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.

This method combines Atlas Caremaps, a tool for visualizing personal care networks, with community mapping using KUMU (a free to access software for public projects to map systems, stakeholders, networks etc) to visualize and enhance the local landscape of care in Clapton Common. It aims to make visible the invisible networks of care and support, fostering connectivity and resource sharing among community members. It's especially helpful for generating cooperative connections, promoting a local gift economy, and supporting asset-based community development and so-called care commons. It may be less helpful in situations where community engagement is low or where the digital divide limits access to the mapping platform. Here is has been used to consolidate initial paper based collaborative mapping exercises as a starting point to build a fuller mapping picture which can ultimately enable partners & care recipients to identify improvements to their care plans and potential for improved sharing of resources through co-design. Tags/ keywords: Method, Care Mapping, Community Care, Care Commons, Support Networks, Caregiving, Care Receiving, Atlas of Care, Equal Care Coop, KUMU, Clapton Common.

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

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 reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. The digital orthophoto mosaic was examined onscreen in ArcGIS 9.0 (ESRI 1999–2004). Once the natural community types were established, GPS points of the plots were overlaid on the 2004 CIR aerial photos using ArcView GIS software. These data layers were utilized to map the natural communities using on-screen digitizing techniques. The minimum mapping unit used was 0.5 ha.

Census Block Groups data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain block group boundaries with associated Census and American Community Survey demographic data.

DescriptionThis map is a thematic web map focused on Community Lifelines based upon the Field (Light) Basemap style. The content of this map is organized by group layers representing each of FEMA’s eight lifeline themes. Each group layer is loaded with public infrastructure data layers characterizing the lifeline in question. The purpose of this map is to centralize all lifeline data layers in one place for managing the group layers which are linked in other thematic maps. Additionally, the Lifeline Map may at times be directly used in derivative web applications, such as tools for analyzing infrastructure.For more about Community Lifelines, see https://www.fema.gov/emergency-managers/practitioners/lifelines.Uses: Management of lifeline group layers, updating layer styling, infrastructure and lifeline mapping, infrastructure and lifeline web application development, infrastructure and lifeline stories and briefings.Keywords: Lifelines, infrastructure, CIKR, critical facilities

This 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 includes bathymetry, marine water body names, undersea feature names, and derived depth values in meters. Land features include administrative boundaries, cities, inland waters, roads, overlaid on land cover and shaded relief imagery.

The map was compiled from a variety of best available sources from several data providers, including General Bathymetric Chart of the Oceans GEBCO_08 Grid version 20100927 and IHO-IOC GEBCO Gazetteer of Undersea Feature Names August 2010 version (https://www.gebco.net), National Oceanic and Atmospheric Administration (NOAA) and National Geographic for the oceans; and DeLorme, HERE, and Esri for topographic content. The basemap was designed and developed by Esri.

The Ocean Basemap currently provides coverage for the world down to a scale of ~1:577k; coverage down to ~1:72k in United States coastal areas and various other areas; and coverage down to ~1:9k in limited regional areas. You can contribute your bathymetric data to this service and have it served by Esri for the benefit of the Ocean GIS community. For details, see the Community Maps Program.

Tip: Here are some famous oceanic locations as they appear in this map. Each URL below launches this map at a particular location via parameters specified in the URL: Challenger Deep, Galapagos Islands, Hawaiian Islands, Maldive Islands, Mariana Trench, Tahiti, Queen Charlotte Sound, Notre Dame Bay, Labrador Trough, New York Bight, Massachusetts Bay, Mississippi Sound

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.

In May 2014, staff at the San Bernardino National Wildlife Refuge (SBNWR) requested the production of a vegetation map to document the ongoing restoration of the refuge. Utilizing object-based image analysis (OBIA) a 9 class vegetation map was produced. This was a piloted effort to develop a simple, repeatable and low-cost land cover mapping framework that could be carried out on other refuges. Thus, iterative steps were taken and refined as part of the mapping process. This document has a Digital Object Identifier: http://dx.doi.org/10.7944/W3WC7M

Crowdsourced Mapping Market Outlook

According to our latest research, the global crowdsourced mapping market size reached USD 2.6 billion in 2024, reflecting robust adoption across multiple sectors. The market is projected to expand at a CAGR of 14.9% from 2025 to 2033, with the total value anticipated to reach USD 8.1 billion by 2033. This strong growth trajectory is driven by increasing demand for real-time, accurate geospatial data, which is essential for applications ranging from urban planning to disaster management. The proliferation of smartphones and connected devices, coupled with rising public engagement in mapping initiatives, continues to accelerate the adoption of crowdsourced mapping solutions globally.

One of the primary growth factors fueling the crowdsourced mapping market is the unprecedented surge in mobile device usage, which has democratized access to mapping technologies for individuals and organizations alike. The ubiquity of GPS-enabled smartphones allows users to contribute geospatial data effortlessly, enabling mapping platforms to gather, verify, and update information in real-time. This capability has proven invaluable for industries requiring up-to-date geographic insights, such as transportation, logistics, and tourism. Additionally, the integration of crowdsourced mapping with emerging technologies like artificial intelligence and machine learning has significantly improved the accuracy, reliability, and utility of maps, making them indispensable for both commercial and governmental applications.

Another significant driver is the growing need for responsive and adaptive mapping solutions in disaster management and environmental monitoring. Crowdsourced mapping platforms have demonstrated their value in crisis situations, where traditional mapping methods often fall short due to delays in data collection and dissemination. By leveraging the collective intelligence and on-ground observations of users, these platforms provide timely situational awareness for first responders and relief agencies. This real-time data capability not only enhances emergency response efforts but also supports long-term planning and recovery operations, making crowdsourced mapping a critical tool for resilience and sustainability initiatives worldwide.

Furthermore, the increasing collaboration between government agencies, enterprises, and non-profit organizations has created a fertile environment for the expansion of the crowdsourced mapping market. Governments are increasingly recognizing the value of participatory mapping in urban planning, infrastructure development, and public safety. Enterprises leverage crowdsourced maps to optimize logistics, enhance customer experiences, and identify new market opportunities. Non-profit organizations employ these tools for advocacy, community engagement, and resource management. The convergence of interests among diverse stakeholders has led to the development of open-source mapping platforms and standards, further accelerating innovation and adoption in the sector.

From a regional perspective, North America currently leads the global crowdsourced mapping market, driven by high digital literacy, advanced technological infrastructure, and a strong culture of civic participation. Europe follows closely, with significant investments in smart city initiatives and environmental sustainability projects. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, expanding internet penetration, and government-led digital transformation programs. In contrast, Latin America and the Middle East & Africa are witnessing steady adoption, primarily in sectors such as disaster response, agriculture, and tourism. Each region presents unique opportunities and challenges, shaping the competitive landscape and growth dynamics of the global market.

Solution Analysis

The solution segment of the crowdsourced mapping market is bifurcated into Software and Services, each playing a crucial role in the ecosystem. Software solutions encompass mapping platforms, mobile applications, and data analytics tools that enable users to collect, visualize, and analyze geospatial data. These platforms often leverage open-source technologies and APIs, facilitating integration with other enterprise systems and third-party data sources. The demand for intuitive, user-friendly mapping software has surged as organizations seek to

Special Service Areas (SSA) boundaries in Chicago. The Special Service Area program is a mechanism used to fund expanded services and programs through a localized property tax levy within contiguous industrial, commercial and residential areas. The enhanced services and programs are in addition to services and programs currently provided through the city. SSA-funded projects could include, but are not limited to, security services, area marketing and advertising assistance, promotional activities such as parades and festivals, or any variety of small scale capital improvements that could be supported through a modest property tax levy. 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).

Open Neighborhoods web mapping application for the City of St Augustine. The app allows you to type an address or place a pin and locate the neighborhood.

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.

Polygon boundary edits were transferred from the paper maps used in the field to the digital shapefiles each week using ArcMap GIS software. Field edits were also transferred to a set of master paper maps that did not go into the field; these will be archived along with the datasheets. The polygons were contained in a field geodatabase structure (.mdb), enabling topography rules and relationships to be established. The geodatabase was archived each week to ensure no loss of data and to allow for reversion or retrieval if needed. Strict nomenclature was enforced for polygons, and a unique name was assigned to each polygon. The names reflected the verified physiognomic formation type by a prefix of representative letters (W = Woodland, SS = shrub savanna, etc.) followed by a number. In the final map, there are 16 vegetation alliances or associations attributed to 74 polygons (Figure 2-3). For each, there is a oneto- one correlation between the alliance or association and map units (polygons). Table 2-3 shows each vegetation community type, the number of polygons attributed with that type, and the total area.

RTB Maps is a cloud-based electronic Atlas. We used ArGIS 10 for Desktop with Spatial Analysis Extension, ArcGIS 10 for Server on-premise, ArcGIS API for Javascript, IIS web services based on .NET, and ArcGIS Online combining data on the cloud with data and applications on our local server to develop an Atlas that brings together many of the map themes related to development of roots, tubers and banana crops. The Atlas is structured to allow our participating scientists to understand the distribution of the crops and observe the spatial distribution of many of the obstacles to production of these crops. The Atlas also includes an application to allow our partners to evaluate the importance of different factors when setting priorities for research and development. The application uses weighted overlay analysis within a multi-criteria decision analysis framework to rate the importance of factors when establishing geographic priorities for research and development.

Datasets of crop distribution maps, agroecology maps, biotic and abiotic constraints to crop production, poverty maps and other demographic indicators are used as a key inputs to multi-objective criteria analysis.

Further metadata/references can be found here: http://gisweb.ciat.cgiar.org/RTBmaps/DataAvailability_RTBMaps.html

User-Generated Map Editors Market Outlook

According to our latest research, the global User-Generated Map Editors market size reached USD 1.54 billion in 2024, reflecting robust expansion driven by increasing demand for customizable map solutions across industries. The market is projected to grow at a CAGR of 13.2% from 2025 to 2033, reaching a forecasted value of USD 4.17 billion by 2033. This growth is fueled by the rising integration of user-generated content in gaming, education, and urban planning, as well as technological advancements that simplify map creation for users of all skill levels.

One of the most significant growth factors for the User-Generated Map Editors market is the surging popularity of interactive and immersive digital experiences, particularly within the gaming sector. As games increasingly incorporate sandbox elements and open-world environments, demand for intuitive map editors enabling players to create and share their own content has soared. This trend is further amplified by the proliferation of online communities and social platforms where user-generated maps can be distributed, rated, and monetized. The democratization of content creation not only enhances user engagement but also extends the lifecycle and replayability of games, making map editors a critical tool for both developers and players.

Another key driver is the expanding application of map editors beyond entertainment, especially in education, urban planning, and simulation-based training. Educational institutions are leveraging map editors to foster creativity and spatial reasoning among students, allowing them to design historical reconstructions, geographical models, and interactive learning environments. In urban planning and simulation, professionals utilize these tools to visualize infrastructure projects, model disaster scenarios, and engage stakeholders through participatory planning. The accessibility of map editors, often supported by cloud-based collaboration and real-time feedback, is transforming how organizations and individuals approach spatial design and problem-solving.

Technological advancements in software development, cloud computing, and artificial intelligence are further propelling the User-Generated Map Editors market. Modern map editors now offer enhanced usability, real-time rendering, and seamless integration with other digital tools. AI-driven features such as auto-completion, terrain generation, and intelligent object placement reduce the learning curve for novice users while empowering professionals to achieve greater precision and efficiency. The increasing availability of cross-platform solutions ensures that users can create and share maps on PC, consoles, mobile devices, and web-based platforms, expanding the market’s reach and versatility across diverse user segments.

From a regional perspective, North America and Europe currently lead the User-Generated Map Editors market, owing to their mature gaming industries, high digital literacy, and early adoption of innovative technologies. However, the Asia Pacific region is witnessing the fastest growth, driven by rapid urbanization, significant investments in education technology, and a burgeoning gaming community. Latin America and the Middle East & Africa are also emerging as promising markets, supported by increasing internet penetration and government initiatives to promote digital skills. Regional disparities in infrastructure, regulatory frameworks, and consumer preferences will continue to shape the competitive dynamics and growth opportunities in the coming years.

Component Analysis

The Component segment of the User-Generated Map Editors market is primarily divided into software and services, each playing a pivotal role in the ecosystem. Software solutions form the backbone of map editing, offering the core functionalities required for map creation, customization, and sharing. These software platforms range from standalone applications to integrated modules within larger gaming or simulation environments. The evolution of user interfaces, drag-and-drop features, and modular toolsets has made software solutions increasingly accessible to users with varying technical expertise, driving mass adoption across different end-user groups.

On the services front, a growing demand for professional support, training, and customization is shaping the market landscape. Enterprises and educational institutions often require tailo

This feature layer contains records of code complaints in the City of Tempe. Records are updated Tuesday through Saturday..Please note that there may be multiple complaint records associated with a single address point. When viewing these data using GIS software, multiple records per address result in stacked points on the map. Data are provided in this exploded format to make it easier for users.The data found here are displayed at https://gis.tempe.gov/codecompliance albeit in a non-exploded form where points aren't stacked.Contact EmailLink: www.tempe.gov/codeData Source: AccelaData Source Type: GeospatialPublish Frequency: WeeklyPublish Method: Automatic (via ETL)

NM EPSCoR RII3 is designed to enhance research competitiveness through investment in three strategic areas: (1) critical Research Infrastructure, (2) Cyberinfrastructure, and (3) Human Infrastructure. These investments will help establish NM as a laboratory for climate change research, and as a model for science‐based public policy. The multi‐disciplinary, multi‐scale effort is envisioned to transform climate change science and policymaking in NM by providing the tools required for quantitative, science‐driven discussion of difficult water policy options facing the State in the 21st Century. This document describes a study to 1) gain a basic understanding of the geography and natural resources of the Rio Hondo Watershed, 2) address issues identified by the Rio Hondo Watershed Group, 3) ascertain the overall health of the Rio Hondo Watershed, and 4) identify policy recommendations by analyzing maps and images created using a mapping software.

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.

A standalone visualization and analysis application that can be used without an internet connection.