This application can be used to help determine if an applicant's project meets the low/moderate income threshold for eligibility to be funded under the Lake County Illinois Community Development Block Grant program.

description: This tool provides a no-cost downloadable software tool that allows users to interact with professional quality GIS maps. Users access pre-compiled projects through a free software product called ArcReader, and are able to open and explore HUD-specific project data as well as design and print custom maps. No special software/map skills beyond basic computer skills are required, meaning users can quickly get started working with maps of their communities.; abstract: This tool provides a no-cost downloadable software tool that allows users to interact with professional quality GIS maps. Users access pre-compiled projects through a free software product called ArcReader, and are able to open and explore HUD-specific project data as well as design and print custom maps. No special software/map skills beyond basic computer skills are required, meaning users can quickly get started working with maps of their communities.

Census Tract data with ACS demographics for use with GIS mapping software, databases, and web applications are from Caliper Corporation.

Web Mapping Market Outlook

The global web mapping market size was valued at approximately USD 3.5 billion in 2023 and is projected to reach USD 8.2 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.8% during the forecast period. The robust growth of this market can be attributed to the increasing demand for geographic information system (GIS) technologies and the expanding applications of web mapping across various industries.

One of the primary growth factors driving the web mapping market is the proliferation of location-based services. With the rise of smartphones and IoT devices, the demand for real-time location data has skyrocketed, fueling the need for advanced web mapping solutions. Businesses are leveraging location-based services to enhance customer engagement, optimize logistics, and improve decision-making processes. Moreover, the integration of web mapping with emerging technologies such as AI and machine learning is further bolstering market growth, allowing for more sophisticated and predictive mapping capabilities.

Another critical factor contributing to the market's expansion is the growing adoption of web mapping solutions in government and public sector initiatives. Governments across the globe are increasingly utilizing web mapping technologies for urban planning, disaster management, and community services. These technologies provide invaluable insights and real-time data that aid in making informed decisions and improving public services. The push for smart city developments and the need for efficient infrastructure management are also significant drivers for the adoption of web mapping solutions in the public sector.

Furthermore, the transportation and logistics industry is witnessing a substantial uptake of web mapping technologies. With the rise of e-commerce and the need for efficient supply chain management, companies are relying on web mapping to optimize routes, monitor shipments, and ensure timely deliveries. The integration of GPS technology and real-time tracking systems with web mapping solutions is enhancing operational efficiencies and reducing costs. This trend is likely to continue as the demand for seamless logistics and transportation services grows.

The concept of an Electronic Map has become increasingly significant in the web mapping market. Electronic maps are digital representations of geographic areas and are pivotal in providing real-time data and location-based insights. They are extensively used in various applications, from navigation systems to urban planning and environmental monitoring. The integration of electronic maps with web mapping technologies allows for enhanced visualization and analysis of spatial data, offering users detailed and interactive geographic information. As the demand for digital mapping solutions continues to grow, electronic maps are playing a crucial role in transforming how geographic information is accessed and utilized across different sectors.

On the regional front, North America remains a dominant player in the web mapping market, primarily due to the early adoption of advanced technologies and the presence of major market players in the region. The Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, driven by rapid urbanization, technological advancements, and increasing investments in smart city projects. Europe and Latin America are also anticipated to witness significant growth, supported by favorable government initiatives and the expanding use of web mapping across various industries.

Component Analysis

The web mapping market can be segmented by component into software and services. The software segment encompasses a wide range of GIS and mapping software that enable users to create, visualize, and analyze geographic data. This segment is witnessing significant growth due to the increasing need for sophisticated mapping tools that offer real-time data and advanced analytical capabilities. Companies are continuously enhancing their software offerings with features like AI integration, cloud compatibility, and user-friendly interfaces, driving the adoption of web mapping software across various industries.

On the other hand, the services segment includes a variety of professional services such as consulting, implementation, and maintenance. As organizations seek to leverage web mapping technologies, they often require expert guidance and support to ensu

The My Community Map web application presents current rezoning and zoning adjustment applications also current permit applications and site plan reviews. Users can search for application data using various location tools and by application number. Users can use a buffer search tool to search for applications within a certain distance of a point on the map. The application also presents General Plan, Planning Overlay, Village and historic property information.

The Monitoring and Mapping Software market is experiencing robust growth, driven by the increasing adoption of drones, advanced sensors, and the rising need for precise geospatial data across diverse sectors. The market's expansion is fueled by applications in construction, agriculture, mining, and urban planning, where real-time data and accurate 3D models are crucial for efficient operations and informed decision-making. The integration of AI and machine learning capabilities within these software solutions is further enhancing their analytical power, enabling automated feature extraction, object recognition, and predictive modeling. This leads to improved efficiency, reduced operational costs, and enhanced safety measures. Key players like Hexagon, Trimble, and Autodesk are driving innovation through continuous product development and strategic acquisitions, while the emergence of open-source solutions like Regard3D and Alicevision fosters community development and wider accessibility. The market is segmented by software type (image/video-based, 3D scanning-based) and deployment (cloud, on-premise), with cloud-based solutions gaining significant traction due to their scalability and accessibility. Looking ahead, the market is expected to witness continued expansion, propelled by ongoing technological advancements, including the development of higher-resolution sensors, improved processing power, and the integration of Internet of Things (IoT) devices. The growing demand for precise mapping and monitoring in infrastructure projects, environmental monitoring, and disaster management will also contribute significantly to market growth. However, factors such as the high initial investment costs associated with sophisticated software and hardware, and the need for specialized expertise to operate and interpret the data, could pose challenges to market penetration. Nevertheless, the overall outlook remains positive, with a substantial increase in market size projected over the forecast period. The market's competitiveness is expected to intensify as more players enter the market and existing companies strive to enhance their product offerings to meet evolving customer demands.

Current community area boundaries in Chicago. The data can be viewed on the Chicago Data Portal with a web browser. However, to view or use the files outside of a web browser, you will need to use compression software and special GIS software, such as ESRI ArcGIS (shapefile) or Google Earth (KML or KMZ), is required.

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

Example citations:

Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

11.1 Refugial potential for vascular plants and mammals (1990-2050)

11.1 Refugial potential for reptiles and amphibians (1990-2050)

12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

Abstract

MEJ aims to create easy-to-use, publicly-available maps that paint a holistic picture of intersecting environmental, social, and health impacts experienced by communities across the US.

With guidance from the residents of impacted communities, MEJ combines environmental, public health, and demographic data into an indicator of vulnerability for communities in every state. MEJ’s goal is to fill an existing data gap for individual states without environmental justice mapping tools, and to provide a valuable tool for advocates, scholars, students, lawyers, and policy makers.

Methodology

The negative effects of pollution depend on a combination of vulnerability and exposure. People living in poverty, for example, are more likely to develop asthma or die due to air pollution. The method MEJ uses, following the method developed for CalEnviroScreen, reflects this in the two overall components of a census tract’s final “Cumulative EJ Impact”: population characteristics and pollution burden. The CalEnviroScreen methodology was developed through an intensive, multi-year effort to develop a science-backed, peer-reviewed tool to assess environmental justice in a holistic way, and has since been replicated by several other states.

CalEnviroScreen Methodology:

• Population characteristics are a combination of socioeconomic data (often referred to as the social determinants of health) and health data that together reflect a populations' vulnerability to pollutants. Pollution burden is a combination of direct exposure to a pollutant and environmental effects, which are adverse environmental conditions caused by pollutants, such as toxic waste sites or wastewater releases. Together, population characteristics and pollution burden help describe the disproportionate impact that environmental pollution has on different communities.

• Every indicator is ranked as a percentile from 0 to 100 and averaged with the others of the same component to form an overall score for that component. Each component score is then percentile ranked to create a component percentile. The Sensitive Populations component score, for example, is the average of a census tract’s Asthma, Low Birthweight Infants, and Heart Disease indicator percentiles, and the Sensitive Populations component percentile is the percentile rank of the Sensitive Populations score.

• The Population Characteristics score is the average of the Sensitive Populations component score and the Socioeconomic Factors component score. The Population Characteristics percentile is the percentile rank of the Population Characteristics score.

• The Pollution Burden score is the average of the Pollution Exposure component score and one half of the Environmental Effects component score (Environmental Effects may have a smaller effect on health outcomes than the indicators included the Exposures component so are weighted half as much as Exposures). The Pollution Burden percentile is the percentile rank of the Pollution Burden score.

• The Populaton Characteristics and Pollution Burden scores are then multiplied to find the final Cumulative EJ Impact score for a census tract, and then this final score is percentile-ranked to find a census tract's final Cumulative EJ Impact percentile.

• Census tracts with no population aren't given a Population Characteristics score.

• Census tracts with an indicator score of zero are assigned a percentile rank of zero. Percentile rank is then only calculated for those census tracts with a score above zero.

• Census tracts that are missing data for more than two indicators don't receive a final Cumulative EJ Impact ranking.

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description: This EnviroAtlas dataset shows the boundary of the Des Moines, IA EnviroAtlas Community. It represents the outside edge of all the block groups included in the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://enviroatlas.epa.gov/EnviroAtlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas ) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets); abstract: This EnviroAtlas dataset shows the boundary of the Des Moines, IA EnviroAtlas Community. It represents the outside edge of all the block groups included in the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://enviroatlas.epa.gov/EnviroAtlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas ) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

description: This EnviroAtlas dataset shows the boundary of the Cleveland, OH EnviroAtlas Community. It represents the outside edge of all the block groups included in the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).; abstract: This EnviroAtlas dataset shows the boundary of the Cleveland, OH EnviroAtlas Community. It represents the outside edge of all the block groups included in the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Large scale community mapping at scales of 1:2500 and 1:5000 derived from aerial photography and detailed mapping processes. Community mapping in this application exists as Vector Tiles.

The Research Software Alliance's (ReSA) mission is to bring research software communities together to collaborate on the advancement of research software. Given the ReSA mission, it is important to understand the landscape of communities involved with research software. In 2020, ReSA completed an initial exercise to scope the international research software community landscape. This work was reported by ReSA's Software Landscape Analysis task force via a blog post. The majority of the communities in the previous analysis represented the global north. To improve the extent of this landscape analysis, ReSA announced a paid opportunity for short-term contractors located in the global south to collect data on communities and funders in their region in early 2022. This document describes how the work was undertaken, a summary of findings, the gaps and opportunities perceived by the data collectors and some highlights. This work identified 126 organisations and communities and 62 funder bodies that support research software in the global south. Their main activities are connecting people, training, and networking, and support through research grants.

To add to this communities list please fill in the following form https://forms.gle/KJE9vkBnM6vhh7cEA

description: This EnviroAtlas dataset shows the boundary of the New York, NY EnviroAtlas Community. It represents the outside edge of all the block groups included in the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets); abstract: This EnviroAtlas dataset shows the boundary of the New York, NY EnviroAtlas Community. It represents the outside edge of all the block groups included in the EnviroAtlas community. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

In accordance with the New Jersey Partnership to Plug-In, “Partnership” (signed June 3rd, 2019), the Department is developing mapping that that will help inform strategic placement of electric vehicle (EV) charging infrastructure. Further, Public Law 2019, chapter 362, “EV Law” (signed January 17th, 2020), prescribes more specific requirements for EV charging infrastructure, with regard to number, power, and distribution of charging stations.

This mapping shows both current and proposed DCFC locations that are compliant with the EV Law, along with the Community DCFC Location Suitability Score developed for each 2010 Census Tract in the state.

The map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The basemap focuses on bathymetry. It also includes inland waters and roads, overlaid on land cover and shaded relief imagery.

This web map references the live tiled map service from the OpenStreetMap project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information such as free satellite imagery, and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: http://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in Esri products under a Creative Commons Attribution-ShareAlike license.Tip: This service is one of the basemaps used in the ArcGIS.com map viewer and ArcGIS Explorer Online. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10.

Supplementary files for article "Smart citizens enabling resilient neighbourhoods (SCERN): Participatory mapping platform for resilience planning at a neighbourhood scale"Urban communities face a range of stressors, including crime, pollution, and infrastructure challenges, which disproportionately affect marginalized populations. Resilience planning can help address these issues, but existing tools often lack meaningful community involvement. This paper introduces the Smart Citizens Enabling Resilient Neighbourhoods (SCERN) participatory mapping tool, a geo-questionnaire-based mobile GIS application designed to engage community members in resilience planning. SCERN facilitates data collection on local stressors and support systems through demographic profiling and spatial mapping, allowing for a nuanced understanding of place-based experiences. This tool was pilot tested at Wilfrid Laurier University in Waterloo Canada, with 33 participants in two groups submitting 113 place reports. Analysis of these reports identified key locations associated with spatial patterns of resilience as well as locations for targeted interventions. Using the tool in combination with a broader resilience planning framework ensures that community members are central to both data collection and planning processes. Furthermore, SCERN's adaptability renders it a valuable resource for urban planners, researchers, and community organizations. By fostering community participation, this tool provides a scalable and customizable approach to resilience planning that prioritizes equity and inclusion.© The Author(s), CC BY-NC-ND 4.0

Community Residences map that is used in the Community Residences Application. The application is used locate other potential Group Home residences within a 1/4 mile and a 1/2 mile buffer of the selected parcel(s).

This map image layer represents the U.S. Department of Health and Human Services (HHS) emPOWER Program, a partnership between ASPR and the Centers for Medicare and Medicaid Services, provides dynamic data and mapping tools to help communities protect the health of more than 4.1 million Medicare beneficiaries who live independently and rely on electricity-dependent medical equipment and health care servicesASPR, in partnership with the Centers for Medicare and Medicaid Services (CMS), provide de-identified and aggregated Medicare beneficiary claims data at the state/territory, county, and ZIP code levels in the HHS emPOWER Map and this public HHS emPOWER REST Service. The REST Service includes aggregated data from the Medicare Fee-For-Service (Parts A&B) and Medicare Advantage (Part C) Programs for beneficiaries who rely on electricity-dependent durable medical equipment (DME) and cardiac implantable devices. Data includes the following DME and devices: cardiac devices (left, right, and bi-ventricular assistive devices (LVAD, RVAD, BIVAD) and total artificial hearts (TAH)), ventilators (invasive, non-invasive and oscillating vests), bi-level positive airway pressure device (BiPAP), oxygen concentrator, enteral feeding tube, intravenous (IV) infusion pump, suction pump, end-stage renal disease (ESRD) at-home dialysis, motorized wheelchair or scooter, and electric bed. Purpose: Over 2.5 million Medicare beneficiaries rely on electricity-dependent medical equipment, such as ventilators, to live independently in their homes. Severe weather and other emergencies, especially those with long power outages, can be life-threatening for these individuals. The HHS emPOWER Map and public REST Service give every public health official, emergency manager, hospital, first responder, electric company, and community member the power to discover the electricity-dependent Medicare population in their state/territory, county, and ZIP Code. Data Source: The REST Service’s data is developed from Medicare Fee-For-Service (Part A & B) (>33M 65+, blind, ESRD [dialysis], dual-eligible, disabled [adults and children]) and Medicare Advantage (Part C) (>21M 65+, blind, ESRD [dialysis], dual-eligible, disabled [adults and children]) beneficiary administrative claims data. This data does not include individuals that are only enrolled in a State Medicaid Program. Note that Medicare DME are subject to insurance claim reimbursement caps (e.g. rental caps) that differ by type, so the DME may have different “look-back” periods (e.g. ventilators are 13 months and oxygen concentrators are 36 months). ZIP Code Aggregation: Some ZIP Codes do not have specific geospatial boundary data (e.g., P.O. Box ZIP Codes). To capture the complete population data, the HHS emPOWER Program identified the larger boundary ZIP Code (Parent) within which the non-boundary ZIP Code (Child) resides. The totals are added together and displayed under the parent ZIP Code. Approved Data Uses: The public HHS emPOWER REST Service is approved for use by all partners and is intended to be used to help inform and support emergency preparedness, response, recovery, and mitigation activities in all communities. Privacy Protections: Protecting the privacy of Medicare beneficiaries is an essential priority for the HHS emPOWER Program. Therefore, all personally identifiable information are removed from the data and numerous de-identification methods are applied to significantly minimize, if not completely mitigate, any potential for deduction of small cells or re-identification risk. For example, any cell size found between the range of 1 and 10 is masked and shown as 11.HHS emPOWER Program Executive SummaryHHS emPOWER Program Informational Power Point.