The Unpublished Digital Geologic-GIS Map of the Igo Quadrangle, California is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (igo_geology.gdb), a 10.1 ArcMap (.mxd) map document (igo_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (whis_geology_gis_readme.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (whis_geology_gis_readme.pdf). Please read the whis_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. 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). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (igo_geology_metadata.txt or igo_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 ArcGIS 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: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 10N. The data is within the area of interest of Whiskeytown National Recreation Area.

description: Seattle Parks and Recreation GIS Map Layer Shapefile - Adult Fitness Equipment Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/0; abstract: Seattle Parks and Recreation GIS Map Layer Shapefile - Adult Fitness Equipment Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/0

Open source GIS software available for download

The Unpublished Digital Geologic-GIS Map of the Valley Head Quadrangle, Alabama and Georgia is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (vahe_geology.gdb), a 10.1 ArcMap (.mxd) map document (vahe_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (liri_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (liri_geology_gis_readme.pdf). Please read the liri_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. 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). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Geological Survey of Alabama. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (vahe_geology_metadata.txt or vahe_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 ArcGIS 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: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 16N. The data is within the area of interest of Little River Canyon National Preserve.

The Digital Geologic Map of the Mathias Point Quadrangle, Maryland 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 ArcMap 9.1 layer (.LYR) 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 GRE Geology-GIS Geodatabase Data Model v. 1.3.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.htm). The GIS data is available as a 9.1 personal geodatabase (mapt_geology.mdb), 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 18N. That data is within the area of interest of Thomas Stone National Historic Site.

The Digital Geologic Map of the Pipe Spring Quadrangle, Arizona 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 12N. That data is within the area of interest of Pipe Spring National Monument.

Data record audit of feature classes within the MD iMAP spatial database.

The Digital Geologic Map (Surficial Map) of the Canyon Village Quadrangle, Yellowstone National Park, Wyoming 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 ArcMap 9.1 layer (.LYR) 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 GRE Geology-GIS Geodatabase Data Model v. 1.4. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.1 personal geodatabase (cnvi_geology.mdb), 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 12N. That data is within the area of interest of Yellowstone National Park.

The GIS HydroAtlas of Madagascar is the final output from the small hydro resource mapping component of the activity “ Renewable Energy Resource Mapping and Geospatial Planning – Madagascar” [Project ID: P145350]. You can find more information about the project here: https://www.esmap.org/re_mapping_madagascar Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP). For more information: Madagascar Small Hydro GIS Atlas, 2017, https://energydata.info/dataset/madagscar-small-hydro-gis-atlas-2017"

Detection loops in the management of the province of Utrecht. Because loops are sometimes under the pavement, they are no longer visible above ground, which is why they are opened up in the context of the WIBON.

Geoportal Podzemni spremnici Grada Zagreba. Podaci se na Portalu otvorenih podataka (data.zagreb.hr) ažuriraju u intervalu od 30 dana.

Investors are able to defer paying taxes on capital gains that are invested in Qualified Opportunity Funds that in turn are invested in distressed communities designated as Opportunity Zones by the governor of each state. Census tracts 86, 87, 90, 91, 92, 93, 94, 110.01, 111.01 and 118 have been designated by the Washington State Department of Commerce as Opportunity Zones. This layer dissolves the aforementioned Census Tracts.

POIs mit Bildern und ausführlichen Beschreibungen der UNESCO-Welterbestätten in Trier und Umgebung

This is a copy of the statewide Census Block Group GIS Tiger file. It is used to determine if a block group (BG) is DAC or not by adding ACS (American Community Survey) Median Household Income (MHI) data at the BG level. The IRWM web based DAC mapping tool uses this GIS layer. Every year this table gets updated after ACS publishes their updated MHI estimates. Created by joining 2018 DAC table to 2010 Block Group feature class. 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. Block Groups (BGs) are defined before tabulation block delineation and numbering, but are clusters of blocks within the same census tract that have the same first digit of their 4-digit census block number from the same decennial census. For example, Census 2000 tabulation blocks 3001, 3002, 3003,.., 3999 within Census 2000 tract 1210.02 are also within BG 3 within that census tract. Census 2000 BGs generally contained between 600 and 3,000 people, with an optimum size of 1,500 people. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated BGs only where the PSAP participant declined to delineate BGs or where the Census Bureau could not identify any local PSAP participant. A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within census tract. Within the standard census geographic hierarchy, BGs never cross county or census tract boundaries, but may cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. BGs have a valid code range of 0 through 9. BGs coded 0 were intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. For Census 2000, rather than extending a census tract boundary into the Great Lakes or out to the U.S. nautical three-mile limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore. The Census Bureau assigned a default census tract number of 0 and BG of 0 to these offshore, water-only areas not included in regularly numbered census tract areas.

Geoportal Polupodzemni spremnici Grada Zagreba. Podaci se na Portalu otvorenih podataka (data.zagreb.hr) ažuriraju u intervalu od 30 dana.

Neal Hot Springs-ESRI Geodatabase (ArcGeology v1.3): - Contains all the geologic map data, including faults, contacts, folds, unit polygons, and attitudes of strata and faults. - List of stratigraphic units and stratigraphic correlation diagram. - Three cross-sections. - Locations of production, injection, and exploration wells. - Locations of 40Ar/39Ar samples. - Location of XRF geochemical samples. - 3D model constructed with EarthVision using geologic map data, cross-sections, drill-hole data, and geophysics (model not in the ESRI geodatabase).

SUBSURFACE_RIGHTS_POLY: This theme portrays information related to the Public Land Survey System, and subsurface minerals of lands in the states of Oregon and Washington.

rechtskräftig seit: 15.01.2004

(Link to Metadata) This metadata applies to the following collection area(s): Eastern VT 2014 0.7m and related SLOPE datasets. Created using ArcGIS "SLOPE" command to produce change in elevation over the distance between the cell and its eight neighbors expressed in percent slope or percent grade, i.e., rise/run * 100. This metadata complies with the VT Geodata Portal format and applies to thematic layers with the same resolution (RESCLASS), e.g., 0p7m, 1m etc., and may include multiple data "collection" efforts. For the original vendor metadata containing specific details on each collections "point cloud" such as flight dates, nominal pulse spacing and RMSEz etc., see the "All Available Lidar" Product page: (http://vcgi.vermont.gov/data/products/ALL-LDR_MIX_LIDAR_STATE_ALL). For an overview of the "Vermont Lidar Initiative" please see "http://vcgi.vermont.gov/lidar".

Web-based GIS for spatiotemporal crop climate niche mapping Interactive Google Earth Engine Application—Version 2, July 2020 https://cropniche.cartoscience.com https://cartoscience.users.earthengine.app/view/crop-niche Google Earth Engine Code /* ---------------------------------------------------------------------------------------------------------------------- # CropSuit-GEE Authors: Brad G. Peter (bpeter@ua.edu), Joseph P. Messina, and Zihan Lin Organizations: BGP, JPM - University of Alabama; ZL - Michigan State University Last Modified: 06/28/2020 To cite this code use: Peter, B. G.; Messina, J. P.; Lin, Z., 2019, "Web-based GIS for spatiotemporal crop climate niche mapping", https://doi.org/10.7910/DVN/UFC6B5, Harvard Dataverse, V1 ------------------------------------------------------------------------------------------------------------------------- This is a Google Earth Engine crop climate suitability geocommunication and map export tool designed to support agronomic development and deployment of improved crop system technologies. This content is made possible by the support of the American People provided to the Feed the Future Innovation Lab for Sustainable Intensification through the United States Agency for International Development (USAID). The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government. Program activities are funded by USAID under Cooperative Agreement No. AID-OAA-L-14-00006. ------------------------------------------------------------------------------------------------------------------------- Summarization of input options: There are 14 user options available. The first is a country of interest selection using a 2-digit FIPS code (link available below). This selection is used to produce a rectangular bounding box for export; however, other geometries can be selected with minimal modification to the code. Options 2 and 3 specify the complete temporal range for aggregation (averaged across seasons; single seasons may also be selected). Options 4–7 specify the growing season for calculating total seasonal rainfall and average season temperatures and NDVI (NDVI is for export only and is not used in suitability determination). Options 8–11 specify the climate parameters for the crop of interest (rainfall and temperature max/min). Option 12 enables masking to agriculture, 13 enables exporting of all data layers, and 14 is a text string for naming export files. ------------------------------------------------------------------------------------------------------------------------- ••••••••••••••••••••••••••••••••••••••••••• USER OPTIONS ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• */ // CHIRPS data availability: https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD // MOD11A2 data availability: https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2 var country = 'MI' // [1] https://en.wikipedia.org/wiki/List_of_FIPS_country_codes var startRange = 2001 // [2] var endRange = 2017 // [3] var startSeasonMonth = 11 // [4] var startSeasonDay = 1 // [5] var endSeasonMonth = 4 // [6] var endSeasonDay = 30 // [7] var precipMin = 750 // [8] var precipMax = 1200 // [9] var tempMin = 22 // [10] var tempMax = 32 // [11] var maskToAg = 'TRUE' // [12] 'TRUE' (default) or 'FALSE' var exportLayers = 'TRUE' // [13] 'TRUE' (default) or 'FALSE' var exportNameHeader = 'crop_suit_maize' // [14] text string for naming export file // ••••••••••••••••••••••••••••••••• NO USER INPUT BEYOND THIS POINT •••••••••••••••••••••••••••••••••••••••••••••••••••• // Access precipitation and temperature ImageCollections and a global countries FeatureCollection var region = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017') .filterMetadata('country_co','equals',country) var precip = ee.ImageCollection('UCSB-CHG/CHIRPS/PENTAD').select('precipitation') var temp = ee.ImageCollection('MODIS/006/MOD11A2').select(['LST_Day_1km','LST_Night_1km']) var ndvi = ee.ImageCollection('MODIS/006/MOD13Q1').select(['NDVI']) // Create layers for masking to agriculture and masking out water bodies var waterMask = ee.Image('UMD/hansen/global_forest_change_2015').select('datamask').eq(1) var agModis = ee.ImageCollection('MODIS/006/MCD12Q1').select('LC_Type1').mode() .remap([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17], [0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0]) var agGC = ee.Image('ESA/GLOBCOVER_L4_200901_200912_V2_3').select('landcover') .remap([11,14,20,30,40,50,60,70,90,100,110,120,130,140,150,160,170,180,190,200,210,220,230], [1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]) var cropland = ee.Image('USGS/GFSAD1000_V1').neq(0) var agMask = agModis.add(agGC).add(cropland).gt(0).eq(1) // Modify user input options for processing with raw data var years = ee.List.sequence(startRange,endRange) var bounds = region.geometry().bounds() var tMinMod = (tempMin+273.15)/0.02 var tMaxMod = (tempMax+273.15)/0.02 //...