The Digital Geologic-GIS Map of Guadalupe Mountains National Park and Vicinity, Texas is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (gumo_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (gumo_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (gumo_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (gumo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (gumo_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (gumo_geology_metadata_faq.pdf). Please read the gumo_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: New Mexico Bureau of Geology and Mineral Resources. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gumo_geology_metadata.txt or gumo_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

description: The Digital Geologic Map of Guadalupe Mountains National Park and Vicinity, Texas is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcView 3.X legend (.AVL) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GIS-Geology Coverage/Shapefile Data Model (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 13N. That data is within the area of interest of Guadalupe Mountains National Park.; abstract: The Digital Geologic Map of Guadalupe Mountains National Park and Vicinity, Texas is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcView 3.X legend (.AVL) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GIS-Geology Coverage/Shapefile Data Model (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 13N. That data is within the area of interest of Guadalupe Mountains National Park.

The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data 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.

Geospatial data about San Antonio, Texas Schools. Export to CAD, GIS, PDF, CSV and access via API.

Geospatial data about San Antonio, Texas Street Centerlines. Export to CAD, GIS, PDF, CSV and access via API.

These ETJ boundaries are updated an average of 1-3 business days after an ordinance has been passed by City Council that warrants an ETJ boundary change. This layer was originally created and maintained by a 3rd party consulting firm, but is currently maintained and updated by the City of Cibolo GIS team. Boundaries are drawn along parcel boundaries which are maintained by the Guadalupe County Appraisal District, or following metes and bounds written by a professional engineer. For reference only. Projected Coordinate System: NAD_1983_StatePlane_Texas_South_Central_FIPS_4204_Feet

This layer depicts the AAMPO study area which includes: Bexar County, Comal County, Guadalupe County, and a portion of Kendall County.

BAARI (Bay Area Aquatic Resource Inventory) was established to meet regional needs for wetlands and stream monitoring. One primary objective was to apply standardized monitoring tools to ensure data comparability and consistent, documented quality. These data help agencies and organizations assess the extent and condition of wetlands in local watersheds and identify and prioritize opportunities for ecological restoration and enhancement in a watershed context.BackgroundBAARI data is part of the Wetland and Riparian Area Monitoring Plan (WRAMP), which consists of a 1-2-3 level monitoring framework. This allows assessment of wetlands at two scales: landscape and highly localized. BAARI is Level 1 of this framework, developed for landscape level analyses of wetland extent, distribution and abundance. Geographic information systems (GIS) and remote sensing are used to map and create inventories of existing wetlands (both modern and historical). These inventories quantify the extent of wetland habitats and projects, and are used for landscape profiles of wetlands at the state, regional, watershed, and local scales. Level 2 entails rapid field assessment of wetland health or ecological condition. In California the California Rapid Assessment Method (CRAM) is a diagnostic tool that two or more trained practitioners can use to assess the condition of a wetland or riparian site in one half day or less using visual indicators in the field. Level 3 monitoring entails intensive sampling of ecological function or specific aspects of wetland condition. These assessments are intensive quantitative measurements of condition, stress, or cause-and-effect relationships. A Level 3 assessment is an in-depth study of a particular attribute of wetland health such as water quality, fish habitat, bird populations, vegetative cover and diversity, or physical processes. Level 3 monitoring can describe the performance of specific ecological functions at the site scale. Information on the WRAMP is available at http://www.mywaterquality.ca.gov/eco_health/wetlands/condition/wramp_toolkit.shtmlMore information on BAARI can be found online at: http://www.sfei.org/BAARI. Description of Updates in Version 2Local experts provided advice on and reviewed BAARIâ??s stream, wetland and riparian GIS layers in specific locations to help update the data as conditions in the field changed and/or to increase its accuracy and detail. Improving the accuracy and detail of BAARI improves the base maps for all monitoring and assessment efforts to understand the distribution, amount and ecological condition of Bay Area aquatic resources. The following updates were made to BAARI under this project:The Santa Clara Valley Water District (SCVWD) provided their GIS based stream data for the Guadalupe River Watershed. SFEIâ??s GIS team incorporated parts of the SCVWD dataset into BAARI to improve the accuracy and detail of the BAARI stream layer with the Guadalupe River watershed. Updates included features such as underground connectors between the upper and lower watershed reaches, and enhanced details of portions of the upper watershed. Watershed Sciences developed six hand-drawn maps showing field verified ditch locations circa 2006. Those data were used in developing the sediment TMDL for the watershed. Watershed sciences provided those maps to SFEIâ??s GIS team and worked with them to compare the remotely sensed stream and ditch locations in the BAARI data set (based on 2009 NAIP imagery) to her maps and other data (including Google Earth using multiple image dates). Based on this careful comparative process, about 500 linear updates were made to the BAARI stream layer for the Sonoma Creek watershed with the data source attributed to Laurel Collinsâ?? maps. SFEI staff added stream names for the whole BAARI dataset (Bay Area 9 counties, ocean shoreline, and Tomales Bay - 530 different names applied to more than 24000 stream segments).Additional corrections to wetland and stream presence, extent, and classification were appended to the dataset by SFEI staff where inaccuracies were identified based on local expertise of wetlands in the Bay Area.All BAARI updates were reviewed by a second GIS staff member to ensure that they were acceptable and followed BAARI mapping protocols. Description of Attribute Fields in BAARIBaylandsRestProj: restoration project associated with this wetland. This field has not been updated in version 2. Refer to http://www.EcoAtlas.org for current listings of ecological restoration projects. Source_Dat: source(s) from which the wetland polygon was digitized, or otherwise incorporated into BAARIWetlandTyp: Coded classification of the wetland type. Codes are defined on p5-6 of "BAARI Mapping Standards" Organization: organization that digitized the wetland polygonClickCode: simplification of the 'WetlandTyp' attribute used for map database queries in web mapping applications such as http://www.EcoAtlas.org. Refers to the standardized wetland classification system employed by the California Aquatic Resources Inventory (CARI). More information about CARI is available at http://www.sfei.org/it/gis/cari ClickLabel: verbal description of the ClickCode codeLegCode: further simplification of the 'WetlandTyp' attribute used in the legends of web mapping applications such as http://www.EcoAtlas.orgLegLabel: verbal description of the LegCode codeORIG_FID: unusedOpenWater: Open Water (1) or a wetland (0)TidRip: unusedGlobalID: Unique identifier, if one exists StreamsWetlandTyp: Coded classification of the stream type. Codes are defined on p9-10 of "BAARI Mapping Standards" Bayland: Identifies whether the feature falls within the historical extent of the Baylands (1) or not (0)Strahler: Strahler stream order of the stream segment.ClickCode: simplification of the 'WetlandTyp' attribute used for map database queries in web mapping applications such as http://www.EcoAtlas.orgClickLabel: verbal description of the ClickCode codeLegCode: further simplification of the 'WetlandTyp' attribute used in the legends of web mapping applications such as http://www.EcoAtlas.orgLegLabel: verbal description of the LegCode codeGlobalID: Unique identifier, if one exists (e.g. ReachCode attribute in NHD)IDNum: Numerical version of GlobalIDStreamName: the recognized Geographic Names Information System (GNIS) name of the streamSource_Dat: source(s) from which the segment was digitized, or otherwise incorporated into BAARI.Name_Source: source from which 'StreamName' was identifiedFNode: "From Node" used to determine stream flow directionTNode: "To Node" used to determine stream flow directionLegHeader: legend header used in the legends of web mapping applications such as http://www.EcoAtlas.orgTMDL_DATA: "Yes" value indicates TMDL data is available for this stream segment. Contact SFEI for information about integrating TMDL data with BAARIWetlands (Non-tidal)WetlandTyp: Coded classification of the wetland type. Codes are defined on p6-9 of "BAARI Mapping Standards" SourceData: source(s) from which the wetland polygon was digitized, or otherwise incorporated into BAARIOrganization: organization that digitized the wetland polygonClickCode: simplification of the 'WetlandTyp' attribute used for map database queries in web mapping applications such as http://www.EcoAtlas.orgClickLabel: verbal description of the ClickCode codeLegCode: further simplification of the 'WetlandTyp' attribute used in the legends of web mapping applications such as http://www.EcoAtlas.orgLegLabel: verbal description of the LegCode codeGlobalID: Unique identifier, if one exists

The Transportation Equity Map utilizes demographic data at the Census block group level to pinpoint areas of Environmental Justice (EJ) significance within the Alamo Area Metropolitan Planning Organization (AAMPO) Region. This geographical scope encompasses Bexar, Comal, Guadalupe counties, and a portion of Kendall County.EJ Areas are demarcated by block groups where either 50% or more of the population is classified as belonging to a minority group and/or where 19.87% of the population falls within the low-income bracket. The primary purpose of the Transportation Equity Map is to serve as a tool for identifying regions warranting further examination. It's essential to understand that the map is designed to prompt additional analysis and not intended as an exhaustive analysis in itself.Data sources for this project are drawn from the U.S. Census 2014-2018 American Community Survey (ACS) 5-Year Estimates. The methodology employed for defining the "Minority" category involves the summation of individuals identifying as Hispanic or Latino and those from non-Hispanic, non-Latino backgrounds who identify with minority race categories. "Low-income individuals" are those whose household income falls at or below 125% of the poverty level. Notably, the region's low-income population constitutes 19.87% of the total.The polygons featured in the Transportation Equity Map correspond to Census block groups. The data integrated into this layer has been compiled from the American Community Survey (ACS) 2014-2018 5-year estimates tables.