The Poverty Mapping Project: Small Area Estimates of Poverty and Inequality data set consists of consumption-based poverty, inequality and related measures for subnational administrative Units in approximately twenty countries throughout Africa, Asia, Europe, North America, and South America. These measures are derived on a country-level basis from a combination of census and survey data using small area estimates techniques. The collection of data have been compiled, integrated and standardized from the original data providers into a unified spatially referenced and globally consistent data set. The data products include shapefiles (vector data), tabular data sets (csv format), and centroids (csv file with latitude and longitude of a geographic Unit and associated poverty estimates). Additionally, a data catalog (xls format) containing detailed information and documentation is provided. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with a number of external data providers.

Section map index of New York City zoning maps to determine which zoning section map relates to specific areas of NYC.

Update frequency: as needed

Full quarter sections within Milwaukee County. These maps show engineering and tax information regarding parcels within the county and municipalities. Please visit our Quarter Section Lookup web app to download PDFs of individual engineering and tax quarter section maps.

Shapefile is projected in Wisconsin State Plane South NAD27 (WKID 32054)

This data release presents geologic map data for the surficial geology of the Aztec 1-degree by 2-degree quadrangle. The map area lies within two physiographic provinces of Fenneman (1928): the Southern Rocky Mountains province, and the Colorado Plateau province, Navajo section. Geologic mapping is mostly compiled from published geologic map data sources ranging from 1:24,000 to 1:250,000 scale, with limited new interpretive contributions. Gaps in map compilation are related to a lack of published geologic mapping at the time of compilation, and not necessarily a lack of surficial deposits. Much of the geology incorporated from published geologic maps is adjusted based on digital elevation model and natural-color image data sources to improve spatial resolution of the data. Spatial adjustments and new interpretations also eliminate mismatches at source map boundaries. This data set represents only the surficial geology, defined as generally unconsolidated to moderately consolidated sedimentary deposits that are Quaternary or partly Quaternary in age, and faults that have documented Quaternary offset. Bedrock and sedimentary material directly deposited as a result of volcanic activity are not included in this database, nor are faults that are not known to have moved during the Quaternary. Map units in the Aztec quadrangle include alluvium, glacial, eolian, mass-wasting, colluvium, and alluvium/colluvium deposit types. Alluvium map units, present throughout the map area, range in age from Quaternary-Tertiary to Holocene and form stream-channel, floodplain, terrace, alluvial-fan, and pediment deposits. Along glaciated drainages terraces are commonly made up of glacial outwash. Glacial map units are concentrated in the northeast corner of the map area and are mostly undifferentiated till deposited in mountain valleys during Pleistocene glaciations. Eolian map units are mostly middle Pleistocene to Holocene eolian sand deposits forming sand sheets and dunes. Mass-wasting map units are concentrated in the eastern part of the map area, and include deposits formed primarily by slide, slump, earthflow, and rock-fall processes. Colluvium and alluvium/colluvium map units form hillslope and undifferentiated valley floor/hillslope deposits, respectively. The detail of geologic mapping varies from about 1:50,000- to 1:250,000-scale depending on the scale of published geologic maps available at the time of compilation, and for new mapping, the resolution of geologic features on available basemap data. Map units are organized within geologic provinces as described by the Seamless Integrated Geologic Mapping (SIGMa) (Turner and others, 2022) extension to the Geologic Map Schema (GeMS) (USGS, 2020). For this data release, first order geologic provinces are the physiographic provinces of Fenneman (1928), which reflect the major geomorphological setting affecting depositional processes. Second order provinces are physiographic sections of Fenneman (1928) if present. Third and fourth order provinces are defined by deposit type. Attributes derived from published source maps are recorded in the map unit polygons to preserve detail and allow database users the flexibility to create derivative map units. Map units constructed by the authors are based on geologic province, general deposit type and generalized groupings of minimum and maximum age to create a number of units typical for geologic maps of this scale. Polygons representing map units were assigned a host of attributes to make that geology easily searchable. Each polygon contains a general depositional process (‘DepositGeneral’) as well as three fields that describe more detailed depositional processes responsible for some deposition in that polygon (‘LocalGeneticType1’ – ‘LocalGeneticType3’). Three fields describe the materials that make up the deposit (‘LocalMaterial1’ – ‘LocalMaterial3’) and the minimum and maximum chronostratigraphic age of a deposit is stored in the ‘LocalAgeMin’ and ‘LocalAgeMax’ fields, respectively. Where a polygon is associated with a prominent landform or a formal stratigraphic name the ‘LocalLandform’ and ‘LocalStratName’ fields are populated. The field ‘LocalThickness’ provides a textual summary of how thick a source publication described a deposit to be. Where three fields are used to describe the contents of a deposit, we attempt to place descriptors in a relative ordering such that the first field is most prominent, however for remotely interpreted deposits and some sources that provide generalized descriptions this was not possible. Values within these searchable fields are generally taken directly from source maps, however we do perform some conservative adjustments of values based on observations from the landscape and/or adjacent source maps. Where new features were interpreted from remote observations, we derive polygon attributes based on a conservative correlation to neighboring maps. Detail provided at the polygon level is simplified into a map unit by matching its values to the DescriptionOfMapUnits_Surficial table. Specifically, we construct map units within each province based on values of ‘DepositGeneral’ and a set of chronostratigraphic age bins that attempt to capture important aspects of Quaternary landscape evolution. Polygons are assigned to the mapunit with a corresponding ‘DepositGeneral’ and the narrowest chronostratigraphic age bin that entirely contains the ‘LocalAgeMin’ and ‘LocalAgeMax’ values of that polygon. Therefore, users may notice some mismatch between the age range of a polygon and the age range of the assigned map unit, where ‘LocalAgeMin’ and ‘LocalAgeMax’ (e.g., Holocene – Holocene) may define a shorter temporal range than suggested by the map unit (e.g., Holocene – late Pleistocene). This apparent discrepancy allows for detailed information to be preserved in the polygons, while also allowing for an integrated suite of map units that facilitate visualization over a large region.

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.

For the latest Land Use Legend, 2022-DWR-Standard-Land-Use-Legend-Remote-Sensing-Version.pdf, please see the Data and Resources section below.

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.

Please click here to view the Data Dictionary, a description of the fields in this table.City of Scottsdale Quarter Sections

The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean Unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean Unit size grids provide a quantitative surface that indicates the size of the input Unit(s) from which population count and density grids are derived. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).

The Poverty Mapping Project: Small Area Estimates of Poverty and Inequality data set consists of consumption-based poverty, inequality and related measures for subnational administrative Units in approximately twenty countries throughout Africa, Asia, Europe, North America, and South America. These measures are derived on a country-level basis from a combination of census and survey data using small area estimates techniques. The collection of data have been compiled, integrated and standardized from the original data providers into a unified spatially referenced and globally consistent data set. The data products include shapefiles (vector data), tabular data sets (csv format), and centroids (csv file with latitude and longitude of a geographic Unit and associated poverty estimates). Additionally, a data catalog (xls format) containing detailed information and documentation is provided. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with a number of external data providers.

Service Definition for a mosaic of compartment maps for Section 29 of the Cloquet Forestry Center. These maps were produced in 1914 to catalog the existing conditions of the CFC.

Produced by adding GCPs at each corner of a clipped map image associated to the corresponding PLSS compartment corner based on legal definition of 1/4, 1/4 Section (ie. Section 29, NE1/4 NE1/4).

First-order Transformation

RMSE = 1 (4 GCPs)

Discover the explosive growth of the Knowledge Area Mapping Map market! Our comprehensive analysis reveals key trends, drivers, and restraints shaping this $500 million (2025 est.) industry, segmented by application and region. Project your business strategy with our forecast to 2033. Explore market share data and competitive landscape insights.

This dataset contains files created, digitized, or georeferenced by Chris DeRolph for mapping the pre-urban renewal community within the boundaries of the Riverfront-Willow St. and Mountain View urban renewal projects in Knoxville TN. Detailed occupant information for properties within boundaries of these two urban renewal projects was extracted from the 1953 Knoxville City Directory. The year 1953 was chosen as a representative snapshot of the Black community before urban renewal projects were implemented. The first urban renewal project to be approved was the Riverfront-Willow Street project, which was approved in 1954 according to the University of Richmond Renewing Inequality project titled ‘Family Displacements through Urban Renewal, 1950-1966’ (link below in the 'Other shapefiles' section). For ArcGIS Online users, the shapefile and tiff layers are available in AGOL and can be found by clicking the ellipsis next to the layer name and selecting 'Show item details' for the layers in this webmap https://knoxatlas.maps.arcgis.com/apps/webappviewer/index.html?id=43a66c3cfcde4f5f8e7ab13af9bbcebecityDirectory1953 is a folder that contains:JPG images of 1953 City Directory for street segments within the urban renewal project boundaries; images collected at the McClung Historical CollectionTXT files of extracted text from each image that was used to join occupant information from directory to GIS address datashp is a folder that contains the following shapefiles:Residential:Black_owned_residential_1953.shp: residential entries in the 1953 City Directory identified as Black and property ownersBlack_rented_residential_1953.shp: residential entries in the 1953 City Directory identified as Black and non-owners of the propertyNon_Black_owned_residential_1953.shp: residential entries in the 1953 City Directory identified as property owners that were not listed as BlackNon_Black_rented_residential_1953.shp: residential entries in the 1953 City Directory not listed as Black or property ownersResidential shapefile attributes:cityDrctryString: full text string from 1953 City Directory entryfileName: name of TXT file that contains the information for the street segmentsOccupant: the name of the occupant listed in the City Directory, enclosed in square brackets []Number: the address number listed in the 1953 City DirectoryBlackOccpt: flag for whether the occupant was identified in the City Directory as Black, designated by the (c) or (e) character string in the cityDrctryString fieldOwnerOccpd: flag for whether the occupant was identified in the City Directory as the property owner, designated by the @ character in the cityDrctryString fieldUnit: unit if listed (e.g. Apt 1, 2d fl, b'ment, etc)streetName: street name in ~1953Lat: latitude coordinate in decimal degrees for the property locationLon: longitude coordinate in decimal degrees for the property locationrace_own: combines the BlackOccpt and OwnerOccpd fieldsmapLabel: combines the Number and Occupant fields for map labeling purposeslastName: occupant's last namelabelShort: combines the Number and lastName fields for map labeling purposesNon-residential:Black_nonResidential_1953.shp: non-residential entries in the 1953 City Directory listed as Black-occupiedNonBlack_nonResidential_1953.shp: non-residential entries in the 1953 City Directory not listed as Black-occupiedNon-residential shapefile attributes:cityDrctryString: full text string from 1953 City Directory entryfileName: name of TXT file that contains the information for the street segmentsOccupant: the name of the occupant listed in the City Directory, enclosed in square brackets []Number: the address number listed in the 1953 City DirectoryBlackOccpt: flag for whether the occupant was identified in the City Directory as Black, designated by the (c) or (e) character string in the cityDrctryString fieldOwnerOccpd: flag for whether the occupant was identified in the City Directory as the property owner, designated by the @ character in the cityDrctryString fieldUnit: unit if listed (e.g. Apt 1, 2d fl, b'ment, etc)streetName: street name in ~1953Lat: latitude coordinate in decimal degrees for the property locationLon: longitude coordinate in decimal degrees for the property locationNAICS6: 2022 North American Industry Classification System (NAICS) six-digit business code, designated by Chris DeRolph rapidly and without careful considerationNAICS6title: NAICS6 title/short descriptionNAICS3: 2022 North American Industry Classification System (NAICS) three-digit business code, designated by Chris DeRolph rapidly and without careful considerationNAICS3title: NAICS3 title/short descriptionflag: flags whether the occupant is part of the public sector or an NGO; a flag of '0' indicates the occupant is assumed to be a privately-owned businessrace_own: combines the BlackOccpt and OwnerOccpd fieldsmapLabel: combines the Number and Occupant fields for map labeling purposesOther shapefiles:razedArea_1972.shp: approximate area that appears to have been razed during urban renewal based on visual overlay of usgsImage_grayscale_1956.tif and usgsImage_colorinfrared_1972.tif; digitized by Chris DeRolphroadNetwork_preUrbanRenewal.shp: road network present in urban renewal area before razing occurred; removed attribute indicates whether road was removed or remains today; historically removed roads were digitized by Chris DeRolph; remaining roads sourced from TDOT GIS roads dataTheBottom.shp: the approximate extent of the razed neighborhood known as The Bottom; digitized by Chris DeRolphUrbanRenewalProjects.shp: boundaries of the East Knoxville urban renewal projects, as mapped by the University of Richmond's Digital Scholarship Lab https://dsl.richmond.edu/panorama/renewal/#view=0/0/1&viz=cartogram&city=knoxvilleTN&loc=15/35.9700/-83.9080tiff is a folder that contains the following images:streetMap_1952.tif: relevant section of 1952 map 'Knoxville Tennessee and Surrounding Area'; copyright by J.U.G. Rich and East Tenn Auto Club; drawn by R.G. Austin; full map accessed at McClung Historical Collection, 601 S Gay St, Knoxville, TN 37902; used as reference for street names in roadNetwork_preUrbanRenewal.shp; georeferenced by Chris DeRolphnewsSentinelRdMap_1958.tif: urban renewal area map from 1958 Knox News Sentinel article; used as reference for street names in roadNetwork_preUrbanRenewal.shp; georeferenced by Chris DeRolphusgsImage_grayscale_1956.tif: May 18, 1956 black-and-white USGS aerial photograph, georeferenced by Chris DeRolph; accessed here https://earthexplorer.usgs.gov/scene/metadata/full/5e83d8e4870f4473/ARA550590030582/usgsImage_colorinfrared_1972.tif: April 18, 1972 color infrared USGS aerial photograph, georeferenced by Chris DeRolph; accessed here https://earthexplorer.usgs.gov/scene/metadata/full/5e83d8e4870f4473/AR6197002600096/usgsImage_grayscale_1976.tif: November 8, 1976 black-and-white USGS aerial photograph, georeferenced by Chris DeRolph; accessed here https://earthexplorer.usgs.gov/scene/metadata/full/5e83d8e4870f4473/AR1VDUT00390010/

Summary Carver County Section file. Description This is a polygon dataset for the Sections within Carver County derived from the County Surveryor's base map.

The SEN12 Global Urban Mapping (SEN12_GUM) dataset consists of Sentinel-1 SAR (VV + VH band) and Sentinel-2 MSI (10 spectral bands) satellite images acquired over the same area for 96 training and validation sites and an additional 60 test sites covering unique geographies across the globe. The satellite imagery was acquired as part of the European Space Agency's Earth observation program Copernicus and was preprocessed in Google Earth Engine. Built-up area labels for the 30 training and validation sites located in the United States, Canada, and Australia were obtained from Microsoft's open-access building footprints. The other 66 training sites located outside of the United States, Canada, and Australia are unlabeled but can be used for semi-supervised learning. Labels obtained from the SpaceNet7 dataset are provided for all 60 test sites.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Point Reyes map area, California. The vector data file is included in "Contours_PointReyes.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html.

10-m interval contours of the Offshore of Point Reyes map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This data set provides local LAI maps for the selected measured sites in Canada. These derived maps may also be useful for validating other LAI maps over these same sites given that the areas are protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The data set may also be useful for monitoring changes in the land surface.The Leaf Area Index (LAI) maps are at 30-m resolution for the selected sites. LAI is defined here as half the total (all-sided) live foliage area per unit horizontal projected ground surface area. Overstory LAI corresponds to all tree foliage except for treeless areas where it corresponds to total foliage. The algorithms were developed from ground measurements and Landsat TM and ETM+ images (Fernandes et. al., 2003). A mask was developed using the Landsat ETM+/TM5 image and available land cover map to identify only those areas with land cover belonging to the sample land cover classes and with Landsat ETM+/TM5 spectral reflectance values that fell within the convex hull of the spectral reflectance values over the plots. LAI was mapped within the masked region using the Landsat ETM+/TM5 image and the developed transfer function. The final LAI map was scaled by a factor of 20 (offset 0). The LAI maps are in Tagged Image File Format (TIFF).

Digital Data from VG96-733A Walsh, GJ, Armstrong, TR�and Ratcliffe, NM, 1996,�Digital bedrock geologic map of the Vermont part of the 7.5 x 15 minute Mount Ascutney and Springfield quadrangles, Vermont: USGS Open-File Report 96-733, 1�plate, scale 1:24000. The bedrock geologic map data at a scale of 1:24,000 depicts types of bedrock underlying unconsolidated materials in Vermont. Data is created by mapping on the ground using standard geologic pace and compass techniques and/or GPS on a USGS 1:24000 topographic base map. Data may be organized by town, quadrangle or watershed. Each data bundle may includes point, line and polygon data and some or all of the following: 1) contacts (lithogic contacts), 2) fault_brittle, 3) fault_ductile, 4) fault_thrust, 5) fault_bed_plane (bedding plane thrust), 6) bedding, 7) bedding_graded (graded bedding) 8) bedding_overturn (overturned bedding), 9) bedding_select (selected points for published map), 10) foliation_n1, n2, n3 etc (foliation data), 11) outcrop (exposed outcrops), 12) field_station (outcrop and data collection point), 13) fold_axis, 14) axial_plane, 15) lamprophyre, 16) water_well_log (water well driller information), 16) linear_int (intersection lineation), 17) linear_str (stretching lineation) 18) x_section_line (line of cross-section), and photolinear (lineaments identified from air photos). Other feature classes may be included with each data bundle. (https://dec.vermont.gov/geological-survey/publication-gis/ofr).

Colour raster copies of different archived issues, so called topographic sections (toposections) at scale 1:25,000 originate in the Third Austrian Military Mapping. The maps were published between 1872 and 1953 in Austro-Hungarian Empire and later in Czechoslovakia and other successor states. The territorial extent of the file significantly exceeds boundaries of today's Czech Republic.

This layer provides quarter-section boundaries for the Stark County tax map. The State of Ohio was subdivided using the Public Land Survey System (PLSS). The PLSS initially subdivided lands into townships, which were numbered using a grid system. Townships were numbered horizontally and cross-referenced with vertical numbers referred to as the range. Each township was further divided into one-mile sections, which were subsequently divided into quarter-sections. This layer does not reflect the initial PLSS boundaries. It respects current jurisdictional boundaries and reflects boundaries within Stark County's cities and villages as well. Each quarter section includes tax district information.

ADMMR map collection: Glance Creek Area, Vertical Sections, State Lease No 2 & 3, Map 8; 1 in. to 50 feet; 17 x 23 in.

Colour raster copies of different archived issues, so called topographic sections (toposections) at scale 1:25,000 originate in the Third Austrian Military Mapping. The maps were published between 1872 and 1953 in Austro-Hungarian Empire and later in Czechoslovakia and other successor states. The territorial extent of the file significantly exceeds boundaries of today's Czech Republic.