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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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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...
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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...
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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...
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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...
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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...
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This project evaluated the potential impacts of storm surges and relative sea level rise on nesting geese and eider species that commonly breed on the Yukon-Kuskokwim Delta (Y-K Delta). Habitat suitability maps for breeding waterbirds were developed to identify current waterbird breeding habitat and distributions. Short-term climate change impacts were assessed by comparing nest densities in relation to magnitude of storms that occurred in the prior fall from 2000-2013. Additionally, nest densities were modeled using random forests in relation to the time-integrated flood index (e.g., a storm specific measure accounting for both water depth and duration of flooding) for four modeled storms (2005, 2006, 2009, and...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: BIRDS, BIRDS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, DELTAS, All tags...
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The Yukon-Kuskokwim Delta of Alaska is a globally important region for numerous avian species including millions of migrating and nesting waterbirds. Climate change effects such as sea level rise and increased storm frequency and intensity have the potential to impact waterbird populations and breeding habitat. In order to determine the potential impacts of these climate-mediated changes, we investigated both short-term and long-term impacts of storm surges to geese and eider species that commonly breed on the Yukon-Kuskokwim Delta.To do this, we used 29 years of ground-based surveys conducted as part of the U.S. Fish and Wildlife Service’s long-term waterbird monitoring program along with flood indices modeled...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: BIRDS, BIRDS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, DELTAS, All tags...
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Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios...
Tags: AB, AZ, Alberta, Arizona, Arizona Plateau, All tags...
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The 2023 Midwest Conservation Blueprint is a basemap of priority lands and waters for conservation in the Midwest. It consists of over 20 social and environmental values that represent diverse interests across society. It guides the realization of a thriving landscape of healthy lands and waters supporting wildlife, fish, and plants, embraced by all who live, work, and recreate in the Midwest. Specifically, it serves as an invitation to all those in the Midwest to better coordinate voluntary conservation actions and investments across the region by focusing and aligning conservation work across jurisdictions, attracting and directing funding sources for conservation, and connecting with conservation partners and...
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The LANDFIRE (LF) Canadian Forest Fire Danger Rating System (CFFDRS) product depicts fuel types as an identifiable association of fuel elements of distinctive species, form, size, arrangement, and continuity. CFFDRS exhibits characteristic fire behavior under the specified burn conditions. In LF 2022 Canadian fuel models are derived from the Fuel Model Guide to Alaska Vegetation (Alaska Fuel Model Guide Task Group, 2018) and subsequent updates. The LF CFFDRS product contains the fuel models used for the Fire Behavior Prediction (FBP) system fuel type inputs. Default values assigned to the Canadian Fuel Models required to run the Prometheus fire behavior software (Prometheus, 2021) are added as attributes to the...
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LANDFIRE's (LF) 2022 Forest Canopy Height (CH) describes the average height of the top of the canopy for a stand. CH is used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CH supplies information for fire behavior models, such as FARSITE (Finney 1998), that can determine the starting point of embers in the spotting model, wind reductions, and the volume of crown fuels. To create this product, plot level CH values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance Canopy Cover and CH are used as predictors of disturbed CH using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and time since...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. LF 2022 Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2013 to 2022. FDist is created from LF 2022 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Canopy Cover (CC), Canopy Height (CH), Canopy Bulk Density (CBD), Canopy Base Height (CBH),...
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Nutrient Reduction is an indicator of the Midwest Landscape Initiative’s (MLI) 2023 Midwest Conservation Blueprint. The Blueprint is a basemap of priority lands and waters for conservation across the Midwest consisting of over 20 social and environmental values representing diverse interests across society. This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative...
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Aquatic Network Connectivity is an indicator of the Midwest Landscape Initiative’s (MLI) 2023 Midwest Conservation Blueprint. The Blueprint is a basemap of priority lands and waters for conservation across the Midwest consisting of over 20 social and environmental values representing diverse interests across society. This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4)...
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Riparian Areas is an indicator of the Midwest Landscape Initiative’s (MLI) 2023 Midwest Conservation Blueprint. The Blueprint is a basemap of priority lands and waters for conservation across the Midwest consisting of over 20 social and environmental values representing diverse interests across society. This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative...
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This dataset consists of a map depicting the distribution of cedar along the Natchez Trace Parkway. Ground-based vegetation classification was provided by the National Park Service and mapped by the U.S. Geological Survey, National Wetlands Research Center. In the final version of "Mapping the Natchez Trace Parkway," the Cedar class was merged with the Pine class (the alliance most frequently mistaken for cedar).
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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.
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Technological advancements in Global Positioning System (GPS) telemetry markers allow almost real-time observation of waterfowl movements and habitat selection. Telemetry data on ducks marked with GPS transmitters can be used to evaluate performance of remote sensing data (for example, dynamic open-water maps produced by Point Blue Conservation Science) for classifying habitats that are flooded and available for waterfowl. Translating dynamic open-water maps to waterfowl-relevant habitat maps provides a major improvement for wildlife researchers and managers to assist in their assessments of the areas and habitats used by waterfowl as hydrologic conditions change, both temporally and spatially. Suitable habitat...


map background search result map search result map Cedar Distribution along the Natchez Trace Parkway 2004 Aquatic Vegetation along the Natchez Trace Parkway 2004 Webinar (2015 Oct 14) Part I Summary: Predicting waterbird nest distributions Classification of Waterfowl Habitat, and Quantification of Interannual Space Use and Movement Distance from Primary Roosts to Night Feeding Locations by Waterfowl in California for October - March of 2015 through 2018 Vegetation Type Conversion in Southern California Between 1943 and 2018 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021 Aquatic Network Connectivity Riparian Areas Nutrient Reduction Midwest Conservation Blueprint 2023 LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Forest Canopy Height (CH) AK LANDFIRE 2022 Fuel Disturbance (FDist) AK LANDFIRE 2022 Canadian Forest Fire Danger Rating System (CFFDRS) AK LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Projections of Rangeland Fractional Component Cover Across Western Northern American Rangelands for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods Webinar (2015 Oct 14) Part I Summary: Predicting waterbird nest distributions LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands Cedar Distribution along the Natchez Trace Parkway 2004 Aquatic Vegetation along the Natchez Trace Parkway 2004 Vegetation Type Conversion in Southern California Between 1943 and 2018 Classification of Waterfowl Habitat, and Quantification of Interannual Space Use and Movement Distance from Primary Roosts to Night Feeding Locations by Waterfowl in California for October - March of 2015 through 2018 LANDFIRE 2022 Historical Disturbance (HDist) HI Aquatic Network Connectivity Riparian Areas Nutrient Reduction Midwest Conservation Blueprint 2023 Projections of Rangeland Fractional Component Cover Across Western Northern American Rangelands for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021 LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Forest Canopy Height (CH) AK LANDFIRE 2022 Fuel Disturbance (FDist) AK LANDFIRE 2022 Canadian Forest Fire Danger Rating System (CFFDRS) AK LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS