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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Illinois,
Missouri,
Navigational Pool 24,
canopy gap,
canopy height model,
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Iowa,
Minnesota,
Navigational Pool 8,
Wisconsin,
canopy gap,
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Illinois,
Iowa,
Navigational Pool 13,
Wisconsin,
canopy gap,
This data release supports interpretations of field-observed root distributions within a shallow landslide headscarp (CB1) located below Mettman Ridge within the Oregon Coast Range, approximately 15 km northeast of Coos Bay, Oregon, USA. (Schmidt_2021_CB1_topo_far.png and Schmidt_2021_CB1_topo_close.png). Root species, diameter (greater than or equal to 1 mm), general orientation relative to the slide scarp, and depth below ground surface were characterized immediately following landsliding in response to large-magnitude precipitation in November 1996 which triggered thousands of landslides within the area (Montgomery and others, 2009). The enclosed data includes: (1) tests of root-thread failure as a function of...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Botany,
Forestry,
Geomorphology,
Oregon,
Soil Sciences,
This dataset contains field measurements of vegetation from the (1) Adirondack Sugar Maple Project (ASM), and (2) Buck Creek North and Buck Creek South Watersheds. The ASM data, collected in 2009 in 20 Adirondack watersheds (2 or 3 0.10 ha plots per watershed), are comprised of general plot characteristics, tree species identification and diameter at breast height (DBH) for all trees greater than 10 cm DBH, canopy position and health ratings, common and scientific names, and species identification and counts for saplings and seedlings. In Buck Creek North Tributary Watershed and Buck Creek South Tributary Watershed, near Inlet, New York, all trees greater than 5 cm DBH were identified in 15 circular plots (245 square...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service;
Tags: Adirondack Mountains,
Forestry,
Soil Sciences,
USGS Science Data Catalog (SDC),
american beech,
Insects and diseases cause significant alterations to native plant communities in Alaska. Dominant tree and shrub species across Alaska are subject to damage, defoliation, and mortality due to a variety of disease agents (wood decay and canker fungi, root disease, etc.) and native insects (bark beetles and woodborers, sawflies, leaf miners, etc.). Large-scale defoliation and mortality of dominant boreal forest communities can result in cascading effects on plant communities and wildlife and can even alter salmon spawning habitats. The United States Department of Agriculture (USDA) conducts annual forest damage aerial surveys using fixed-wing aircraft along predetermined routes across Alaska’s forests, with up to...
Insects and diseases cause significant alterations to native plant communities in Alaska. Dominant tree and shrub species across Alaska are subject to damage, defoliation, and mortality due to a variety of disease agents (wood decay and canker fungi, root disease, etc.) and native insects (bark beetles and woodborers, sawflies, leaf miners, etc.). Large-scale defoliation and mortality of dominant boreal forest communities can result in cascading effects on plant communities and wildlife and can even alter salmon spawning habitats. The United States Department of Agriculture (USDA) conducts annual forest damage aerial surveys using fixed-wing aircraft along predetermined routes across Alaska’s forests. Insect damage...
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. - A continuous grid dataset quantifying woody biomass (tons per acre) within 25 miles of communities in the Seward Peninsula – Nulato Hills – Kotzebue Lowlands (SNK) Rapid Ecoregional Assessment (REA).
This dataset contains data pertaining to ground surface cover in 30 meter plots around a random selection of points within chaparral from Santa Barbara county south to San Diego County in southern California, USA. These data were obtained from historical aerial imagery from 1943 to 1959 and current imagery from 2016 to 2018 and they were compared to quantify changes in cover type over time. These data support the following publication: Syphard, A.D., Brennan, T.J., Rustigian‐Romsos, H. and Keeley, J.E., 2022. Fire‐driven vegetation type conversion in southern California. Ecological Applications, p.e2626. https://doi.org/10.1002/eap.2626.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Botany,
Forestry,
Land Use Change,
Remote Sensing,
Southern California,
The U.S. Geological Survey (USGS) computed rasters of pre-solved values for the watersheds draining to the pixel delineation point representing the watershed's percent forested land cover from the National Land Cover Dataset (NLCD) 2016 data (land cover values 41-43). These values, which cover the conterminous United States at a scale of 30m pixel size, will be served in the National StreamStats Fire-Hydrology application to describe delineated watersheds ( https://streamstats.usgs.gov/ ). The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Raster;
Tags: Forestry,
Geography,
Hydrology,
USGS Science Data Catalog (SDC),
United States,
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Illinois,
Iowa,
Navigational Pool 13,
Wisconsin,
canopy gap,
As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Illinois,
Missouri,
Navigational Pool 21,
canopy gap,
canopy height model,
This dataset shows communities that have at least one sawmill.
Insects and diseases cause significant alterations to native plant communities in Alaska. Dominant tree and shrub species across Alaska are subject to damage, defoliation, and mortality due to a variety of disease agents (wood decay and canker fungi, root disease, etc.) and native insects (bark beetles and woodborers, sawflies, leaf miners, etc.). Large-scale defoliation and mortality of dominant boreal forest communities can result in cascading effects on plant communities and wildlife and can even alter salmon spawning habitats. The United States Department of Agriculture (USDA) conducts annual forest damage aerial surveys using fixed-wing aircraft along predetermined routes across Alaska’s forests. Insect damage...
These data were compiled for the creation of a continuous, transboundary land cover map of Bird Conservation Region 33, Sonoran and Mojave Deserts (BCR 33). Objective(s) of our study were to, 1) develop a machine learning (ML) algorithm trained to classify vegetation land cover using remote sensing spectral data and phenology metrics from 2013-2020, over a large subregion of the Sonoran and Mojave Deserts BCR, 2) Calibrate, validate, and refine the final ML-derived vegetation map using a collection of openly sourced remote sensing and ground-based ancillary data, images, and limited fieldwork, and 3) Harmonize a new transboundary classification system by expanding existing land cover mapping resources from the United...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
Baja California,
Botany,
California,
Ecology,
***This data set is superseded by Welty, J.L., and Jeffries, M.I., 2021, Combined wildland fire datasets for the United States and certain territories, 1800s-Present: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZXGFY3.*** This dataset is comprised of four different zip files. Zip File 1: A combined wildfire polygon dataset ranging in years from 1878-2019 (142 years) that was created by merging and dissolving fire information from 12 different original wildfire datasets to create one of the most comprehensive wildfire datasets available. Attributes describing fires that were reported in the various source data, including fire name, fire code, ignition date, controlled date, containment date, and...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Botany,
Ecology,
Forestry,
Land Use Change,
North America,
We developed a LiDAR-based habitat model for the threatened Marbled Murrelet (MAMU) in the Siuslaw National Forest, Oregon, using a two-step approach. First, we tested the applicability of the LiDAR-based model developed for the Coos Bay District of the Bureau of Land Management (BLM) to the Siuslaw N.F. In the second step, we tested alternative habitat models developed with forest structural data and Murrelet survey data from the Siuslaw N.F. We compared the performance of each model to provide forest managers with the best predictive tool to guide habitat management for the Marbled Murrelet. This shapefile contains the probability of Marbled Murrelet occupancy values of each model for vegetation polygons defined...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Ecology,
Forestry,
Land Use Change,
Oregon,
Oregon Coast Range,
This dataset was developed for the BLM-Rapid Ecoregional Assessment (REA) project for the Seward Peninsula - Nulato Hills - Kotzebue Sound Lowlands. This datasets represents the Change Agent, pests and disease, specifically identifiying beetle infestations. The information was collected, cooperatively by aerial surveys by both the USFS, Forest Health Protection (FHP) and ADNR, Div. of Forestry with beetle data clipped to the REA project boundary. The data represents a 10 year cumulative effect for 1989-2010.
Data on forest damage caused by insect and disease agents in the CYR study area was limited to the United States Department of Agriculture (USDA) Forest Service annual forest damage aerial surveys. Data on insect distribution and ranges within the CYR study area was identified as a data gap. The United States Department of Agriculture (USDA) conducted annual forest damage aerial surveys using fixed-wing aircraft along predetermined routes across Alaska’s forests, with up to 25% of the total forested area of Alaska surveyed each year. Insect damage within one to two miles on either side of flight paths was recorded by drawing polygons onto 1:250,000 scale USGS topographic maps or a digital elevation model. Some damage...
A summary data set of all fire polygons we could locate as of December 2007 . We used multiple datasets to developed this layer including data gathered from the internet, publically available databases, and personal contacts with dozens of agency personnel throught the western U.S. Data were assessed for utility (but not accuracy) and formatted for consistency. Each source data set was then attributed consistently with fields for record number and year (of fire). Because various resource management entities map fires somewhat independently (especially in more recent years) we merged overlapping polygons for each year.. Users are encouraged to understand the contents of this data file before using it.
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