7 datasets found
  1. City of Fresno, California City Limits

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Feb 26, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    City of Fresno, California City Limits [Dataset]. https://koordinates.com/layer/96890-city-of-fresno-california-city-limits/
    Explore at:
    shapefile, mapinfo tab, geodatabase, dwg, geopackage / sqlite, mapinfo mif, kml, pdf, csvAvailable download formats
    Dataset updated
    Feb 26, 2024
    Dataset provided by
    City of Fresno
    Authors
    City of Fresno, California
    Area covered
    Description

    Vector polygon map data of city limits from Fresno, California containing 1 feature.

    City limits GIS (Geographic Information System) data provides valuable information about the boundaries of a city, which is crucial for various planning and decision-making processes. Urban planners and government officials use this data to understand the extent of their jurisdiction and to make informed decisions regarding zoning, land use, and infrastructure development within the city limits.

    By overlaying city limits GIS data with other layers such as population density, land parcels, and environmental features, planners can analyze spatial patterns and identify areas for growth, conservation, or redevelopment. This data also aids in emergency management by defining the areas of responsibility for different emergency services, helping to streamline response efforts during crises..

    This city limits data is available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

  2. Fresno County, CA Parcels

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 12, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    City of Fresno, California (2018). Fresno County, CA Parcels [Dataset]. https://koordinates.com/layer/96884-fresno-county-ca-parcels/
    Explore at:
    mapinfo mif, geodatabase, csv, geopackage / sqlite, kml, mapinfo tab, pdf, shapefile, dwgAvailable download formats
    Dataset updated
    Sep 12, 2018
    Dataset provided by
    City of Fresno
    Authors
    City of Fresno, California
    Area covered
    Description

    Vector polygon map data of property parcels from Fresno County, California containing 202,076 features.

    Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

    Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

    Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

  3. City of Fresno, CA Enterprise Zones

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 12, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    City of Fresno, CA Enterprise Zones [Dataset]. https://koordinates.com/layer/96891-city-of-fresno-ca-enterprise-zones/
    Explore at:
    mapinfo tab, shapefile, geodatabase, geopackage / sqlite, dwg, pdf, mapinfo mif, kml, csvAvailable download formats
    Dataset updated
    Sep 12, 2018
    Dataset provided by
    City of Fresno
    Authors
    City of Fresno, California
    Area covered
    Description

    This layer is sourced from gis4u.fresno.gov.

  4. i15 LandUse Fresno2009 east

    • data.ca.gov
    • data.cnra.ca.gov
    • +3more
    Updated Feb 16, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    California Department of Water Resources (2022). i15 LandUse Fresno2009 east [Dataset]. https://data.ca.gov/dataset/i15-landuse-fresno2009-east
    Explore at:
    geojson, zip, arcgis geoservices rest api, kml, csv, htmlAvailable download formats
    Dataset updated
    Feb 16, 2022
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This map is designated as Final.

    Land-Use Data Quality Control

    Every published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.

    Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.

    Provisional datasets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.

    The 2009 Fresno County, east, land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM), Water Use Efficiency Branch (WUE). Digitized land use boundaries and associated attributes were gathered by staff from DWR’s South Central Region (SCRO), using extensive field visits and aerial photography. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Prior to the summer field survey by SCRO, WUE staff analyzed Landsat 5 imagery to identify fields likely to have winter crops. The combined land use data went through standard quality control procedures before final processing. Quality control procedures were performed jointly by staff at DWR’s WUE Land Use Unit and SCRO, under the supervision of Steve Ewert. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. 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 Standards version 2.1, dated March 9, 2016. 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. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of eastern Fresno County conducted by DWR, South Central Regional Office staff, under the leadership of Steve Ewert, Senior Land and Water Use Supervisor. The field work for this survey was conducted during the summer of 2009. SCRO staff physically visited each delineated field, noting the crops grown at each location. Field survey boundary data was developed using: 1. Eastern Fresno County was surveyed using the 2006 two-meter resolution National Agriculture Imagery Program (NAIP) digital aerial photos as a base for the preliminary line work. Line work for this survey was digitized using ArcMap software. When the 2009 one-meter resolution NAIP aerial photography became available, this was used to review the digital land use data. 2. The western boundary of the survey area is defined by the western boundaries of DWR’s Detailed Analysis Units 235 and 237. The northern boundary of the survey area is defined in part by the county boundary and also by the northern boundaries of the following U.S. Geological Survey’s (U.S.G.S) 7.5’ quadrangles: Friant (U.S.G.S. No. 36119H6), Academy (U.S.G.S. No. 36119H5), Piedra (U.S.G.S. No. 36119G4) and Pine Flat Dam (U.S.G.S. No. 36119G3). The eastern boundary of the survey area is defined in part by the county boundary and also by the eastern boundaries of the following quadrangles: Academy (U.S.G.S. No. 36119H5), Pine Flat Dam (U.S.G.S. No. 36119G3) and Orange Cove North (U.S.G.S. No. 36119F3). The southern boundary of the survey area is defined by the county boundary. 3. Digital aerial photographs and land use field boundaries were copied onto laptop computers for field data collection. The staff took these laptops into the field and virtually all areas were visited to positively identify the agricultural land uses. Land use codes were digitized directly into the laptop computers using ArcMap software using a standardized digitizing process. Some staff took printed aerial photos into the field instead of laptops and wrote land use codes directly onto these photo field sheets. Attributes for these areas were digitized later in the office. The field visits occurred between July 2009 and January 2010. Urban areas were primarily mapped by photo interpretation. Sources of irrigation water were not mapped in this survey. 4. Shapefiles of the field boundary lines and point attributes of the survey data were brought into ARCINFO. Both quadrangle and survey-wide polygon shapefiles were created, and underwent quality checks. 5. Winter grain fields were mapped using an analysis of Landsat 5 imagery. Two major assumptions in the analysis were that 1.) Winter grain was grown on some of the fields where corn, sudan or tomatoes were grown during the summer or where fields were fallow during the summer. 2.) For the fields listed above, we assumed that fields with high winter canopy cover were grain fields. To detect the winter grain fields of eastern Fresno County for the 2009 land use survey, corn fields were queried from the initial shapefile of the land use survey and classified using Landsat 5 imagery. The corn field polygons were buffered in 30 meters to reduce edge effects on the classification. The buffering eliminated some of the smaller fields leaving 798 fields to be classified. The Landsat 5 image acquired on 04/23/2009 was selected as the most appropriate for mapping grain for this survey. Approximately 10 percent of the corn fields were non-randomly selected to represent winter grain and fallow fields. Using a false color infrared display, bright red fields were selected to represent grain and light blue (non-red) fields were selected to represent fallow fields. Using the Hawth’s tools function, the selected fields were randomly divided into training (60%) and accuracy assessment (40%) categories. The polygons were then converted into raster format from vector format. Using ERDAS Imagine, the raster files were used to mask the Landsat 5 image and create two subset Landsat images representing training fields only and training plus accuracy assessment fields. eCognition Developer version 8.0 software was used with the Landsat image of training fields to segment each field into smaller signature areas. Polygons representing these signature areas were exported from eCognition Developer and the attributes of grain or fallow were added to these polygons. Spectral signatures based upon Landsat 5 bands 1,2,3,4,5, and 7 were created using ERDAS Imagine 2010. After associating the signatures with the image of training and accuracy assessment fields combined, a supervised classification was performed using the maximum likelihood parametric rule to classify each pixel. Zonal attributes of the fields were calculated using the recoded image. Based on the zonal attribute plurality, fields were classified as either winter grain or winter fallow. When there were no errors in the identification of “grain” and “fallow” fields in the fields reserved for accuracy assessment, a supervised classification was performed on the Landsat pixels representing all summer corn fields. Landsat images of each classified corn field were visually inspected in ArcMap to determine the reasonableness of the classification results. In addition to the Landsat 5 scene acquired on 04/23/2009, scenes acquired on 08/10/2008, 11/14/2008, 03/06/2009, 03/22/2009, 04/07/2009, 05/09/2009, 05/25/2009 and 06/26/2009 were used for the visual review of the results. Using the above methods, 660 fields were identified as winter grain. In a second process, polygons representing 315 fields that had initially been mapped as fallow, sudan or tomatoes during the 2009 summer field work were selected from the original land use survey shapefile. These were combined with the polygons representing the previously selected training fields. The polygons were converted from vector to raster format. The resulting raster file was used to mask the April 23, 2009 Landsat 5 image using ERDAS Imagine to produce a subset image. This new image was associated with the signatures previously developed to classify winter grain fields, and a supervised classification of each pixel was performed using the maximum likelihood parametric rule. After recoding, zonal attributes were calculated for each polygon. Based on the plurality calculated for each field, fields were identified as either grain or fallow for the winter season. Polygons identified as grain fields were individually inspected in ArcMap to assure the reasonableness of the classification results. Using the above methods, 67 fields were identified as winter grain. Polygons representing all winter grain crops identified by classifying the Landsat 5 images were merged together. The original land use shapefile was updated by adding grain as a first crop to the selected polygons and moving the summer crop into the set of cells that represent a second crop. All field boundary changes were incorporated into the original shapefile. The

  5. c

    i15 LandUse Fresno2000

    • gis.data.cnra.ca.gov
    • data.ca.gov
    • +4more
    Updated Aug 1, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    gis_admin@water.ca.gov_DWR (2022). i15 LandUse Fresno2000 [Dataset]. https://gis.data.cnra.ca.gov/datasets/c76419442b054e1b942eb1ed786af0f3
    Explore at:
    Dataset updated
    Aug 1, 2022
    Dataset authored and provided by
    gis_admin@water.ca.gov_DWR
    Area covered
    Description

    The 2000 Fresno 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 San Joaquin District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and San Joaquin District. The finalized data include a shapefile of central and western Fresno County (land use vector data) and JPG files (raster data from aerial imagery). Important Points about Using this Data Set: 1. The land use boundaries were either drawn on-screen using developed photoquads, or 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 the 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. If the data is compared to the previous digital survey (i.e. the two coverages intersected for change detection determination) there will be land use changes that may be unexpected. The linework was created independently, so even if a field’s physical boundary hasn’t changed between surveys, the lines may differ due to difference in digitizing. Numerous thin polygons (with very little area) will result. A result could be UV1 (paved roads) to F1 (cotton). In reality, paved roads are not converted to cotton fields, but these small polygons would be created due to the differences in digitizing the linework for each survey. Additionally, this kind of comparison may yield polygons of significant size with unexpected changes. These changes will almost always involve non-cropped land, mainly U (urban), UR1 (single family homes on 1 – 5 acres), UV (urban vacant), NV (native vegetation), and I1 (land not cropped that year, but cropped within the past three years). The unexpected results (such as U to NV, or UR1 to NV) occur mainly because of interpretation of those non-cropped land uses with aerial imagery. Newer surveys or well funded surveys have had the advantage of using improved quality (higher resolution) imagery or additional labor, where more accurate identification of land use is possible, and more accurate linework is created. For example, an older survey may have a large polygon identified as UR, where the actual land use was a mixture of houses and vacant land. A newer survey may have, for that same area, delineated separately those land uses into smaller polygons. The result of an intersection would include changes from UR to UV (which is normally an unlikely change). It is important to understand that the main purpose of DWR performing land use surveys is to aid in development of agricultural water use data. Thus, given our goals and budget, our emphasis is on obtaining accurate agricultural land uses with less emphasis on obtaining accurate non-agricultural land uses (urban and native areas). 5. Water source information was not collected for this survey. 6. Not all land use codes will be represented in the survey.

  6. c

    i15 LandUse Fresno1994

    • gis.data.cnra.ca.gov
    • data.ca.gov
    • +6more
    Updated Nov 17, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    gis_admin@water.ca.gov_DWR (2022). i15 LandUse Fresno1994 [Dataset]. https://gis.data.cnra.ca.gov/datasets/c4bc8843dd824a1aa44792e73ad25fa0
    Explore at:
    Dataset updated
    Nov 17, 2022
    Dataset authored and provided by
    gis_admin@water.ca.gov_DWR
    Area covered
    Description

    The 1994 Fresno 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 San Joaquin District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and San Joaquin 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. Water source and irrigation method information was not collected for this survey. 5. 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.

  7. County Land Use Surveys

    • data.cnra.ca.gov
    • data.ca.gov
    • +2more
    zip
    Updated Aug 21, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    California Department of Water Resources (2024). County Land Use Surveys [Dataset]. https://data.cnra.ca.gov/dataset/county-land-use-surveys
    Explore at:
    zip(2315694), zip(21496454), zip(3918753), zip(16805189), zip(1666296), zip(464095), zip(6621547), zip(1200375), zip(983808), zip(1605640), zip(28962), zip(1747606), zip(2793798), zip(1269963), zip(29307), zip(999421), zip(8492130), zip(1286265), zip(1570103), zip(18151216), zip(1220622), zip(1703087), zip(4472090), zip(1507745), zip(867615), zip(1307710), zip(3652530), zip(1794395), zip(4292237), zip(3255617), zip(19017613), zip(7565044), zip(1873726), zip(2839252), zip(9769951), zip(2982393), zip(10213014), zip(526434), zip(23687041), zip(4513350), zip(2219775), zip(1446531), zip(4447997), zip(1080894), zip(14074588), zip(3737394), zip(445030), zip(1256496), zip(826916), zip(6165331), zip(15423139), zip(646287), zip(23650932), zip(217182), zip(2143698), zip(1955626), zip(3221490), zip(4816590), zip(2587966), zip(2809264), zip(378720), zip(2605159), zip(1321110), zip(2654105), zip(7774965), zip(1604050), zip(9090270), zip(12729609), zip(1093467), zip(2600224), zip(3980836), zip(10203106), zip(2303263), zip(5129271), zip(29824), zip(1567734), zip(1004916), zip(698628), zip(10835478), zip(318787), zip(1887064), zip(8653870), zip(1200935), zip(18806631), zip(1335326), zip(2521283), zip(1149952), zip(3332579), zip(14077924), zip(2199892), zip(3169665), zip(2059891), zip(3703588), zip(1814126), zip(1251089), zip(1503509), zip(6705586), zip(14838420), zip(2192148), zip(1310666), zip(29308), zip(383970), zip(23800505), zip(1257450), zip(1936637), zip(921279), zip(33757424), zip(3104964), zip(3530243), zip(2254067), zip(10657157), zip(7984506), zip(1750733), zip(11165233), zip(738847), zip(15069648), zip(1157418), zip(3794407), zip(5734228), zip(26367433), zip(4786086), zip(1956161), zip(6986883), zip(14780550), zip(29481), zip(6122568), zip(1310201), zip(1393314), zip(3843140), zip(3665014), zip(1602547), zip(10317706), zip(8366319), zip(944517), zip(968729), zip(21073906), zip(819268), zip(4679451), zip(2042540), zip(1275654), zip(1011840), zip(6243794), zip(3471267), zip(884368), zip(851266), zip(2948512), zip(2619215), zip(7340471), zip(983951), zip(3920963), zip(1374839), zip(629138), zip(2634495), zip(3670681), zip(938390), zip(278580), zip(5710414), zip(2443949), zip(304772), zip(519308), zip(22855), zip(1166127), zip(18082167), zip(6905359), zip(1261220), zip(3023928), zip(1789302), zip(2673855), zip(1306121), zip(7277559), zip(1266931), zip(3333145), zip(11381247), zip(3322418), zip(1543314), zip(518868), zip(9657647), zip(15272771), zip(10426348), zip(6611222), zip(4983522), zip(6604964), zip(1592668), zip(1434630), zip(2753666), zip(910152), zip(753428), zip(834553), zip(4410828), zip(3309082), zip(375661), zip(2825588), zip(2452088), zip(2054143), zip(1049041), zip(2084853), zip(987579), zip(7616495), zip(10604183), zip(1723341), zip(7853706), zip(6196257), zip(1996545), zip(5383870), zip(4325007), zip(40382675), zip(1219016), zip(2972655), zip(24443249), zip(694815), zip(1193639), zip(1355782), zip(1624192), zip(7127940), zip(504256), zip(559980), zip(3772537), zip(1876561), zip(2765379), zip(3136735)Available download formats
    Dataset updated
    Aug 21, 2024
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Description

    This is collection of DWR County Land Use Surveys. You may scroll the list below to download any individual survey of interest. Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer. For Statewide Crop Mapping follow the link below : https://data.cnra.ca.gov/dataset/statewide-crop-mapping For Region Land Use Surveys follow link below: https://data.cnra.ca.gov/dataset/region-land-use-surveys Questions about the survey data may be directed to Landuse@water.ca.gov.

  8. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
City of Fresno, California City Limits [Dataset]. https://koordinates.com/layer/96890-city-of-fresno-california-city-limits/
Organization logo

City of Fresno, California City Limits

Explore at:
shapefile, mapinfo tab, geodatabase, dwg, geopackage / sqlite, mapinfo mif, kml, pdf, csvAvailable download formats
Dataset updated
Feb 26, 2024
Dataset provided by
City of Fresno
Authors
City of Fresno, California
Area covered
Description

Vector polygon map data of city limits from Fresno, California containing 1 feature.

City limits GIS (Geographic Information System) data provides valuable information about the boundaries of a city, which is crucial for various planning and decision-making processes. Urban planners and government officials use this data to understand the extent of their jurisdiction and to make informed decisions regarding zoning, land use, and infrastructure development within the city limits.

By overlaying city limits GIS data with other layers such as population density, land parcels, and environmental features, planners can analyze spatial patterns and identify areas for growth, conservation, or redevelopment. This data also aids in emergency management by defining the areas of responsibility for different emergency services, helping to streamline response efforts during crises..

This city limits data is available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Search
Clear search
Close search
Google apps
Main menu