Filters: Tags: usfs (X)
472 results (69ms)|
Filters
Date Range
Extensions
Types Contacts
Categories Tag Types Tag Schemes |
Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2019; Station AMTSF01
This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 26 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
This dataset includes magnetotelluric (MT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and audiomagnetotellurics, the USGS collected MT data at 24 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2019; Station AMTKM01
This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 26 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
Audiomagnetotelluric sounding data in the Silverton Caldera complex, Colorado, 2019; Station AMTAG06
This dataset includes audiomagnetotelluric (AMT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and magnetotellurics, the USGS collected AMT data at 26 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
This dataset includes magnetotelluric (MT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and audiomagnetotellurics, the USGS collected MT data at 24 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
This dataset includes magnetotelluric (MT) sounding data collected in July 2019 in the Silverton Caldera complex, Colorado, in the Southern Rocky Mountain Volcanic Field, by the U.S. Geological Survey (USGS). Along with geologic mapping, airborne magnetics, airborne electromagnetics, and audiomagnetotellurics, the USGS collected MT data at 24 sites along five profiles ranging from 2 to 5 kilometers in length: across Red Mountain of the Silverton caldera, within the caldera in Eureka Graben, across the south-eastern margin of the caldera along Arrastra Gulch, across the southern margin of the caldera along the western margin of Kendall Mountain, and across the south-western margin of the caldera along South Fork...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
LANDFIRE disturbance data are developed to provide temporal and spatial information related to landscape change for determining vegetation transitions over time and for making subsequent updates to LANDFIRE vegetation, fuel and other data. Disturbance data include attributes associated with disturbance year, type, and severity. These data are developed through use of Landsat satellite imagery, local agency derived disturbance polygons, and other ancillary data. DATA SUMMARY: The disturbance data are developed through a multistep process. Inputs to this process include; Landsat imagery and derived NBR (normalized burn ratio) data; polygon data developed by local agencies for the LANDFIRE Refresh effort; fire data...
The LANDFIRE existing vegetation layers describe the following elements of existing vegetation for each LANDFIRE mapping zone: existing vegetation type, existing vegetation canopy cover, and existing vegetation height. Vegetation is mapped using predictive landscape models based on extensive field reference data, satellite imagery, biophysical gradient layers, and classification and regression trees.DATA SUMMARY: The existing vegetation type (EVT) data layer represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western Hemisphere (http://www.natureserve.org/publications/usEcologicalsystems.jsp). A terrestrial ecological system is defined as a group...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
LANDFIRE disturbance data are developed to provide temporal and spatial information related to landscape change for determining vegetation transitions over time and for making subsequent updates to LANDFIRE vegetation, fuel and other data. Disturbance data include attributes associated with disturbance year, type, and severity. These data are developed through use of Landsat satellite imagery, local agency derived disturbance polygons, and other ancillary data. DATA SUMMARY: The disturbance data are developed through a multistep process. Inputs to this process include; Landsat imagery and derived NBR (normalized burn ratio) data; polygon data developed by local agencies for the LANDFIRE Refresh effort; fire data...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
Broad-scale alterations of historical fire regimes and vegetation dynamics have occurred in many landscapes in the U.S. through the combined influence of land management practices, fire exclusion, ungulate herbivory, insect and disease outbreaks, climate change, and invasion of non-native plant species. The LANDFIRE Project produces maps of simulated historical fire regimes and vegetation conditions using the LANDSUM landscape succession and disturbance dynamics model. The LANDFIRE Project also produces maps of current vegetation and measurements of current vegetation departure from simulated historical reference conditions. These maps support fire and landscape management planning outlined in the goals of the National...
Types: Downloadable;
Tags: BLM,
Bureau of Land Management,
DOI,
Fire,
Fire Regime Condition Class Departure Index,
The following habitat management areas were used in the creation of this feature class: PHMA: Areas identified as having the highest habitat value for maintaining sustainable GRSG populations and include breeding, late brood-rearing, and winter concentration areas.GHMA: Areas that are occupied seasonally or year-round and are outside of PHMAs.IHMA: Areas in Idaho that provide a management buffer for and that connect patches of PHMAs. IHMAs encompass areas of generally moderate to high habitat value habitat or populations but that are not as important as PHMAs.OHMA: Areas in Nevada and Northeastern California, identified as unmapped habitat in the Proposed RMP/Final EIS, that are within the Planning Area and contain...
A raster dataset representing the resilience and resistance classes combined with relative high and low greater sage-grouse breeding bird densities.
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arizona,
CRS,
California,
Colorado,
Geospatial,
A raster dataset of the percent of tilled agriculture within a 5km radius moving window. This dataset was made by reclassifying the 2014 National Agricultural Statistics Service Cropland Datalayer into to include values of only tilled agriculture, then conductding a moving window analysis on the resulting raster to provide a dataset depicting amount of tilled agriculture within a 5km radius of each 30m pixel. This data was published July 2016.
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arizona,
CRS,
California,
Colorado,
Geospatial,
The LANDFIRE fuel data describe the composition and characteristics of both surface fuel and canopy fuel. Specific products include fire behavior fuel models, canopy bulk density (CBD), canopy base height (CBH), canopy cover (CC), canopy height (CH), and fuel loading models (FLMs). These data may be implemented within models to predict the behavior and effects of wildland fire. These data are useful for strategic fuel treatment prioritization and tactical assessment of fire behavior and effects. DATA SUMMARY: Canopy height (CH) describes the average height of the top of the canopy for a stand. A spatially-explicit map of canopy height supplies information for fire behavior models such as FARSITE (Finney 1998) to...
A raster dataset of the percent of precipitation that falls during summer (July-September). This dataset was made by dividing the 30-year Normal summer (July - September) precipitation value by the 30-year Normal Annual precipitation value. Data is provided at a 900m resolution. This data was published July 2016.
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arizona,
CRS,
California,
Colorado,
Geospatial,
Existing timber type mylars were developed by the Alaska Regional Office in 1978 using 1:15,840 aerial photography flown in the 1950's-1970's, and digitized primarily under contract. The North Slope Borough digitized the Big Islands and Gravina Management Areas. Other full quads were done primarily by the Brodie Group. The remaining quads were done by the Chugach NF staff using LIDES or ARC/INFO. Additional mapping was done by Bob Green for the BLM Window and Whittier. Warren Oja did mapping for Cooper Landing. The forty quads under contract were as follows: Anchorage A1-A4, Bering Glacier A8 & B8, Cordova A1-A2, Cordova B1-B5, Cordova C3-C4, Middleton Island D1/2, Seward A3-A4, Seward B2-B8, Seward C1-C8, Seward...
Land & Resource Management Plan (L&RMP) Land Suitability Class This is a derived layer of forestland capability, suitability and availability for timber production. Water is assigned census or non-census water using the water bodies layer. Land is assigned to forest or non-forest using existing vegetation. Forestland both capable (productive) and other (non-productive) forestland, as well as non-forest are determined by CALVEG types (TABLE 38). Each CALVEG type is assigned a forest productivity code (TABLE 43). Suitability information is derived from productive forest CALVEG types that are available, minus the unsuitable forestlands (UNSU). Availability (TABLE 11) is derived by determining all forestland from CALVEG...
|
|
