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. Our final map product is a geographic information system (GIS) database of vegetation structure and composition across the Crater Lake National Park terrestrial landscape, including wetlands. The database includes photos we took at all relevé, validation, and accuracy assessment plots, as well as the plots that were done in the previous wetlands inventory. We conducted an accuracy assessment of the map by evaluating 698 stratified random accuracy assessment plots throughout the project area. We intersected these field data with the vegetation map, resulting in an overall thematic accuracy of 86.2 %. The accuracy of the Cliff, Scree & Rock Vegetation map unit was difficult to assess, as only 9% of this vegetation type was available for sampling due to lack of access. In addition, fires that occurred during the 2017 accuracy assessment field season affected our sample design and may have had a small influence on the accuracy. Our geodatabase contains the locations where particular associations are found at 600 relevé plots, 698 accuracy assessment plots, and 803 validation plots.

The global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 10% from 2025 to 2033, reaching approximately $39 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of cloud-based GIS solutions offers enhanced accessibility, scalability, and cost-effectiveness, particularly appealing to smaller organizations. Secondly, the burgeoning need for precise spatial data analysis in various applications, including urban planning, geological exploration, and water resource management, significantly contributes to market growth. Thirdly, advancements in technologies such as AI and machine learning are integrating into GIS tools, leading to more sophisticated analytical capabilities and improved decision-making. Finally, the increasing availability of high-resolution satellite imagery and other geospatial data further fuels market expansion. However, market growth is not without challenges. High initial investment costs associated with implementing and maintaining sophisticated GIS systems can pose a barrier to entry for smaller businesses. Furthermore, the complexity of GIS software and the need for specialized skills to operate and interpret data effectively can limit widespread adoption. Despite these restraints, the market’s overall trajectory remains positive, with the cloud-based segment projected to maintain a dominant market share due to its inherent advantages. Growth will be geographically diverse, with North America and Europe continuing to be significant markets, while Asia-Pacific is expected to experience the fastest growth due to rapid urbanization and infrastructure development. The continued development of user-friendly interfaces and increased integration with other business intelligence tools will further accelerate market expansion in the coming years.

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. We used ERDAS Imagine ® Professional 9.2, ENVI ® 4.5, and ArcGIS ® 9.3 with Arc Workstation to develop the vegetation spatial database. Existing GIS datasets that we used to provide mapping information include a NPS park boundary shapefile for VICK (including a 100 meter buffer boundary around the Louisiana Circle, South Fort, and Navy Circle satellite units), a land cover shapefile created by the NWRC (Rangoonwala et al. 2007), and the National Elevation Dataset (NED) (used as the source of the 10-meter elevation model and derived streams, slope, and hillshade). To make the entire spatial data set consistent with NPSVI policies to map only to park boundaries, we clipped the vegetation in and around the previously buffered areas around the Louisiana Circle, South Fort, and Navy Circle satellite unit NPS boundaries. We also added to the spatial database vegetation polygons for the previously omitted Grant’s Canal satellite unit by heads-up digitizing this area from a National Agricultural Information Program (NAIP) image.

This mapping tool provides a representation of the general watershed boundaries for stream systems declared fully appropriated by the State Water Board. The boundaries were created by Division of Water Rights staff by delineating FASS critical reaches and consolidating HUC 12 sub-watersheds to form FASS Watershed boundaries. As such, the boundaries are in most cases conservative with respect to the associated stream system. However, users should check neighboring FASS Watersheds to ensure the stream system of interest is not restricted by other FASS listings. For more information regarding the Declaration of Fully Appropriated Stream Systems, visit the Division of Water Rights’ Fully Appropriated Streams webpage. How to Use the Interactive Mapping Tool: If it is your first time viewing the map, you will need to click the “OK” box on the splash screen and agree to the disclaimer before continuing. Navigate to your point of interest by either using the search bar or by zooming in on the map. You may enter a stream name, street address, or watershed ID in the search bar. Click on the map to identify the location of interest and one or more pop-up boxes may appear with information about the fully appropriated stream systems within the general watershed boundaries of the identified location. The information provided in the pop-up box may include: (a) stream name, (b) tributary, (c) season declared fully appropriated, (d) Board Decisions/Water Right Orders, and/or (e) court references/adjudications. You may toggle the FAS Streams reference layer on and off to find representative critical reaches associated with the FASS Watershed layer. Please note that this layer is for general reference purposes only and ultimately the critical reach listed in Appendix A of Water Rights Order 98-08 and Appendix A together with any associated footnotes controls. Note: A separate FAS Watershed boundary layer was created for the Bay-Delta Watershed. The Bay-Delta Watershed layer should be toggled on to check if the area of interest is fully appropriated under State Water Board Decision 1594.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial mapping products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2018, 2020 and 2022 and Open Street Map (OSM) from 2019. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov/) and Geofabrik GmbH - Open Street Map (https://www.geofabrik.de/geofabrik/openstreetmap.html), respectively. The imagery was classified using Random Forest (RF) Modeling to produce land cover maps with three main classifications - bare, vegetation, and shadows. An updated roads and trails map for the Upper Scotts Creek Watershed, including the BLM Recreational Area, was created to estimate road and trail densities in the watershed. Separate metadata records for each product (Land_Cover_Maps_Scotts_Creek_Watershed_CA_2018_2020_2022_metadata.xml, and Roads_and_Trails_Map_Upper_Scotts_Creek_Watershed_CA _2022_metadata.xml) are provided on the ScienceBase page for each child item. Users should be aware of the inherent errors in remote sensing products.

The market for GIS Mapping Tools is projected to reach a value of $XX million by 2033, growing at a CAGR of XX% during the forecast period (2025-2033). The market growth is attributed to the increasing adoption of GIS mapping tools by various industries, including government, utilities, and telecom, for a wide range of applications such as geological exploration, water conservancy projects, and urban planning. The convergence of GIS with other technologies such as artificial intelligence (AI) and the Internet of Things (IoT) is further driving market growth, as these technologies enable GIS mapping tools to provide more accurate and real-time data analysis. The market is segmented by type (cloud-based, web-based), application (geological exploration, water conservancy projects, urban planning, others), and region (North America, Europe, Asia Pacific, Middle East & Africa). North America is expected to remain the largest market for GIS mapping tools throughout the forecast period, due to the early adoption of these technologies and the presence of leading vendors such as Esri, MapInfo, and Autodesk. Asia Pacific is expected to experience the highest growth rate during the forecast period, due to the increasing adoption of GIS mapping tools in emerging economies such as China and India. Key industry players include Golden Software Surfer, Geoway, QGIS, GRASS GIS, Google Earth Pro, CARTO, Maptive, Shenzhen Edraw Software, MapGIS, Oasis montaj, DIVA-GIS, Esri, MapInfo, Autodesk, BatchGeo, Cadcorp, Hexagon, Mapbox, Trimble, and ArcGIS.

The Cloud GIS market is experiencing robust growth, projected to reach a substantial value with a Compound Annual Growth Rate (CAGR) of 14% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing need for real-time data processing and analysis across various sectors, including urban planning, environmental management, and logistics, is fueling demand for cloud-based Geographic Information Systems (GIS). The scalability and cost-effectiveness offered by cloud platforms, compared to on-premise solutions, are significant advantages attracting businesses of all sizes. Furthermore, advancements in cloud computing technologies, such as improved storage capacity, enhanced processing power, and advanced analytics capabilities, are accelerating market adoption. The integration of AI and machine learning within Cloud GIS platforms is also a major contributor, enabling sophisticated spatial analysis and predictive modeling. Competition among leading providers like Esri, Hexagon, and Mapbox is intense, focusing on developing innovative solutions, expanding partnerships, and strengthening customer engagement through user-friendly interfaces and comprehensive support services. Geographical expansion, particularly in developing economies with increasing digital infrastructure, further contributes to market growth. However, data security concerns and the reliance on stable internet connectivity remain potential restraints. The market segmentation reveals a diverse landscape. The "Type" segment likely includes various cloud deployment models (e.g., public, private, hybrid), each catering to specific organizational needs and security requirements. The "Application" segment is equally broad, encompassing diverse use cases like smart city initiatives, precision agriculture, disaster response management, and infrastructure development. North America currently holds a significant market share due to early adoption and a mature technological landscape, but the Asia-Pacific region is expected to witness rapid growth driven by increasing urbanization and infrastructure investments. The competitive landscape is dynamic, with companies focusing on strategic partnerships, acquisitions, and continuous product innovation to maintain a leading position. Future growth will be largely influenced by the expansion of 5G networks, the continued advancement of AI/ML in spatial analysis, and the increasing availability of high-resolution geospatial data.

3D Geospatial Mapping Market Outlook

According to our latest research, the global 3D geospatial mapping market size in 2024 is valued at USD 7.68 billion, reflecting robust adoption across multiple industries. The market is expected to expand at a CAGR of 13.2% from 2025 to 2033, reaching a forecasted size of USD 23.13 billion by 2033. This remarkable growth is primarily driven by the increasing integration of advanced mapping technologies in urban planning, disaster management, and infrastructure development, along with the rising demand for real-time, high-resolution geospatial data.

One of the primary growth factors propelling the 3D geospatial mapping market is the rapid urbanization witnessed globally, which necessitates sophisticated planning and management solutions. As cities expand and infrastructure projects become more complex, stakeholders are increasingly relying on 3D geospatial mapping technologies to create accurate digital twins of urban environments. This enables better visualization, simulation, and analysis, leading to enhanced decision-making in urban planning, construction, and public safety. Furthermore, the proliferation of smart city initiatives, particularly in Asia Pacific and North America, is accelerating the adoption of 3D geospatial mapping solutions, as these technologies are essential for integrating various urban systems and optimizing resource allocation.

Another significant driver is the growing frequency and intensity of natural disasters, which has heightened the need for advanced disaster management tools. 3D geospatial mapping plays a crucial role in risk assessment, emergency response, and post-disaster recovery by providing detailed spatial data and real-time situational awareness. Governments and humanitarian organizations are leveraging these technologies to map disaster-prone areas, model potential impacts, and coordinate relief efforts more effectively. The integration of 3D mapping with AI, IoT, and remote sensing technologies further enhances its utility in disaster management, making it an indispensable tool for building resilient communities.

The increasing adoption of 3D geospatial mapping in transportation and logistics is also contributing to market growth. With the rise of autonomous vehicles, smart transportation networks, and the need for efficient supply chain management, accurate and up-to-date geospatial data has become critical. 3D mapping enables precise navigation, route optimization, and infrastructure monitoring, reducing operational costs and improving safety. Additionally, the construction and utilities sectors are leveraging these solutions for project planning, asset management, and maintenance, further expanding the market’s reach. The convergence of cloud computing, big data analytics, and geospatial technologies is making these solutions more accessible and scalable, driving their adoption across diverse end-user segments.

Regionally, North America currently leads the 3D geospatial mapping market due to its advanced technological infrastructure and significant investments in smart city and defense projects. However, Asia Pacific is poised for the fastest growth, fueled by rapid urbanization, government initiatives, and increased spending on infrastructure development. Europe also holds a substantial share, driven by stringent environmental monitoring regulations and the expansion of transportation networks. The Middle East & Africa and Latin America are emerging markets, with growing adoption in oil & gas, utilities, and disaster management applications. This regional diversification underscores the global relevance and potential of the 3D geospatial mapping market.

Component Analysis

The 3D geospatial mapping market is segmented by component into software, hardware, and services, each playing a critical role in delivering comprehensive mapping solutions. The software segment dominates the market, accounting for the largest share in 2024, as advanced mapping platforms and analytics tools become indispensable for processing and vis

The data, ground truth labels, and model checkpoints are needed for the code repository: https://github.com/wangzhecheng/GridMapping.

Unzip these zip files such that the directory structure looks like: GridMapping/checkpoint/... GridMapping/data/... GridMapping/results/... GridMapping/ground_truth/...

This project consists of 11 files: 1) a zipped folder with a geodatabase containing seven raster files and two shapefiles, 2) a zipped folder containing the same layers found in the geodatabase, but as standalone files, 3) 9 .xml files containing the metadata for the spatial datasets in the zipped folders. These datasets were generated in ArcPro 3.0.3. (ESRI). Six raster files (drainaged, geology, nlcd, precipitation, slope, solitexture) present spatially distributed information, ranked according to the relative importance of each class for groundwater recharge. The scale used for these datasets is 1-9, where low scale values are assigned to datasets with low relative importance for groundwater recharge, while high scale values are assigned to datasets with high relative importance for groundwater recharge. The seventh raster file contains the groundwater recharge potential map for the Anchor River Watershed. This map was calculated using the six raster datasets mentioned previously. Here, the values assigned represent Very Low to Very High groundwater recharge potential (scale 1 - 5, 1 being Very Low and 5 being Very High). Finally, the two shapefiles represent the groundwater wells and the polygons used for model validation. This data is part of the manuscript titled: Mapping Groundwater Recharge Potential in High Latitude Landscapes using Public Data, Remote Sensing, and Analytic Hierarchy Process, published in the journal remote sensing.

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.

To produce the digital map, a combination of 1:12,000-scale ortho imagery acquired in 2003, 2004, and 2005 and all of the GPS-referenced ground data were used to interpret the complex patterns of vegetation and land-use. All imagery was acquired from the U.S. Department of Agriculture - Farm Service Agency’s Aerial Photography Field Office and the National Agriculture Imagery Program. In the end, 32 map units (13 vegetated and 19 land-use) were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed, and revised. One hundred-twenty four accuracy assessment (AA) data points were collected in 2006 and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 89%.

Project Size = 6,784 acres San Antonio Missions National Historical Park = 844 acres Map Classes = 32 13 Vegetated 19 Non-vegetated Minimum Mapping Unit = ½ hectare is the program standard but this was modified at SAAN to ¼ acre. Total Size = 1,122 Polygons Average Polygon Size = 6 acres Overall Thematic Accuracy = 89%

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for American Memorial Park. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. To produce the spatial database and map layer, 0.6-meter, 4-band Quickbird satellite imagery from 2006 was provided by PACN. By comparing the signatures on the imagery to field and ground data 27 map classes (16 vegetated, three barren, and eight land-use / land-cover) were developed and directly crosswalked or matched to their corresponding NVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases and maps were printed, field tested, reviewed, and revised. The final map layer was accessed for thematic accuracy by overlaying 48 independent accuracy assessment points.

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the map data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

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. To produce the digital map, a combination of 1:12,000-scale true color aerial photography, 1:12,000-scale true color ortho-rectified imagery, and 3 years of ground-truthing were used to interpret the complex patterns of vegetation and land-use. In the end, 52 map units were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed and revised. 1,122 accuracy assessment data points were collected and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 82%.

The Drone GIS Mapping market is experiencing robust growth, driven by increasing demand for high-resolution geospatial data across various sectors. The market's expansion is fueled by advancements in drone technology, offering enhanced capabilities in image capture, processing, and analysis. Applications like precision agriculture, infrastructure monitoring (construction and energy), and mining operations are significantly contributing to market expansion. The thematic mapping segment holds a substantial market share due to its wide applicability in environmental monitoring, urban planning, and disaster management. Topographic mapping is also witnessing strong growth, driven by the need for accurate elevation data in construction and infrastructure projects. While the initial investment in drones and software can be a barrier to entry for some, the overall cost-effectiveness compared to traditional surveying methods, coupled with faster turnaround times, makes drone GIS mapping increasingly attractive. North America and Europe currently dominate the market, due to higher technological adoption and established GIS infrastructure; however, rapidly developing economies in Asia-Pacific are expected to demonstrate significant growth in the coming years, particularly in regions like China and India. The market is segmented by application (energy, construction, agriculture, mining, other) and by type of mapping (thematic, topographic, cadastral, navigation, series). This segmentation highlights the diverse applications of drone GIS mapping and drives further market diversification. Competition is currently strong, with various players offering a range of services and solutions. The forecast period of 2025-2033 presents promising opportunities for market expansion. Continued technological advancements, including improved sensor technology, AI-powered data processing, and cloud-based solutions, will further enhance the efficiency and accuracy of drone GIS mapping. Government initiatives promoting digitalization and infrastructure development will also play a crucial role in driving market growth. However, challenges such as regulatory hurdles regarding drone operations and data privacy, along with the need for skilled professionals to operate and interpret the data, will need to be addressed to ensure sustained market growth. The market is poised for significant expansion, with increasing adoption across diverse sectors and regions propelling its trajectory over the forecast period. We project a strong and sustained CAGR, reflecting the combined effect of technological advancement and growing market demands.

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.

To produce the digital map 38 map units (21 vegetated and 17 land use) were developed and directly cross-walked or matched to their corresponding plant associations and land use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed, and revised.

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.

All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcMap© software and are included in a comprehensive geodatabase. Draft maps created from the vegetation classification were field-tested and revised before independent ecologists conducted an assessment of the map’s accuracy during 2014.

The cloud-based mapping service market is experiencing robust growth, driven by increasing demand for location-based services across diverse sectors. The market size in 2025 is estimated at $15 billion, projecting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors, including the rising adoption of cloud computing, the increasing availability of high-resolution geospatial data, and the growing need for real-time location intelligence in applications like urban planning, logistics, and environmental monitoring. Furthermore, advancements in mapping technologies such as AI-powered image analysis and 3D modeling are enhancing the capabilities of cloud-based mapping services, making them more versatile and valuable to businesses and governments alike. The ease of accessibility, scalability, and cost-effectiveness offered by cloud-based solutions are further propelling market growth, attracting a wide range of users from small businesses to large enterprises. This growth trajectory is further supported by the ongoing integration of cloud-based mapping services with other technologies like IoT (Internet of Things) and big data analytics. This convergence enables the creation of sophisticated location-based applications that offer advanced functionalities, such as predictive analytics, route optimization, and asset tracking. While challenges remain, such as data security concerns and the need for robust internet connectivity, the overall market outlook remains positive, with a projected market value exceeding $45 billion by 2033. The competitive landscape includes established players like ESRI and Trimble, alongside emerging innovative companies continuously improving the technology and expanding market reach. This dynamic interplay of technological advancements, increasing demand, and competitive innovation is set to shape the future of cloud-based mapping services.

Geospatial datasets from The Regional Centre for Mapping of Resources for Development (RCMRD)

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.

The vegetation map was developed through on-screen digitizing of available black and white digital ortho-photographs from 1984 and 1999. The photos were compiled into a GIS with a standard set of ancillary layers provided by the park service (boundaries, roads, facilities, etc.). Using the vegetation classification as the foundation for the map legend, map units were defined with respect to interpretable patterns in the photography, and with an eye to those patterns that would be most important in natural and cultural resources management within the park. The map included 19 map classes and covered a total of 278.13 ha.