These toronto contours are zipped files which contain both AutoCAD and shapefile format files. Originals held on DVD along with composite file for contours at 1m and 2m intervals as well as elevation points (DEM), TIN, breaklines and hulls. DVD also includes data for Brampton and Mississauga.See DVD for all data. Please note that the contour files are listed as open data. All other layers remain restricted to use by the University of Toronto community.

DVD available at the Map and Data Library. DVD #379.

The 2012 Triangulated irregular network (TIN) product is a mesh composed of irregular triangles. The dataset is freely downloadable as a zipped file.

The dataset is a 10 m-resolution DEM in grid format covering the whole Italian territory. The DEM is encoded as “ESRI ASCII Raster” obtained by interpolating the original DEM in Triangular Irregular Network (TIN) format. The TIN version benefited from the systematic application of the DEST algorithm. The projection is UTM, the World Geodetic System 1984 (WGS 84). To provide the dataset as a single seamless DEM, the sole zone 32 N was selected, although about half of Italy belongs to zone 33 N. The database is arranged in 193 square tiles having 50 km side. Data e Risorse Questo dataset non ha dati ambiente terremoti vulcani

no abstract provided

Data obtained from computational DFT calculations on Cubic TiN is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files. This structure was obtained from ICSD (Collection code = 26947)

Object detection Dataset was collected with a Himax HM01B0 greyscale camera. The datasets contain QVGA images of Bottles and Tin-Cans and their respective labels. The labels follow the PascalVOC format specification. The dataset also include tfrecod files for ease of use with tensorflow. This dataset was used in our paper Bio-inspired Autonomous Exploration Policies with CNN-based Object Detection on Nano-drones

This zip folder contains ASCII text files of vectors at the specified volcano at 12-hour intervals, from January 1, 1990 through December 28, 2009. The wind vectors are divided into five files, names by their elevation range above sea level in the atmosphere: 00-05km.txt; 05-11km.txt; 11-16km.txt; 16-24km.txt; and 24-30km.txt. The zip folder also contains a subfolder "figures", with Wind rose plots of wind direction and speed over this time period. The plots are by season, and by elevation, given a total of 20 plots (4 seasons, 5 elevation ranges). A summary plot is also included which gives the year-round wind pattern at the volcano, at 0-5 km elevation. Plots are in both jpg and pdf format.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Greenlee108 is located in T4S R31E Sec 36 NE in the Big Lue Mts - 15 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

Data obtained from computational DFT calculations on Hexagonal TiN is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

This report and digital data release presents 82 new rock geochemical analyses on historic U.S. Bureau of Mines (USBM) samples. These samples were originally collected by the USBM as part of their critical and strategic minerals project, which investigated tin occurrences associated with the Ohio Creek pluton, south-central Alaska. Historic USBM sample materials were retrieved by DGGS from the DGGS Geologic Materials Center (GMC), where the USBM samples were transferred as part of the federally funded Minerals Data and Information Rescue in Alaska (MDIRA) program in the late 1990s and early 2000s. The text and analytical data and tables associated with this report are being released in digital format as PDF files and .csv files. We provide analytical data, detection limits and, when available, the method documentation provided to us by the lab. We also provide the sample location in geographic coordinates, the sample material cited by the originating literature, a reference to the originating report, and the type of sample material that was obtained from the archive and sent to the lab.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2019 along the Florida Reef Tract (FRT) from Miami to Key West within a 939.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Fehr and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in 2016/2017 and 2019 using the methods of Yates and others (2017). Most of the elevation data from the 2016/2017 time period were collected during 2016, so as an abbreviated naming convention, we refer to this time period as 2016. Due to file size limitations, the elevation-change data was divided into five blocks. A seafloor stability threshold was determined for the 2016-2019 FRT elevation-change datasets based on the vertical uncertainty of the 2016 and 2019 digital elevation models (DEMs). Five stability categories (which include, Stable: 0.0 meters (m) to ±0.24 m or 0.0 m to ±0.49 m; Moderately stable: ±0.25 m to ±0.49 m; Moderately unstable: ±0.50 m to ±0.74 m; Mostly unstable: ±0.75 m to ±0.99 m; and Unstable: ±1.00 m to Max/Min elevation change) were created and used to define levels of stability and instability for each elevation-change value (total of 235,153,117 data points at 2-m horizontal resolution) based on the amount of erosion and accretion during the 2016 to 2019 time period. Seafloor-stability point and triangulated irregular network (TIN) surface models were created for each block at five different elevation-change data resolutions (1st order through 5th order) with each resolution becoming increasingly more detailed. The stability models were used to determine the level of seafloor stability at potential areas of interest for coral restoration and 14 habitat types found along the FRT. Stability surface (TIN) models were used for areas defined by specific XY geographic points, while stability point models were used for areas defined by bounding box coordinate locations. This data release includes ArcGIS Pro map packages containing the binned and color-coded stability point and surface (TIN) models, potential coral restoration locations, and habitat files for each block; maps of each stability model; and data tables containing stability and elevation-change data for the potential coral restoration locations and habitat types. Data were collected under Florida Keys National Marine Sanctuary permit FKNMS-2016-068. Coral restoration locations were provided by Mote Marine Laboratory under Special Activity License SAL-18-1724-SCRP.

This draft dataset contains the output files of crystal structure prediction calculations (density-functional theory relaxations and phonon calculations) on the ternary K-Sn-P phase diagram. All calculations were performed with the CASTEP DFT package (https://www.castep.org/) and the "matador" Python library (https://github.com/ml-evs/matador).

Contents:

• "convergence_tests_*/": contains the results of convergence tests on the K-P system at two levels of accuracy "polish" and "searches" on the corresponding edge of the K-Sn-P ternary system
• "phonons_*/": contains CASTEP output files for phonon calculations on the predicted low-lying phases on the corresponding edge of the K-Sn-P phase diagram
• "polish_*/": contains CASTEP output files of relaxations on the corresponding edge of the K-Sn-P system at the "polish" level of accuracy using various different xc-functionals or external pressures.
• "searches_*/": contains ".res" files that provide the relaxed structure from each different crystal structure prediction method on the corresponding edge of the K-Sn-P system.

Data obtained from computational DFT calculations on Tetragonal TiN is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

Dataset

This dataset was created by Tin Aung Yin AI

Released under Data files © Original Authors

Contents

It contains the following files:

Data obtained from computational DFT calculations on Orthorhombic TiN is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. were derived from the NVC. NatureServe developed a preliminary list of potential vegetation types. These data were combined with existing plot data (Cully 2002) to derive an initial list of potential types. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the park’s small size and the large amount of field data, the map units are equivalent to existing vegetation associations or local associations/descriptions (e.g., Prairie Dog Colony). In addition to vegetation type, vegetation structures were described using three attributes: height, coverage density, and coverage pattern. In addition to vegetation structure and context, a number of attributes for each polygon were stored in the associated table within the GIS database. Many of these attributes were derived from the photointerpretation; others were calculated or crosswalked from other classifications. Table 2.7.2 shows all of the attributes and their sources. Anderson Level 1 and 2 codes are also included (Anderson et al. 1976). These codes should allow for a more regional perspective on the vegetation types. Look-up tables for the names associated with the codes is included within the geodatabase and in Appendix D. The look-up tables contain all the NVC formation information as well as alliance names, unique IDs, and the ecological system codes (El_Code) for the associations. These El_Codes often represent a one-to-many relationship; that is, one association may be related to more than one ecological system. The NatureServe conservation status is included as a separate item. Finally, slope (degrees), aspect, and elevation were calculated for each polygon label point using a digital elevation model and an ArcView script. The slope figure will vary if one uses a TIN (triangulated irregular network) versus a GRID (grid-referenced information display) for the calculation (Jenness 2005). A grid was used for the slope figure in this dataset. Acres and hectares were calculated using XTools Pro for ArcGIS Desktop.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2017 and 2018 at Crocker Reef near Islamorada, Florida (FL), within a 6.11 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2017 and 2018 using the methods of Yates and others (2017). A seafloor stability threshold was determined for the 2017-2018 Crocker Reef elevation-change dataset based on the vertical uncertainty of the 2017 and 2018 digital elevation models (DEMs). Five stability categories (which include, Stable: 0.0 meters (m) to ±0.24 m or 0.0 m to ±0.49 m; Moderately stable: ±0.25 m to ±0.49 m; Moderately unstable: ±0.50 m to ±0.74 m; Mostly unstable: ±0.75 m to ±0.99 m; and Unstable: ±1.00 m to Max/Min elevation change) were created and used to define levels of stability and instability for each elevation-change value (1,525,339 data points at 2-m horizontal resolution) based on the amount of erosion and accretion during the 2017 to 2018 time period. Seafloor-stability point and triangulated irregular network (TIN) surface models were created at five different elevation-change data resolutions (1st order through 5th order) with each resolution becoming increasingly more detailed. The stability point models were used to determine the level of seafloor stability at seven habitat types found at Crocker Reef. This data release includes ArcGIS map packages containing the binned and color-coded stability point and surface (TIN) models and habitat files; maps of each stability model; and data tables containing stability and elevation-change data for the habitat types. Data were collected under Florida Keys National Marine Sanctuary permit FKNMS-2016-068.

Water depths for the lower Sixmile Creek reservoir in Ithaca, Tompkins County, N.Y. that were measured during 1938 were found in the files of the GIS Program, City of Ithaca. This agency computed bathymetric elevations and created a bathymetric surface (TIN) of the reservoir. A contour-line shapefile was created from this TIN.

This dataset contains a series of high resolution raster Digital Elevation Models (DEM) (1m resolution) around the coastal perimeter of Torres Strait community islands (Badu, Boigu, Dauan, Erub, Hammond, Iama, Mabuiag, Masig, Mer, Moa, Poruma, Saibai, Ugar, Warraber). This dataset was developed for the purpose of mapping levels of coastal inundation under different sea level rise and storm tide scenarios. To enable the creation of maps of the various scenarios from the DEM the Highest Astronomical Tide (HAT) and storm surge values for 1yr, 100yr and 1000yr Annual Return Interval (ARI) relative to the Mean Sea Level (MSL) for each island were compiled from Harper (2011). These height thresholds are provided in spreadsheet format.

The DEM dataset was produced predominantly from LiDAR (light detection and ranging) surveys taken in 2011 and provided to the Torres Strait Regional Authority (TSRA) by the Department of Natural Resources and Mines, Queensland Government.

LiDAR data is a remote sensing technology that measures distance by illuminating a target with a laser and analysing the reflected light. For the Torres Strait region LiDAR aircraft were used to collect height values above sea level to gain a very accurate and detailed coverage of the terrain of the islands captured.

The data captured was then modelled using ArcMap software to calculate a DEM for each island. Due to the large size of some of the islands only areas subject to inundation were processed and included in this dataset. The XYZ LiDAR data was captured and grouped into 1x1km tiles. These 1x1km areas were then merged to follow the coastline of each island from 1 data file for small islands, such as Masig through to 49 files for large islands such as Saibai. The entire dataset is made up from 112 separate DEM files. The XYZ data was converted to TIN files, then transformed from TIN to a DEM raster. The DEM raster has a projection of GDA94 / MGA Zone 55.

The height datum used in this dataset is the Australian Height Datum (AHD) which approximates to Mean Sea Level (MSL). Height datums in the Torres Strait have been unofficially revised by DERM from a Spatial Infrastructure Audit that was conducted in 2011.

The raster files are intended to be displayed by classifying different levels of coastal inundation as specified in Harper (2011). Each island has a different conversions between MSL to HAT and storm surge levels. These must be applied appropriately to the DEM of each island in order to assess the potential inundation hazards.

Limitations:

The LiDAR used to create the DEM did not measure heights below the level of the water at the time that the measurements were taken. As a result the DEM cuts off at the level of the tide when the LiDAR was taken. For some islands the DEM goes down to below the Mean Sea Level (MSL), while in others it only goes down to the MSL+0.6m. This makes this dataset unsuitable for investigating low tide effects. In addition to this the DEM is not clipped to the coastline and so areas that were covered in water the DEM shows an interpolation between the heights of closest neighbouring coastline (due to the TIN process). This must be considered when using this dataset for a purpose other than looking at high tide conditions.

In this dataset most of the base data was from LiDAR data. However for the Moa communities of Saint Pauls and Kubin no LiDAR data was available and so datasets developed by Dr Kevin Parnell from Schlenker Orthophotography were used instead. This data that was captured in 1999. This data is not as accurate as LiDAR data and this should be kept in mind when analysing these areas. A tender has been released for capture of LiDAR data for Saint Pauls and Kubin to occur in 2014.

References:

Harper Bruce, Mason Luciano, Botev Ivan, Smith Mitchell, Callaghan Jeff (2011). "Torres Strait Extreme Water Level Study". Systems Engineering Australia Pty Ltd. Accessible from http://www.tsra.gov.au/_data/assets/pdf_file/0006/2004/tsewls_finalreport_lowres.pdf

The data are stored as Athena project files for samples reported in the paper and Pt foil/SnO2 reference spectra. Data have been processed and the resultant k & R-plots used in the paper have been generated from these files.