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Polygon locations of fire perimeters in the Sky Island mountain ranges in the Madrean Archipelago Ecoregion of the southwestern United States and northern Mexico. These fires occurred from 1985 to 2017 and were mapped using Landsat satellite imagery.
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Two UAS surveys were flown within the 2020 Glass fire extent designated as Glass 1 with 338 images and Glass 3 with 352. Both sites were flown at 50m AGL using a 3DR Solo with a Ricoh GR II in a nadir position. The imagery was processed in WebODM with the following parameters: mesh-octree-depth=13, orthophoto-resolution=1,pc-filter=0,pc-quality=ultra. An orthomosiac and height-above-ground (HAG) raster were derived from both photogrammetry projects. The raster data released herein is a selected area of interest from both study sites. The point clouds are the full, raw dense-clouds; the centroids point file is a collection of hand digitized locations of the in-situ plots from each study site; and the csv is the observed...
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This dataset provides location information and some limited attributes of known and potential ciénegas in the Madrean Archipelago ecoregion and closely surrounding area. This was created using point data and information provided by Dean Hendrickson and Thomas Minckley, combined with potential locations derived from analysis of classified raster land cover images and other specialized datasets. Ciénegas, as defined here, are wetlands in arid and semi-arid regions associated with groundwater or lotic components that ideally result in perennial waters on temporal scales of decades to centuries. Ciénegas are typically located at elevations ranging from 0 to 2000m. Ciénegas are typified by significant differences in...
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Distant tsunamis require short-notice evacuations in coastal communities to minimize threats to life safety. Given the available time to evacuate and potential distances out of hazard zones, coastal transportation planners and emergency managers can expect large proportions of populations to evacuate using vehicles. A community-wide, short-notice, distant-tsunami evacuation is challenging because it creates a sudden, significant, and concentrated demand on road-network systems. Transportation planners and emergency managers need methods to help them determine if a road network can handle an evacuation surge and if not, where interventions can best reduce overall clearance times. We use the coastal community of Bay...
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This dataset contains hydrological data collected at a series of leaky weirs on a working ranchland site in a semiarid ecosystem in Cochise County, Arizona, from 2018-2020. Leaky weirs are a type of structure being experimented with by land managers in aridlands to reduce peak flow events and increase recharge to the aquifer. The weirs are constructed of rock cemented into place in areas of exposed bedrock within the channel are built to allow for water to leak through slowly. Three sites were instrumented for monitoring, one control and two sites treated with ‘leaky weirs’. At each site, at least one pressure transducer was installed in a piezometer to measure water level. Each site also had multiple “3-in-1” gauges,...
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This tabular, machine-readable CSV file contains annual phenometrics at locations in ponderosa pine ecosystems across Arizona and New Mexico that experienced stand-clearing, high-severity fire. The locations represent areas of vegetative recovery towards pre-fire (coniferous/pine) vegetation communities or towards novel grassland, shrubland, or deciduous replacements. Each sampled area is associated with the point location (latitude/longitude) as well as multiple calendar year phenometrics derived from the time-series of normalized difference vegetation index (NDVI) values in the phenology software package Timesat v3.2.
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Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the central Cascade Mountain area, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest patches identified in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras...
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Annual (1986-2020) land-use/land cover maps at 30-meter resolution of the Tucson metropolitan area, Arizona and the greater Santa Cruz Watershed including Nogales, Sonora, Mexico. Maps were created using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier in Google Earth Engine. The maps contain 13 classes based on the National Land Cover Classification scheme and modified to reflect local land cover types. Data are presented as a stacked, multi-band raster with one "band" for each year (Band 1 = 1986, Band 2 = 1987 and so on). Note that the year 2012 was left out of our time series because of lack of quality Landsat data....
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We produced a time series of maps of habitat structure within wetlands of the Central Valley of California. The structure of open water and tall emergent vegetation, such as Typha spp. and Schoenoplectus spp., is critical for migratory birds. Through field observation and digitization of high resolution imagery we identified the locations of tall emergent vegetation, water, and other land cover. Using a random forest classification, we classified multispectral Landsat 8 imagery 2013-2017. We used images from the fall when most wetlands are flooded and the summer to separate trees and tall emergent vegetation. The final maps show the distribution and extent of tall emergent vegetation within wetlands. Final time...
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We produced a series of maps of moist soil seed plants within managed wetlands in the Central Valley of California from 2007-2011 & 2013-2017. Moist soil seed plants, such as swamp timothy (Crypsis schoenoides) and watergrass (Echinochloa crusgallim), are a critical food source for migratory birds. Vegetation maps were created by classifying Landsat imagery from 2007-2011 and 2013-2017. A support vector machine learning classifier was trained using phenology metrics of moist soil seed plants, emergent vegetation, water, and other land cover observed via field surveys and high resolution imagery. Productivity maps of swamp timothy were based on a regression model of seed head weight with Landsat vegetation indices....
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Distant tsunamis require short-notice evacuations in coastal communities to minimize threats to life safety. Given the available time to evacuate and potential distances out of hazard zones, coastal transportation planners and emergency managers can expect large proportions of populations to evacuate using vehicles. A community-wide, short-notice, distant-tsunami evacuation is challenging because it creates a sudden, significant, and concentrated demand on road-network systems. Transportation planners and emergency managers need methods to help them determine if a road network can handle an evacuation surge and if not, where interventions can best reduce overall clearance times. We use the coastal community of Bay...
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This data release comprises the raster data files and code necessary to perform all analyses presented in the associated publication. The 16 TIF raster data files are classified surface water maps created using the Dynamic Surface Water Extent (DSWE) model implemented in Google Earth Engine using published technical documents. The 16 tiles cover the country of Cambodia, a flood-prone country in Southeast Asia lacking a comprehensive stream gauging network. Each file includes 372 bands. Bands represent surface water for each month from 1988 to 2018, and are stacked from oldest (Band 1 - January 1988) to newest (Band 372 - December 2018). DSWE classifies pixels unobscured by cloud, cloud shadow, or snow into five...
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The USGS, in cooperation with the U.S. Fish and Wildlife Service and the National Fish and Wildlife Foundation, compiled a map of geomorphic and vegetation features along a 140-km segment of the main stem Klamath River below Iron Gate Dam, CA. Flood disturbance within the study reach is produced by the combined effect of natural flows and reservoir releases. The physical response of the Klamath River to flood disturbance is strongly dependent upon sediment storage in bars and floodplains. The map provides a summary of channel and riparian vegetation classes that were used to estimate vegetation change over time due to sediment flow and storage in bars and floodplains. Study results will be useful for interpreting...
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The USGS, in cooperation with the U.S. Fish and Wildlife Service and the National Fish and Wildlife Foundation, compiled a map of geomorphic and vegetation features along a 140-km segment of the main stem Klamath River below Iron Gate Dam, CA. Flood disturbance within the study reach is produced by the combined effect of natural flows and reservoir releases. The physical response of the Klamath River to flood disturbance is strongly dependent upon sediment storage in bars and floodplains. The map provides a summary of channel and riparian vegetation classes that were used to estimate vegetation change over time due to sediment flow and storage in bars and floodplains. Study results will be useful for interpreting...
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USGS researchers with the Patterns in the Landscape – Analyses of Cause and Effect (PLACE) project are releasing a collection of high-frequency surface water map composites derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Using Google Earth Engine, the team developed customized image processing steps and adapted the Dynamic Surface Water Extent (DSWE) to generate surface water map composites in California for 2003-2019 at a 250-m pixel resolution. Daily maps were merged to create 6, 3, 2, and 1 composite(s) per month corresponding to approximately 5-day, 10-day, 15-day, and monthly products, respectively. The resulting maps are available as downloadable files for each year. Each...
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Here we provide information for the PlanetScope and d Deutsches Zentrum fur Luft- und Raumfahrt (DLR) Earth Sensing Imaging Spectrometer (DESIS) Derived Spectral Library of Agricultural Crops in California which was developed using PlanetScope Dove-R high spatial resolution data and DESIS hyperspectral data acquired for 2020. PlanetScope images are available through Planet Labs (2022). The DESIS images used for this dataset are available through the German Aerospace Center and Teledyne Brown (2022). The crop type data and confidence layer for 2020 can be accessed through the United States Department of Agriculture National Agricultural Statistics Service (2022). The PlanetScope and DESIS Derived Spectral Library...
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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,...
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This dataset supports the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States" (DOI:10.1016/j.rse.2020.112013). The data release allows users to replicate, test, or further explore results. The dataset consists of 4 separate items based on the analysis approach used in the original publication 1) the 'Phenocam' dataset uses images from a phenocam in a pinyon juniper ecosystem in Grand Canyon National Park to determine phenological patterns of multiple plant species. The 'Phenocam' dataset consists of scripts and tabular data developed while performing analyses and includes the final NDVI values for all areas...
This dataset consists of raster geotiff and tabular outputs of annual map projections of land use and land cover for the California Central Valley for the period 2011-2101 across 5 future scenarios. Four of the scenarios were developed as part of the Central Valley Landscape Conservation Project. The 4 original scenarios include a Bad-Business-As-Usual (BBAU; high water, poor management), California Dreamin’ (DREAM; high water, good management), Central Valley Dustbowl (DUST; low water, poor management), and Everyone Equally Miserable (EEM; low water, good management). These scenarios represent alternative plausible futures, capturing a range of climate variability, land management activities, and habitat restoration...
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As part of a 2018 Northwest Climate Adaptation and Science Center project, USGS researchers are releasing a series of spatially-explicit land-cover projections for the period 2018-2050 covering part of the northern Great Basin (Beaty Butte Herd Management Area, Hart Mountain National Antelope Refuge, and Sheldon National Refuge). The dataset contains an empirically-based business-as-usual (BAU) and an RCP8.5 climate change scenario executed for shrub, herbaceous, and bare cover types. Each scenario is executed 30 times (i.e. Monte Carlo simulations) to account for variability across historical change estimates derived from annual fractional cover maps generated by the National Land Cover Database. The map dates...


map background search result map search result map Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA Wetland Habitat Structure Maps for the Central Valley of California 2013-2017 Wetland Moist Soil Seed Maps for the Central Valley of California 2007-2017 Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires Implementation of a Surface Water Extent Model using Cloud-Based Remote Sensing - Code and Maps Spatially-explicit land-cover scenarios of federal lands in the northern Great Basin: 2018-2050 Data release associated with the journal article "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States" Mapped fire perimeters from the Sky Island Mountains of US and Mexico: 1985-2017 Vehicular Demand estimation for short-notice, distant-tsunami evacuation of Bay Farm Island, CA Hydrologic Data Collected at Leaky Weirs, Cienega Ranch, Willcox, AZ (March 2019 - October 2020) Sediment mobility and river corridor assessment for a 140-km segment of the mainstem Klamath River below Iron Gate Dam, CA - vegetation mapping 2005 Sediment mobility and river corridor assessment for a 140-km segment of the mainstem Klamath River below Iron Gate Dam, CA - vegetation mapping 2009 DSWEmod surface water map composites generated from daily MODIS images - California Integrated modeling of climate and land change impacts on future dynamic wetland habitat – a case study from California’s Central Valley Spatial Database of Known and Potential Ciénegas in the Greater Madrean Archipelago Ecoregion Annual (1986-2020) land-use/land cover maps of the Santa Cruz Watershed and Tucson metropolitan area, Arizona PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season County-level maps of cropland surface water inundation measured from Landsat and MODIS Post-fire burn severity metrics from 2020 Glass fire in northern California from UAS surveys Hydrologic Data Collected at Leaky Weirs, Cienega Ranch, Willcox, AZ (March 2019 - October 2020) Vehicular Demand estimation for short-notice, distant-tsunami evacuation of Bay Farm Island, CA Post-fire burn severity metrics from 2020 Glass fire in northern California from UAS surveys PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season Spatially-explicit land-cover scenarios of federal lands in the northern Great Basin: 2018-2050 Annual (1986-2020) land-use/land cover maps of the Santa Cruz Watershed and Tucson metropolitan area, Arizona Spatial Database of Known and Potential Ciénegas in the Greater Madrean Archipelago Ecoregion Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA Mapped fire perimeters from the Sky Island Mountains of US and Mexico: 1985-2017 Integrated modeling of climate and land change impacts on future dynamic wetland habitat – a case study from California’s Central Valley Implementation of a Surface Water Extent Model using Cloud-Based Remote Sensing - Code and Maps Wetland Habitat Structure Maps for the Central Valley of California 2013-2017 Wetland Moist Soil Seed Maps for the Central Valley of California 2007-2017 Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires County-level maps of cropland surface water inundation measured from Landsat and MODIS DSWEmod surface water map composites generated from daily MODIS images - California Data release associated with the journal article "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States"