Skip to main content
Advanced Search

Filters: Tags: MODIS (X)

88 results (10ms)   

Filters
Date Range
Extensions (Less)
Types (Less)
Contacts (Less)
Categories (Less)
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
In many places along the lower Colorado River, saltcedar (Tamarix spp) has replaced the native shrubs and trees, including arrowweed, mesquite, cottonwood and willows. Some have advocated that by removing saltcedar, we could save water and create environments more favourable to these native species. To test these assumptions we compared sap flux measurements of water used by native species in contrast to saltcedar, and compared soil salinity, ground water depth and soil moisture across a gradient of 200?1500 m from the river's edge on a floodplain terrace at Cibola National Wildlife Refuge (CNWR). We found that the fraction of land covered (fc) with vegetation in 2005?2007 was similar to that occupied by native...
thumbnail
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Some Cropland Data Layer states used Landsat 5 TM and/or Landsat 7 ETM+ satellite imagery to supplement the classification. Ancillary classification inputs include: the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer...
thumbnail
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
thumbnail
To analyze temporal trends, we disaggregated the change depicted by the 5-year forest loss hotspot map by identifying the year of maximum forest cover loss within the set of 5 annual intervals (2000-2001, 01-02, 02-03, 03-04 and 04-05). Taking into account the fact that the most important MODIS inputs for change detection within the regression tree models were for the growing season (June-August), we expected that change occurring during fall and winter might only be detected during the subsequent growing season. Hence, results reflect annual intervals from August of the preceding year to August of the following year. MODIS data alone are inadequate for accurate change area estimation because most forest clearing...
The TopoWx ("Topography Weather") gridded dataset contains historical 30-arcsec resolution (~800-m) interpolations of minimum and maximum topoclimatic air temperature for the conterminous U.S. Using both DEM-based variables and MODIS land skin temperature as predictors of air temperature, interpolation procedures include moving window regression kriging and geographically weighted regression. This temperature set was created independently of the NCCWSC funded project, "Can Camouflage Keep up with Climate Change? Connecting Downscaled Climate Models to Adaptation for a Key Forest Species", but was in part motivated by the project.
thumbnail
Locating meadow study sitesMeadow centers as recorded in the ‘Copy of sitecords_areaelev from Caruthers thesis.xls’ file delivered by Debinski in November 2012 were matched to polygons as recorded in files ‘teton97map_area.shp’ and ‘gallatin97map_area.shp’ both also delivered by Debinski in November 2012.In cases where the meadow center did not fall within a meadow polygon, if there was a meadow polygon of the same meadow TYPE nearby (judgment was used here), the meadow center was matched with the meadow polygon of same meadow TYPE. In total, 29 of 30 Gallatin meadow sites and 21 of 25 Teton meadow sites were positively located.Identifying meadow pixels for analysisThe native MODIS 250-meter grid was reprojected...
thumbnail
Locating meadow study sitesMeadow centers as recorded in the ‘Copy of sitecords_areaelev from Caruthers thesis.xls’ file delivered by Debinski in November 2012 were matched to polygons as recorded in files ‘teton97map_area.shp’ and ‘gallatin97map_area.shp’ both also delivered by Debinski in November 2012.In cases where the meadow center did not fall within a meadow polygon, if there was a meadow polygon of the same meadow TYPE nearby (judgment was used here), the meadow center was matched with the meadow polygon of same meadow TYPE. In total, 29 of 30 Gallatin meadow sites and 21 of 25 Teton meadow sites were positively located.Identifying meadow pixels for analysisThe native MODIS 250-meter grid was reprojected...
thumbnail
This dataset provides an estimate of 2015 cheatgrass percent cover in the northern Great Basin at 250 meter spatial resolution. The dataset was generated by integrating eMODIS NDVI satellite data with independent variables that influence cheatgrass germination and growth into a regression-tree model. Individual pixel values range from 0 to 100 with an overall mean value of 9.85 and a standard deviation of 12.78. A mask covers areas not classified as shrub/scrub or grass/herbaceous by the 2001 National Land Cover Database. The mask also covers areas higher than 2000 meters in elevation because cheatgrass is unlikely to exist at more than 2% cover above this threshold. Cheatgrass is an invasive grass that has invaded...
thumbnail
Some of the CYR rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - An aboveground live forest biomass map for the conterminous U.S., Alaska and Puerto Rico is derived from modeling field biomass estimates, collected nationwide by the USDA Forest Service Forest Inventory and Analysis (FIA) program, as functions of 250-m resolution satellite image products and other digital geographic layers....
thumbnail
The study's goal was to downscale 2013 250-m expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) to 30 m (Gu, Y. and Wylie, B.K., 2015, Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations, Remote Sensing of Environment, v. 171, p. 291-298)using 2013 Landsat 8 data. The eMODIS NDVI was downscaled for four periods: mid spring, early summer, late summer and mid fall. The objective was to capture phenologies during periods that correspond to 1) annual grass growth, 2) annual grass senescence, 3) the optimal NDVI profile separation between sagebrush and other shrubs in the region, and...
thumbnail
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
thumbnail
Abstract: This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center. Â Purpose: The purpose of this dataset is to portray broad distribution patterns of forest cover in the United States and provide input to national scale modeling projects. The data should not be displayed at scales smaller...
thumbnail
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, models were developed relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data...
thumbnail
This dataset provides an estimate of 2015 cheatgrass percent cover in the northern Great Basin at 250 meter spatial resolution. The dataset was generated by integrating eMODIS NDVI satellite data with independent variables that influence cheatgrass germination and growth into a regression-tree model. Individual pixel values range from 0 to 100 with an overall mean value of 9.85 and a standard deviation of 12.78. A mask covers areas not classified as shrub/scrub or grass/herbaceous by the 2001 National Land Cover Database. The mask also covers areas higher than 2000 meters in elevation because cheatgrass is unlikely to exist at more than 2% cover above this threshold. Cheatgrass is an invasive grass that has invaded...
thumbnail
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
thumbnail
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
thumbnail
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
thumbnail
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
thumbnail
These data are a compilation of four mask layers (regions), and enhanced vegetation indices calculated from airborne or satellite imagery. The mask layers were used created to extract satellite EVI data from the four airborne or satellite imagery datasets. The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. These data were created to compare Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared...
thumbnail
This dataset represents a summary of potential cropland inundation for the state of California applying high-frequency surface water map composites derived from two satellite remote sensing platforms (Landsat and Moderate Resolution Imaging Spectroradiometer [MODIS]) with high-quality cropland maps generated by the California Department of Water Resources (DWR). Using Google Earth Engine, we examined inundation dynamics in California croplands from 2003 –2020 by intersecting monthly surface water maps (n=216 months) with mapped locations of precipitation amounts, rice, field, truck (which comprises truck, nursery, and berry crops), deciduous (deciduous fruits and nuts), citrus (citrus and subtropical), vineyards,...


map background search result map search result map USDA, National Agricultural Statistics Service, 2009 Cropland Data Layer Wyoming US Forest Service - Forest Type Groups (Western US) US Forest Service -  FIA Forest Type Groups of the Southeastern United States Liberia woody above-ground biomass (tonnes/hectare) Gabon woody above-ground biomass (tonnes/hectare) Côte d'Ivoire woody above-ground biomass (tonnes/hectare) Angola woody above ground biomass (tonnes/hectare) Aboveground forest biomass (Mg/ha) for Alaska, USA US Forest Service - Forest Type Groups (Southeast US) Annual forest cover loss hotspot dataset for Boreal Forest biome (2000-2005) Hydrological Analysis of Greater Yellowstone Ecosystem Montane Meadow Condition using MODIS data Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 Estimating downscaled eMODIS NDVI using Landsat 8 in the central Great Basin shrub steppe An analysis of montane meadow drying in the Greater Yellowstone Ecosystem using remotely sensed NDVI from the MODIS period of record (lsp metrics) Enhanced Vegetation Index (EVI) parameter data products from Landsat 5, Landsat 8 MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS), Colorado River Delta, Mexico Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 BLM REA CYR 2013 Distribution of Woody Forest Biomass in the Central Yukon County-level maps of cropland surface water inundation measured from Landsat and MODIS Hydrological Analysis of Greater Yellowstone Ecosystem Montane Meadow Condition using MODIS data An analysis of montane meadow drying in the Greater Yellowstone Ecosystem using remotely sensed NDVI from the MODIS period of record (lsp metrics) USDA, National Agricultural Statistics Service, 2009 Cropland Data Layer Wyoming Liberia woody above-ground biomass (tonnes/hectare) Gabon woody above-ground biomass (tonnes/hectare) Côte d'Ivoire woody above-ground biomass (tonnes/hectare) Estimating downscaled eMODIS NDVI using Landsat 8 in the central Great Basin shrub steppe Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 County-level maps of cropland surface water inundation measured from Landsat and MODIS US Forest Service - Forest Type Groups (Western US) BLM REA CYR 2013 Distribution of Woody Forest Biomass in the Central Yukon US Forest Service - Forest Type Groups (Southeast US) Angola woody above ground biomass (tonnes/hectare) US Forest Service -  FIA Forest Type Groups of the Southeastern United States Aboveground forest biomass (Mg/ha) for Alaska, USA Annual forest cover loss hotspot dataset for Boreal Forest biome (2000-2005)