange of CO2 between the atmosphere and terrestrial ecosystems. It is particularly important to monitor GPP in Southeast Asia because of increasing rates of tropical forest degradation and deforestation in the region in recent decades. The newly available, improved, third generation Normalized Difference Vegetation Index (NDVI3g from the Global Inventory Modelling and Mapping Studies (GIMMS group provides a long temporal dataset, from July 1981 to December 2011, for terrestrial carbon cycle and climate response research. However, GIMMS NDVI3g-based GPP estimates are not yet available. We applied the GLOPEM-CEVSA model, which integrates an ecosystem process model and a production efficiency model, to estimate GPP in Southeast Asia based on three independent results of the fraction of photosynthetically active radiation absorbed by vegetation (FPAR from GIMMS NDVI3g (GPPNDVI3g, GIMMS NDVI1g (GPPNDVI1g, and the Moderate Resolution Imaging Spectroradiometer (MODIS MOD15A2 FPAR product (GPPMOD15. The GPP results were validated using ground data from eddy flux towers located in different forest biomes, and comparisons were made among the three GPPs as well as the MOD17A2 GPP products (GPPMOD17. Based on validation with flux tower derived GPP estimates the results show that GPPNDVI3g is more accurate than GPPNDVI1g and is comparable in accuracy with GPPMOD15. In addition, GPPNDVI3g and GPPMOD15 have good spatial-temporal consistency. Our results indicate that GIMMS NDVI3g is an effective dataset for regional GPP simulation in Southeast Asia, capable of accurately tracking the variation and trends in long-term terrestrial ecosystem GPP dynamics.

Comprehensive genomic analysis identifies pathogenic variants in maturity-onset diabetes of the young (MODY) patients in South India.

Science.gov (United States)

Mohan, Viswanathan; Radha, Venkatesan; Nguyen, Thong T; Stawiski, Eric W; Pahuja, Kanika Bajaj; Goldstein, Leonard D; Tom, Jennifer; Anjana, Ranjit Mohan; Kong-Beltran, Monica; Bhangale, Tushar; Jahnavi, Suresh; Chandni, Radhakrishnan; Gayathri, Vijay; George, Paul; Zhang, Na; Murugan, Sakthivel; Phalke, Sameer; Chaudhuri, Subhra; Gupta, Ravi; Zhang, Jingli; Santhosh, Sam; Stinson, Jeremy; Modrusan, Zora; Ramprasad, V L; Seshagiri, Somasekar; Peterson, Andrew S

2018-02-13

Maturity-onset diabetes of the young (MODY) is an early-onset, autosomal dominant form of non-insulin dependent diabetes. Genetic diagnosis of MODY can transform patient management. Earlier data on the genetic predisposition to MODY have come primarily from familial studies in populations of European origin. In this study, we carried out a comprehensive genomic analysis of 289 individuals from India that included 152 clinically diagnosed MODY cases to identify variants in known MODY genes. Further, we have analyzed exome data to identify putative MODY relevant variants in genes previously not implicated in MODY. Functional validation of MODY relevant variants was also performed. We found MODY 3 (HNF1A; 7.2%) to be most frequently mutated followed by MODY 12 (ABCC8; 3.3%). They together account for ~ 11% of the cases. In addition to known MODY genes, we report the identification of variants in RFX6, WFS1, AKT2, NKX6-1 that may contribute to development of MODY. Functional assessment of the NKX6-1 variants showed that they are functionally impaired. Our findings showed HNF1A and ABCC8 to be the most frequently mutated MODY genes in south India. Further we provide evidence for additional MODY relevant genes, such as NKX6-1, and these require further validation.

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.

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

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

MODIS and GIMMS Inferred Northern Hemisphere Spring Greenup in Responses to Preseason Climate

Science.gov (United States)

Xu, X.; Riley, W. J.; Koven, C.; Jia, G.

2017-12-01

We compare the discrepancies in Normalized Difference Vegetation Index (NDVI) inferred spring greenup (SG) between Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) instruments carried by the Global Inventory Monitoring and Modeling Studies (GIMMS) in North Hemisphere. The interannual variation of SG inferred by MODIS and GIMMS NDVI is well correlated in the mid to high latitudes. However, the presence of NDVI discrepancies leads to discrepancies in SG with remarkable latitudinal characteristics. MODIS NDVI inferred later SG in the high latitude while earlier SG in the mid to low latitudes, in comparison to GIMMS NDVI inferred SG. MODIS NDVI inferred SG is better correlated to preseason climate. Interannual variation of SG is only sensitive to preseason temperature. The GIMMS SG to temperature sensitivity over two periods implied that the inter-biome SG to temperature sensitivity is relatively stable, but SG to temperature sensitivity decreased over time. Over the same period, MODIS SG to temperature sensitivity is much higher than GIMMS. This decreased sensitivity demonstrated the findings from previous studies with continuous GIMMS NDVI analysis that vegetation growth (indicated by growing season NDVI) to temperature sensitivity is reduced over time and SG advance trend ceased after 2000s. Our results also explained the contradictive findings that SG advance accelerated after 2000s according to the merged GIMMS and MODIS NDVI time series. Despite the found discrepancies, without ground data support, the quality of NDVI and its inferred SG cannot be effectively evaluated. The discrepancies and uncertainties in different NDVI products and its inferred SG may bias the scientific significance of climate-vegetation relationship. The different NDVI products when used together should be first evaluated and harmonized.

Comparing the Dry Season In-Situ Leaf Area Index (LAI Derived from High-Resolution RapidEye Imagery with MODIS LAI in a Namibian Savanna

Directory of Open Access Journals (Sweden)

Manuel J. Mayr

2015-04-01

Full Text Available The Leaf Area Index (LAI is one of the most frequently applied measures to characterize vegetation and its dynamics and functions with remote sensing. Satellite missions, such as NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS operationally produce global datasets of LAI. Due to their role as an input to large-scale modeling activities, evaluation and verification of such datasets are of high importance. In this context, savannas appear to be underrepresented with regards to their heterogeneous appearance (e.g., tree/grass-ratio, seasonality. Here, we aim to examine the LAI in a heterogeneous savanna ecosystem located in Namibia’s Owamboland during the dry season. Ground measurements of LAI are used to derive a high-resolution LAI model with RapidEye satellite data. This model is related to the corresponding MODIS LAI/FPAR (Fraction of Absorbed Photosynthetically Active Radiation scene (MOD15A2 in order to evaluate its performance at the intended annual minimum during the dry season. Based on a field survey we first assessed vegetation patterns from species composition and elevation for 109 sites. Secondly, we measured in situ LAI to quantitatively estimate the available vegetation (mean = 0.28. Green LAI samples were then empirically modeled (LAImodel with high resolution RapidEye imagery derived Difference Vegetation Index (DVI using a linear regression (R2 = 0.71. As indicated by several measures of model performance, the comparison with MOD15A2 revealed moderate consistency mostly due to overestimation by the aggregated LAImodel. Model constraints aside, this study may point to important issues for MOD15A2 in savannas concerning the underlying MODIS Land Cover product (MCD12Q1 and a potential adjustment by means of the MODIS Burned Area product (MCD45A1.

Siberian Earth System Science Cluster - A web-based Geoportal to provide user-friendly Earth Observation Products for supporting NEESPI scientists

Science.gov (United States)

Eberle, J.; Gerlach, R.; Hese, S.; Schmullius, C.

2012-04-01

To provide earth observation products in the area of Siberia, the Siberian Earth System Science Cluster (SIB-ESS-C) was established as a spatial data infrastructure at the University of Jena (Germany), Department for Earth Observation. This spatial data infrastructure implements standards published by the Open Geospatial Consortium (OGC) and the International Organizsation for Standardization (ISO) for data discovery, data access, data processing and data analysis. The objective of SIB-ESS-C is to faciliate environmental research and Earth system science in Siberia. The region for this project covers the entire Asian part of the Russian Federation approximately between 58°E - 170°W and 48°N - 80°N. To provide discovery, access and analysis services a webportal was published for searching and visualisation of available data. This webportal is based on current web technologies like AJAX, Drupal Content Management System as backend software and a user-friendly surface with Drag-n-Drop and further mouse events. To have a wide range of regular updated earth observation products, some products from sensor MODIS at the satellites Aqua and Terra were processed. A direct connection to NASA archive servers makes it possible to download MODIS Level 3 and 4 products and integrate it in the SIB-ESS-C infrastructure. These data can be downloaded in a file format called Hierarchical Data Format (HDF). For visualisation and further analysis, this data is reprojected, converted to GeoTIFF and global products clipped to the project area. All these steps are implemented as an automatic process chain. If new MODIS data is available within the infrastructure this process chain is executed. With the link to a MODIS catalogue system, the system gets new data daily. With the implemented analysis processes, timeseries data can be analysed, for example to plot a trend or different time series against one another. Scientists working in this area and working with MODIS data can make use

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.

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

Directory of Open Access Journals (Sweden)

Sriharsha Madhavan

2016-02-01

Full Text Available The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source—a V-grooved blackbody for the Thermal Emissive Bands (TEB. The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 µm channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST at NASA/GSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher brightness temperature for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model

Science.gov (United States)

Hilker, Thomas; Galvão, Lênio Soares; Aragão, Luiz E. O. C.; de Moura, Yhasmin M.; do Amaral, Cibele H.; Lyapustin, Alexei I.; Wu, Jin; Albert, Loren P.; Ferreira, Marciel José; Anderson, Liana O.; dos Santos, Victor A. H. F.; Prohaska, Neill; Tribuzy, Edgard; Barbosa Ceron, João Vitor; Saleska, Scott R.; Wang, Yujie; de Carvalho Gonçalves, José Francisco; de Oliveira Junior, Raimundo Cosme; Cardoso Rodrigues, João Victor Figueiredo; Garcia, Maquelle Neves

2017-06-01

As a preparatory study for future hyperspectral missions that can measure canopy chemistry, we introduce a novel approach to investigate whether multi-angle Moderate Resolution Imaging Spectroradiometer (MODIS) data can be used to generate a preliminary database with long-term estimates of chlorophyll. MODIS monthly chlorophyll estimates between 2000 and 2015, derived from a fully coupled canopy reflectance model (ProSAIL), were inspected for consistency with eddy covariance fluxes, tower-based hyperspectral images and chlorophyll measurements. MODIS chlorophyll estimates from the inverse model showed strong seasonal variations across two flux-tower sites in central and eastern Amazon. Marked increases in chlorophyll concentrations were observed during the early dry season. Remotely sensed chlorophyll concentrations were correlated to field measurements (r2 = 0.73 and r2 = 0.98) but the data deviated from the 1:1 line with root mean square errors (RMSE) ranging from 0.355 μg cm-2 (Tapajós tower) to 0.470 μg cm-2 (Manaus tower). The chlorophyll estimates were consistent with flux tower measurements of photosynthetically active radiation (PAR) and net ecosystem productivity (NEP). We also applied ProSAIL to mono-angle hyperspectral observations from a camera installed on a tower to scale modeled chlorophyll pigments to MODIS observations (r2 = 0.73). Chlorophyll pigment concentrations (ChlA+B) were correlated to changes in the amount of young and mature leaf area per month (0.59 ≤ r2 ≤ 0.64). Increases in MODIS observed ChlA+B were preceded by increased PAR during the dry season (0.61 ≤ r2 ≤ 0.62) and followed by changes in net carbon uptake. We conclude that, at these two sites, changes in LAI, coupled with changes in leaf chlorophyll, are comparable with seasonality of plant productivity. Our results allowed the preliminary development of a 15-year time series of chlorophyll estimates over the Amazon to support canopy chemistry studies using future

Using the Surface Reflectance MODIS Terra Product to Estimate Turbidity in Tampa Bay, Florida

Directory of Open Access Journals (Sweden)

Douglas L. Rickman

2010-12-01

Full Text Available Turbidity is a commonly-used index of the factors that determine light penetration in the water column. Consistent estimation of turbidity is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Traditional methods monitoring fixed geographical locations at fixed intervals may not be representative of the mean water turbidity in estuaries between intervals, and can be expensive and time consuming. Although remote sensing offers a good solution to this limitation, it is still not widely used due in part to required complex processing of imagery. There are satellite-derived products, including the Moderate Resolution Imaging Spectroradiometer (MODIS Terra surface reflectance daily product (MOD09GQ Band 1 (620–670 nm which are now routinely available at 250 m spatial resolution and corrected for atmospheric effect. This study shows this product to be useful to estimate turbidity in Tampa Bay, Florida, after rainfall events (R2 = 0.76, n = 34. Within Tampa Bay, Hillsborough Bay (HB and Old Tampa Bay (OTB presented higher turbidity compared to Middle Tampa Bay (MTB and Lower Tampa Bay (LTB.

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

expertise. Secondly, a baseline map of cropped areas was established, utilizing MODIS time-series data, Landsat ETM+ data and a custom dot-grid sampling method. This product aids in disaggregating crop location and density, and establishes a nominal quantitative assessment of farming practices. The techniques used to generate these results for Kenya can be expanded for use throughout developing Africa and beyond.

OSU MODIS FLH Bloom Product

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Two bloom products were developed for the Oregon coast based on the observed change between running 8-day composite chlorophyll-a (CHL) and fluorescence line-height...

Investigation of Cloud Properties and Atmospheric Profiles with MODIS

Science.gov (United States)

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

1997-01-01

The WINter Cloud Experiment (WINCE) was directed and supported by personnel from the University of Wisconsin in January and February. Data sets of good quality were collected by the MODIS Airborne Simulator (MAS) and other instruments on the NASA ER2; they will be used to develop and validate cloud detection and cloud property retrievals over winter scenes (especially over snow). Software development focused on utilities needed for all of the UW product executables; preparations for Version 2 software deliveries were almost completed. A significant effort was made, in cooperation with SBRS and MCST, in characterizing and understanding MODIS PFM thermal infrared performance; crosstalk in the longwave infrared channels continues to get considerable attention.

Investigation of Cloud Properties and Atmospheric Profiles with Modis

Science.gov (United States)

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

1997-01-01

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

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.

Detection of Asian Dust Storm Using MODIS Measurements

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Yong Xie

2017-08-01

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

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.

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

2012-01-01

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.

Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

Science.gov (United States)

Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

2017-12-01

The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

Substantial proportion of MODY among multiplex families participating in a Type 1 diabetes prediction programme.

Science.gov (United States)

Petruzelkova, L; Dusatkova, P; Cinek, O; Sumnik, Z; Pruhova, S; Hradsky, O; Vcelakova, J; Lebl, J; Kolouskova, S

2016-12-01

Patients with maturity-onset diabetes of the young (MODY) might be over-represented in families with histories of Type 1 diabetes. Our aim was to re-evaluate families participating in the Czech T1D Prediction Programme (PREDIA.CZ) with at least two members affected with diabetes to assess the proportion of MODY among these families and determine its most significant clinical predictors. Of the 557 families followed up by the PREDIA.CZ, 53 (9.5%) had two or more family members with diabetes. One proband with diabetes from these families was chosen for direct sequencing of the GCK, HNF1A, HNF4A and INS genes. Non-parametric tests and a linear logistic regression model were used to evaluate differences between MODY and non-MODY families. MODY was genetically diagnosed in 24 of the 53 families with multiple occurrences of diabetes (45%). Mutations were detected most frequently in GCK (58%), followed by HNF1A (38%) and INS (4%). MODY families were more likely to have a parent with diabetes and had a higher proportion of females with diabetes than non-MODY families. Higher age (P MODY families already presenting with diabetes. A prediction programme for Type 1 diabetes would provide a useful new source of patients with MODY most likely to benefit from an accurate diagnosis. This identification has implications for patient treatment and disease prognosis. © 2015 Diabetes UK.

Remote Sensing of Leaf Area Index from LiDAR Height Percentile Metrics and Comparison with MODIS Product in a Selectively Logged Tropical Forest Area in Eastern Amazonia

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Yonghua Qu

2018-06-01

Full Text Available Leaf area index (LAI is an important parameter to describe the capacity of forests to intercept light and thus affects the microclimate and photosynthetic capacity of canopies. In general, tropical forests have a higher leaf area index and it is a challenge to estimate LAI in a forest with a very dense canopy. In this study, it is assumed that the traditional Light Detection and Ranging (LiDAR-derived fractional vegetation cover (fCover has weak relationship with leaf area index in a dense forest. We propose a partial least squares (PLS regression model using the height percentile metrics derived from airborne LiDAR data to estimate the LAI of a dense forest. Ground inventory and airborne LiDAR data collected in a selectively logged tropical forest area in Eastern Amazonia are used to map LAI from the plot level to the landscape scale. The results indicate that the fCover, derived from the first return or the last return, has no significant correlations with the ground-based LAI. The PLS model evaluated by the leave-one-out validation shows that the estimated LAI is significantly correlated with the ground-based LAI with an R2 of 0.58 and a root mean square error (RMSE of 1.13. A data comparison indicates that the Moderate Resolution Imaging Spectrometer (MODIS LAI underestimates the landscape-level LAI by about 22%. The MODIS quality control data show that in the selected tile, the cloud state is not the primary factor affecting the MODIS LAI performance; rather, the LAI from the main radiative transfer (RT algorithm contributes much to the underestimation of the LAI in the tropical forest. In addition, the results show that the LiDAR-based LAI has a better response to the logging activities than the MODIS-based LAI, and that the leaf area reduction caused by logging is about 13%. In contrast, the MODIS-based LAI exhibits no apparent spatial correlation with the LiDAR-based LAI. It is suggested that the main algorithm of MODIS should be

A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

Energy Technology Data Exchange (ETDEWEB)

Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.; Chen, Jiquan; Baldocchi, Dennis D.; Cook, David R.; Oren, Ram; Richardson, Andrew D.; Wharton, Sonia; Ma, Siyan; Martin, Timothy A.; Verma, Shashi B.; Suyker, Andrew E.; Scott, Russell L.; Monson, Russell K.; Litvak, Marcy; Hollinger, David Y.; Sun, Ge; Davis, Kenneth J.; Bolstad, Paul V.; Burns, Sean P.; Curtis, Peter S.; Drake, Bert G.; Falk, Matthias; Fischer, Marc L.; Foster, David R.; Gu, Lianhong; Hadley, Julian L.; Katul, Gabriel G.; Matamala, Roser; McNulty, Steve; Meyers, Tilden P.; Munger, J. William; Noormets, Asko; Oechel, Walter C.; U, Kyaw Tha Paw; Schmid, Hans Peter; Starr, Gregory; Torn, Margaret S.; Wofsy, Steven C.

2009-01-28

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated

Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

Science.gov (United States)

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

2015-04-01

Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.

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

Assessment of MODIS-derived indices (2001-2013) to drought across Taiwan's forests

Science.gov (United States)

Chang, Chung-Te; Wang, Hsueh-Ching; Huang, Cho-ying

2017-12-01

Tropical and subtropical ecosystems, the largest terrestrial carbon pools, are very susceptible to the variability of seasonal precipitation. However, the assessment of drought conditions in these regions is often overlooked due to the preconceived notion of the presence of high humidity. Drought indices derived from remotely sensed imagery have been commonly used for large-scale monitoring, but feasibility of drought assessment may vary across regions due to climate regimes and local biophysical conditions. Therefore, this study aims to evaluate the feasibility of 11 commonly used MODIS-derived vegetation/drought index in the forest regions of Taiwan through comparison with the station-based standardized precipitation index with a 3-month time scale (SPI3). The drought indices were further transformed (standardized anomaly, SA) to make them better delineate the spatiotemporal variations of drought conditions. The results showed that the Normalized Difference Infrared Index utilizing the near-infrared and shortwave infrared bands (NDII6) may be more superior to other indices in delineating drought patterns. Overall, the NDII6 SA-SPI3 pair yielded the highest correlation (mean r ± standard deviation = 0.31 ± 0.13) and was most significant in central and south Taiwan (r = 0.50-0.90) during the cold, dry season (January and April). This study illustrated that the NDII6 is suitable to delineate drought conditions in a relatively humid region. The results suggested the better performance of the NDII6 SA-SPI3 across the high climate gradient, especially in the regions with dramatic interannual amplifications of rainfall. This synthesis was conducted across a wide bioclimatic gradient, and the findings could be further generalized to a much broader geographical extent.

Properties of Linear Contrails Detected in 2012 Northern Hemisphere MODIS Imagery

Science.gov (United States)

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

2015-01-01

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

Two cases of diabetic ketoacidosis in HNF1A-MODY linked to severe dehydration: is it time to change the diagnostic criteria for MODY?

Science.gov (United States)

Pruhova, Stepanka; Dusatkova, Petra; Neumann, David; Hollay, Erik; Cinek, Ondrej; Lebl, Jan; Sumnik, Zdenek

2013-09-01

Hepatocyte nuclear factor-1A maturity-onset diabetes of the young (HNF1A-MODY) is a monogenic form of diabetes caused by heterozygous mutations in HNF1A. Currently, a history of diabetic ketoacidosis (DKA) is an exclusion criterion for genetic testing for MODY. In this article, we describe two unrelated patients aged 17 and 24 years with severe DKA developed several years after the diagnosis of HNF1A-MODY. Both patients were treated with insulin, but their metabolic control was poor (HbA1c 15%, 140 mmol/mol and 13%, 119 mmol/mol, respectively) due to noncompliance and missed insulin injections. In both patients, DKA followed a course of recurrent vomiting with dehydration and prerenal acute kidney injury. Their glycemia, blood pH, and base excess at admission were 97 mmol/L [1,748 mg/dL], 6.80, and -33 mmol/L (patient 1) and 34 mmol/L [613 mg/dL], 7.03, and -14 mmol/L (patient 2). This anecdotal observation supports the notion that a history of DKA does not exclude MODY.

Investigating the early snowmelt of 2015 in the Cascade Mountains using new MODIS-based snowmelt timing maps

Science.gov (United States)

O'Leary, D., III; Hall, D. K.; Medler, M. J.; Flower, A.; Matthews, R.

2017-12-01

The spring of 2015 brought an alarmingly early snowmelt to the Cascade Mountains, impacting flora, fauna, watersheds, and wildfire activity. It is important that we understand these events because model-based projections suggest that snowmelt may arrive an average of 10-40 days earlier across the continental US by the year 2100. Available snow measurement methods including SNOTEL stations and stream gauges offer insights into point locations and individual watersheds, but lack the detail needed to assess snowmelt anomalies across the landscape. In this study we describe our new MODIS-based snowmelt timing maps (STMs), validate them with SNOTEL measurements, then use them to explore the spatial patterns of the 2015 snowmelt in the Cascades. We found that the Cascade Mountains experienced snowmelt 41 days earlier than the 2001-2015 average, with many areas melting >70 days early. Of concern to land managers, these events may be the `new normal' in the decades to come.

Mapping rice areas of South Asia using MODIS multitemporal data

Science.gov (United States)

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

2011-01-01

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

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

Science.gov (United States)

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

2011-12-01

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

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

Effect of the Absorbed Photosynthetically Active Radiation Estimation Error on Net Primary Production Estimation - A Study with MODIS FPAR and TOMS Ultraviolet Reflective Products

International Nuclear Information System (INIS)

Kobayashi, H.; Matsunaga, T.; Hoyano, A.

2002-01-01

Absorbed photosynthetically active radiation (APAR), which is defined as downward solar radiation in 400-700 nm absorbed by vegetation, is one of the significant variables for Net Primary Production (NPP) estimation from satellite data. Toward the reduction of the uncertainties in the global NPP estimation, it is necessary to clarify the APAR accuracy. In this paper, first we proposed the improved PAR estimation method based on Eck and Dye's method in which the ultraviolet (UV) reflectivity data derived from Total Ozone Mapping Spectrometer (TOMS) at the top of atmosphere were used for clouds transmittance estimation. The proposed method considered the variable effects of land surface UV reflectivity on the satellite-observed UV data. Monthly mean PAR comparisons between satellite-derived and ground-based data at various meteorological stations in Japan indicated that the improved PAR estimation method reduced the bias errors in the summer season. Assuming the relative error of the fraction of PAR (FPAR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to be 10%, we estimated APAR relative errors to be 10-15%. Annual NPP is calculated using APAR derived from MODIS/ FPAR and the improved PAR estimation method. It is shown that random and bias errors of annual NPP in a 1 km resolution pixel are less than 4% and 6% respectively. The APAR bias errors due to the PAR bias errors also affect the estimated total NPP. We estimated the most probable total annual NPP in Japan by subtracting the bias PAR errors. It amounts about 248 MtC/yr. Using the improved PAR estimation method, and Eck and Dye's method, total annual NPP is 4% and 9% difference from most probable value respectively. The previous intercomparison study among using fifteen NPP models4) showed that global NPP estimations among NPP models are 44.4-66.3 GtC/yr (coefficient of variation = 14%). Hence we conclude that the NPP estimation uncertainty due to APAR estimation error is small

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

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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

Quality Assessment of S-NPP VIIRS Land Surface Temperature Product

Directory of Open Access Journals (Sweden)

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.

Global Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

Science.gov (United States)

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

2012-12-01

Flooding is among the most destructive, frequent, and costly natural disasters faced by modern society, with several major events occurring each year. In the past few years, major floods have devastated parts of China, Thailand, Pakistan, Australia, and the Philippines, among others. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we have developed, and are now operating, a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours after flooding events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard. The LANCE system typically processes imagery in less than 3 hours after satellite overpass, and our flood mapping system can output flood products within ½ hour of acquiring the LANCE products. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial assessment of flooding extent by late afternoon, every day, and more robust assessments after accumulating imagery over a longer period; the MODIS sensors are optical, so cloud cover remains an issue, which is partly overcome by using multiple looks over one or more days. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), 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 extents. We have made progress on some of these issues

CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition2A)

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Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

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

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.

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

Directory of Open Access Journals (Sweden)

J. F. Burkhart

2017-07-01

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

Applications of MODIS Fluorescence Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity in Coastal and Estuarine Waters

Science.gov (United States)

Fischer, A.; Ryan, J. P.; Moreno-Madriñán, M. J.

2012-12-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS), calibration updates, improved aerosol retrievals, and new aerosol models have led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean-color. This has opened the way for studying coastal ocean phenomena and processes at finer spatial scales. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and increases in local concentrations of phytoplankton, which could result in harmful algal blooms. In two case studies we present improved and validated MODIS coastal observations of fluorescence line height (FLH) to: (1) assess trends in water quality for Tampa Bay, Florida; and (2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California, as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and imagery from Tampa Bay, we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout this large, optically complex estuarine system. A systematic analysis of sampling sites throughout the bay illustrates that the correlations between FLH and in situ chlorophyll-a are influenced by water quality parameters of total nitrogen, total phosphorous, turbidity and biological oxygen demand. Sites that correlated well with satellite imagery were in depths

Spectro-radiometers ASTER and MODIS - character of data, their accessibility and exploitability in area of environment

International Nuclear Information System (INIS)

Hlasny, T.; Bucha, T.; Rasi, R.

2005-01-01

In this presentation some basic information about spectro-radiometers ASTER and MODIS are presented. Relative wide opportunities of exploitation of these products in area of environment, their high spectral and in case of MODIS time resolution are discussed. These parameters create starting-point for building-up of regional monitoring systems of different biophysical characteristics of terrestrial ecosystems and monitoring of time and spatial variability. Next effort in this area should be aimed on development and optimisation of regional models based on monitoring of time and spatial changes of vegetable and foliar indexes (NDVI, EVI, LAI), photosynthetically active part of radiation absorbed by vegetation (FPAR) and likewise, as well as detail analyses of these data in context of global climatic changes. Perspectives of remote sensing earth in the Slovak republic are discussed

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

Science.gov (United States)

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

2017-01-01

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

Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.

Science.gov (United States)

Bonnefond, Amélie; Philippe, Julien; Durand, Emmanuelle; Dechaume, Aurélie; Huyvaert, Marlène; Montagne, Louise; Marre, Michel; Balkau, Beverley; Fajardy, Isabelle; Vambergue, Anne; Vatin, Vincent; Delplanque, Jérôme; Le Guilcher, David; De Graeve, Franck; Lecoeur, Cécile; Sand, Olivier; Vaxillaire, Martine; Froguel, Philippe

2012-01-01

Maturity-onset of the young (MODY) is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X). Here, we aimed to use whole-exome sequencing (WES) in a four-generation MODY-X family to identify a new susceptibility gene for MODY. WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing) was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay) of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130) present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11) co-segregated with diabetes in the family (with a LOD-score of 3.68). No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. Beyond neonatal diabetes mellitus (NDM), KCNJ11 is also a MODY gene ('MODY13'), confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS). Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.

Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.

Directory of Open Access Journals (Sweden)

Amélie Bonnefond

Full Text Available BACKGROUND: Maturity-onset of the young (MODY is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X. Here, we aimed to use whole-exome sequencing (WES in a four-generation MODY-X family to identify a new susceptibility gene for MODY. METHODOLOGY: WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. PRINCIPAL FINDINGS: By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130 present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11 co-segregated with diabetes in the family (with a LOD-score of 3.68. No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. CONCLUSIONS/SIGNIFICANCE: Beyond neonatal diabetes mellitus (NDM, KCNJ11 is also a MODY gene ('MODY13', confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS. Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.

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

Science.gov (United States)

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

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

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.

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

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

Science.gov (United States)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2A)

Science.gov (United States)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-MODIS_Edition2A)

Science.gov (United States)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2B)

Science.gov (United States)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

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

Science.gov (United States)

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

2013-01-01

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

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

A global examination of the response of ecosystem water-use efficiency to drought based on MODIS data.