Whitebark Pine Habitat Model From LiDAR
공공데이터포털
This data was produced under contract for Alberta Agriculture and Forestry, Forest Management Branch in 2015-2016. Variables used were elevation, aspect, slope, landscape mesotopography (e.g. ridge, upper slope, etc). LiDAR coverageyielded a resolution of 1m2 pixels. Canopy height was included in this model. In these files there is a report assessing accuracy of the models compared with field observation data. detailed accuracy data by township is available upon request.
Limber Pine Habitat Model From DEM
공공데이터포털
This data was produced under contract for Alberta Agriculture and Forestry, Forest Management Branch in 2015-2016. Variables used were elevation, aspect, slope, landscape mesotopography (e.g. ridge, upper slope, etc). DEM was used where there was no LiDAR coverage, with a resolution of 25 m2 pixels. Canopy height was not included in this model because it was a product generated by LiDAR. In these files there is a report assessing accuracy of the models compared with field observation data. detailed accuracy data by township is available upon request.
Limber Pine Habitat Model From Lidar
공공데이터포털
This data was produced under contract for Alberta Agriculture and Forestry, Forest Management Branch in 2015-2016. Variables used were elevation, aspect, slope, landscape mesotopography (e.g. ridge, upper slope, etc). Where there was LiDAR coverage, resolution was 1m2 pixels. Canopy height was included in this model as a product generated by LiDAR. In these files there is a report assessing accuracy of the models compared with field observation data. detailed accuracy data by township is available upon request.
ALS Analysis into Forest Structure Change -Batemans Bay
공공데이터포털
Export DataAccess API These datasets were produced as part of a study undertaken by the University of Newcastle, commissioned by the NSW Natural Resources Commission. The study produced a report, titled ‘Retrospective Analysis of Forest Structure Change: ALS Data Comparison and Interpretation’.These datasets are part of a web application on the Spatial Collaboration Portal, accessible through the below URL:https://portal.spatial.nsw.gov.au/portal/home/item.html?id=7ab99290b6514fed880df16af1fcc7e6Metadata Portal Metadata InformationContent TitleALS Analysis into Forest Structure Change -Batemans BayContent TypeScene Layer/Scene Layer PackageDescriptionALS derived canopy height & coverage models and associated factors.Initial Publication Date24/05/2024Data Currency24/05/2024Data Update FrequencyOtherContent SourceOtherFile TypeMap Feature ServiceAttributionData produced by University of Newcastle for the Natural Resources CommissionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)OtherSpatial Reference System (web service)OtherWGS84 Equivalent ToOtherSpatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonsStandard and SpecificationData CustodianNSW Natural Resources CommissionPoint of ContactEmma Pearce (Emma.Pearce@nrc.nsw.gov.au)Data AggregatorData DistributorSpatial VisionAdditional Supporting InformationTRIM Number
Harpers Ferry Digital Elevation Model
공공데이터포털
LiDAR derived Digital Elevation Model of HAFE. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.
Harpers Ferry Digital Elevation Model
공공데이터포털
LiDAR derived Digital Elevation Model of HAFE. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.
Prince William Forest Park Forest Digital Elevation Model
공공데이터포털
LiDAR derived Digital Elevation Model of PRWI. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.
ALS Analysis into Forest Structure Change - Bulahdelah
공공데이터포털
Export DataAccess APIThese datasets were produced as part of a study undertaken by the University of Newcastles, commissioned by the NSW Natural Resources Commission. The study produced a report, titled ‘Retrospective Analysis of Forest Structure Change: ALS Data Comparison and Interpretation’.These datasets are part of a web application on the Spatial Collaboration Portal, accessible through the below URL:https://portal.spatial.nsw.gov.au/portal/home/item.html?id=7ab99290b6514fed880df16af1fcc7e6Metadata Portal Metadata InformationContent TitleALS Analysis into Forest Structure Change - BulahdelahContent TypeOtherDescriptionALS derived canopy height & coverage models and associated factors.Initial Publication Date24/05/2024Data Currency24/05/2024Data Update FrequencyOtherContent SourceOtherFile TypeImagery LayerAttributionData produced by University of Newcastle for the Natural Resources CommissionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)OtherSpatial Reference System (web service)OtherWGS84 Equivalent ToOtherSpatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonsStandard and SpecificationData CustodianNSW Natural Resources CommissionPoint of ContactEmma Pearce (Emma.Pearce@nrc.nsw.gov.au)Data AggregatorData DistributorSpatial VisionAdditional Supporting InformationTRIM Number
Pine Grosbeak Predicted Habitat - CWHR B535 [ds2348]
공공데이터포털
The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).