This dataset contains model-based county-level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2020 or 2019 county population estimates, and American Community Survey (ACS) 2016–2020 or 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census 2020 county boundary file in a GIS system to produce maps for 29 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

A Normalized Difference Vegetation Index (NDVI) was applied to the source NAIP 2022 60cm imagery. NDVI=(NearIR-Red)/(NearIR+Red). The color ramp (produced by ESRI) goes from brown (less healthy vegetation) to red to green (healthier vegetation or more "greenness").This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This data layer is an Esri file geodatabase polygon feature class that contains parcel boundaries maintained by local government agencies in Indiana. It was released by the Indiana Geographic Information Office (IGIO) on November 9, 2022. The IGIO compiled the data as part of the Indiana Data Harvest program between the Indiana Geographic Information Council (IGIC) and Indiana local governments to provide the most accurate framework data for the citizens of Indiana.

Notice: this is not the latest Heat Island Severity image service.This layer contains the relative heat severity for every pixel for every city in the United States, including Alaska, Hawaii, and Puerto Rico. This 30-meter raster was derived from Landsat 8 imagery band 10 (ground-level thermal sensor) from the summer of 2022, patched with data from 2021 where necessary.Federal statistics over a 30-year period show extreme heat is the leading cause of weather-related deaths in the United States. Extreme heat exacerbated by urban heat islands can lead to increased respiratory difficulties, heat exhaustion, and heat stroke. These heat impacts significantly affect the most vulnerable—children, the elderly, and those with preexisting conditions.The purpose of this layer is to show where certain areas of cities are hotter than the average temperature for that same city as a whole. Severity is measured on a scale of 1 to 5, with 1 being a relatively mild heat area (slightly above the mean for the city), and 5 being a severe heat area (significantly above the mean for the city). The absolute heat above mean values are classified into these 5 classes using the Jenks Natural Breaks classification method, which seeks to reduce the variance within classes and maximize the variance between classes. Knowing where areas of high heat are located can help a city government plan for mitigation strategies.This dataset represents a snapshot in time. It will be updated yearly, but is static between updates. It does not take into account changes in heat during a single day, for example, from building shadows moving. The thermal readings detected by the Landsat 8 sensor are surface-level, whether that surface is the ground or the top of a building. Although there is strong correlation between surface temperature and air temperature, they are not the same. We believe that this is useful at the national level, and for cities that don’t have the ability to conduct their own hyper local temperature survey. Where local data is available, it may be more accurate than this dataset. Dataset SummaryThis dataset was developed using proprietary Python code developed at The Trust for Public Land, running on the Descartes Labs platform through the Descartes Labs API for Python. The Descartes Labs platform allows for extremely fast retrieval and processing of imagery, which makes it possible to produce heat island data for all cities in the United States in a relatively short amount of time.What can you do with this layer?This layer has query, identify, and export image services available. Since it is served as an image service, it is not necessary to download the data; the service itself is data that can be used directly in any Esri geoprocessing tool that accepts raster data as input.In order to click on the image service and see the raw pixel values in a map viewer, you must be signed in to ArcGIS Online, then Enable Pop-Ups and Configure Pop-Ups.Using the Urban Heat Island (UHI) Image ServicesThe data is made available as an image service. There is a processing template applied that supplies the yellow-to-red or blue-to-red color ramp, but once this processing template is removed (you can do this in ArcGIS Pro or ArcGIS Desktop, or in QGIS), the actual data values come through the service and can be used directly in a geoprocessing tool (for example, to extract an area of interest). Following are instructions for doing this in Pro.In ArcGIS Pro, in a Map view, in the Catalog window, click on Portal. In the Portal window, click on the far-right icon representing Living Atlas. Search on the acronyms “tpl” and “uhi”. The results returned will be the UHI image services. Right click on a result and select “Add to current map” from the context menu. When the image service is added to the map, right-click on it in the map view, and select Properties. In the Properties window, select Processing Templates. On the drop-down menu at the top of the window, the default Processing Template is either a yellow-to-red ramp or a blue-to-red ramp. Click the drop-down, and select “None”, then “OK”. Now you will have the actual pixel values displayed in the map, and available to any geoprocessing tool that takes a raster as input. Below is a screenshot of ArcGIS Pro with a UHI image service loaded, color ramp removed, and symbology changed back to a yellow-to-red ramp (a classified renderer can also be used): A typical operation at this point is to clip out your area of interest. To do this, add your polygon shapefile or feature class to the map view, and use the Clip Raster tool to export your area of interest as a geoTIFF raster (file extension ".tif"). In the environments tab for the Clip Raster tool, click the dropdown for "Extent" and select "Same as Layer:", and select the name of your polygon. If you then need to convert the output raster to a polygon shapefile or feature class, run the Raster to Polygon tool, and select "Value" as the field.Other Sources of Heat Island InformationPlease see these websites for valuable information on heat islands and to learn about exciting new heat island research being led by scientists across the country:EPA’s Heat Island Resource CenterDr. Ladd Keith, University of ArizonaDr. Ben McMahan, University of Arizona Dr. Jeremy Hoffman, Science Museum of Virginia Dr. Hunter Jones, NOAA Daphne Lundi, Senior Policy Advisor, NYC Mayor's Office of Recovery and ResiliencyDisclaimer/FeedbackWith nearly 14,000 cities represented, checking each city's heat island raster for quality assurance would be prohibitively time-consuming, so The Trust for Public Land checked a statistically significant sample size for data quality. The sample passed all quality checks, with about 98.5% of the output cities error-free, but there could be instances where the user finds errors in the data. These errors will most likely take the form of a line of discontinuity where there is no city boundary; this type of error is caused by large temperature differences in two adjacent Landsat scenes, so the discontinuity occurs along scene boundaries (see figure below). The Trust for Public Land would appreciate feedback on these errors so that version 2 of the national UHI dataset can be improved. Contact Dale.Watt@tpl.org with feedback.

This dataset contains model-based census tract level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This dataset contains model-based place (incorporated and census designated places) estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia —at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the 2020 Census place boundary file in a GIS system to produce maps for 40 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."

The Geospatial Analytics Market size was valued at USD 79.06 USD billion in 2023 and is projected to reach USD 202.74 USD billion by 2032, exhibiting a CAGR of 14.4 % during the forecast period. The growing adoption of location-based technologies and the increasing need for data-driven decision-making in various industries are key factors driving market growth. Geospatial analytics captures, produces and displays GIS (geographic information system)-maps and pictures that may be weather maps, GPS or satellite photos. The geospatial analysis as a tool works with state of art technology in every formats namely; the GPS, sensors that locates, social media, mobile devices, multi of the satellite imagery to produce data visualizations that are facilitating trend-finding in complex relations between people and places as well are the situations' understanding. Visualizations are depicted through the use of maps, graphs, figures, and cartograms that illustrate the entire historical picture as well as a current changing trend. This is why the forecast becomes more confident and the situation is anticipated better. Recent developments include: February 2024: Placer.ai and Esri, a Geographic Information System (GIS) technology provider, partnered to empower customers with enhanced analytics capabilities, integrating consumer behavior analysis. Additionally, the agreement will foster collaborations to unlock further features by synergizing our respective product offerings., December 2023: CKS and Esri India Technologies Pvt Ltd teamed up to introduce the 'MMGEIS' program, focusing on students from 8th grade to undergraduates, to position India as a global leader in geospatial technology through skill development and innovation., December 2023: In collaboration with Bayanat, the UAE Space Agency revealed the initiation of the operational phase of the Geospatial Analytics Platform during its participation in organizing the Space at COP28 initiatives., November 2023: USAID unveiled its inaugural Geospatial Strategy, designed to harness geospatial data and technology for more targeted international program delivery. The strategy foresees a future where geographic methods enhance the effectiveness of USAID's efforts by pinpointing development needs, monitoring program implementation, and evaluating outcomes based on location., May 2023: TomTom International BV, a geolocation technology specialist, expanded its partnership with Alteryx, Inc. Through this partnership, Alteryx will use TomTom’s Maps APIs and location data to integrate spatial data into Alteryx’s products and location insights packages, such as Alteryx Designer., May 2023: Oracle Corporation announced the launch of Oracle Spatial Studio 23.1, available in the Oracle Cloud Infrastructure (OCI) marketplace and for on-premises deployment. Users can browse, explore, and analyze geographic data stored in and managed by Oracle using a no-code mapping tool., May 2023: CAPE Analytics, a property intelligence company, announced an enhanced insurance offering by leveraging Google geospatial data. Google’s geospatial data can help CAPE create appropriate solutions for insurance carriers., February 2023: HERE Global B.V. announced a collaboration with Cognizant, an information technology, services, and consulting company, to offer digital customer experience using location data. In this partnership, Cognizant will utilize the HERE location platform’s real-time traffic data, weather, and road attribute data to develop spatial intelligent solutions for its customers., July 2022: Athenium Analytics, a climate risk analytics company, launched a comprehensive tornado data set on the Esri ArcGIS Marketplace. This offering, which included the last 25 years of tornado insights from Athenium Analytics, would extend its Bronze partner relationship with Esri. . Key drivers for this market are: Advancements in Technologies to Fuel Market Growth. Potential restraints include: Lack of Standardization Coupled with Shortage of Skilled Workforce to Limit Market Growth. Notable trends are: Rise of Web-based GIS Platforms Will Transform Market.

The Geospatial Analytics Market size was valued at USD 98.93 billion in 2023 and is projected to reach USD 227.04 billion by 2032, exhibiting a CAGR of 12.6 % during the forecasts period. The Geospatial Analytics Market describes an application of technologies and approaches processing geographic and spatial data for intelligence and decision-making purposes. This market comprises of mapping tools and software, spatial data and geographic information systems (GIS) used in various fields including urban planning, environmental, transport and defence. Use varies from inventory tracking and control to route optimization and assessment of changes in environment. Other trends are the growth of big data and machine learning to improve the predictive methods, the improved real-time data processing the use of geographic data in combination with other technologies, for example, IoT and cloud. Some of the factors that are fuelling the need to find a marketplace for GIS solutions include; Increasing importance of place-specific information Increasing possibilities for data collection The need to properly manage spatial information in a high stand environment. Recent developments include: In May 2023, Google launched Google Geospatial Creator, a powerful tool that allows users to create immersive AR experiences that are both accurate and visually stunning. It is powered by Photorealistic 3D Tiles and ARCore from Google Maps Platform and can be used with Unity or Adobe Aero. Geospatial Creator provides a 3D view of the world, allowing users to place their digital content in the real world, similar to Google Earth and Google Street View. , In April 2023, Hexagon AB launched the HxGN AgrOn Control Room. It is a mobile app that allows managers and directors of agricultural companies to monitor all field operations in real time. It helps managers identify and address problems quickly, saving time and money. Additionally, the app can help to improve safety by providing managers with a way to monitor the location and status of field workers. , In December 2022, ESRI India announced the availability of Indo ArcGIS offerings on Indian public clouds and services to provide better management, collecting, forecasting, and analyzing location-based data. , In May 2022, Trimble announced the launch of the Trimble R12i GNSS receiver, which has a powerful tilt adjustment feature. It enables land surveyors to concentrate on the task and finish it more quickly and precisely. , In May 2021, Foursquare purchased Unfolded, a US-based provider of location-based services. This US-based firm provides location-based services and goods, including data enrichment analytics and geographic data visualization. With this acquisition, Foursquare aims to provide its users access to various first and third-party data sets and integrate them with the geographical characteristics. , In January 2021, ESRI, a U.S.-based geospatial image analytics solutions provider, introduced the ArcGIS platform. ArcGIS Platform by ESRI operates on a cloud consumption paradigm. App developers generally use this technology to figure out how to include location capabilities in their apps, business operations, and goods. It aids in making geospatial technologies accessible. .

This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 29 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the Census tract 2022 boundary file in a GIS system to produce maps for 40 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values.The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: April 2025 (preliminary values at the county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: June 24th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

The Geographic Information System (GIS) industry is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) of 10.80% from 2025 to 2033. This expansion is driven by increasing adoption across diverse sectors, including agriculture, utilities, mining, construction, transportation, and oil and gas. The rising need for precise location-based data for efficient operations, optimized resource management, and informed decision-making fuels this market growth. Advancements in hardware, such as high-resolution sensors and drones, coupled with sophisticated software capabilities like advanced spatial analytics and cloud-based GIS solutions, are key contributors. Furthermore, the proliferation of location-based services (LBS) and the growing adoption of telematics and navigation systems are expanding the applications of GIS technology. While data security concerns and the need for skilled professionals present some challenges, the overall market outlook remains positive. The segmentation of the GIS market reveals a strong demand across various components (hardware and software) and functionalities (mapping, surveying, telematics and navigation, and location-based services). North America currently holds a significant market share due to early adoption and technological advancements, but regions like Asia are exhibiting rapid growth fueled by infrastructure development and increasing digitalization. Leading companies like Bentley Systems, Esri, Trimble, and Hexagon AB are at the forefront of innovation, continuously developing and implementing advanced GIS solutions to meet the evolving needs of different industries. The forecast for the next decade points to further market consolidation, with leading players investing heavily in research and development to enhance their product offerings and expand their market reach. The continued integration of GIS with other technologies such as AI and IoT will further drive market expansion and create new opportunities for growth. Comprehensive Coverage GIS Industry Report (2019-2033) This in-depth report provides a comprehensive analysis of the Geographic Information System (GIS) industry, projecting robust growth from $XXX million in 2025 to $YYY million by 2033. The study covers the historical period (2019-2024), base year (2025), and forecast period (2025-2033), offering invaluable insights for businesses, investors, and policymakers. Keywords: GIS market, GIS software, GIS hardware, GIS solutions, geospatial technology, location intelligence, mapping software, surveying equipment, spatial analysis, geospatial analytics. Recent developments include: November 2022 : The new Geodata Portal and broadband maps for the state will be accessible starting on November 18, 2022, according to a statement from the Connecticut Office of Policy and Management (OPM). This announcement was made on GIS Day 2022, which encourages people to learn about geography and the practical uses of GIS that can improve society., November 2022 : The lt. governor of the Indian state, Jammu and Kashmir, launched a GIS-based system in the region. It highlights the significance of GIS technology in addressing new challenges and exploring new opportunities and its real-world applications, accelerating growth in business, government, and society.. Key drivers for this market are: Growing role of GIS in smart cities ecosystem, Integration of location-based mapping systems with business intelligence systems. Potential restraints include: Integration issues with traditional systems, Data quality and accuracy issues. Notable trends are: The Rising Smart Cities Development and Urban Planning to Drive the Market Growth.

This data layer is an Esri file geodatabase polyline feature class that contains street centerlines maintained by county agencies in Indiana. It was released by the Indiana Geographic Information Office (IGIO) on December 1, 2022. The IGIO compiled the data as part of the Indiana Data Harvest program between the Indiana Geographic Information Council (IGIC) and all Indiana counties to provide the most accurate framework data for the citizens of Indiana. These layers include address points, street centerlines, land parcels, and governmental boundaries.

This is a ZIPPED csv comma-delimited file used to produce the Change of Assessment.

Statewide Ecopia 3 foot Land Cover (2021-2022)This raster land cover data is based off of high-resolution statewide imagery from 2021-2022. It was used by Ecopia to extract and digitize the entire state into 7 different land cover classes. Download Notes:This service can be entered into ArcGIS Pro where "Download Rasters" can be used to download approximately 20 square miles at a time. (Rt. click layer in TOC > Data > Download Rasters)Alternatively, the entire statewide 3ft dataset is available as a zipped download from here (includes colormap file): Ecopia_Statewide_3ft_Raster_TilesClasses available at bottom of this pages.Data SpecificationImagery Used for Extraction: Pixel resolution: 15 cm (6")Camera sensor: Hexagon Pushbroom (Content Mapper)Date of capture: 06/25/2021 - 08/14/2022Date of Vector Extraction: June 2023Extraction Methodology:Ecopia uses proprietary extraction and modeling software to process raw images into high-resolution land cover classifications.Quality Measurements:Measure Name - Threshold across Impervious Polygons:False Negatives <= 5% All PolygonsFalse Positives <= 5% All PolygonsValid Interpretation >= 95% All PolygonsMinimum Area 100% All PolygonsValid Geometry 100% All PolygonsMeasure Name - Threshold across Natural Polygons:False Negatives <=5% All PolygonsFalse Positives <=5% All PolygonsValid Interpretation >=90% All PolygonsMinimum Area 100% All PolygonsValid Geometry 100% All PolygonsLand Cover Classes:UnclassifiedImperviousImpervious, covered by treesShrub/low vegetationTree/forest/high vegetationOpen waterRailroadVegetation (Canopy Mapping)Tree canopy will be captured as a unique polygon layer. It can therefore overlap impervious layers.High vegetation is distinguished from low vegetation based on crown, texture, and derived height models. Leveraging stereo imagery produces results using 3D elevation models used to aid the distinction of vegetation categories. Distinguishing low from high vegetation is based on a 5m threshold, but this is not always feasible, especially in areas where heavy canopy prevents a visualization of the ground. In these circumstances, high vegetation will be given the priority over low vegetation. For more information visit: www.ecopiatech.comClasses:0: No data - Null, clear1: Unclassified2: Impervious3: Impervious, Covered by Tree Canopy6: Shrub/Low Vegetation7: Tree/Forest/High Vegetation8: Open Water12: Railroad

[Metadata] This layer contains the collection dates of the imagery contained in the image service shown here: https://geodata.hawaii.gov/arcgis/rest/services/SoH_Imagery/Vivid_2022/ImageServer. Source: USDA Farm Production and Conservation Business Center Geospatial Operations Group, April, 2023.For additional information, please see https://files.hawaii.gov/dbedt/op/gis/data/Vivid_2022_Metadata.pdf, or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

The dataset is a feature class showing the boundaries of 515 groundwater basins and subbasins as defined by the California Department of Water Resources as last modified by the Basin Boundary Emergency Regulation adopted on October 21, 2015 and subsequent modifications requested through the Basin Boundary Modification Request Process. This data is current as of December 9, 2022. The file is in ESRI geodatabase format and is intended for use with compatible GIS software. Groundwater basins are represented as polygon features and designated on the basis of geological and hydrological conditions - usually the occurrence of alluvial or unconsolidated deposits. When practical, large basins are also subdivided by political boundaries, as in the Central Valley. Basins are named and numbered per the convention of the Department of Water Resources.

This dataset contains data used to test the protocol for high-resolution mapping and monitoring of recreational impacts in protected natural areas (PNAs) using unmanned aerial vehicle (UAV) surveys, Structure-from-Motion (SfM) data processing and geographic information systems (GIS) analysis to derive spatially coherent information about trail conditions (Tomczyk et al., 2023). Dataset includes the following folders:

Cocora_raster_data (~3GB) and Vinicunca_raster_data (~32GB) - a very high-resolution (cm-scale) dataset derived from UAV-generated images. Data covers selected recreational trails in Colombia (Valle de Cocora) and Peru (Vinicunca). UAV-captured images were processed using the structure-from-motion approach in Agisoft Metashape software. Data are available as GeoTIFF files in the UTM projected coordinate system (UTM 18N for Colombia, UTM 19S for Peru). Individual files are named as follows [location]_[year]_[product]_[raster cell size].tif, where:

[location] is the place of data collection (e.g., Cocora, Vinicucna)

[year] is the year of data collection (e.g., 2023)

[product] is the tape of files: DEM = digital elevation model; ortho = orthomosaic; hs = hillshade

[raster cell size] is the dimension of individual raster cell in mm (e.g., 15mm)

Cocora_vector_data. and Vinicunca_vector_data – mapping of trail tread and conditions in GIS environment (ArcPro). Data are available as shp files. Data are in the UTM projected coordinate system (UTM 18N for Colombia, UTM 19S for Peru).

Structure-from-motio n processing was performed in Agisoft Metashape (https://www.agisoft.com/, Agisoft, 2023). Mapping was performed in ArcGIS Pro (https://www.esri.com/en-us/arcgis/about-arcgis/overview, Esri, 2022). Data can be used in any GIS software, including commercial (e.g. ArcGIS) or open source (e.g. QGIS).

Tomczyk, A. M., Ewertowski, M. W., Creany, N., Monz, C. A., & Ancin-Murguzur, F. J. (2023). The application of unmanned aerial vehicle (UAV) surveys and GIS to the analysis and monitoring of recreational trail conditions. International Journal of Applied Earth Observations and Geoinformation, 103474. doi: https://doi.org/10.1016/j.jag.2023.103474

This dataset contains model-based census tract level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7