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This dataset is the second (2013) of two 500-meter land use land cover (LULC) time-periods datasets (2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Cape Verde,
Capo Verde,
biota,
land cover,
land use,
Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) to model natural and semi-natural vegetation. Landcover classes are drawn from NatureServe's Ecological System concept, with 109 of the 125 total classes mapped at the system level. For the majority of classes, a decision tree classifier was used to discriminate landcover types, while a minority of classes (e.g. urban classes, sand dunes, burn scars, etc.) were mapped using other techniques. Twenty mapping areas, each characterized by similar ecological and spectral characteristics, were modeled independently of one another. These mapping...
Categories: Web Site;
Tags: data,
data downloading (usgs),
digital elevation models,
landcover,
mapping,
This dataset shows Marinas within the Gulf of Mexico
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Alabama,
Aransas County,
Baldwin County,
Boat,
Boat Ramps,
A map of actual vegetation cover of Oregon was developed as part of the Oregon Gap Analysis Program, a project of the Idaho Cooperative Fish and Wildlife Research Unit, in cooperation with the Oregon Department of Fish and Wildlife and the Oregon Natural Heritage Program. The Idaho Geographic Information Center of the Idaho Department of Water Resources digitized the original maps and subsequent four edits using ARC/INFO GIS software. The digital data layer has been deposited at the Oregon GIS Service Center, Department of Energy, 625 Marion St., N.E., Salem, Oregon 97310. LANDSAT Multi-Spectral Scanner false-color infrared positive prints at a scale of 1:250,000 were visually photo-interpreted to identify boundaries...
Advanced very high resolution radiometer (AVHRR) satellite data were acquired and composited into 14 day periods from 31 March 2000 to 12 October 2000 to map vegetation characteristics over the Alaskan landscape. Unique spatial and temporal qualities of the AVHRR data provide information that leads to a better understanding of regional biophysical characteristics of vegetation communities and patterns. These data provided synoptic views of the landscape and depicted phenological diversity, temporal vegetation phenology (green-up, peak of green, and senescence), photosynthetic activity, and regional landscape patterns. Products generated from the AVHRR composited data include a number of phenological datasets as...
This dataset shows the Land-Use/ Land-Cover of the Crown of the Continent with a 50km buffer.This dataset was developed by the Crown Managers Partnership, as part of a transboundary collaborative management initiative for the Crown of the Continent Ecosystem, based on commonly identified management priorities that are relevant at the landscape scale. The CMP is collaborative group of land managers, scientists, and stakeholder in the CCE. For more information on the CMP and its collaborators, programs, and projects please visit: http://crownmanagers.org/The optimal land cover products available for the CCE are the Canadian land cover distributed by GeoBase and MSDI Montana Land Use/Land Cover Datadistributed by...
Potential pollinator habitat was derived by ranking land use classifications and grassland quality based on ground truthing and remotely sensed features indicative of remnant prairie. High resolution (10m) land use data served as the basemap (Hartley et al 2017) from which most categories were identified. All known prairie remnants, prairie plantings, and clusters of mima mounds were delineated. Mima mounds were detected by deriving a slope at 1m scale with greater than 5% from high resolution LiDar data (3m). Mima mounds are indicative of areas in which the topsoil has not been significantly disturbed, and therefore have a higher potential to contain native prairie vegetation. Based on an in-depth literature review...
Categories: Data;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Landcover,
Landuse,
USGS Science Data Catalog (SDC),
coastal Louisiana,
environment,
The vegetation and landcover of Valley Forge National Historical Park (VAFO) were mapped to the association level of the National Vegetation Classification System developed by The Nature Conservancy and network of Natural Heritage Programs. The mapping process was based on the USGS-NPS Vegetation Mapping Program with some modifications due to the size of the mapped polygons. A total of 308 plots were used to assess the thematic accuracy of the database.The estimated overall thematic accuracy of the database is 81.20 percent. At a 90 percent confidence interval, the estimated minimum overall thematic accuracy is 77.40 percent and the estimated maximum is 85.00 percent. Based on hypothesis testing, the final association...
Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept, with 109 of the 125 total classes mapped at the system level. For the majority of classes, a decision tree classifier was used to discriminate landcover types, while a minority of classes (e.g. urban classes, sand dunes, burn scars, etc.) were mapped using other techniques. Twenty mapping areas, each characterized by similar ecological and spectral characteristics,...
One of the determinants of runoff is the occurrence of excess rainfall events where rainfall rates exceed the infiltration capacity of soils. To help understand runoff risks, we calculated the probability of excess rainfall events across the Hawaiian landscape by comparing the probability distributions of projected rainfall frequency and land cover-specific infiltration capacity. We characterized soil infiltration capacity based on different land cover types (bare soil, grasses, and woody vegetation) and compared them to the frequency of large rainfall events under current and future (pseudo-global warming) climate scenarios. Here we provide a raster stack that contain the probability of excess rainfall exceeding...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Shift,
Ecohydrology,
Hawai’i,
Infiltration,
Landcover,
Sea level rise caused by climate change is an ongoing phenomenon and a concern both locally and worldwide. Low-lying coastal areas are particularly at risk to flooding and inundation, affecting a large proportion of the human population concentrated in these areas as well as natural communities-particularly animal species that depend on these habitats as a key component of their life cycle. While more local, state, and federal governments have become concerned with the potential effects that predicted sea levels will have on their communities and coastal landscapes, more information is needed on the potential effects that changes in sea level will have on coastal habitats and species.ehensive Habitat Type Dataset...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
Academics & scientific researchers,
BIOLOGICAL CLASSIFICATION,
BIRDS,
CRANES AND ALLIES,
Sea level rise caused by climate change is an ongoing phenomenon and a concern both locally and worldwide. Low-lying coastal areas are particularly at risk to flooding and inundation, affecting a large proportion of the human population concentrated in these areas as well as natural communities-particularly animal species that depend on these habitats as a key component of their life cycle. While more local, state, and federal governments have become concerned with the potential effects that predicted sea levels will have on their communities and coastal landscapes, more information is needed on the potential effects that changes in sea level will have on coastal habitats and species.ehensive Habitat Type Dataset...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
Academics & scientific researchers,
BIOLOGICAL CLASSIFICATION,
The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 NAIP dataset (1m) as the basemap, E-Cognition image objects were derived from the multiresolution segmentation algorithm at 75 and 250 segments. Attempts to refine the data training methods using E-cognition, to extrapolate automating categories of this information to the entire map resulted with exceedingly low accuracy. Therefore, a raster was produced by piecing together several data resources, which provide reliable data for specific LULC categories. This process involved stitching together more reliable sources for specific categories to apply to higher resolution (75) segmentation product....
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2015,
Complete,
Data,
EARTH SCIENCE,
EARTH SCIENCE > LAND SURFACE,
These data were compiled to provide satellite remote sensing observations of landcover in the vicinity of wetlands fed by geothermal springs in Dixie Meadows, Nevada, USA. Objectives of the study were to map landcover of water, vegetation, and soil between October 5, 2015, and January 21, 2022, using available imagery from the Sentinel-2 mission. The U.S. Geological Survey's Southwest Biological Science Center (SBSC) and Grand Canyon Monitoring and Research Center (GCMRC) processed 110 Sentinel-2 satellite images representing bottom of atmosphere surface reflectance and classified them within Google Earth Engine (GEE) using threshold values of the Green Normalized Difference Vegetation Index (gNDVI) and its inverse...
Categories: Data;
Tags: Bureau of Land Management Lands,
Churchill County,
Department of Defense Lands,
Dixie Meadows,
Dixie Valley,
NWFP-20 - Northwest Forest Plan Effectiveness Monitoring (20-Year Report)Estimated completion June 2015This project is a continuation of research completed for the 15-year Report for NWFP Effectiveness Monitoring. We are continuing to develop and refine modeling techniques and data, to provide improved multi-date GNN maps of forest vegetation and older forest. Key improvements to GNN modeling to be implemented in this project are: (1) addition of more inventory plots, with yearly matching of plots to LandTrendr imagery for model development; (2) incorporation of measures of disturbance history, derived from LandTrendr algorithms, as spatial predictors; (3) improved GNN outlier analysis using TimeSync; and (4) additional...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: BLM,
Bureau of Land Management,
CA,
CLAMS,
CMONster,
Raster file of snow cover index at 30m pixel level developed from path36: 14 March, path 35: 1998, 3730: 2 February, 1986, and 1 February, 1998, Landsat images. These images were classified separately and then mosaicked together. Extent corresponds to the area of the Central Wyoming and Lander Extent mapping boundary. Snow classification ranges across five classes from 'No Snow' as class 1 and 'Complete Snow Coverage' as class 5.
This dataset is the second (circa 2000) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Gambia,
Land Cover,
Land Use,
biota,
land cover,
This study addressed the potential ability to link landscape indices to stream water quality in a predominately agricultural landscape located in the Mississinewa River watershed, East-Central Indiana. A methodology for developing and analyzing landscape indices using a GIS and remotely sensed and geospatial data was applied to 30 Hydrologic Unit Code (HUC) 14-digit subwatersheds. Six indices, three representing natural area extent characteristics and three representing natural area disturbance characteristics were developed. The resulting indices were then tested to determine if they could be linked to water quality variables (Total Phosphorus, Nitrate, E.COLI, and macroinvertebrate [EPT/C] Ephemeroptera, Plecoptera,...
Categories: Publication;
Types: Citation;
Tags: Data Visualization & Tools,
GIS,
Indiana,
Landcover,
Landscapes,
This landcover raster was generated through a Random Forest predictive model developed in R using a combination of image-derived and ancillary variables, and field-derived training points grouped into 18 classes. Overall accuracy, generated internally through bootstrapping, was 72.7%. A series of post-modeling steps brought the final number of land cover classes to 28.
Categories: Data;
Types: Citation;
Tags: Birds,
CMR,
Charles M. Russell National Wildlife Refuge,
Data Visualization & Tools,
Landcover,
Some of the SNK 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. - The classification of local-scale ecosystems (ecotypes) combines physiography (e.g., riverine, coastal), topography (DEM), geology and vegetation from the landcover spectral database derived from the satellite image processing. These layers are used to model ecotypes in a way that best partitions geomorphic, hydrologic, pedologic,...
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