The table Firm survey wave 1 and 2 (GIS) is part of the dataset SEDRI Ethiopia firm survey (GIS), available at https://redivis.com/datasets/rxq3-9x047we25. It contains 1585 rows across 3377 variables.

Public Land Survey SystemThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the Bureau of Land Management data, displays the Public Land Survey System (PLSS) in the United States. Per BLM, "The BLM is required to perform cadastral surveys on all federal interest and Indian lands. As part of survey work, the BLM maintains an essential land grid, known as the rectangular survey system or Public Land Survey System (PLSS), which is the basis for identifying legal descriptions of land parcels."PLSS Township 7N 22EData downloaded: October 17, 2023Data source: BLM National Public Land Survey System PolygonsNGDAID: 10 (BLM National PLSS Public Land Survey System Polygons)OGC API Features Link: (Public_Land_Survey_System - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information: About the Public Land Survey SystemSupport documentation: BLM National PLSS Public Land Survey System PolygonsFor feedback please contact: ArcGIScomNationalMaps@esri.comNGDA Data SetThis data set is part of the NGDA Cadastre Theme Community. Per the Federal Geospatial Data Committee (FGDC), Cadastre is defined as the "past, current, and future rights and interests in real property including the spatial information necessary to describe geographic extents. Rights and interests are benefits or enjoyment in real property that can be conveyed, transferred, or otherwise allocated to another for economic remuneration. Rights and interests are recorded in land record documents. The spatial information necessary to describe geographic extents includes surveys and legal description frameworks such as the Public Land Survey System, as well as parcel-by-parcel surveys and descriptions. Does not include federal government or military facilities."For other NGDA Content: Esri Federal Datasets

The United States Public Land Survey (PLS) divided land into one square mile units, termed sections. Surveyors used trees to locate section corners and other locations of interest (witness trees). As a result, a systematic ecological dataset was produced with regular sampling over a large region of the United States, beginning in Ohio in 1786 and continuing westward.
We digitized and georeferenced archival hand drawn maps of these witness trees for 27 counties in Ohio. This dataset consists of a GIS point shapefile with 11,925 points located at section corners, recording 26,028 trees (up to four trees could be recorded at each corner). We retain species names given on each archival map key, resulting in 70 unique species common names. PLS records were obtained from hand-drawn archival maps of original witness trees produced by researchers at The Ohio State University in the 1960’s. Scans of these maps are archived as “The Edgar Nelson Transeau Ohio Vegetation Survey” at The Ohio State University: http://hdl.handle.net/1811/64106.
The 27 counties are: Adams, Allen, Auglaize, Belmont, Brown, Darke, Defiance, Gallia, Guernsey, Hancock, Lawrence, Lucas, Mercer, Miami, Monroe, Montgomery, Morgan, Noble, Ottawa, Paulding, Pike, Putnam, Scioto, Seneca, Shelby, Williams, Wyandot. Coordinate Reference System: North American Datum 1983 (NAD83). This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.

Usage

The prefixes f1_ and f2_ indicate that variables correspond to either wave 1 or wave 2, respectively.

In support of new permitting workflows associated with anticipated WellSTAR needs, the CalGEM GIS unit extended the existing BLM PLSS Township & Range grid to cover offshore areas with the 3-mile limit of California jurisdiction. The PLSS grid as currently used by CalGEM is a composite of a BLM download (the majority of the data), additions by the DPR, and polygons created by CalGEM to fill in missing areas (the Ranchos, and Offshore areas within the 3-mile limit of California jurisdiction).CalGEM is the Geologic Energy Management Division of the California Department of Conservation, formerly the Division of Oil, Gas, and Geothermal Resources (as of January 1, 2020).Update Frequency: As Needed

This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific 'production' or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys), and the Bureau of Census 2015 Cartographic State Boundaries. The Entity-Attribute section of this metadata describes these components in greater detail. Please note that the data on this site, although published at regular intervals, may not be the most current PLSS data that is available from the BLM. Updates to the PLSS data at the BLM State Offices may have occurred since this data was published. To ensure users have the most current data, please contact the BLM PLSS Data Set Manager.

These are the cadastral reference features that provide the basis and framework for parcel mapping and for other mapping. This feature data set contains PLSS and Other Survey System data. The other survey systems include subdivision plats and those types of survey reference systems. This feature data set also include feature classes to support the special conditions in Ohio. This data set represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non rectangular components of the PLSS) Meandered Water, Corners and Conflicted Areas (known areas of gaps or overlaps between Townships or state boundaries). The Entity-Attribute section of this metadata describes these components in greater detail.

BLM Alaska PLSS Intersected: This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non rectangular components of the PLSS) Meandered Water, Corners and Conflicted Areas (known areas of gaps or overlaps between Townships or state boundaries). The Entity-Attribute section of this metadata describes these components in greater detail.

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. Special Surveys are non-PLSS survey areas from BLM survey records which represent federal parcels.

Alaska Survey Boundary contains miscellaneous state, federal, and private surveys.

This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the Base - Survey Boundary category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction.

Each state survey feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: http://dnr.alaska.gov/projects/las/ Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.

The global UAV Aerial Survey Services market is experiencing robust growth, driven by increasing demand across diverse sectors. Technological advancements in drone technology, offering higher resolution imagery and improved data processing capabilities, are significantly contributing to this expansion. The market's versatility, providing cost-effective and efficient solutions for various applications, further fuels its growth. Specific sectors like construction, agriculture, and energy are key drivers, utilizing UAV surveys for site mapping, precision agriculture, pipeline inspections, and environmental monitoring. While regulatory hurdles and data security concerns present challenges, the market is overcoming these limitations through the development of standardized operating procedures and robust data encryption techniques. Assuming a conservative CAGR of 15% (a reasonable estimate given the rapid technological advancements and increasing adoption rates in this sector), and a 2025 market size of $2 billion, the market is projected to reach approximately $4.2 Billion by 2033. This substantial growth is further fueled by the increasing affordability and accessibility of UAV technology, enabling more businesses to leverage aerial survey services. The segmentation of the UAV Aerial Survey Services market reveals that orthophoto and oblique image services are widely utilized, catering to diverse application needs. Forestry and agriculture are dominant sectors, with construction, power and energy, and oil & gas industries rapidly adopting this technology. Regional analysis highlights strong growth in North America and Asia-Pacific, driven by significant investments in infrastructure development and agricultural modernization. Europe follows closely, spurred by government initiatives promoting sustainable development and environmental monitoring. The competitive landscape includes both established players like Kokusai Kogyo and Zenrin, and emerging specialized companies, indicating a dynamic and competitive market with potential for further consolidation and innovation. The continued development of advanced data analytics capabilities, integrated with UAV imagery, will create new opportunities and drive market expansion.

The global market for Surveying and Mapping RTK (Real-Time Kinematic) products is experiencing robust growth, projected to reach $783 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.9% from 2025 to 2033. This expansion is driven by increasing infrastructure development globally, particularly in rapidly urbanizing regions and developing nations. The rising adoption of precision agriculture, coupled with the growing demand for accurate land and resource management, significantly contributes to market growth. Furthermore, advancements in RTK technology, leading to improved accuracy, reliability, and efficiency, are fueling wider adoption across various sectors. The integration of RTK systems with other technologies like GIS (Geographic Information Systems) and drones further enhances their utility and contributes to the overall market expansion. Specific application areas, like urban planning and construction, roads and bridges, and mineral resource exploration, are key contributors to market demand, while segments such as dual-frequency RTK systems are witnessing faster adoption due to their superior performance capabilities. Major players like Leica (Hexagon), Trimble, and FARO are driving innovation and market competition, while several regional players are catering to specific geographic needs. The market segmentation by application (Land and Resources Management, Urban Planning and Construction, Roads and Bridges, Mineral Resources, Others) and type (Single-Frequency RTK, Dual-Frequency RTK) provides crucial insights into market dynamics. While land and resource management currently holds a significant share, the urban planning and construction sector is projected to experience the fastest growth due to increasing urbanization and infrastructure projects. Similarly, dual-frequency RTK systems are gaining traction due to their higher accuracy, enabling more sophisticated applications. Regional variations in market growth are expected, with North America and Asia-Pacific likely to dominate due to robust infrastructure investments and technological advancements in these regions. However, emerging economies in regions like South America and Africa present significant untapped potential for future growth, driven by increasing government investments in infrastructure and surveying projects. The overall market outlook for Surveying and Mapping RTK products remains positive, propelled by technological advancements, rising demand across multiple sectors, and expanding applications globally.

Feature layer of locations corresponding to surveys that are produced by Vermont licensed land surveyors and submitted—as .pdf copies—to the Vermont Land Survey Library.Locations are attributed with information such as name of surveyor, date of survey, survey type (e.g., subdivision), and municipality. When the feature layer is opened in ArcGIS Online, the .pdf copies (as feature attachments) can be viewed/downloaded.Effective January 1, 2020 and as stated in27 V.S.A. § 341, surveys are required for property line changes in Vermont. Licensed land surveyors who produce the surveys are to submit a digital copy of them to the library in.pdf format (see27 V.S.A. §1401 and 27 V.S.A. §1403).The copies of surveys are for public reference only, with the originals that most often reside with the Municipality remaining the official documents. The purpose of the land survey library is to improve knowledge of who owns what lands where throughout Vermont.For more information about land surveying in Vermont, see theVermont Society of Land Surveyors (VSLS) and the Vermont Survey Law Manual (PDF).

This dataset is part of the Cadastral National Spatial Data Infrastructure (CadNSDI) publication dataset for rectangular and non‐rectangular Public Land Survey System (PLSS) data.

This dataset represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular surveys. The primary source for the data is cadastral survey records housed by the BLM supplemented with local records and geographic control coordinates from states, counties as well as other federal agencies such as the USGS and USFS. The data has been converted from source documents to digital form and transferred into a GIS format that is compliant with FGDC Cadastral Data Content Standards and Guidelines for publication. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. This data set includes the following: PLSS Fully Intersected (all of the PLSS feature at the atomic or smallest polygon level), PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners and Conflicted Areas (known areas of gaps or overlaps between Townships or state boundaries). The Entity-‐ Attribute section of this metadata describes these components in greater detail.

The CadNSDI or the Cadastral Publication Data Standard is the cadastral data component of the NSDI. This is the publication guideline for cadastral data that is intended to provide a common format and structure and content for cadastral information that can be made available across jurisdictional boundaries, providing a consistent and uniform cadastral data to meet business need that includes connections to the source information from the data stewards. The data stewards determine which data are published and should be contacted for any questions on data content or for additional information. The cadastral publication data is data provided by cadastral data producers in a standard form on a regular basis.

Cadastral publication data has two primary components, land parcel data and cadastral reference data. It is important to recognize that the publication data are not the same as the operation and maintenance or production data. The production data is structured to optimize maintenance processes, is integrated with internal agency operations and contains much more detail than the publication data. The publication data is a subset of the more complete production data and is reformatted to meet a national standard so data can be integrated across jurisdictional boundaries and be presented in a consistent and standard form nationally.

Note: This is a large dataset. To download, go to ArcGIS Open Data Set and click the download button, and under additional resources select the shapefile or geodatabase option. A land survey point from a GCDB LX file, survey plat, or captured from a CFF land net coverage. Includes points generated by calculating an aliquot breakdown of a section.

The 2002 Sierra County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). The data was gathered using aerial photography and extensive field visits, the land use boundaries and attributes were digitized, and the resultant data went through standard quality control procedures before finalizing. The land uses that were gathered were detailed agricultural land uses, and lesser detailed urban and native vegetation land uses. The data was gathered and digitized by staff of DWR’s Central District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and Central District. Important Points about Using this Data Set: 1. The land use boundaries were hand drawn directly on USGS quad maps and then digitized. They were drawn to depict observable areas of the same land use. They were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. 2. This survey was a "snapshot" in time. The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and, to an extent possible, whatever additional information the aerial photography might provide. For example, the surveyor might have seen a cropped field in the photograph, and the field visit showed a field of corn, so the field was given a corn attribute. In another field, the photograph might have shown a crop that was golden in color (indicating grain prior to harvest), and the field visit showed newly planted corn. This field would be given an attribute showing a double crop, grain followed by corn. The DWR land use attribute structure allows for up to three crops per delineated area (polygon). In the cases where there were crops grown before the survey took place, the surveyor may or may not have been able to detect them from the field or the photographs. For crops planted after the survey date, the surveyor could not account for these crops. Thus, although the data is very accurate for that point in time, it may not be an accurate determination of what was grown in the fields for the whole year. If the area being surveyed does have double or multicropping systems, it is likely that there are more crops grown than could be surveyed with a "snapshot". 3. If the data is to be brought into a GIS for analysis of cropped (or planted) acreage, two things must be understood: a. The acreage of each field delineated is the gross area of the field. The amount of actual planted and irrigated acreage will always be less than the gross acreage, because of ditches, farm roads, other roads, farmsteads, etc. Thus, a delineated corn field may have a GIS calculated acreage of 40 acres but will have a smaller cropped (or net) acreage, maybe 38 acres. b. Double and multicropping must be taken into account. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. To estimate actual cropped acres, the two crops are added together (38 acres of grain and 38 acres of corn) which results in a total of 76 acres of net crop (or planted) acres. 4. Not all land use codes will be represented in the survey.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.3, dated April 13, 2022. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. See the CADWR Land User Viewer (gis.water.ca.gov/app/CADWRLandUseViewer) for the most current contact information. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov.

This data layer is an element of the Oregon GIS Framework. This theme contains PLS lines for the State of Oregon. This PLS theme includes donation claims lands. Attributes in this theme show Township Range and Section values.

The RTK (Real-Time Kinematic) Survey Systems market, valued at $783 million in 2025, is poised for robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 5.9% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing adoption of precise positioning technologies across various sectors, including land and resources management, urban planning and construction, and mineral resource exploration, fuels demand. The rising complexity of infrastructure projects and the need for accurate data for efficient planning and execution further contribute to market growth. Technological advancements, such as the development of more accurate and reliable dual-frequency RTK systems, are also significantly impacting the market. Furthermore, the increasing integration of RTK systems with other technologies like GIS (Geographic Information Systems) and drones enhances their functionality and appeal across various applications. Governments' increasing focus on infrastructure development and smart city initiatives in developing economies like those in Asia-Pacific creates significant growth opportunities. However, market growth may be somewhat tempered by certain restraining factors. The high initial investment cost associated with RTK equipment and the requirement for skilled personnel to operate the systems could limit wider adoption, especially among small and medium-sized enterprises (SMEs). Furthermore, the potential impact of economic downturns on infrastructure spending could also temporarily slow market growth. Nonetheless, the long-term outlook for the RTK Survey Systems market remains positive, driven by continuous technological advancements and expanding applications across various industries. The market segmentation by application (Land and Resources Management, Urban Planning and Construction, Roads and Bridges, Mineral Resources, Others) and type (Single-Frequency RTK, Dual-Frequency RTK) provides further insights into market dynamics and allows for tailored strategies to penetrate specific niche markets. Competition amongst established players like Leica (Hexagon), Trimble, and FARO, as well as emerging companies from China, is expected to remain intense, driving innovation and pricing pressures. This in-depth report provides a comprehensive analysis of the global RTK Survey Systems market, projecting a multi-million-unit market by 2033. We delve into market dynamics, competitive landscapes, and future growth trajectories, offering invaluable insights for stakeholders across the industry. The study covers the historical period (2019-2024), base year (2025), and forecast period (2025-2033), leveraging extensive data analysis to deliver actionable intelligence. Keywords: RTK GPS, Real-Time Kinematic, GNSS Surveying, Surveying Equipment, Land Surveying, GIS, Mapping, Positioning Systems, Precision Agriculture.

The Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (sahi_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (sahi_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (sahi_geology_metadata.txt or sahi_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The Digital Surficial Geologic-GIS Map of the Stroudsburg Quadrangle, New Jersey and Pennsylvania is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (stro_surficial_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (stro_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (stro_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (dewa_surficial_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (dewa_surficial_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (stro_surficial_geology_metadata_faq.pdf). Please read the dewa_surficial_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Pennsylvania Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (stro_surficial_geology_metadata.txt or stro_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).