The North America Non Profit Software market report offers a thorough competitive analysis, mapping key players’ strategies, market share, and business models. It provides insights into competitor dynamics, helping companies align their strategies with the current market landscape and future trends.

This web map shows the location of designated spots available for application for temporarily setting up of street counters to hold nonprofit making activities in Hong Kong. It is a set of data made available by the Lands Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of CSDI Portal at https://portal.csdi.gov.hk.

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

This layer contains the Version 2.0 BEAD Project Area Unit (PAU) boundaries, last updated December 12th, 2024.PAUs define the areas where prospective applicants can bid for funding under the federal BEAD program. The final version of the PAUs comes after OBAE made extensive changes in response to public comments and suggestions. These changes resulted in a greater number of PAUs that took greater account for existing network infrastructure, allowing applicants to better design successful BEAD projects.Note: OBAE has received formal approval of the BEAD Challenge Process results by NTIA. However, in the time since the Challenge Process has ended, OBAE has been made aware of new enforceable commitments and defaults. OBAE is currently in the process of deduplicating the NTIA BEAD-Eligible BSLs using this new grant information. When this deduplication process is complete, the PAUs will be updated to contain attributes which summarize the amount of Unserved (BEAD-Eligible), Underserved and Served BSLs within each unit. Additionally, PAUs without any eligible locations for BEAD will be removed from the map.Prequalified Tribal communities, nonprofits, internet service providers, cooperatives and other entities may submit applications for BEAD, the state’s largest funding program to deploy broadband infrastructure, starting January 3, 2025. The state will be awarding $675 million in grants through BEAD.If you have any questions about the PAUs or the BEAD program in general, please email OBAE at: Broadband@connect.nm.govOBAE used the following geographic boundaries to split the state of New Mexico into 255 PAUs:NTIA High-Cost Areas – NTIA High-Cost Areas were given their own PAUs, represented by the abbreviation "HC" in the PAU name (note: many of these High Cost Areas were subdivided into a collection of smaller PAUs). Tribal Boundaries – Tribal areas were made into their own PAUs (non-contiguous regions of the same Tribe/Pueblo are all one PAU). PAUs representing Tribal Land are denoted with the abbreviation "TL" in their name.For Tribal areas partially overlapping NTIA High-Cost Areas, separate PAUs were created from the overlap (similar to a Venn diagram). These areas contain the abbreviation "TL/HC" in their PAU name.School Districts – School district boundaries were used as the starting point for the majority of the PAUs.Census Tracts/ Block Groups – For larger or densely populated areas, Census Tracts or CBGs were used to further subdivide. Other infrastructure/geographic boundaries (roads, rivers, mountain ranges, wire center boundaries, etc.) -- for larger or more densely populated areas that could not be subdivided by the above boundaries, other infrastructure/geographic boundaries such as major highways, geographic features, and wire center boundaries were used.The features in this GIS layer are "topology-correct," meaning there are no gaps or overlaps between features.Source data used to digitize PAU boundaries:NM Census Block Groups + Tracts -- U.S. Census Bureau 2023 New Mexico TIGER/Line Geodatabase Index of /geo/tiger/TGRGDB23 (census.gov)NM School Districts -- "School Districts 2023," New Mexico Public Education Department School District Boundary Atlas, EDAC/RGIS Browse rgis data School Districts 2023 (unm.edu) NOTE: this layer originally contained topology errors (overlaps and gaps between features) when downloaded from RGIS. During the creation of this PAU layer, school districts were simplified to correct topology errors. Please contact michael.felzan@respec.com with questions or to request the topology-corrected version of this layer.NM Tribal Land (Pueblos, Reservations, Off-Reservation Trust Land, Joint-Use Areas) -- 2020 Census American Indian/Alaska Native/Native Hawaiian Areas (AIANNH) New Mexico TIGER/Line Shapefile, 2020, Nation, U.S., American Indian/Alaska Native/Native Hawaiian (AIANNH) Areas - Catalog (data.gov)Navajo Nation Regions -- shapefile obtained via Navajo Nation Land DepartmentNM High Cost Areas -- NTIA Block Group Extremely High-Cost Areas BEAD Allocation Methodology | Internet for AllNM Hydrography Lines -- U.S. Geological Survey, 2023, National Hydrography Dataset Plus High Resolution (NHDPlus HR) - USGS National Map Downloadable Data Collection - ScienceBase-CatalogNM Road Lines -- New Mexico Road Centerlines, NM911, published 4/30/2024 via https://rgis.unm.edu/Wire Center Boundaries -- data obtained from GeoTelSpatial Reference: NAD83 / UTM Zone 13N (EPSG: 26913)Field Descriptions:Info -- PAU layer version + date last modifiedPAU_Name -- Name of PAU. Each name generally describes the School District/Tribe or Pueblo the PAU falls within + two-digit number. PAUs which represent Tribal Land, NTIA High Cost areas, or areas in which Tribal Land intersects NTIA High Cost Areas are denoted by the abbreviations, "TL," "HC," "TL/HC," respectively.PAU_OID -- Unique numeric ID given to each PAU.

This application encourages collaboration between charities and other organizations providing care and humanitarian aid to victims of Tungiasis, or superinfection by Tunga penetrans, also known as the Chigoe flea, Jigger and sand flea. The study area is Kenya, with hopes to expand across sub-Saharan Africa. Representatives of nonprofit or charitable organizations are prompted to enter contact information and then draw a polygon on the map representing approximate geographic coverage. Health care workers and scientists can enter demographic information about individuals who seek treatment for Tungiasis in order to better understand and identify underlying factors that contribute to this neglected tropical disease.

This dashboard shows recycling data collected from tribal nations, cities/towns, counties, and non-profits across Arizona. The original data (2013 - 2022) was cleaned and new data is now being collected via Survey123 as of the 2024 (current) reporting year.Other Information:The map in this dashboard is unique since locations are submitted as points in Survey123, but uses Arcade to spatially join with polygons and construct pop-ups that show multiple years of submissions in a table format. While non-profits are displayed as points, these too use Arcade to construct the pop-ups showing all previously submitted data via non-spatial joins. The representation of the tribal nation, city/town, and county data as polygons allows users to understand the reach of recycling programs in their community, and the inclusion of graphs lets them understand exactly what is being collected when the data is available. Since this data is collected via Survey123, users get updated data immediately without the need to wait for data to be cleaned, formatted, and mapped manually.