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This data set provides a polygon shapefile delineating relatively large, slow-moving (4-17 cm/year in the radar line-of-sight direction) landslides in the continental U.S. western coastal states (California, Oregon, and Washington). The polygons also are provided in a Google Earth .kmz file. Delineated landslides were identified from displacement signals captured by InSAR (Interferometric Synthetic Aperture Radar) interferograms of ALOS PALSAR (Advanced Land Observing Satellite; Phased Array type L-band Synthetic Aperture Radar) images between 2007 and 2011, and ALOS-2 PALSAR-2 images between 2015 and 2019. The ALOS PALSAR images utilized cover the three states entirely; the ALOS-2 PALSAR images utilized cover primarily...
Near-surface site characteristics are critical for accurately modeling ground motion, which in turn influences seismic hazard analysis and design of critical infrastructure. Currently, there are many strong motion accelerometers within the Advanced National Seismic System (ANSS) that are missing this information. We use a Geographic Information Systems (GIS) based framework to intersect the site coordinates of approximately 5,500 ANSS accelerometers located throughout the United States and its territories with geology and velocity information. We consider: (1) surficial geology from digitized geologic maps (Horton, 2017; Wilson et al., 2015; Sherrod et al., 2007; Bawiec, 1999; Saucedo, 2005; Bedrossian et al., 2012;...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANSS,
Alabama,
American Samoa,
Arizona,
Arkansas,
The LCMAP Hawaii Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products for Hawaii. The LCMAP Hawaii Reference Data Product includes the collection of an independent dataset of 600 30-meter by 30-meter plots across Hawaii. This dataset was collected via manual image interpretation to aid in validation of the land cover and land cover change products as well as area estimates. The LCMAP Reference Data Product collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across Hawaii from 2000–2019.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: LCMAP,
Land Change Monitoring, Assessment, and Projection,
Land Use Change,
Remote Sensing,
USGS Science Data Catalog (SDC),
The LCMAP Intensification Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Intensification Reference Data Product includes the collection of an independent dataset of 2,000 30-meter by 30-meter plots selected via stratified random sampling across the conterminous United States (CONUS). This dataset was collected via manual image interpretation to aid in validation of the land cover and land cover change products as well as area estimates. The LCMAP Intensification Reference Data Product collected variables related to primary and secondary land use, primary and secondary land cover(s),...
Categories: Data;
Tags: Conterminous United States (CONUS),
LCMAP,
Land Change Monitoring, Assessment, and Projection,
Land Use Change,
Landsat,
Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2018
This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2018), with the data processed through September 30, 2018. The primary data for water year 2018 (a water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends) were downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2018) and processed following the guidelines documented in Over and others (2010). Daily potential evapotranspiration (PET) is computed from average daily air temperature, average daily dewpoint temperature, daily total wind speed, and daily total solar radiation, and disaggregated to hourly PET by using the...
LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
This data release contains time-lapse imagery taken at U.S. Geological Survey (USGS) stream gaging stations with associated hydrologic and meteorological data related to each image. These data are to help improve the development of models in detecting water elevation at a given stream gaging station. Images of the water surface and surroundings at USGS stream gaging stations were taken at varying time intervals ranging between every five minutes to an hour. Cameras used include trail cameras, web cameras, and the custom river imagery sensing (RISE) camera. Time-lapse images for each USGS stream gaging station are provided in compressed files (file extension .7z). These files are named in a format to identify the...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Remote Sensing,
USGS Science Data Catalog (SDC),
Water Resources,
camera,
image,
These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
Accurate and consistent estimates of shrubland ecosystem components are crucial to a better understanding of ecosystems condition in arid and semiarid lands. We developed an innovative approach by integrating multiple information to quantify shrubland components as continuous field products within the National Land Cover Database (NLCD). The approach consists of five major parts: field sample collection, high-resolution mapping of shrubland components using WorldView-3 imagery and regression tree models, Landsat 8 radiometric balancing and phenological mosaicking, coarse resolution estimate of shrubland components across a large geographic extent using Landsat 8 phenological mosaics and regression tree models, and...
Accurate and consistent estimates of shrubland ecosystem components are crucial to a better understanding of ecosystems condition in arid and semiarid lands. We developed an innovative approach by integrating multiple information to quantify shrubland components as continuous field products within the National Land Cover Database (NLCD). The approach consists of five major parts: field sample collection, high-resolution mapping of shrubland components using WorldView-3 imagery and regression tree models, Landsat 8 radiometric balancing and phenological mosaicking, coarse resolution estimate of shrubland components across a large geographic extent using Landsat 8 phenological mosaics and regression tree models, and...
U.S. Geological Survey (USGS) scientists completed a multidisciplinary data collection effort during the week of October 21-25, 2019, using new technologies to map and validate bathymetry over a large stretch of the non-tidal Potomac River. The work was initiated as an effort to validate commercially-acquired topobathymetric light detection and ranging (lidar) data funded through a partnership between the USGS and the Interstate Commission on the Potomac River Basin (ICPRB). The goal was to compare airborne lidar data to bathymetric data collected through more traditional means (boat-based sonar, wading Real Time Kinematic Global Navigational Satellite System (RTK-GNSS) surveys) and through unmanned aerial systems...
This data release contains data used in an associated publication: Petrakis, R.E., Norman, L.M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., and Pulliam, H.R., 2021, Hierarchical Clustering for Paired Watershed Experiments: Case Study in Southeastern Arizona, U.S.A.: Water, v. 13, no. 21, p. 2955, https://doi.org/10.3390/w13212955. The overarching effects and benefits of land management decisions, such as through watershed restoration, are often not fully understood due to a lacking control within an experimental design. This can be addressed through the application of a paired watershed approach, allowing for comparison between treatment and control watersheds. We developed and applied a statistic-based...
This USGS data release represents field surveyed elevation points and source lidar points used to develop an objective method for estimating boundary roughness from publicly available elevation data. Also included is the Python script written to execute a routine to convert a 1 meter digital elevation model into a 1 meter boundary roughness raster. This data set has two separate items: 1. The Supplemental Information used to validate the bare earth surface within a forested floodplain. 2. The Python script and associated ArcGIS toolbox
The geographic information system (GIS) format spatial data set of vegetation for Apostle Islands National Lakeshore (APIS) was created for the National Park Service (NPS) Vegetation Inventory Program (VIP). The APIS covers an area of approximately 28,972 ha (71,591 acres). The map classification scheme used to create the vegetation data set is designed to represent local vegetation types at the finest level possible using the National Vegetation Classification (NVC) Standard (Vr 2). Physiognomic information was also recorded, including height (woody vegetation), canopy density, and coverage patterns. The vegetation data set was developed by interpreting aerial photographs collected in 2004 and extensive field surveys....
This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface-water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface-water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface-water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine...
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