The Nature Conservancy has a long history of leveraging geospatial technology to advance conservation science and planning. Storage, access, analysis, compute and resulting products are paramount to our work. These might seem like basic components of a GIS, but given the rapid advancements in Earth observation, machine learning and generative AI, TNC must continuously track and keep pace with relevant technology.This year, our annual report focuses on the role of Earth observation (EO) in advancing our science, policy and decision-making as an organization. EO uses remote sensing technologies to monitor land, freshwater, marine ecosystems and the atmosphere. It involves tracking changes in both natural and human environments. Increasingly, EO is advancing with the development of smaller and very high-resolution satellites, complemented by in situ instruments that can monitor Earth daily with higher accuracy. Our challenge is how to utilize these technologies for conservation gains most effectively.

For decades, TNC’s conservation science and planning has been informed by geospatial technology. This dynamic field combines the disciplines of Geographic Information Systems (GIS), remote sensing and machine learning. At least one in every three TNC staff generates and uses maps to complete tasks such as monitoring preserves in the field and, increasingly through remote technologies, negotiate land and water transactions or illustrate the benefits of ecosystems and the costs of losing them. Together, the TNC Geospatial Systems team and the Geospatial Leadership Council have joined forces to bring you this annual report & map book that features:25 use cases or applications illustrating how geospatial technology is supporting and advancing our conservation work around the worldA global map series from our Global Science and Protect Oceans, Lands and Water teams showing crisis and last chance ecosystems under high development pressure14 feature maps depicting specific conservation projectsResults from our annual survey that reached over 1,500 staff“As we seek to tackle the biggest challenges facing our planet, it is crucial to ensure that our teams and partners are able to leverage the most accurate and rigorous mapping data—and that geospatial professionals conducting this science reflect the diversity of the places we work,” says Jennifer Morris, CEO of The Nature ConservancyFor the first time we have categorized three mapping types that convey all our conservation science and planning work into predictive modeling, prioritization with two aspects (asset & threat mapping and spatial action mapping), and monitoring & evaluation. This edition emphasizes spatial action mapping, or the mapping of strategies in priority places that inform decisions on when, where and what may be the best conservation actions to take.Fundamental to TNC’s mission is a focus on place. Maps are core to our mission in helping us understand the places we work and in engaging audiences through the stories they reveal. In this edition we have initiated the process of creating cartographic guidelines that encourage a cohesive look and feel within TNC while promoting our “conservation mapping brand.”

The global geospatial analytics market is predicted to expand significantly, with a projected CAGR of 11.28% from 2025 to 2033. Valued at 89.23 billion USD in 2025, the market is expected to reach new heights during the forecast period. Key drivers fueling this growth include increasing adoption of GIS (Geographic Information Systems) and GPS (Global Positioning Systems), rising demand for location-based services, and growing awareness of the benefits of geospatial data in decision-making. Additionally, advancements in cloud computing, artificial intelligence, and machine learning further contribute to the market's expansion. Key segments in the geospatial analytics market include services, types, technologies, and regions. Consulting, integration and deployment, support and maintenance are prominent services offered in the market. Surface and field analytics, network and location analytics, geovisualization, and other types are also significant segments. Remote sensing GIS GPS, other technologies, and their applications across various regions, including North America, Europe, Asia Pacific, Middle East & Africa, and South America, shape the market dynamics. Recent developments include: Sept 2022 Sanborn Map Company Inc., a provider of geospatial solutions for government and commercial clients, has acquired Applied Geographics, Inc., which helped numerous organisations in finding the most effective GIS, location intelligence, and geospatial solutions., January 2022 With the help of integrated and improved data, ideal site analysis and path planning, and customized customer experiences, Blueprint Technologies and Precisely have announced a partnership to help businesses gain a competitive edge., Geospatial analytics is being used by telecom companies like T-Mobile to optimise coverage and quality of service while planning deployments. While organising service deployments and coverage, telecommunications providers must consider a wide range of criteria. They must take into account the varying usage patterns, service demands, and the dynamic nature of the areas they serve., According to industry analysts, the abundance of geospatial data accessible is outpacing people's capacity to comprehend it as government and business deploy more satellites, drones, and sensors than ever before. Artificial intelligence, according to Mark Munsell, Deputy Director for Data and Digital Innovation at the National Geospatial-Intelligence Agency., Geospatial intelligence experts Orbital Insight and Carahsoft Technologies Corp. have joined forces. Carahsoft will act as Orbital Insight's Master Government Aggregator in accordance with the agreement. Through Carahsoft's reseller partners, Information Technology Enterprise Solutions - Software 2 (ITES-SW2), NASA Solutions for Enterprise-Wide Procurement (SEWP) V, National Association of State Procurement Officials (NASPO), ValuePoint, National Cooperative Purchasing Alliance (NCPA), and OMNIA Partners contracts, the company's AI-powered geospatial data analytics are now accessible to the public sector.. Potential restraints include: High Initial Investment Cost.

USGS Structures from The National Map (TNM) consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities across all US states and territories. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently included are: School, School:Elementary, School:Middle, School:High, College/University, Technical/Trade School, Ambulance Service, Fire Station/EMS Station, Law Enforcement, Prison/Correctional Facility, Post Office, Hospital/Medical Center, Cabin, Campground, Cemetery, Historic Site/Point of Interest, Picnic Area, Trailhead, Vistor/Information Center, US Capitol, State Capitol, US Supreme Court, State Supreme Court, Court House, Headquarters, Ranger St ...

Author: E Gunderson, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8, high schoolResource type: lessonSubject topic(s): gisRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

1. Create a custom map using Google Maps
2. Collect and plot data using Google MapsSummary: Students will learn the basics of Google Maps while using geospatial data to create their neighborhood map with the places they spend time. They will also collect data of their choice from another source (website, book, personal life) and plot the data using Google Maps.

Aerial map of the University of Virginia campus, 1975. This map was digitized and georeferenced by Virginia Tech University Library. GeoTIFF can be downloaded as a ZIP package at the following location; https://secure-archive.gis.vt.edu/gisdata/public/DigitizedMapCollections/VirginiaTechUniversityLibraries/VTU_DMC_000023.zip. The associated ZIP package contains an original scanned image and an image georeferenced using ArcGIS Pro.

TerraMetrics, Inc., proposes a Phase II R/R&D program to implement the TerraBlocks^TM Server architecture that provides geospatial data authoring, storage and delivery capabilities. TerraBlocks enables successful deployment, display and visual interaction of diverse, massive, multi-dimensional science datasets within popular web-based geospatial platforms like Google Earth and NASA World Wind.

TerraBlocks is a wavelet-encoded data storage technology and server architecture for NASA science data deployment into widely available web-based geospatial applications. The TerraBlocks approach provides dynamic geospatial data services with an emphasis on 1) server and data storage efficiency, 2) maintaining server-to-client science data integrity and 3) offering client-specific delivery of large Earth science geospatial datasets. The TerraBlocks approach bridges the gap between inflexible, but fast, pre-computed tile delivery approaches and highly flexible, but slower, map services approaches.

The pursued technology exploits the use of a network-friendly, wavelet-compressed data format and server architecture that extracts and delivers appropriately-sized blocks of multi-resolution geospatial data to geospatial client applications on demand and in interactive real time.

The Phase II project objective is to provide a complete and fully-functional prototype TerraBlocks data authoring and server software package delivery to NASA and simultaneously set the stage for commercial availability. The Phase III objective is to commercially deploy the TerraBlocks technology, with the collaboration of our commercial and government partners, to provide the enabling basis for widely available third-party data authoring and web-based geospatial application data services.

Author: M Crampton, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 4, grade 8, high schoolResource type: lessonSubject topic(s): mapsRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

1. Acquire skills in data based mapping.
2. Recognize patterns of distribution.
3. Analyze patterns of distribution.
4. Construct and evaluate hypotheses of those distributions.
5. Explain the concept of regions.Summary: Students become cartographers in this introductory lesson as they learn how to map data. Students will generate hypotheses based on the patterns and seek additional data to test the hypotheses. The lesson assumes data on U.S. states, but data at a local, national or global scale may be used.

The USGS Transportation downloadable data from The National Map (TNM) is based on TIGER/Line data provided through U.S. Census Bureau and supplemented with HERE road data to create tile cache base maps. Some of the TIGER/Line data includes limited corrections done by USGS. Transportation data consists of roads, railroads, trails, airports, and other features associated with the transport of people or commerce. The data include the name or route designator, classification, and location. Transportation data support general mapping and geographic information system technology analysis for applications such as traffic safety, congestion mitigation, disaster planning, and emergency response. The National Map transportation data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and structure ...

Block groups from the 2010 Census.

The USGS Governmental Unit Boundaries service from The National Map (TNM) represents major civil areas for the Nation, including States or Territories, counties (or equivalents), Federal and Native American areas, congressional districts, minor civil divisions, incorporated places (such as cities and towns), and unincorporated places. Boundaries data are useful for understanding the extent of jurisdictional or administrative areas for a wide range of applications, including mapping or managing resources, and responding to natural disasters. Boundaries data also include extents of forest, grassland, park, wilderness, wildlife, and other reserve areas useful for recreational activities, such as hiking and backpacking. Boundaries data are acquired from a variety of government sources. The data represents the source data with minimal editing or review by USGS. Please refer to the feature-level metadata for information on the data source. The National Map boundaries data is commonly combined with other data themes, such as elevation, hydrography, structures, and transportation, to produce general reference base maps. The National Map viewer allows free downloads of public domain boundaries data in either Esri File Geodatabase or Shapefile formats. For additional information on the boundaries data model, go to https://nationalmap.gov/boundaries.html.

The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. It defines the areal extent of surface water drainage to a point except in coastal or lake front areas where there could be multiple outlets as stated by the "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" "Standard" (https://pubs.usgs.gov/tm/11/a3/). Watershed boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. This dataset represents the hydrologic unit boundaries to the 12-digit for the entire United States. Some areas may also include additional subdivisions representing the 14- and 16-digit hydrologic unit (HU). At a minimum, the HUs are delineated at 1:24,000-scale in the conterminous United States, 1:25,000-scale in Hawaii, Pacific basin and the Cari ...

The USGS Map Indices service from The National Map (TNM) consists of 1x1 Degree, 30x60 Minute (100K), 15 Minute (63K), 7.5 Minute (24K), and 3.75 Minute grid polygons used in The National Map viewer for reference and to download data. At 1:24,000-scale (24K), the standard map size is 7.5 minutes of latitude by 7.5 minutes of longitude. At 1:100,000-scale (100K), the standard map size is 30 minutes of latitude by 60 minutes of longitude. The National Map viewer allows free download of public domain USGS map indices data in Esri File Geodatabase format.

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise (slr) and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: http://www.coast.noaa.gov/slr This metadata record describes the digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available data known to exist at the time of DEM creation that met project specifications, for mainland Virginia, this includes portions of the following counties: Alexandria, Arlington, Charles City, Chesapeake, Essex, Fairfax, Falls Church, Franklin City, Fredericksburg City, Gloucester, Hampton, Isle of Wight, James City, King and Queen, King George, King William, Lancaster, Mathews, Middlesex, New Kent, Newport News, Norfolk, Northumberland, Poquoson City, Portsmouth, Prince George, Prince William, Richmond, Southampton, Stafford, Suffolk, Surry, Sussex, Virginia Beach, Westmoreland, Williamsburg, and York. This DEM also includes the District of Columbia. The DEM is derived from the following lidar: 1. New Kent, Charles City, Prince George Counties 2012 FEMA Middle Counties VA Lidar This data may be downloaded from the William and Mary Center for Geospatial Analysis: http://www.wm.edu/as/cga/VALIDAR/ The project report for this data may be accessed at: http://gisfiles.wm.edu/files/lidar/Middle_Counties/Metadata/Project_Report/Dewberry_ProjectReport_MiddleCounties.pdf Additional coverage provided by the Virginia Base Map Program (VBMP). This data is a digital terrain model initially generated by the Center for Geospatial Technology (CGIT) for the Virginia Geographic Information Network (VGIN) using the mass points and break lines from 2002 VBMP aerial photography. 2. King William County 2011 FEMA King William County VA Lidar This data may be downloaded from the William and Mary Center for Geospatial Analysis: http://www.wm.edu/as/cga/VALIDAR/ The project report for this data may be accessed at: http://gisfiles.wm.edu/files/lidar/KingWilliamCo/KingWilliam_Metadata/Dewberry_ProjectReport_KingWilliam.pdf Additional coverage provided by the Virginia Base Map Program (VBMP). This data is a digital terrain model initially generated by the Center for Geospatial Technology (CGIT) for the Virginia Geographic Information Network (VGIN) using the mass points and break lines from 2002 VBMP aerial photography. 3. Hampton and Portsmouth Cities 2011 FEMA Virginia Southern Cities Lidar This data may be downloaded from the William and Mary Center for Geospatial Analysis: http://www.wm.edu/as/cga/VALIDAR/ The project report for this data may be accessed at: http://gisfiles.wm.edu/files/lidar/SouthernCities/SouthernCities_Metadata/Dewberry_ProjectReport_SouthernCities.pdf 4. Franklin City and Southampton County 2011 FEMA Virginia Counties South Lidar This data may be downloaded from the William and Mary Center for Geospatial Analysis: http://www.wm.edu/as/cga/VALIDAR/ The project report for this data may be accessed at: http://gisfiles.wm.edu/files/lidar/VA_Counties_South/SouthernCo_Metadata/Dewberry_ProjectReport_Southampton.pdf 5. Fredericksburg City and Essex, King George, Prince William, Richmond, Stafford, Westmoreland Counties 2011 FEMA Virginia Counties North Lidar This data may be downloaded from the William and Mary Center for Geospatial Analysis: http://www.wm.edu/as/cga/VALIDAR/ The project report for this data may be accessed at: http://gisfiles.wm.edu/files/lidar/VA_Counties_North/NorthernCo_Metadata/Dewberry_ProjectReport_NorthernCounties.pdf 6. Northumberland, Middlesex, Lancaster, King and Queen, Gloucester, Mathews, James City, Williamsburg, Surry, Isle of Wight, Suffolk Counties 2010/2011 USGS Eleven County Coastal VA Lidar This data may be downloaded from the William and Mary Center for Geospatial Analysis: http://www.wm.edu/as/cga/VALIDAR/ The project report for this data may be accessed at: http://gisfiles.wm.edu/files/lidar/a11county/Metadata/PROJECT_REPORT/Final%20Project%20Report%20for%20USGS%20Virginia%20LiDAR_01312011.pdf Additional coverage for Surry and King and Queen counties provided by the Virginia Base Map Program (VBMP). This data is a digital terrain model initially generated by the Center for Geospatial Technology (CGIT) for the Virginia Geographic Information Network (VGIN) using the mass points and break lines from 2002 VBMP aerial photography. 7. Alexandria, Arlington, and Falls Church Counties 2008 NGA Capital Region Lidar The lidar data is not publicly available, the data was provided by the State of Virginia as bare earth DEMs. 8. Fairfax County 2008 NGA Capital Region Lidar The lidar data is not publicly available, the data was provided by the State of Virginia as bare earth DEMs. 2012 FEMA Virginia Lidar This data may be downloaded from USGS EarthExplorer at: http://earthexplorer.usgs.gov/ 9. York, Poquoson City, Newport News, Norfolk, Chesapeake, Virginia Beach, and Sussex Counties Data provided by the Virginia Base Map Program (VBMP). This data is a digital terrain model initially generated by the Center for Geospatial Technology (CGIT) for the Virginia Geographic Information Network (VGIN) using the mass points and break lines from 2002 VBMP aerial photography. 2010 US Army Corps of Engineers (USACE) Lidar This data may be downloaded at: http://www.coast.noaa.gov/dataviewer/index.html?action=advsearch&qType=in&qFld=ID&qVal=1132 The metadata for this data may be accessed at: http://coast.noaa.gov/dataviewer/webfiles/metadata/usace2010_va_template.html 10.District of Columbia Washington, DC and Environs, 2008, 1/9 Arc second National Elevation Dataset (NED) This data may be downloaded at: http://viewer.nationalmap.gov/viewer/ Hydrographic breaklines were delineated from LiDAR intensity imagery generated from the LiDAR datasets. The DEM is hydro flattened such that water elevations are less than or equal to 0 meters. The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 10 meters.

Author: M Crampton, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8, high schoolResource type: lessonSubject topic(s): mapsRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

1. Acquire skills in data based mapping.
2. Recognize patterns of distribution.
3. Explain the concept of region.
4. Analyze multiple strategies used to map data.Summary: Students will understand the importance of recognizing patterns on the map as well as recognizing the strategy used by the mapmaker. The lessons assumes data on U.S. states, but data at a local, national or global scale may be used. Students should be familiar with choropleth mapping.

Historical military terrain map of Fort Belvoir, Virginia and surrounding vicinities. This map was digitized and georeferenced by Virginia Tech University Library. Additional information can be found at the following url(s); https://ngmdb.usgs.gov/img4/ht_icons/Browse/VA/VA_Belvoir_184053_1948_24000.jpg, https://ngmdb.usgs.gov/img4/ht_icons/Browse/VA/VA_Belvoir_187359_1944_31680.jpg. GeoTIFF can be downloaded as a ZIP package at the following location; https://secure-archive.gis.vt.edu/gisdata/public/DigitizedMapCollections/VirginiaTechUniversityLibraries/VTU_DMC_000003.zip. The associated ZIP package contains an original scanned image and an image georeferenced using ArcGIS Pro.

These data document and inventory seagrasses for the management of the resource, identify "healthy" areas that may deserve special protection efforts, and identify potential "problem" areas that require further investigation. These data are intended for use in documenting large-scale trends in the status of this resource. The Indian River Lagoon (IRL) Surface Water Improvement and Management (SWIM) Plan directs the South Florida and St. Johns River Water Management Districts to map seagrasses in the Indian River Lagoon at two to three-year intervals. Dewberry was contracted by the St. Johns River Water Management District (SJRWMD) to complete aerial imagery acquisition, orthophotography, field work, photointerpretation, and ArcGIS geodatabase delivery of seagrass maps within the Indian River Lagoon System (IRL). As a water resource manager, the SJRWMD requires geospatial technologies to help assess, monitor, analyze and manage water quality within the Indian River Lagoon. The many options surrounding geospatial technology today must be implemented strategically and cost effectively. The information derived from geospatial data can be instrumental only if the development of such data is designed to provide actionable information. The SJRWMD has made a significant investment in analyzing changes in seagrass distribution through the use of geospatial technology. The mapping and trend analysis performed under this project provides quantifiable data vital to the assessment of water quality and the general health of the estuarine system. The resultant data provides an overall picture of the seagrass resource in the IRL over time. The maps serve as important management tool for assessing distribution trends of the seagrass resource. They help identify healthy areas that may deserve special protection efforts along with potential problem areas that require further investigation.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

The City of Evanston has just over 120 cul-de-sacs.

Author: A Larsen, educator, Minnesota Alliance for Geographic EducationGrade/Audience: high schoolResource type: lessonSubject topic(s): urban geography, gis, geographic thinkingRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.

Standard 2. Geographic Inquiry is a process in which people ask geographic questions and gather, organize and analyze information to solve problems and plan for the future.Objectives: Students will be able to:

1. Develop skills to effectively manipulate and use ArcGIS software.
2. Analyze map layers to identify current conditions and predict future needs.
3. Use geospatial technology to determine the best location for a restaurant.
4. Justify their selection of the best location for a restaurant.Summary: In this location lesson, students will identify and locate a restaurant for their community using ArcGIS. Students will review ArcGIS with several introductory activities as a pre-assessment of their understanding of geospatial technology. Waconia is the example used in this lesson, but any community may be used.