Skip to main content
Advanced Search

Filters: Tags: satellite (X)

42 results (7ms)   

Filters
Contacts (Less)
View Results as: JSON ATOM CSV
thumbnail
Satellite imagery showing parts of the Alaska Gulf, Copper River and Cook Inlet regions. Mountains are snow capped. Identified are Mounts Wrangell, Sanford, Drum, Spurr and Hayes Volcano. Alaska n.d.
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
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
These data can be used in a geographic information system (GIS) for any number of purposes such as assessing wildlife habitat, water quality, pesticide runoff, land use change, etc. The State data sets are provided with a 300 meter buffer beyond the State border to faciliate combining the State files into larger regions. The user must have a firm understanding of how the datasets were compiled and the resulting limitations of these data. The National Land Cover Dataset was compiled from Landsat satellite TM imagery (circa 1992) with a spatial resolution of 30 meters and supplemented by various ancillary data (where available). The analysis and interpretation of the satellite imagery was conducted using very large,...
thumbnail
This dataset provides a near-real-time estimate of 2018 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through July 1, 2018. This is the second iteration of an early estimate of herbaceous annual cover for 2018 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/P9KSR9Z4). The pixel values for this most recent estimate ranged from 0 to100% with...
thumbnail
The Sea Surface Temperature (SST) data of the nearshore region of the North Pacific show temperature ranges in degrees C using points whose locations correspond to the centroids of AVHRR Pathfinder version 5 monthly, global, 4 km data set (PFSST V50). The pathfinder rasters are available from the Physical Oceanography Distributed Active Archive Center (PO.DAAC), hosted by NASA JPL. The data points in this dataset lie within a 20 km buffer from the GSHHS (Global Self-consistent, Hierarchical, High-resolution Shoreline) coastline. The GSHHS vector data are available from the National Geophysical Data Center (NGDC). Furthermore, each point in the SST dataset is categorized by the ecoregion in which it is located. This...
thumbnail
The introduction of exotic plant species into the western United States has caused substantial changes to rangeland disturbance regimes and ecosystem structure and function. For example, exotic annual grass (EAG) invasion in western rangelands has increased wildfire frequency, which greatly reduces rangeland ecosystem diversity and leads to single-species dominance in many areas. Rangeland monocultures do not provide optimal carbon sequestration and other environmental processes necessary to sustain historically normal ecosystem structure, including the ecological diversity needed to support sagebrush obligates like Greater Sagegrouse, pygmy rabbit, and pronghorn. These obligates, as well as others, require contiguous,...
thumbnail
This data release consists of a video and individual image frames extracted from the original high frame rate video and used to derive remotely sensed estimates of surface flow velocity via particle image velocimetry (PIV). These data were acquired from the Tanana River near Nenana, Alaska, on July 14, 2020. The video was obtained from a satellite operated by Planet Labs as part of the SkySat constellation. The original video was recorded at 30 frames per second and is provided in a compressed, lower-resolution .mp4 format video file for viewing. In addition, Planet Labs provided the individual frames comprising the video as full resolution TIFF images. This data release consists of individual frames extracted...
thumbnail
The dataset provides a near real time estimation of 2020 herbaceous mostly annual fractional cover predicted on July 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P96PVZIF., Boyte et al. 2018 https://doi.org/10.5066/P9RIV03D.), but starting this year we are mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation,...
The Hydrologic Remote Sensing Branch (HRSB) community is intended to host remote sensing technology datasets and information products to help WMA and Water Science Center (WSC) staff more safely and effectively gage streams, monitor water quality, and measure the hydrologic cycle.
thumbnail
The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.org/10.5066/F71J98QK). This model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. A second model was developed that did not include the mean of 17-years of annual herbaceous percent cover, and this model's test mean error rate (n = 1670), based...
The goal of this project is to create critically needed coastal fog datasets. Anticipated products from the collaboration between on-the-ground natural resource managers and a multidisciplinary coalition of physical scientists are: 1) a compilation of existing fog related data from multiple sources: satellite (AVHRR, GOES, Modis, Landsat), NOAA buoy , and airport and meteorological stations, 2) USGS Open File report documenting the results of a multiday working session with climatologists, remote sensing specialists, fog modelers, statisticians, and natural resource managers, convened to review the data, examine and assess the correlations between data streams and models, specify initial parameters to be extracted...
Categories: Data, Project; Tags: 2011, California Landscape Conservation Cooperative, California coast, Coastal, Coastal, All tags...
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 Story Map Journal discusses broad-scale data available for various natural resource topics. Links to download broad-scale data are provided in the discussion text. The interactive web maps depict examples of broad-scale data made publicly available and served by the various organizational owners of the data.
Types: Map Service; Tags: Aerial, Air Quality, BISON, BLM, Biodiversity Information Serving Our Nation, All tags...
thumbnail
This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=b0817400a441487baf1409580acc6620 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low-latitude, hemispheric storage generally occur too early in the models, and model-specific errors in amplitude of the low-latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation...
The Sea Surface Temperature (SST) data of the nearshore region of the North Pacific show temperature ranges in degrees C using points whose locations correspond to the centroids of AVHRR Pathfinder version 5 monthly, global, 4 km data set (PFSST V50). The pathfinder rasters are available from the Physical Oceanography Distributed Active Archive Center (PO.DAAC), hosted by NASA JPL. The data points in this dataset lie within a 20 km buffer from the GSHHS (Global Self-consistent, Hierarchical, High-resolution Shoreline) coastline. The GSHHS vector data are available from the National Geophysical Data Center (NGDC). Furthermore, each point in the SST dataset is categorized by the ecoregion in which it is located. This...
thumbnail
Groundwater storage depletion is a critical issue for many of the major aquifers in the U.S., particularly during intense droughts. The GRACE (Gravity Recovery and Climate Experiment) satellites launched in 2002, with sensors designed to measure changes in the Earth’s gravitational field at large spatial scales (≥ ~200,000 km2). These changes are primarily driven by changes in water storage on the Earth’s surface. Estimates of groundwater storage changes based on these gravity measurements have attracted considerable media attention in the U.S. and globally. However, groundwater storage changes are computed indirectly by subtracting snow, surface water, and soil moisture storage from the total water storage monitored...


map background search result map search result map National Land Cover Data Set 1992 for Wyoming 30 meter Aboveground forest biomass (Mg/ha) for Alaska, USA Puerto Rico biomass error map Aboveground forest biomass (Mg/ha) for the eastern USA Estimating downscaled eMODIS NDVI using Landsat 8 in the central Great Basin shrub steppe Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2018 Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) BLM NOC Sources of Broad-Scale Data by Agency Story Map BLM NOC Sources of Broad-Scale Data by Topic Story Map Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Satellite video and individual image frames from the Tanana River, Alaska, July 14, 2020, for Particle Image Velocimetry Satellite video and individual image frames from the Tanana River, Alaska, July 14, 2020, for Particle Image Velocimetry Puerto Rico biomass error map National Land Cover Data Set 1992 for Wyoming 30 meter Estimating downscaled eMODIS NDVI using Landsat 8 in the central Great Basin shrub steppe Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2018 Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Aboveground forest biomass (Mg/ha) for Alaska, USA Aboveground forest biomass (Mg/ha) for the eastern USA BLM NOC Sources of Broad-Scale Data by Topic Story Map BLM NOC Sources of Broad-Scale Data by Agency Story Map