This orthomosaic can be used to practice using the ArcGIS Pro workflow to create plots and extract vegetation indices.

Vegetation classified in the Copper River area by the State of Alaska, Department of Natural Resources, Division of Forestry, Fairbanks Area, from 2009 through 2010.

The Division of Forestry completed a forest inventory on Alaska state owned lands in 2016. The project area encompasses forest lands in the Upper Kuskokwim River near the communities of McGrath and Nikolai. The purpose of this GIS layer, is to create a spatial coverage of vegetation on state lands to aid in forest management.

The USDA Long-Term Agroecosystem Research was established to develop national strategies for sustainable intensification of agricultural production. As part of the Agricultural Research Service, the LTAR Network incorporates numerous geographies consisting of experimental areas and locations where data are being gathered. Starting in early 2019, two working groups of the LTAR Network (Remote Sensing and GIS, and Data Management) set a major goal to jointly develop a geodatabase of LTAR Standard GIS Data Layers. The purpose of the geodatabase was to enhance the Network's ability to utilize coordinated, harmonized datasets and reduce redundancy and potential errors associated with multiple copies of similar datasets. Project organizers met at least twice with each of the 18 LTAR sites from September 2019 through December 2020, compiling and editing a set of detailed geospatial data layers comprising a geodatabase, describing essential data collection areas within the LTAR Network. The LTAR Standard GIS Data Layers geodatabase consists of geospatial data that represent locations and areas associated with the LTAR Network as of late 2020, including LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This geodatabase was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. The creation of the geodatabase began with initial requests to LTAR site leads and data managers for geospatial data, followed by meetings with each LTAR site to review the initial draft. Edits were documented, and the final draft was again reviewed and certified by LTAR site leads or their delegates. Revisions to this geodatabase will occur biennially, with the next revision scheduled to be published in 2023. Resources in this dataset:Resource Title: LTAR Standard GIS Data Layers, 2020 version, File Geodatabase. File Name: LTAR_Standard_GIS_Layers_v2020.zipResource Description: This file geodatabase consists of authoritative GIS data layers of the Long-Term Agroecosystem Research Network. Data layers include: LTAR site locations, LTAR site points of contact and street addresses, LTAR experimental boundaries, LTAR site "legacy region" boundaries, LTAR eddy flux tower locations, and LTAR phenocam locations.Resource Software Recommended: ArcGIS,url: esri.com Resource Title: LTAR Standard GIS Data Layers, 2020 version, GeoJSON files. File Name: LTAR_Standard_GIS_Layers_v2020_GeoJSON_ADC.zipResource Description: The contents of the LTAR Standard GIS Data Layers includes geospatial data that represent locations and areas associated with the LTAR Network as of late 2020. This collection of geojson files includes spatial data describing LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This dataset was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. Resource Software Recommended: QGIS,url: https://qgis.org/en/site/

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. were derived from the NVC. NatureServe developed a preliminary list of potential vegetation types. These data were combined with existing plot data (Cully 2002) to derive an initial list of potential types. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the park’s small size and the large amount of field data, the map units are equivalent to existing vegetation associations or local associations/descriptions (e.g., Prairie Dog Colony). In addition to vegetation type, vegetation structures were described using three attributes: height, coverage density, and coverage pattern. In addition to vegetation structure and context, a number of attributes for each polygon were stored in the associated table within the GIS database. Many of these attributes were derived from the photointerpretation; others were calculated or crosswalked from other classifications. Table 2.7.2 shows all of the attributes and their sources. Anderson Level 1 and 2 codes are also included (Anderson et al. 1976). These codes should allow for a more regional perspective on the vegetation types. Look-up tables for the names associated with the codes is included within the geodatabase and in Appendix D. The look-up tables contain all the NVC formation information as well as alliance names, unique IDs, and the ecological system codes (El_Code) for the associations. These El_Codes often represent a one-to-many relationship; that is, one association may be related to more than one ecological system. The NatureServe conservation status is included as a separate item. Finally, slope (degrees), aspect, and elevation were calculated for each polygon label point using a digital elevation model and an ArcView script. The slope figure will vary if one uses a TIN (triangulated irregular network) versus a GRID (grid-referenced information display) for the calculation (Jenness 2005). A grid was used for the slope figure in this dataset. Acres and hectares were calculated using XTools Pro for ArcGIS Desktop.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for Olympic National Park. The vegetation map is a geotiff raster, and at 67MB may be difficult to download. An ArcGIS file geodatabase contains plot data and lookup tables that relate map class units to mapping associations. The geodatabase includes a vegetation Feature dataset with the park boundary and project boundary used in the map. The map development process was organized around the random forests machine learning algorithm. The modeling used 2,519 plots representing 150 vegetation associations and 50 map classes. Imagery from the National Agriculture Imagery Program and the Sentinel-2 and Landsat 8 satellites, airborne lidar bare earth and canopy height data, elevation data from the U.S. Geological Survey 3D Elevation Program, and climate normals from the PRISM Climate Group were used to develop a variety of predictor metrics. The predictors and the map class calls at each plot were input to a process in which each map class was modeled against every other map class in a factorial random forests scheme. We used the plot-level modeling outcomes and species composition data to adjust the crosswalk between association and map class so that floristic consistency and model accuracy were jointly optimized across all classes. The map was produced by predicting the factorial models and selecting the overall best-performing class at each 3-meter pixel. The final vegetation map, including a buffer surrounding the park, contains 43 natural vegetated classes, seven mostly unvegetated natural classes, and four classes representing burned areas or anthropogenic disturbance.

Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

Vegetation cover types used to develop a forest inventory conducted by the State of Alaska Division of Forestry. Inventory with supporting ground plots on State, Federal and Native Corporation land in the Cordova Area.

The State of Alaska and the Forest Service entered into a Challenge Cost-share agreement in June 2015, to complete a timber stand inventory in young-growth forest. This work supports collecting, analyzing, and using forest resource information to implement sound, sustainable forest management practices across Southeast Alaska, while offering training and developing job opportunites for rural residents in natural resource fields. This layer depicts the field-sampled plots for the timber cruise, as well as plot status and date completed. These points are sampled on a standard grid, created using the Alaska Region Stand Exam Preparation (StExPrep) program.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Our final map product is a geographic information system (GIS) database of vegetation structure and composition across the Crater Lake National Park terrestrial landscape, including wetlands. The database includes photos we took at all relevé, validation, and accuracy assessment plots, as well as the plots that were done in the previous wetlands inventory. We conducted an accuracy assessment of the map by evaluating 698 stratified random accuracy assessment plots throughout the project area. We intersected these field data with the vegetation map, resulting in an overall thematic accuracy of 86.2 %. The accuracy of the Cliff, Scree & Rock Vegetation map unit was difficult to assess, as only 9% of this vegetation type was available for sampling due to lack of access. In addition, fires that occurred during the 2017 accuracy assessment field season affected our sample design and may have had a small influence on the accuracy. Our geodatabase contains the locations where particular associations are found at 600 relevé plots, 698 accuracy assessment plots, and 803 validation plots.

A Research Line is a feature representing linear or transect based locations, where some form of research observation, test, trial, measure, or monitoring activity has, or will take place. Coordinates are taken along the full length of the transect. These features are generally long and narrow with no appreciable width (less than 10 meters). This data class is one of three primitive data classes: Research Point (RESPOINT), Research Line (RESLINE), and Research Polygon (RESPOLY).

Additional Documentation

Research Plot - User Guide (Word) Research Plot - FAQ (Word)

Status

On going: data is being continually updated

Maintenance and Update Frequency

As needed: data is updated as deemed necessary

Contact

Adam Hogg, adam.hogg@ontario.ca

The data referenced here is licensed under the Ontario Geospatial Data Exchange (OGDE) Agreement and is available to members of the OGDE for professional, non-commercial use only. To find out more about the OGDE visit Land Information Ontario on Ontario.ca.

Timber stands sampled for volume for a Timber Inventory of State Forest Lands in the Middle Yukon River Area 2015

The City of Waterloo provides cemetery services at Parkview Cemetery and the northern portion of Mount Hope Cemetery. This layer contains the polygon lot features which delineate the geographic location of cemetery plots within Parkview Cemetery. These polygon features can be joined with the Cemetery Interments dataset in order to associate interments data with a geographic location. This data will be updated monthly.

This dataset contains the 50 hectare permanent tree plot. It was established in 1980 in the tropical moist forest of Barro Colorado Island (BCI) in Gatun Lake in central Panama. Censuses have been carried out in 1981-1983, 1985, 1990, 1995, 2000, and 2005. In each census, all free-standing woody stems at least 10 mm diameter at breast height were identified, tagged, and mapped. Over 350,000 individual trees have been censused over 25 years.

These data are the total number and average number of saplings and seedlings of trees detected from 0.05-ha circular plot habitat samples taken in 2005 at sample points at Spears and Didion Ranches, Placer County, California. Seedlings and saplings were counted from nine 1-square meter (0.56-m radius) circular plots located within each 0.05-ha circular habitat sampling plot. There were three 0.05-ha circular habitat sampling plots at each of the 15 sample points. One 1-square meter plot was located at the center of 0.05-ha plot, and the eight remaining plots were located 8 m away from the center point at 45 degree intervals in the circular.

TIME PERIOD COVERED These data were collected between May-July 2004 by field crews working for California Department of Fish and Game. GEOGRAPHIC EXTENT OF THE RECORDS Vegetation plots occur in two study areas on public lands in Yuba and Tehama Counties in the Sierra Nevada foothills. NUMBER OF RECORDS There are 183 records with habitat attributes measured from 0.05 - 0.10 hectare sampling plots. BASE DATA STRUCTURE The file is a flat Excel table which gives vegetation attributes for each habitat plot. Each habitat plot is represented by two key fields called "SAMPLE_ID" and "PLOT_NUM" which relate these habitat records to bird and herpetile survey data collected in the same year from the same sample points. WHAT EACH RECORD REPRESENTS Each record in the table represents the average values for habitat attributes from plots that can be linked with bird count data from the same points. Average values for each sample represent the mean of average values from 3 habitat plots measured at each point.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for Mount Rainier National Park. The vegetation map is a geotiff raster, and at 67MB may be difficult to download. An ArcGIS file geodatabase contains plot data and lookup tables that relate map class units to mapping associations. The geodatabase includes a vegetation Feature dataset with the park boundary and project boundary used in the map. The map development process was organized around the random forests machine learning algorithm. The modeling used 1,900 plots representing 124 vegetation associations and 37 map classes. Imagery from the National Agriculture Imagery Program and the Sentinel-2 and Landsat 8 satellites, airborne lidar bare earth and canopy height data, elevation data from the U.S. Geological Survey 3D Elevation Program, and climate normals from the PRISM Climate Group were used to develop a variety of predictor metrics. The predictors and the map class calls at each plot were input to a process in which each map class was modeled against every other map class in a factorial random forests scheme. We used the plot-level modeling outcomes and species composition data to adjust the crosswalk between association and map class so that floristic consistency and model accuracy were jointly optimized across all classes. The map was produced by predicting the factorial models and selecting the overall best-performing class at each 3-meter pixel. The final vegetation map, including a buffer surrounding the park, contains 33 natural vegetated classes, five mostly unvegetated natural classes, and four classes representing burned areas or anthropogenic disturbance

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The WHSA vegetation map was developed using a combined strategy of automated digital image classification and direct analog image interpretation of aerial photography and satellite imagery. Initially, the aerial photography and satellite imagery were processed and entered into a GIS along with ancillary spatial layers. A working map legend of ecologically based vegetation map units was developed using the vegetation classification described in the report as the foundation. The intent was to develop map units that targeted the plant-association level wherever possible within the constraints of image quality, information content, and resolution. With the provisional legend and ground-control points provided by the field-plot data (the same data used to develop the vegetation classification), a combination of heads-up screen digitizing of polygons based on image interpretation and supervised image classifications were conducted. The outcome was a vegetation map composed of a suite of map units defined by plant associations and represented by sets of mapped polygons with similar spectral and site characteristics.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following the development of the vegetation classification, the vegetation map was further edited and refined in 2005 to develop an association-level vegetation map. Using ArcGIS 9.0, polygon boundaries were revised onscreen based on the plot data and additional informal field observations collected while in the field during plot sampling. Field notes and limited field mapping supplemented the GIS mapping. Given the large amount of time used in gathering plot data, further ground-truthing was minimal. Each polygon was attributed with the name of a USNVC association or a land use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. The vegetation is mapped to the association level with one exception—because of their small size and interdigitization on the landscape, three of the herbaceous wetland communities, Bluejoint Wet Meadow (CEGL005174), Medium-depth Emergent Marsh (CEGL006519), and Cattail Marsh (CEGL006513) were mapped as a single map class: the Emergent Marsh - Shrub Swamp System. The Enriched Hardwood Forest Seeps, small occurrences within upland forests that are distinguished by their herb flora, are less than the minimum mapping unit (0.5 ha) and were not mapped. The shapefile was projected in Universal Transverse Mercator (UTM) Zone 18 North, North American Datum (NAD) 1983.

This data package contains the point locations for the core research plots maintained by the Bonanza Creek LTER program. Geospatial_Data_Presentation_Form: vector digital data.