This deep learning model is used for extracting windows and doors in textured building data displayed in 3D views. Manually digitizing windows/doors from 3D building data can be a slow process. This model automates the extraction of these objects from a 3D view and can help in speeding up 3D editing and analysis workflows. Using this model, existing building data can be enhanced with additional information on location, size and orientation of windows and doors. The extracted windows and doors can be further used to perform 3D visibility analysis using existing 3D geoprocessing tools in ArcGIS.This model can be useful in many industries and workflows. National Government and state-level law enforcement could use this model in security analysis scenarios. Local governments could use windows and door locations to help with tax assessments with CAMA (computer aided mass appraisal) plus impact-studies for urban planning. Public safety users might be interested in regards to physical or visual access to restricted areas, or the ability to build evacuation plans. The commercial sector, with everyone from real-estate agents to advertisers to office/interior designers, would be able to benefit from knowing where windows and doors are located. Even utilities, especially mobile phone providers, could take advantage of knowing window sizes and positions. To be clear, this model doesn't solve these problems, but it does allow users to extract and collate some of the data they will need to do it.Using the modelThis model is generic and is expected to work well with a variety of building styles and shapes. To use this model, you need to install supported deep learning frameworks packages first. See Install deep learning frameworks for ArcGIS for more information. The model can be used with the Interactive Object Detection tool.A blog on the ArcGIS Pro tool that leverages this model is published on Esri Blogs. We've also published steps on how to retrain this model further using your data.InputThe model is expected to work with any textured building data displayed in 3D views. Example data sources include textured multipatches, 3D object scene layers, and integrated mesh layers. OutputFeature class with polygons representing the detected windows and doors in the input imagery. Model architectureThe model uses the FasterRCNN model architecture implemented using ArcGIS API for Python.Training dataThis model was trained using images from the Open Images Dataset.Sample resultsBelow, are sample results of the windows detected with this model in ArcGIS Pro using the Interactive Object Detection tool, which outputs the detected objects as a symbolized point feature class with size and orientation attributes.

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

This data was prepared as input for the Selkie GIS-TE tool. This GIS tool aids site selection, logistics optimization and financial analysis of wave or tidal farms in the Irish and Welsh maritime areas. Read more here: https://www.selkie-project.eu/selkie-tools-gis-technoeconomic-model/

This research was funded by the Science Foundation Ireland (SFI) through MaREI, the SFI Research Centre for Energy, Climate and the Marine and by the Sustainable Energy Authority of Ireland (SEAI). Support was also received from the European Union's European Regional Development Fund through the Ireland Wales Cooperation Programme as part of the Selkie project.

File Formats

Results are presented in three file formats:

tif Can be imported into a GIS software (such as ARC GIS) csv Human-readable text format, which can also be opened in Excel png Image files that can be viewed in standard desktop software and give a spatial view of results

Input Data

All calculations use open-source data from the Copernicus store and the open-source software Python. The Python xarray library is used to read the data.

Hourly Data from 2000 to 2019

• Wind - Copernicus ERA5 dataset 17 by 27.5 km grid
  10m wind speed

• Wave - Copernicus Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis dataset 3 by 5 km grid

Accessibility

The maximum limits for Hs and wind speed are applied when mapping the accessibility of a site.
The Accessibility layer shows the percentage of time the Hs (Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis) and wind speed (ERA5) are below these limits for the month.

Input data is 20 years of hourly wave and wind data from 2000 to 2019, partitioned by month. At each timestep, the accessibility of the site was determined by checking if
the Hs and wind speed were below their respective limits. The percentage accessibility is the number of hours within limits divided by the total number of hours for the month.

Environmental data is from the Copernicus data store (https://cds.climate.copernicus.eu/). Wave hourly data is from the 'Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis' dataset.
Wind hourly data is from the ERA 5 dataset.

Availability

A device's availability to produce electricity depends on the device's reliability and the time to repair any failures. The repair time depends on weather
windows and other logistical factors (for example, the availability of repair vessels and personnel.). A 2013 study by O'Connor et al. determined the
relationship between the accessibility and availability of a wave energy device. The resulting graph (see Fig. 1 of their paper) shows the correlation between accessibility at Hs of 2m and wind speed of 15.0m/s and availability. This graph is used to calculate the availability layer from the accessibility layer.

The input value, accessibility, measures how accessible a site is for installation or operation and maintenance activities. It is the percentage time the
environmental conditions, i.e. the Hs (Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis) and wind speed (ERA5), are below operational limits.
Input data is 20 years of hourly wave and wind data from 2000 to 2019, partitioned by month. At each timestep, the accessibility of the site was determined
by checking if the Hs and wind speed were below their respective limits. The percentage accessibility is the number of hours within limits divided by the total
number of hours for the month. Once the accessibility was known, the percentage availability was calculated using the O'Connor et al. graph of the relationship between the two. A mature technology reliability was assumed.

Weather Window

The weather window availability is the percentage of possible x-duration windows where weather conditions (Hs, wind speed) are below maximum limits for the
given duration for the month.

The resolution of the wave dataset (0.05° × 0.05°) is higher than that of the wind dataset
(0.25° x 0.25°), so the nearest wind value is used for each wave data point. The weather window layer is at the resolution of the wave layer.

The first step in calculating the weather window for a particular set of inputs (Hs, wind speed and duration) is to calculate the accessibility at each timestep.
The accessibility is based on a simple boolean evaluation: are the wave and wind conditions within the required limits at the given timestep?

Once the time series of accessibility is calculated, the next step is to look for periods of sustained favourable environmental conditions, i.e. the weather
windows. Here all possible operating periods with a duration matching the required weather-window value are assessed to see if the weather conditions remain
suitable for the entire period. The percentage availability of the weather window is calculated based on the percentage of x-duration windows with suitable
weather conditions for their entire duration.The weather window availability can be considered as the probability of having the required weather window available
at any given point in the month.

Extreme Wind and Wave

The Extreme wave layers show the highest significant wave height expected to occur during the given return period. The Extreme wind layers show the highest wind speed expected to occur during the given return period.

To predict extreme values, we use Extreme Value Analysis (EVA). EVA focuses on the extreme part of the data and seeks to determine a model to fit this reduced
portion accurately. EVA consists of three main stages. The first stage is the selection of extreme values from a time series. The next step is to fit a model
that best approximates the selected extremes by determining the shape parameters for a suitable probability distribution. The model then predicts extreme values
for the selected return period. All calculations use the python pyextremes library. Two methods are used - Block Maxima and Peaks over threshold.

The Block Maxima methods selects the annual maxima and fits a GEVD probability distribution.

The peaks_over_threshold method has two variable calculation parameters. The first is the percentile above which values must be to be selected as extreme (0.9 or 0.998). The second input is the time difference between extreme values for them to be considered independent (3 days). A Generalised Pareto Distribution is fitted to the selected
extremes and used to calculate the extreme value for the selected return period.

The Digital Geologic Map of the Lucas quadrangle, Kentucky 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 (luca_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 16N. That data is within the area of interest of Mammoth Cave National Park.

DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

DNRGPS does not require installation. Simply run the application .exe

See the DNRGPS application documentation for more details.

Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

Prerequisite: .NET 4 Framework

DNR Data and Software License Agreement

Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.

description: The Digital Geologic Map of parts of the Bridger and Lodge Grass 30' X 60' Quadrangles, Montana 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 Resource 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 (lgbr_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 Bighorn Canyon National Recreation Area.; abstract: The Digital Geologic Map of parts of the Bridger and Lodge Grass 30' X 60' Quadrangles, Montana 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 Resource 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 (lgbr_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 Bighorn Canyon National Recreation Area.

The Digital Geologic Map of the Storck Quadrangle, Virginia is comprised 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, ArcMap 9.1 layer (.LYR) files, and an ArcMap 9.1 map document (.MXD) file. 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 an 9.1 personal geodatabase (strk_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 Fredericksburg and Spotsylvania County Battlefields Memorial National Military Park.

description: The Digital Geologic Map of Tallgrass Prairie National Preserve, Kansas is composed of GIS data layers complete with ArcMap 9.2 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.2 ArcMap (.MXD) Document that displays the digital map in 9.2 ArcGIS. The data were completed as a component of the Geologic Resource 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). Source geologic maps and data used to complete this GRE digital dataset were provided by the following: Kansas Geological Survey (KGS). Detailed information concerning the sources used and their contribution the GRE product are listed in the Source Citation sections(s) of this metadata record (tapr_metadata.txt; available at http://nrdata.nps.gov/tapr/nrdata/geology/gis/tapr_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 2.0. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.2 personal geodatabase (tapr_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. That data is within the area of interest of Tallgrass Prairie National Preserve.; abstract: The Digital Geologic Map of Tallgrass Prairie National Preserve, Kansas is composed of GIS data layers complete with ArcMap 9.2 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.2 ArcMap (.MXD) Document that displays the digital map in 9.2 ArcGIS. The data were completed as a component of the Geologic Resource 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). Source geologic maps and data used to complete this GRE digital dataset were provided by the following: Kansas Geological Survey (KGS). Detailed information concerning the sources used and their contribution the GRE product are listed in the Source Citation sections(s) of this metadata record (tapr_metadata.txt; available at http://nrdata.nps.gov/tapr/nrdata/geology/gis/tapr_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 2.0. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.2 personal geodatabase (tapr_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. That data is within the area of interest of Tallgrass Prairie National Preserve.

description: The Digital Geologic Map of the Bohemotash Mountain Quadrangle, California 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 10N. That data is within the area of interest of Whiskeytown-Shasta-Trinity National Recreation Area.; abstract: The Digital Geologic Map of the Bohemotash Mountain Quadrangle, California 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 10N. That data is within the area of interest of Whiskeytown-Shasta-Trinity National Recreation Area.

description: The Digital Surficial Geologic Map of the China Bend quadrangle, Washington is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) 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: Bureau of Reclamation. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (chbe_metadata.txt; available at http://nrdata.nps.gov/laro/nrdata/geology/gis/chbe_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (chbe_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 11N. That data is within the area of interest of Lake Roosevelt National Recreation Area.; abstract: The Digital Surficial Geologic Map of the China Bend quadrangle, Washington is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) 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: Bureau of Reclamation. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (chbe_metadata.txt; available at http://nrdata.nps.gov/laro/nrdata/geology/gis/chbe_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (chbe_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 11N. That data is within the area of interest of Lake Roosevelt National Recreation Area.

"This is a contour feature set depicting a surface of predicted migration intensity (Window Passage Rate, WPR) in units of targets per square km per hour. Predictions are based on data collected from 23 spring and 22 fall locations throughout the Great Lakes by the US Fish and Wildlife Service Avian Radar Team. Predictions were generated by sampling targets from the highest 2 of 11 areas (""windows"") of radar return arrayed altitudinally with consistently low interference (radar ""clutter""). This method allowed for greater comparability among sites as it helps control for site effects in radar returns due to clutter. Window data were further corrected for level of effort (e.g. time radar on, precipitation interference) for each site. Predictions were generated by interpolating overall WPA during this season with landscape variables (% water cover, % forest cover, night light illumination, latitude, longitude, and proximity to a Great Lake) as spatial predictors of WPR. Fields Value_Min and Value_Max contain the minimum and maximum predicted WPR values for each of 20 passage rate categories. Fields SE and CoV contain the standard error and covariance of the predicted WPR for each cell. See Supplementary Information for details.

The purpose of this dataset is to provide a broad view of differences in aerial migration intensity across the Upper Midwest Great Lakes region. This dataset may be used to identify general areas of greater and lesser airspace use by birds and bats. These estimates may also reflect differences in potential stopover intensity or use of terrestrial resources. "

description: The Digital Geologic Map of Hubbell Trading Post National Historic Site and Vicinity, 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 ArcMap 9.1 layer (.LYR) files. The data were completed as a component of the Geologic Resource 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 (hutr_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 Hubbell Trading Post National Historic Site.; abstract: The Digital Geologic Map of Hubbell Trading Post National Historic Site and Vicinity, 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 ArcMap 9.1 layer (.LYR) files. The data were completed as a component of the Geologic Resource 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 (hutr_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 Hubbell Trading Post National Historic Site.

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024.Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area.The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

This layer shows the location of buildings with statutory notice(s) complied with/ withdrawn/ superseded after 1 May 2024 under Mandatory Building Inspection Scheme in Hong Kong. It is a set of data made available by the Buildings Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.

description: The Digital Geologic Map of Canyon de Chelly National Monument and Vicinity, Arizona and New Mexico is composed of GIS data layers complete with ArcMap 9.2 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.2 ArcMap (.MXD) Document that displays the digital map in 9.2 ArcGIS. The data were completed as a component of the Geologic Resource 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). Source geologic maps and data used to complete this GRE digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRE product are listed in the Source Citation sections(s) of this metadata record (cach_metadata.txt; available at http://nrdata.nps.gov/cach/nrdata/geology/gis/cach_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 2.0. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.2 personal geodatabase (cach_geology.mdb), and as 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 Canyon de Chelly National Monument.; abstract: The Digital Geologic Map of Canyon de Chelly National Monument and Vicinity, Arizona and New Mexico is composed of GIS data layers complete with ArcMap 9.2 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.2 ArcMap (.MXD) Document that displays the digital map in 9.2 ArcGIS. The data were completed as a component of the Geologic Resource 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). Source geologic maps and data used to complete this GRE digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRE product are listed in the Source Citation sections(s) of this metadata record (cach_metadata.txt; available at http://nrdata.nps.gov/cach/nrdata/geology/gis/cach_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 2.0. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.2 personal geodatabase (cach_geology.mdb), and as 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 Canyon de Chelly National Monument.

description: The Digital Geologic Map (Surficial Map) of the Norris Junction 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 (nrju_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.; abstract: The Digital Geologic Map (Surficial Map) of the Norris Junction 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 (nrju_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.

description: The Digital Geologic Map of the Island of Hawaii 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 (havo_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 5N. That data is within the area of interest of Hawaii Volcanoes National Park.; abstract: The Digital Geologic Map of the Island of Hawaii 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 (havo_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 5N. That data is within the area of interest of Hawaii Volcanoes National Park.

description: The Digital Geologic Map of Theodore Roosevelt National Park, North Dakota 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 Theodore Roosevelt National Park.; abstract: The Digital Geologic Map of Theodore Roosevelt National Park, North Dakota 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 Theodore Roosevelt National Park.

The Digital Geologic Map for the Clarno Unit, John Day Fossil Beds National Monument, Oregon (Plate II) is composed of GIS data layers complete with ArcMap 9.2 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.2 ArcMap (.MXD) Document that displays the digital map in 9.2 ArcGIS. The data were completed as a component of the Geologic Resource 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 9.2 personal geodatabase (clu2_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 11N. That data is within the area of interest of John Day Fossil Beds National Monument.

The Digital Surficial Geologic Map of the Broadax Draw quadrangle, Washington is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) 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: Bureau of Reclamation. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (brdr_metadata.txt; available at http://nrdata.nps.gov/laro/nrdata/geology/gis/brdr_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (brdr_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 11N. That data is within the area of interest of Lake Roosevelt National Recreation Area.