Environmental Sensitivity Index (ESI) maps are an integral component in oil-spill contingency planning and assessment. They serve as a source of information in the event of an oil spill incident. ESI maps are a product of the Hazardous Materials Response Division of the Office of Response and Restoration (OR&R).ESI maps contain three types of information: shoreline habitats (classified according to their sensitivity to oiling), human-use resources, and sensitive biological resources. Most often, this information is plotted on 7.5 minute USGS quadrangles, although in Alaska, USGS topographic maps at scales of 1:63,360 and 1:250,000 are used, and in other atlases, NOAA charts have been used as the base map. Collections of these maps, grouped by state or a logical geographic area, are published as ESI atlases. Digital data have been published for most of the U.S. shoreline, including Alaska, Hawaii and Puerto Rico.

Environmental Sensitivity Index (ESI) data characterize the marine and coastal environments and wildlife based on sensitivity to spilled oil. Coastal species that are listed as threatened, endangered, or as a species of concern, by either federal or state governments, are a primary focus. A subset of the ESI data, the ESI Threatened and Endangered Species (T&E) databases focus strictly on these species. Species are mapped individually. In addition to showing spatial extent, each species polygon, point, or line has attributes describing abundance, seasonality, threatened/endangered status, and life history. Both the state and federal status is provided, along with the year the ESI data were published. This is important, as the status of a species can vary over time. As always, the ESI data are a snapshot in time. The biology layers focus on threatened/endangered status, areas of high concentration, and areas where sensitive life stages may occur. Supporting data tables provide species-/location-specific abundance, seasonality, status, life history, and source information. Human-use resources mapped include managed areas (parks, refuges, critical habitats, etc.) and resources that may be impacted by oiling and/or cleanup, such as beaches, archaeological sites, marinas, etc. ESIs are available for the majority of the US coastline, as well as the US territories. ESI data are available as PDF maps, as well as in a variety of GIS formats. For more information, go to http://response.restoration.noaa.gov/esi . To download complete ESI data sets, go to http://response.restoration.noaa.gov/esi_download .

Idaho Department of Environmental Quality GISDEQ's MissionTo protect human healthand preserve the quality of Idaho's air, land, and waterfor use and enjoyment today and in the future.DEQ is a state department created by the Idaho Environmental Protection and Health Act to ensure clean air, water, and land in the state and protect Idaho citizens from the adverse health impacts of pollution.As a regulatory agency, DEQ enforces various state environmental regulations and administers a number of federal environmental protection laws including the Clean Air Act, the Clean Water Act, and the Resource Conservation and Recovery Act.The agency is committed to working in partnership with local communities, businesses, and citizens to identify and implement cost-effective environmental solutions.Idaho DEQ GIS Home PageIdaho DEQ GIS HUB Open DataIdaho DEQ Home PageIDEQ ArcGIS Server Mapping ApplicationsFinal 2022 305b Integrated ReportGround Water Quality Monitoring WellsIDEQ 2020 Nitrate Priority AreasIDEQ Source Water Assessment and ProtectionIDEQ Source Water Grant Project Locator Tool

Data shows polygon locations of Potential Environmental Justice Areas (PEJA) and is defined in the PEJA field. PEJA's have been identified based on data from the 2014-2018 5-year American Community Survey (ACS), conducted by the US Census Bureau. Environmental justice efforts focus on improving the environment in communities, specifically minority and low-income communities, and addressing disproportionate adverse environmental impacts that may exist in those communities. The information balloon for each census block group area displays the census block group ID, population, percent minority, percent below poverty level, county, municipality, and a link to more information on the Department of Environmental Conservation's website https://www.dec.ny.gov/public/333.html The data was collected by the US Census Bureau as part of the American Community Survey. Reported income and race/ethnicity data were analyzed by OEJ to determine the presence of Potential Environmental Justice Areas. The designated areas are then considered for additional outreach within the permitting process, for grant eligibility, and for targeted enforcement of Environmental Conservation Law violations. Utilized established methods as originally detailed in the Interim Environmental Justice Policy, US EPA Region 2, December 2000, and recommended by the Environmental Justice Advisory Group, Recommendations for the New York State Department of Environmental Conservation Environmental Justice Program, January 2, 2002. Individual thresholds for low-income populations (statewide), minority populations (rural communities), and minority populations (urban communities) were determined by using ArcGIS 10.3 (used to indicate if census block groups overlapped Census designated urban areas) and IBM SPSS Statistics 26 (to conduct a K-means clustering algorithm on ACS data for the three categories). More detail is provided under processing steps. Service updated annually. For more information or to download layer see https://gis.ny.gov/gisdata/inventories/details.cfm?DSID=1273Download the metadata to learn more information about how the data was created and details about the attributes. Use the links within the metadata document to expand the sections of interest see http://gis.ny.gov/gisdata/metadata/nysdec.PEJA.xml

Environmental pollution is a persistent problem in terrestrial ecosystems, including remote mountain areas. This study investigates the extent and patterns of littering on three popular hiking trails among mountaineers and tourists in the Dolomites range located in northeastern Italy. The data was collected adopting a citizen science approach with the participation of university students surveying the trails and recording the macroscopic waste items through a GPS-based offline platform. The waste items were categorized according to their material type, usage, and geographical location, and the sorted data was applied to Esri GIS ArcMapTM 10.8.1.

The air quality in Beijing, especially its PM2.5 level, has become of increasing public concern because of its importance and sensitivity related to health risks. A set of monitored PM2.5 data from 31 stations, released for the first time by the Beijing Environmental Protection Bureau, covering 37 days during autumn 2012, was processed using spatial interpolation and overlay analysis. Following analyses of these data, a distribution map of cumulative exceedance days of PM2.5 and a temporal variation map of PM2.5 for Beijing have been drawn. Computational and analytical results show periodic and directional trends of PM2.5 spreading and congregating in space, which reveals the regulation of PM2.5 overexposure on a discontinuous medium-term scale. With regard to the cumulative effect of PM2.5 on the human body, the harm from lower intensity overexposure in the medium term, and higher overexposure in the short term, are both obvious. Therefore, data of population distribution were integrated into the aforementioned PM2.5 spatial spectrum map. A spatial statistical analysis revealed the patterns of PM2.5 gross exposure and exposure probability of residents in the Beijing urban area. The methods and conclusions of this research reveal relationships between long-term overexposure to PM2.5 and people living in high-exposure areas of Beijing, during the autumn of 2012.

Seattle Parks and Recreation ARCGIS park feature map layer web services are hosted on Seattle Public Utilities' ARCGIS server. This web services URL provides a live read only data connection to the Seattle Parks and Recreations Environmental Learning Centers dataset.

Environmental Justice neighborhoods are the focus of the state's Executive Office of Energy and Environmental Affairs' (EEA) Environmental Justice (EJ) Policy, which establishes EJ as an integral consideration in all EEA programs, to the extent applicable and allowable by law. For more information please visit EEA's Environmental Justice Web page, which includes a detailed fact sheet as well as text of the full policy.More details...Polygons in the 2020 Environmental Justice (EJ) Populations layer are 2020 Census block groups across the state that meet one or more of the criteria listed below. (i) the annual median household income is not more than 65 percent of the statewide annual median household income; (ii) minorities comprise 40 percent or more of the population; (iii) 25 percent or more of households lack English language proficiency; or (iv) minorities comprise 25 percent or more of the population and the annual median household income of the municipality in which the neighborhood is located does not exceed 150 percent of the statewide annual median household income.Map service also available.

This is a link to the Department of Environmental Protection (DEP) Open Data Portal which is operated by DEP's Geospatial Data Center on an Esri platform.

The research project from which this dataset was produced was designed to help bridge the divide in understanding of the possible environmental causes of breast cancer in the United Kingdom. This divide exists between the official cancer research and treatment world, and other unofficial groups of diverse expertise. The geographic information system methodology used (Geographic Information Systems for Participation, or GIS-P) was intended to increase the understanding of the various positions in the debate both for the researchers, but also more importantly, between the communities of interest. The intention was to stimulate debate through the shared understanding that could be achieved by debating the knowledge and viewpoints expressed through the maps. In this respect, debate stimulation was more important than to capture detailed participatory derived spatial data (as has been the case with previous GIS-P projects). In practice, the process proved problematic, which explains the relatively limited quantity of GIS-P data collected.

This article uses a multiscale approach for assessing landscape changes in one of the world’s biodiversity hotspots in Brazil, the Rio Doce State Park (PERD). In this article, we assess land use changes over a 30 year period. Our results show that, while inside the park landscape changes were minimal, in the park buffer zone human induced changes are steadily rising due to an increase in eucalyptus plantations and urban sprawl that grew by 4% and 1.9%, respectively. Agricultural land has been reduced by 6.35%, but there are trends that a form of welcome forest transition has been occurring. We report an increase in native forests from 40,588 ha in 1985 to 45,690 ha in 2015. The analysis of human impacts in the study area delivers very different results when varying the pixel size from 25 ha to 900 m2. The former shows a very high level of human influence while the latter reveals small but vital patches of native forest offering hopeful opportunities for sustainable natural resource management in this critical biome. Our work stresses the importance of better targeted policy making and sympathetic land use management of buffer zones of protected areas. Currently, such zones suffer from many development pressures and often experience contradictory policy frameworks which encourage a clash between biodiversity conservation and intensive agro husbandry production. Highlights: • We characterize land use transitions in a hotspot of biodiversity in Brazil. • Analysis at finer resolution show that there is still hope for forest recovery. • For instilling sustainable forest transitions there is the need for fresh governance.

IntroductionBuilt environment attributes have been linked to cardiovascular disease (CVD) risk. Therefore, identifying built environment attributes that are associated with CVD risk is relevant for facilitating effective public health interventions.ObjectiveTo conduct a systematic review of literature to examine the influence of built environmental attributes on CVD risks.Data SourceMultiple database searches including Science direct, CINAHL, Masterfile Premier, EBSCO and manual scan of reference lists were conducted.Inclusion CriteriaStudies published in English between 2005 and April 2015 were included if they assessed one or more of the neighborhood environmental attributes in relation with any major CVD outcomes and selected risk factors among adults.Data ExtractionAuthor(s), country/city, sex, age, sample size, study design, tool used to measure neighborhood environment, exposure and outcome assessments and associations were extracted from eligible studies.ResultsEighteen studies met the inclusion criteria. Most studies used both cross-sectional design and Geographic Information System (GIS) to assess the neighborhood environmental attributes. Neighborhood environmental attributes were significantly associated with CVD risk and CVD outcomes in the expected direction. Residential density, safety from traffic, recreation facilities, street connectivity and high walkable environment were associated with physical activity. High walkable environment, fast food restaurants, supermarket/grocery stores were associated with blood pressure, body mass index, diabetes mellitus and metabolic syndrome. High density traffic, road proximity and fast food restaurants were associated with CVDs outcomes.ConclusionThis study confirms the relationship between neighborhood environment attributes and CVDs and risk factors. Prevention programs should account for neighborhood environmental attributes in the communities where people live.

Data for maps and figures in "Global Potential for Harvesting Drinking Water from Air using Solar Energy" in Nature.

Current statewide map of the geographic territories of Environmental Enforcement Officers. Part of a dataset that contains administrative boundaries for Vermont's Agency of Natural Resources. The dataset includes feature classes for ACT 250, Environmental Enforcement, Fisheries, Forestry, Lieutennant Chief Warden, Park, Solid Waste, Warden, Watershed Planning, Wastewater, Wildlife, Wildlife Management Units, River Management Engineering Districts, and Tactical Planning Basin.

This public GIS dataset comes from the Alaska GAP project, and it is part of the final project report (Gotthard, Pyare, Huettmann et al. 2013). Here we present a copy of the original data set as a value-added product for basic use and training purposes. It consists of 53 environmental layers for all of Alaska in an ArcGIS 10 format and usually with a pixel size of 60m. These layers were compiled from various sources, and authorships should be fully honoured as stated in the details of this metadata. Output maps were clipped using a state of Alaska coastline in the Alaska Albers NAD83 projection; very small islands are excluded.The data layers were initially compiled for ecological niche models of Alaska's terrestrial biodiversity using Maxent and other Machine Learning algorithms. However, they can also be used for many other purposes, e.g. strategic conservation planning and individual information and assessments. The datasets are a snapshot in space and time (2012) but likely remain valid for years to come. It is appreciated that these data layers are 'living products', and it is hoped that this public data publication here will progress and trigger many updates and data quality improvements for Alaska and its public high-quality data over time. The following variables are included in this dataset: Boundaries Coastline, Climate Precipitation January til December Average monthly precipitation (mm), Climate Precipitation Average annual precipitation (mm), Climate Temperature January til December Average monthly temperature (deg C), Climate Temperature annual temperature (dec C), Climate First day of thaw (Julian date), Climate First day of freeze (Julian date), Climate Length of growing season Number of days, Disturbance Insect history (Year), Distance to Disturbance Insect location (m), Disturbance Fire history Year of fire (1942 til 2007), distance to Disturbance Fire location (m), Soils Grid (category), Surfacial Geology Grid values, Glacial Distance (m), Distance(m) to lotic water, Distance (m) to permafrost boundary, Distance(m) to lentic water, Saltwater Presence, Distance (m) to Sea Ice Extent 2003-2007 December, Distance (m) to Sea Ice Extent 2003-2007 July, Distance to Development Infrastructure, Landcover Vegetation (Landfire), Landcover nlcd60, Elevation (m), Slope (%), Aspect (Degrees from due south), Terrain Ruggedness index, Extent nullgrid 9999, Coast raster.

The global 4D Geographic Information System (GIS) market size was valued at USD 2743 million in 2025 and is projected to reach USD 7931.3 million by 2033, exhibiting a CAGR of 14.5% during the forecast period (2025-2033). The market growth is attributed to the increasing adoption of 4D GIS in various industries, including environmental monitoring, urban planning, traffic monitoring, and the military. Furthermore, the growing need for accurate and timely geospatial information for decision-making is driving the demand for 4D GIS solutions. The market for 4D GIS is segmented by type (remote sensing 4D GIS, sensor-based 4D GIS) and application (environmental monitoring, urban planning, traffic monitoring, military, others). Remote sensing 4D GIS is expected to hold a significant market share due to its ability to provide high-resolution images and data for various applications. In terms of application, environmental monitoring is expected to witness the highest growth rate during the forecast period, owing to the increasing need for real-time monitoring of environmental parameters such as air quality, water quality, and land use. Key players in the market include ESRI, Hexagon, GeoMarvel, Autodesk, Bentley Systems, Trimble Inc., and 4D Mapper. 4D Geographic Information System (GIS)

This Innovative Technology Experiences for Students and Teachers (ITEST) project has developed, implemented, and evaluated a series of innovative Socio-Environmental Science Investigations (SESI) using a geospatial curriculum approach. It is targeted for economically disadvantaged 9th grade high school students in Allentown, PA, and involves hands-on geospatial technology to help develop STEM-related skills. SESI focuses on societal issues related to environmental science. These issues are multi-disciplinary, involve decision-making that is based on the analysis of merged scientific and sociological data, and have direct implications for the social agency and equity milieu faced by these and other school students. This project employed a design partnership between Lehigh University natural science, social science, and education professors, high school science and social studies teachers, and STEM professionals in the local community to develop geospatial investigations with Web-based Geographic Information Systems (GIS). These were designed to provide students with geospatial skills, career awareness, and motivation to pursue appropriate education pathways for STEM-related occupations, in addition to building a more geographically and scientifically literate citizenry. The learning activities provide opportunities for students to collaborate, seek evidence, problem-solve, master technology, develop geospatial thinking and reasoning skills, and practice communication skills that are essential for the STEM workplace and beyond. Despite the accelerating growth in geospatial industries and congruence across STEM, few school-based programs integrate geospatial technology within their curricula, and even fewer are designed to promote interest and aspiration in the STEM-related occupations that will maintain American prominence in science and technology. The SESI project is based on a transformative curriculum approach for geospatial learning using Web GIS to develop STEM-related skills and promote STEM-related career interest in students who are traditionally underrepresented in STEM-related fields. This project attends to a significant challenge in STEM education: the recognized deficiency in quality locally-based and relevant high school curriculum for under-represented students that focuses on local social issues related to the environment. Environmental issues have great societal relevance, and because many environmental problems have a disproportionate impact on underrepresented and disadvantaged groups, they provide a compelling subject of study for students from these groups in developing STEM-related skills. Once piloted in the relatively challenging environment of an urban school with many unengaged learners, the results will be readily transferable to any school district to enhance geospatial reasoning skills nationally.

https://github.com/gruizmer/COW2NUTRIENT/tree/master/ToolPaper_DataFiles * These folders supply supporting datasets for the manuscript "COW2NUTRIENT: An environmental GIS-based decision support tool for the assessment of nutrient recovery systems in livestock facilities." * The datasets are recorder as comma-separated values (.csv) and Microsoft Excel® (.xlsx) files. Column data entries have names and units. Some data are about animal facility population and location, amount of nutrient-rich waste generated (kg/yr), amount of nutrient recovered (kg P/yr), installing, capital, and maintenance costs (USD), technologies and their ranking and frequency of being selected for each combination of normalization-aggregation methods, average chlorophyll-a concentration in water in the watershed (ug/L), and average phosphorus concentration in water in the watershed (ug/L). * The folder “Manuscript” has subfolders with datasets for creating manuscript Figures 4, 8, 9, and 10 as well as datasets for Tables 9 and 10. * The folder “Supplementary Material” holds subfolders with datasets for creating Supplementary Material Figures 1-5, 8, 9, 11, and 12. This dataset is associated with the following publication: Martin-Hernandez, E., M. Martin, and G.J. Ruiz-Mercado. A geospatial environmental and techno-economic framework for sustainable phosphorus management at livestock facilities. Resources, Conservation and Recycling. Elsevier Science BV, Amsterdam, NETHERLANDS, 175: 105843, (2021).

This data set contains vector polygons representing the boundaries of all hardcopy cartographic products and digital data extents produced as part of the Environmental Sensitivity Index (ESI) for Southern California. This data set comprises a portion of the ESI data for Southern California. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.Please note that this data was selected from a larger dataset for use in the San Diego Ocean Planning Partnership, a collaborative pilot project between the California State Lands Commission and the Port of San Diego. For more information about the Partnership, please visit: https://www.sdoceanplanning.org/When within the San Diego Ocean Planning Partnership web mapping application, clicking on a polygon will present a link to an online version of the map. To add the data itself to the application, please use the add data widget and the following web service URL: https://idpgis.ncep.noaa.gov/arcgis/rest/services/NOS_ESI/ESI_SouthernCalifornia_Data/MapServer

Various Environmental GIS Data