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TwitterThe Geodatabase to Shapefile Warning Tool examines feature classes in input file geodatabases for characteristics and data that would be lost or altered if it were transformed into a shapefile. Checks include:
1) large files (feature classes with more than 255 fields or over 2GB), 2) field names longer than 10 characters
string fields longer than 254 characters, 3) date fields with time values 4) NULL values, 5) BLOB, guid, global id, and raster field types, 6) attribute domains or subtypes, and 7) annotation or topology
The results of this inspection are written to a text file ("warning_report_[geodatabase_name]") in the directory where the geodatabase is located. A section at the top provides a list of feature classes and information about the geodatabase as a whole. The report has a section for each valid feature class that returned a warning, with a summary of possible warnings and then more details about issues found.
The tool can process multiple file geodatabases at once. A separate text file report will be created for each geodatabase. The toolbox was created using ArcGIS Pro 3.7.11.
For more information about this and other related tools, explore the Geospatial Data Curation toolkit
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TwitterThe TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independentdata set, or they can be combined to cover the entire nation. Linear Water Features includes single-line drainage water features and artificial path features that run through double-line drainage features such as rivers and streams, and serve as a linear representation of these features. The artificial path features may correspond to those in the USGS National Hydrographic Dataset (NHD). However, in many cases the features do not match NHD equivalent feature and will not carry the NHD metadata codes. These features have a MAF/TIGER Feature Classification Code (MTFCC) beginning with an "H" to indicate the super class of Hydrographic Features.
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Twittersocial system, socio-economic resources, justice, BES, Environmental disamentities, Environmental Justice, Zoning Board of Appeals
Summary
For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities.
Description
This feature class layer is a point dataset of authorizing ordinances from the Baltimore City Council and Mayor from 1930 until 1999 concerning identified environmental disamentities. The data was gathered from records from the City Council since 1930 relating to decisions concerning land-uses considered to be environmental disamentities and is to be used to examine environmental injustices involving low income/minority communities in Baltimore. To examine if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the Ordinance_master dataset and using ISTAR 2004 data in conjunction with Baltimore parcel data. The Ordinance_ID number associated with each point relates to its appeal number from the City Council. Multiple points on the data layer have the same Ordinance_ID. This point layer can be joined with the Ordinance_master data layer based on the field "Ordinance_ID" and using the relationship "Ordinance_point_relationship".
Credits
UVM Spatial Analysis Lab
Use limitations
None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data.
Extent
West -76.707701 East -76.526991
North 39.371885 South 39.200794
This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.
The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.
The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.
Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.
This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.
The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.
The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.
Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.
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TwitterThe mission of the USGS Gap Analysis Program (GAP) is providing state, regional and national assessments of the conservation status of native vertebrate species and natural land cover types and facilitating the application of this information to land management activities. The PAD-US geodatabase is required to organize and assess the management status (i.e. apply GAP Status Codes) of elements of biodiversity protection. The goal of GAP is to 'keep common species common' by identifying species and plant communities not adequately represented in existing conservation lands. Common species are those not currently threatened with extinction. By identifying their habitats, gap analysis gives land managers and policy makers the information they need to make better-informed decisions when identifying priority areas for conservation. In cooperation with UNEP-World Conservation Monitoring Centre, GAP ensures PAD-US also supports global analyses to inform policy decisions by maintaining World Database for Protected Areas (WDPA) Site Codes and data for International Union for the Conservation of Nature (IUCN) categorized protected areas in the United States. GAP seeks to increase the efficiency and accuracy of PAD-US updates by leveraging resources in protected areas data aggregation and maintenance as described in "A Map of the Future", published following the PAD-US Design Project (July, 2009). While PAD-US was originally developed to support the GAP Mission stated above, the dataset is robust and has been expanded to support the conservation, recreation and public health communities as well. Additional applications become apparent over time.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains the recreation opportunity information that the Forest Service collects through the Recreation Portal and shares with the public on https://www.recreation.gov, the Forest Service World Wide Web pages (https://www.fs.usda.gov/) and the Interactive Visitor Map. This recreation data contains detailed descriptions of recreational sites, areas, activities & facilities. This published dataset consists of one point feature class for recreational areas, one spatial view and three related tables such as activities, facilities & rec area advisories. The purpose of each related table is described belowRECAREAACTIVITIES: This related table contains information about the activities that are associated with the rec area.RECAREAFACILITIES: This related table contains information about the amenities that are associated with the rec area.RECAREAADVISORIES: This table contains events, news, alerts and warnings that are associated with the rec area.RECAREAACTIVITIES_V: This spatial view/feature class is generated by joining the RECAREAACTIVITIES table to the RECREATION OPPORTUNITIES Feature Class. Please note that the RECAREAID is the unique identifier present in point feature class and in the related tables as well. The RECAREAID is used as foreign key to access relate records.This published data is updated nightly from an XML feed maintained by the CIO Rec Portal team. This data is intended for public use and distribution. MetadataThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.
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TwitterThe New Hampshire Hydrography Dataset (NHHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the state's surface water drainage system. The NHHD, developed at 1:24,000 scale, is an extract from the high-resolution National Hydrography Dataset (NHD) housed at the US Geological Survey. The NHHD Shapefile Extract contains the NHDFlowline, NHDWaterbody and NHDArea feature classes from the original NHHD geodatabase. These shapefiles cover the extent of the sixteen cataloging units that intersect the State of NH, and contain reach codes for networked features, stream order, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the the Atlantic Ocean. However, because this data is no longer contained in the original geodatabase, the networking capabilities of the NHDFlowline has been lost.
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TwitterNotice: this is not the latest Heat Island Anomalies image service.This layer contains the relative degrees Fahrenheit difference between any given pixel and the mean heat value for the city in which it is located, for every city in the contiguous United States, Alaska, Hawaii, and Puerto Rico. This 30-meter raster was derived from Landsat 8 imagery band 10 (ground-level thermal sensor) from the summer of 2022, with patching from summer of 2021 where necessary.Federal statistics over a 30-year period show extreme heat is the leading cause of weather-related deaths in the United States. Extreme heat exacerbated by urban heat islands can lead to increased respiratory difficulties, heat exhaustion, and heat stroke. These heat impacts significantly affect the most vulnerable—children, the elderly, and those with preexisting conditions.The purpose of this layer is to show where certain areas of cities are hotter or cooler than the average temperature for that same city as a whole. This dataset represents a snapshot in time. It will be updated yearly, but is static between updates. It does not take into account changes in heat during a single day, for example, from building shadows moving. The thermal readings detected by the Landsat 8 sensor are surface-level, whether that surface is the ground or the top of a building. Although there is strong correlation between surface temperature and air temperature, they are not the same. We believe that this is useful at the national level, and for cities that don’t have the ability to conduct their own hyper local temperature survey. Where local data is available, it may be more accurate than this dataset. Dataset SummaryThis dataset was developed using proprietary Python code developed at The Trust for Public Land, running on the Descartes Labs platform through the Descartes Labs API for Python. The Descartes Labs platform allows for extremely fast retrieval and processing of imagery, which makes it possible to produce heat island data for all cities in the United States in a relatively short amount of time.In order to click on the image service and see the raw pixel values in a map viewer, you must be signed in to ArcGIS Online, then Enable Pop-Ups and Configure Pop-Ups.Using the Urban Heat Island (UHI) Image ServicesThe data is made available as an image service. There is a processing template applied that supplies the yellow-to-red or blue-to-red color ramp, but once this processing template is removed (you can do this in ArcGIS Pro or ArcGIS Desktop, or in QGIS), the actual data values come through the service and can be used directly in a geoprocessing tool (for example, to extract an area of interest). Following are instructions for doing this in Pro.In ArcGIS Pro, in a Map view, in the Catalog window, click on Portal. In the Portal window, click on the far-right icon representing Living Atlas. Search on the acronyms “tpl” and “uhi”. The results returned will be the UHI image services. Right click on a result and select “Add to current map” from the context menu. When the image service is added to the map, right-click on it in the map view, and select Properties. In the Properties window, select Processing Templates. On the drop-down menu at the top of the window, the default Processing Template is either a yellow-to-red ramp or a blue-to-red ramp. Click the drop-down, and select “None”, then “OK”. Now you will have the actual pixel values displayed in the map, and available to any geoprocessing tool that takes a raster as input. Below is a screenshot of ArcGIS Pro with a UHI image service loaded, color ramp removed, and symbology changed back to a yellow-to-red ramp (a classified renderer can also be used): A typical operation at this point is to clip out your area of interest. To do this, add your polygon shapefile or feature class to the map view, and use the Clip Raster tool to export your area of interest as a geoTIFF raster (file extension ".tif"). In the environments tab for the Clip Raster tool, click the dropdown for "Extent" and select "Same as Layer:", and select the name of your polygon. If you then need to convert the output raster to a polygon shapefile or feature class, run the Raster to Polygon tool, and select "Value" as the field.Other Sources of Heat Island InformationPlease see these websites for valuable information on heat islands and to learn about exciting new heat island research being led by scientists across the country:EPA’s Heat Island Resource CenterDr. Ladd Keith, University of ArizonaDr. Ben McMahan, University of Arizona Dr. Jeremy Hoffman, Science Museum of Virginia Dr. Hunter Jones, NOAA Daphne Lundi, Senior Policy Advisor, NYC Mayor's Office of Recovery and ResiliencyDisclaimer/FeedbackWith nearly 14,000 cities represented, checking each city's heat island raster for quality assurance would be prohibitively time-consuming, so The Trust for Public Land checked a statistically significant sample size for data quality. The sample passed all quality checks, with about 98.5% of the output cities error-free, but there could be instances where the user finds errors in the data. These errors will most likely take the form of a line of discontinuity where there is no city boundary; this type of error is caused by large temperature differences in two adjacent Landsat scenes, so the discontinuity occurs along scene boundaries (see figure below). The Trust for Public Land would appreciate feedback on these errors so that version 2 of the national UHI dataset can be improved. Contact Dale.Watt@tpl.org with feedback.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The New England Protected Open Space dataset maintained by Harvard Forest is a compilation of existing open space datasets in the New England region including The Nature Conservancy's Secured Areas, National Conservation Easement Database, Protected Areas Database of the U.S., and data provided by states and land trusts.
Data are provided with the full attribute table and with minimal attribute table that keeps only the most essential fields (these have "_min" in the file name).
The data with full and minimal attribute tables are available as file geodatabase feature classes (POS.gdb.zip) and shapefiles (POSv1_1_April2021.zip, POSv1_1_April2021_min.zip).
It is recommended to use the geodatabase feature class if you have access to Esri products, as the POS field names are all longer than 10 characters and are truncated in the shapefile versions.
Version 1.1 is a partial update, rather than an exhaustive update using all data sources - please read the metadata for more details!
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File Geodatabase Feature Class
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Tags
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Summary
There is no summary for this item.
Description
MD Property View 2003 A&T Database. For more information on the A&T Database refer to the enclosed documentation. This layer was edited to remove spatial outliers in the A&T Database. Spatial outliers are those points that were not geocoded and as a result fell outside of the Baltimore City Boundary; 416 spatial outliers were removed from this layer. The field BLOCKLOT2 can be used to join this layer with the Baltimore City parcel layer.
Credits
There are no credits for this item.
Use limitations
There are no access and use limitations for this item.
Extent
West -76.713418 East -76.526031
North 39.374429 South 39.197452
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File Geodatabase Feature Class
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Tags
Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation
Summary
Serves as a basis for performing various analyses based on parcel data.
Description
Assessments & Taxation (A&T) Database from MD Property View 2004 for Harford County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab.
It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields).
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TwitterThe New Hampshire Hydrography Dataset (NHHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the state's surface water drainage system. The NHHD, developed at 1:24,000 scale, is an extract from the high-resolution National Hydrography Dataset (NHD) housed at the US Geological Survey.The NHHD Shapefile Extract contains the NHDFlowline, NHDWaterbody and NHDArea feature classes from the original NHHD geodatabase. These shapefiles cover the extent of the sixteen cataloging units that intersect the State of NH, and contain reach codes for networked features, stream order, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the the Atlantic Ocean. However, because this data is no longer contained in the original geodatabase, the networking capabilities of the NHDFlowline has been lost. This dataset contains data published by USGS in April 2019.
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File Geodatabase Feature Class
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Tags
Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation
Summary
Serves as a basis for performing various analyses based on parcel data.
Description
Assessments & Taxation (A&T) Database from MD Property View 2004 for Harford County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab.
It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields).
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File Geodatabase Feature Class
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Tags
There are no tags for this item.
Summary
There is no summary for this item.
Description
MD Property View 2003 A&T Database. For more information on the A&T Database refer to the enclosed documentation. This layer was edited to remove spatial outliers in the A&T Database. Spatial outliers are those points that were not geocoded and as a result fell outside of the Baltimore City Boundary; 416 spatial outliers were removed from this layer. The field BLOCKLOT2 can be used to join this layer with the Baltimore City parcel layer.
Credits
There are no credits for this item.
Use limitations
There are no access and use limitations for this item.
Extent
West -76.713418 East -76.526031
North 39.374429 South 39.197452
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
The US Department of Homeland Security, Homeland Infrastructure Foundations - Level Data (HIFLD) provided geographic shapefiles for United States hospitals. This feature class/shapefile contains locations of Hospitals for US territories of Puerto Rico. The dataset only includes hospital facilities based on data acquired from various state departments or federal sources which has been referenced in the SOURCE field. Hospital facilities which do not occur in these sources will be not present in the database. The source data was available in a variety of formats (pdfs, tables, webpages, etc.) which was cleaned and geocoded and then converted into a spatial database. The database does not contain nursing homes or health centers. Hospitals have been categorized into children, chronic disease, critical access, general acute care, long term care, military, psychiatric, rehabilitation, special, and women based on the range of the available values from the various sources after removing similarities. This feature class/shapefile contains Hospitals derived from various sources (refer SOURCE field) for the Homeland Infrastructure Foundation-Level Data (HIFLD) database. This feature class/shape file has a one-to-many relationship class (HospitalsToTrauma) relate with the “Trauma_Levels” table. This table captures the relationship between Hospitals and the state trauma level designations. “Hospitals” is the origin using STATE as the primary key. “Trauma_Levels” table is the destination using STATE as the foreign key. This dataset is based on information from the period 20120605-20170329.
The complete dataset for 50 States can be obtained from the HIFLD website: https://hifld-dhs-gii.opendata.arcgis.com/datasets/5eafb083e43a457b9810c36b2414d3d3_0 The shape file metadata can be obtained from: https://www.arcgis.com/sharing/rest/content/items/5eafb083e43a457b9810c36b2414d3d3/info/metadata/metadata.xml?format=default&output=html
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TwitterThis resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads shapefile includes all features within the MTS Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in the MTS that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.
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File Geodatabase Feature Class
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Tags
Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation
Summary
Serves as a basis for performing various analyses based on parcel data.
Description
Assessments & Taxation (A&T) Database from MD Property View 2004 for Anne Arundel County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab.
It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields).
A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 897 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords."
Credits
Maryland Department of Planning
Use limitations
BES use only.
Extent
West -76.838738 East -76.395283
North 39.238726 South 38.708588
Scale Range
There is no scale range for this item.
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TwitterEcoregions denote areas of general similarity in ecosystems and in the type quality, and quantity of environmental resources. The ecoregions shown here have been derived from the "Level III Ecoregions of the continental United States" GIS coverage created by the US Environmental Protection Agency. The useco polygon was converted to a shapefile in ArcToolbox using the "Feature Class To Shapefile" tool. The shapefile was reprojected from Albers Conical Equal Area to Oregon Lambert. The shapefile was clipped to the boundary of Oregon.
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TwitterBrownfields_BACI
File Geodatabase Feature Class
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Tags
Biophysical Resources, Air, Land, Water, BES, Brownfields, Pollution
Summary
BES Analysis
Description
Brownfield parcels in Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This dataset appears to have a high degree of positional accuracy based on comparisons with high resolution imagery.
Credits
Maryland Department of the Environment
Use limitations
BES research only.
Extent
West -76.661468 East -76.530941
North 39.334224 South 39.235433
Scale Range
There is no scale range for this item.
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TwitterThis data release contains a digital geospatial dataset generated by the U.S. Geological Survey under a cooperative agreement with the Water Replenishment District of Southern California to characterize the three-dimensional hydrogeology of the Los Angeles Coastal Plain. The geospatial dataset covers about 580 square miles of the largest coastal plain of southern California and contains the unit tops and extents of the three-dimensional chronostratigraphic model (3D CM) and supporting well data. The 3D CM was constructed in EarthVision using methods described in Development of a Groundwater-Simulation Model in the Los Angeles Coastal Plain, Los Angeles County, California; Chapter B (Ponti and Martin, 2021). Specifically, the geospatial database contains (1) a shapefile (point feature class) for the altitude of the top of each chronostratigraphic unit where it exists on a spatial grid in the 3D CM; and (2) a shapefile (point feature class) of wells used to construct the 3D CM including their corresponding name, _location, source of well data, and depths of stratigraphic picks.
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TwitterThis polygon feature class is a data set compiled by DWR employees in 2013 and represents the statewide Groundwater Management Plan (Plan) boundaries predating the Sustainable Groundwater Management Act (SGMA) requirements. Each polygon represents the area in which a Plan is to be implemented. The boundaries were provided to DWR by the affiliated public agency and compiled into a single statewide data set. Spatial plan boundaries were provided by agencies to DWR either via shapefiles or PDFs. PDFs were georeferenced and turned into GIS layers by DWR employees. This feature class is for legacy purposes only and will not be changed nor updated. It needs to be memorialized for spatial coverage of Groundwater Management Plans prior to SGMA and because SGMA only requires medium and high priority basins to have a Groundwater Sustainability Plan. The Plans outlined in this shapefile by medium and high priority basins are in effect until SGMA goes into effect. Some low and very low priority basins will likely use the existing plans to get funding for future basin management (since it is only voluntary for them to provide a Plan under SGMA, but they already have one in place). The data set is considered complete because of its legacy status. However, anyone using the data set will notice boundary inconsistencies, agency plan overlaps, mismatches, and other topology errors. The data set is based on boundary estimations and in the cases of medium and high priority basins will be outdated with in implementation of SGMA.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 3.1, dated September 11, 2019. This data set was not produced by DWR. Data were originally developed and supplied by each individual plan agency and compiled by DWR. 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.
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TwitterThe Geodatabase to Shapefile Warning Tool examines feature classes in input file geodatabases for characteristics and data that would be lost or altered if it were transformed into a shapefile. Checks include:
1) large files (feature classes with more than 255 fields or over 2GB), 2) field names longer than 10 characters
string fields longer than 254 characters, 3) date fields with time values 4) NULL values, 5) BLOB, guid, global id, and raster field types, 6) attribute domains or subtypes, and 7) annotation or topology
The results of this inspection are written to a text file ("warning_report_[geodatabase_name]") in the directory where the geodatabase is located. A section at the top provides a list of feature classes and information about the geodatabase as a whole. The report has a section for each valid feature class that returned a warning, with a summary of possible warnings and then more details about issues found.
The tool can process multiple file geodatabases at once. A separate text file report will be created for each geodatabase. The toolbox was created using ArcGIS Pro 3.7.11.
For more information about this and other related tools, explore the Geospatial Data Curation toolkit