The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) collaborated on the creation of the global land datasets using Landsat data from 1972 through 2008. NASA and the USGS have again partnered to develop the Global Land Survey 2010 (GLS2010), a new global land data set with core acquisition dates of 2008-2011. This dataset consists of both Landsat TM and ETM+ images that meet quality and cloud cover standards established by the earlier GLS collections. Data acquired in 2011 were used to fill areas of low image quality or excessive cloud cover.
Minnesota's original public land survey plat maps were created between 1848 and 1907 during the first government land survey of the state by the U.S. Surveyor General's Office. This collection of more than 3,600 maps includes later General Land Office (GLO) and Bureau of Land Management maps up through 2001. Scanned images of the maps are available in several digital formats and most have been georeferenced.
The survey plat maps, and the accompanying survey field notes, serve as the fundamental legal records for real estate in Minnesota; all property titles and descriptions stem from them. They also are an essential resource for surveyors and provide a record of the state's physical geography prior to European settlement. Finally, they testify to many years of hard work by the surveying community, often under very challenging conditions.
The deteriorating physical condition of the older maps (drawn on paper, linen, and other similar materials) and the need to provide wider public access to the maps, made handling the original records increasingly impractical. To meet this challenge, the Office of the Secretary of State (SOS), the State Archives of the Minnesota Historical Society (MHS), the Minnesota Department of Transportation (MnDOT), MnGeo and the Minnesota Association of County Surveyors collaborated in a digitization project which produced high quality (800 dpi), 24-bit color images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes of data. Funding was provided by MnDOT.
In 2010-11, most of the JPEG plat map images were georeferenced. The intent was to locate the plat images to coincide with statewide geographic data without appreciably altering (warping) the image. This increases the value of the images in mapping software where they can be used as a background layer.
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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
Control Point Download Link
Survey and Plat Line Download Link
Subdivision Download Link
Lot and Block Download Link
Record of Survey Download Link
The surveys and plats feature layer includes information related to the following topics.Control Point - The control point dataset represents corner points that have been observed by IDL staff or a licensed surveyor. Corners are points on the surface of the earth, determined by the surveying process, which defines an extremity on a boundary of the public lands. Points are represented by a type to determine the source of the corner. Control points have been gathered from various sources. These points are used to adjust the Parcel Fabric. This allows for a more accurate GIS representation of ground conditions.Survey and Plat Line - A record of survey is a detailed map that documents and identifies the physical land boundaries or property lines for a specific parcel of land. This feature class represents the parcel lines documented in a record of survey. These records of surveys can include subdivision plats and surveys performed by federal entities. The metes and bounds information is stored as attribute values.Subdivision - "Subdivision" means the division of a lot, tract, or parcel of land into two or more lots, plats, sites, or other divisions of land for the purpose, whether immediate or future, of sale or of building development. It includes resubdivision and, when appropriate to the context, relates to the process of subdividing or to the land or territory subdivided.Lots and Blocks - A lot is an individual piece of land which is intended to be conveyed in its entirety to a buyer. A block is generally a group of contiguous lots bounded by streets, such as a city block.Record of Surveys - A record of survey is a detailed map that documents and identifies the physical land boundaries or property lines for a specific parcel of land. This feature class represents the parcels documented in a record of survey. These records of surveys do not include subdivision plats, lots, or blocks.State Surface Ownership - This feature class contains the surface ownership for endowment lands managed by the Idaho Department of Lands. There is also data for other state agencies, but this data is not complete.PLSS Township - Townships are normally a square approximately six miles on a side with cardinal boundaries conforming to meridians and parallels, containing 36 sections of one square mile each.PLSS Section - The first set of divisions for a PLSS Township. Typically 640 acres or 1 square mile.PLSS Subsection - Is a quarter, quarter-quarter, sixteenth, or government lot division of the PLSS.
description: Minnesota's original public land survey plat maps were created between 1848 and 1907 during the first government land survey of the state by the U.S. Surveyor General's Office. This collection of more than 3,600 maps includes later General Land Office (GLO) and Bureau of Land Management maps up through 2001. Scanned images of the maps are available in several digital formats and most have been georeferenced. The survey plat maps, and the accompanying survey field notes, serve as the fundamental legal records for real estate in Minnesota; all property titles and descriptions stem from them. They also are an essential resource for surveyors and provide a record of the state's physical geography prior to European settlement. Finally, they testify to many years of hard work by the surveying community, often under very challenging conditions. The deteriorating physical condition of the older maps (drawn on paper, linen, and other similar materials) and the need to provide wider public access to the maps, made handling the original records increasingly impractical. To meet this challenge, the Office of the Secretary of State (SOS), the State Archives of the Minnesota Historical Society (MHS), the Minnesota Department of Transportation (MnDOT), MnGeo (formerly the Land Management Information Center - LMIC) and the Minnesota Association of County Surveyors collaborated in a digitization project which produced high quality (800 dpi), 24-bit color images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes of data. Funding was provided by MnDOT. In 2010-11, most of the JPEG plat map images were georeferenced. The intent was to locate the plat images to coincide with statewide geographic data without appreciably altering (warping) the image. This increases the value of the images in mapping software where they can be used as a background layer.; abstract: Minnesota's original public land survey plat maps were created between 1848 and 1907 during the first government land survey of the state by the U.S. Surveyor General's Office. This collection of more than 3,600 maps includes later General Land Office (GLO) and Bureau of Land Management maps up through 2001. Scanned images of the maps are available in several digital formats and most have been georeferenced. The survey plat maps, and the accompanying survey field notes, serve as the fundamental legal records for real estate in Minnesota; all property titles and descriptions stem from them. They also are an essential resource for surveyors and provide a record of the state's physical geography prior to European settlement. Finally, they testify to many years of hard work by the surveying community, often under very challenging conditions. The deteriorating physical condition of the older maps (drawn on paper, linen, and other similar materials) and the need to provide wider public access to the maps, made handling the original records increasingly impractical. To meet this challenge, the Office of the Secretary of State (SOS), the State Archives of the Minnesota Historical Society (MHS), the Minnesota Department of Transportation (MnDOT), MnGeo (formerly the Land Management Information Center - LMIC) and the Minnesota Association of County Surveyors collaborated in a digitization project which produced high quality (800 dpi), 24-bit color images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes of data. Funding was provided by MnDOT. In 2010-11, most of the JPEG plat map images were georeferenced. The intent was to locate the plat images to coincide with statewide geographic data without appreciably altering (warping) the image. This increases the value of the images in mapping software where they can be used as a background layer.
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).
Global Land Survey 2010 images were acquired from 2008 to 2011 by Landsat 7 ETM+ and Landsat 5 Thematic Mapper (TM).
The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) collaborated on the creation of the global land datasets using Landsat data from 1972 through 2008. Each of these global datasets was created from the primary Landsat sensor in use at the time: the Multispectral Scanner (MSS) in the 1970s, the Thematic Mapper (TM) in 1990, the Enhanced Thematic Mapper Plus (ETM+) in 2000, and a combination of TM and ETM+, as well as EO-1 ALI data, in 2005.
This dataset includes high quality (800 Dots Per Inch - DPI), 24 bit color images of Minnesota's original Public Land Survey (PLS) plats created during the first government land survey of the state from 1848 to 1907. Currently housed at the Office of the Secretary of State, these plats were created by the U.S. Surveyor General's Office. This collection of more than 3,600 maps also includes later General Land Office (GLO) and the Bureau of Land Management (BLM) maps - up to the year 2001.
Minnesota's survey plat maps serve as the fundamental legal records for real estate in the state; all property titles and descriptions stem from them. They also serve as an essential resource for surveyors and as an analytical tool for the state's physical geography prior to European settlement. Finally, they serve as a testimony to years and years of hard work by the surveying community, often under challenging conditions.
In recent years the deteriorating physical condition of the older maps and the needs of technologically more sophisticated researchers, who require access to the maps, have made handling the original paper records increasingly less practical. To meet this challenge, the Office of the Secretary of State, the State Archives of the Minnesota Historical Society, the Minnesota Department of Transportation, MnGeo (formerly the Land Management Information Center - LMIC) and the Minnesota Association of County Surveyors collaborated in a digitization project which produced images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes worth of data. Funding was provided by the Minnesota Department of Transportation.
The Digital Geologic Map of the U.S. Geological Survey Mapping in the Western Portion of Amistad National Recreation Area, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Eddie Collins, Amanda Masterson and Tom Tremblay (Texas Bureau of Economic Geology); Rick Page (U.S. Geological Survey); Gilbert Anaya (International Boundary and Water Commission). Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (wpam_metadata.txt; available at http://nrdata.nps.gov/amis/nrdata/geology/gis/wpam_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (wpam_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of Amistad National Recreation Area.
This Quarter Section feature class depicts PLSS Second Divisions . PLSS townships are subdivided in a spatial hierarchy of first, second, and third division. These divisions are typically aliquot parts ranging in size from 640 acres to 160 to 40 acres, and subsequently all the way down to 2.5 acres. The data in this feature class was translated from the PLSSSecondDiv feature class in the original production data model, which defined the second division for a specific parcel of land. Metadata
This coverage contains the section lines for the Public Land Survey System (PLSS). These lines form polygons which are labelled for PLSS township, range and section number. Coordinates were digitized from U. S. Geological Survey 7.5' topographic maps (paper copies) using a digitizing program developed in-house by the Geological Survey Bureau, Iowa DNR. The digitizing tablet accuracy was 1/50 inch. Section lines from individual quads were combined and edited using PC Arc/Info.
description: This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer; abstract: This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer
description: The TRSQ digital data set represents the Township, Range, Section, Quarter section, and Quarter-quarter section divisions of the state. Beginning in the late 1840s, the federal government began surveying Minnesota as part of the Public Land Survey System (PLSS). The resulting network of land survey lines divided the state into townships, ranges, sections, quarter sections, quarter-quarter sections and government lots, and laid the groundwork for contemporary land ownership patterns. The quarter-quarter section remains an important subdivision for rural Minnesota since these lines are used to define local boundaries, roads, and service areas. All survey lines were extended across water bodies despite the fact that U.S. Geological Survey (USGS) base maps depict them only on land. This addition allows all sections and townships to be represented as closed areas ensuring that township and range location can be determined for any point in the state. It also means that the data is not affected if lake levels change over time. The township, range and section boundaries were digitized at MnGeo (formerly the Land Management Information Center - LMIC) from the USGS 30' x 60' map series (1:100,000-scale). Quarter section and quarter-quarter section subdivisions were calculated using the section lines. They were not digitized from original plat book survey lines or from the meandered lines that surveyors laid out around water bodies. The existence of government lots within a quarter-quarter section is recorded in the data set; however, the government lot boundaries were not digitized. If a quarter-quarter section contains more than one government lot, the number of lots is recorded -- see Lineage, Section 2, for more detail. Note: For most uses, TRSQ has been superseded by the Minnesota Department of Natural Resources (DNR) 1:24,000-scale 'Control Point Generated PLS' data set which is free online. See https://gisdata.mn.gov/dataset/plan-mndnr-public-land-survey for more information. Also, many county surveyors offices have more accurate PLS (Public Land Survey) data sets. For county webpages and contact information, see http://www.mngeo.state.mn.us/cty_contacts.html .; abstract: The TRSQ digital data set represents the Township, Range, Section, Quarter section, and Quarter-quarter section divisions of the state. Beginning in the late 1840s, the federal government began surveying Minnesota as part of the Public Land Survey System (PLSS). The resulting network of land survey lines divided the state into townships, ranges, sections, quarter sections, quarter-quarter sections and government lots, and laid the groundwork for contemporary land ownership patterns. The quarter-quarter section remains an important subdivision for rural Minnesota since these lines are used to define local boundaries, roads, and service areas. All survey lines were extended across water bodies despite the fact that U.S. Geological Survey (USGS) base maps depict them only on land. This addition allows all sections and townships to be represented as closed areas ensuring that township and range location can be determined for any point in the state. It also means that the data is not affected if lake levels change over time. The township, range and section boundaries were digitized at MnGeo (formerly the Land Management Information Center - LMIC) from the USGS 30' x 60' map series (1:100,000-scale). Quarter section and quarter-quarter section subdivisions were calculated using the section lines. They were not digitized from original plat book survey lines or from the meandered lines that surveyors laid out around water bodies. The existence of government lots within a quarter-quarter section is recorded in the data set; however, the government lot boundaries were not digitized. If a quarter-quarter section contains more than one government lot, the number of lots is recorded -- see Lineage, Section 2, for more detail. Note: For most uses, TRSQ has been superseded by the Minnesota Department of Natural Resources (DNR) 1:24,000-scale 'Control Point Generated PLS' data set which is free online. See https://gisdata.mn.gov/dataset/plan-mndnr-public-land-survey for more information. Also, many county surveyors offices have more accurate PLS (Public Land Survey) data sets. For county webpages and contact information, see http://www.mngeo.state.mn.us/cty_contacts.html .
For large areas, like Washington State, download as a file geodatabase. Large data sets like this one, for the State of Washington, may exceed the limits for downloading as shape files, excel files, or KML files. For areas less than a county, you may use the map to zoom to your area and download as shape file, excel or KML, if that format is desired.The Boundary layer consists of lines representing the boundaries of Parcels and Legal Descriptions. (See the metadata for those two layers.) Boundary lines are the places that are surveyed in order to delimit the extent of Parcels and Legal Descriptions. The character and accuracy of Boundary locations is held in the attributes of the Points that are at the ends of Boundary lines. All the boundaries of Parcels and Legal Descriptions are covered by a Boundary line. Currently the Boundary layer has little functionality. The only distinction it makes is between upland boundaries and shorelines. In the future Boundary lines will have a richer set of attributes in order to accommodate cartographic needs to distinguish between types of boundaries.WA Boundaries Metadata
https://data.gov.tw/licensehttps://data.gov.tw/license
API URL: https://api.nlsc.gov.tw/other/LandUsePointQuery, Input parameters: /X coordinate/Y coordinate[/coordinate type code (4326, 3826, default will use longitude and latitude)], Return result: XML; including the tile year in the latest year, survey year and month, primary category code (Lcode_C1) and description (Lname_C1), secondary category code (Lcode_C2) and description (Lname_C2), third category code (Lcode_C3) and description (NAME), API syntax example: https://api.nlsc.gov.tw/other/LandUsePointQuery/120.634413/24.153282/4326
This dataset comes from the Department of Licensing and Regulatory Affairs' Office of Land Survey and Remonumentation (OLSR). See Act 345 of 1990: State Survey and Remonumentation Act for more information.The system of record was queried for approved locations where grid coordinates were provided. Records with coordinates outside the state's geographical boundary were retained (34 locations). The columns "DMS LAT" and "DMS LONG" were added to the extraction table and populated with data from fields "Latitude N" and "Longitude W" and formatted to DMS2. The data was exported as feature class using geoprocessing tool "Convert Coordinate Notation," geographic coordinate system WGS 1984 Web Mercator (auxiliary sphere).This dataset was last updated June 6, 2022, with quarterly updates to begin in 2023.More Metadata
Digital line graph (DLG) data are digital representations of cartographic information. DLGs of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 1:100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management planimetric maps at a scale of 1:100,000 are used. Intermediate-scale DLGs are sold in five categories: (1) Public Land Survey System; (2) boundaries; (3) transportation; (4) hydrography; and (5) hypsography. All DLG data distributed by the USGS are DLG-Level 3 (DLG-3), which means the data contain a full range of attribute codes, have full topological structuring, and have passed certain quality-control checks.
https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/
The Surveying and Mapping Services industry in Canada has weathered uncertain conditions as downstream industries including residential, commercial, industrial construction and government authorities, fared with volatility brought on by the COVID-19 pandemic. The industry's performance is largely tied to developments in residential and nonresidential construction markets, which fuel both private- and public-sector spending.As Canadian oil, gas and mining companies cut back spending on exploration and development projects in response to falling commodity prices, and construction stalled in resource-rich provinces, demand for surveying and mapping services for these projects fell. While growth from the residential construction market helped offset some losses, rising interest intended to offset rising inflation have hampered residential demand. Thus, even as energy prices came roaring back, many surveyors saw a reduction in demand. Over the five years to 2023, industry revenue has been contracting at a CAGR of 1.7% and is expected to reach $1.7 billion, including an expected drop of 3.2% over the current year.The return to growth of downstream construction markets will likely keep industry demand afloat moving forward. In addition to solid demand from industrial building construction as commodity prices remain high, housing market expansion will stimulate demand for cadastral, property line and construction surveying. The continued adoption of new technology will also enable companies to realize new efficiencies and improve the quality of their services, expanding sizable profit margins further. Industry revenue is forecast to rise at a CAGR of 1.2% to $1.8 billion over the five years to 2028.
NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024.
Thank you for your interest in DWR land use datasets.
The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023.
Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer.
For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys.
For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.
For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.
Recommended citation for DWR land use data: California Department of Water Resources. (Water Year for the data). Statewide Crop Mapping—California Natural Resources Agency Open Data. Retrieved “Month Day, YEAR,” from https://data.cnra.ca.gov/dataset/statewide-crop-mapping.
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The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) collaborated on the creation of the global land datasets using Landsat data from 1972 through 2008. NASA and the USGS have again partnered to develop the Global Land Survey 2010 (GLS2010), a new global land data set with core acquisition dates of 2008-2011. This dataset consists of both Landsat TM and ETM+ images that meet quality and cloud cover standards established by the earlier GLS collections. Data acquired in 2011 were used to fill areas of low image quality or excessive cloud cover.