GIS2DJI is a Python 3 program created to exports GIS files to a simple kml compatible with DJI pilot. The software is provided with a GUI. GIS2DJI has been tested with the following file formats: gpkg, shp, mif, tab, geojson, gml, kml and kmz. GIS_2_DJI will scan every file, every layer and every geometry collection (ie: MultiPoints) and create one output kml or kmz for each object found. It will import points, lines and polygons, and converted each object into a compatible DJI kml file. Lines and polygons will be exported as kml files. Points will be converted as PseudoPoints.kml. A PseudoPoints fools DJI to import a point as it thinks it's a line with 0 length. This allows you to import points in mapping missions. Points will also be exported as Point.kmz because PseudoPoints are not visible in a GIS or in Google Earth. The .kmz file format should make points compatible with some DJI mission software.

VDatum is designed to vertically transform geospatial data among a variety of tidal, orthometric and ellipsoidal vertical datums - allowing users to convert their data from different horizontal/vertical references into a common system and enabling the fusion of diverse geospatial data in desired reference levels.This particular layer allows you to convert from NAVD 88 to MHHW.Units: metersThese data are a derived product of the NOAA VDatum tool and they extend the tool's Mean Higher High Water (MHHW) tidal datum conversion inland beyond its original extent.VDatum was designed to vertically transform geospatial data among a variety of tidal, orthometric and ellipsoidal vertical datums - allowing users to convert their data from different horizontal/vertical references into a common system and enabling the fusion of diverse geospatial data in desired reference levels (https://vdatum.noaa.gov/). However, VDatum's conversion extent does not completely cover tidally-influenced areas along the coast. For more information on why VDatum does not provide tidal datums inland, see https://vdatum.noaa.gov/docs/faqs.html.Because of the extent limitation and since most inundation mapping activities use a tidal datum as the reference zero (i.e., 1 meter of sea level rise on top of Mean Higher High Water), the NOAA Office for Coastal Management created this dataset for the purpose of extending the MHHW tidal datum beyond the areas covered by VDatum. The data do not replace VDatum, nor do they supersede the valid datum transformations VDatum provides. However, the data are based on VDatum's underlying transformation data and do provide an approximation of MHHW where VDatum does not provide one. In addition, the data are in a GIS-friendly format and represent MHHW in NAVD88, which is the vertical datum by which most topographic data are referenced.Data are in the UTM NAD83 projection. Horizontal resolution varies by VDatum region, but is either 50m or 100m. Data are vertically referenced to NAVD88 meters.More information about the NOAA VDatum transformation and associated tools can be found here.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

Warning: This raster is a grid of a floating-point values; not a surface. To derive an accurate height transformation value, this raster grid must be downloaded in terms of NZGD2000 and then converted into a surface using bilinear interpolation.

The Napier 1962 to NZVD2016 Conversion Raster provides users with a two arc-minute (approximately 3.6 kilometres) raster image of the conversion of normal-orthometric heights from the Napier 1962 local vertical datum to the New Zealand Vertical Datum 2016 (NZVD2016).

The conversion value is represented by the attribute “O”, in metres. This conversion and NZVD2016 are formally defined in the LINZ standard LINZS25009.

The height conversion grid models the difference between the Napier 1962 vertical datum and NZVD2016 using the LINZ GPS-levelling marks. From the GPS-levelling marks the expected accuracy is better than 2 centimetres (95% Confidence interval).

More information on converting heights between vertical datums can be found on the LINZ website.

Warning: This raster is a grid of a floating-point values; not a surface. To derive an accurate height transformation value, this raster grid must be downloaded in terms of NZGD2000 and then converted into a surface using bilinear interpolation.

The Dunedin 1958 to NZVD2016 Conversion Raster provides users with a two arc-minute (approximately 3.6 kilometres) raster image of the conversion of normal-orthometric heights from the Dunedin 1958 local vertical datum to the New Zealand Vertical Datum 2016 (NZVD2016).

The conversion value is represented by the attribute “O”, in metres. This conversion and NZVD2016 are formally defined in the LINZ standard LINZS25009.

The height conversion grid models the difference between the Dunedin 1958 vertical datum and NZVD2016 using the LINZ GPS-levelling marks. From the GPS-levelling marks the expected accuracy is better than 2 centimetres (95% Confidence interval).

More information on converting heights between vertical datums can be found on the LINZ website.

The Office of the Geographer’s Global Large Scale International Boundary Detailed Polygons file combines two datasets, the Office of the Geographer’s Large Scale International Boundary Lines and NGA shoreline data. The LSIB is believed to be the most accurate worldwide (non- W. Europe) international boundary vector line file available. The lines reflect U.S. government (USG) policy and thus not necessarily de facto control. The 1:250,000 scale World Vector Shoreline (WVS) coastline data was used in places and is generally shifted by several hundred meters to over a km. There are no restrictions on use of this public domain data. The Tesla Government PiX team performed topology checks and other GIS processing while merging data sets, created more accurate island shoreline in numerous cases, and worked closely with the US Dept. of State Office of the Geographer on quality control checks.

Methodology: Tesla Government’s Protected Internet Exchange (PiX) GIS team converted the LSIB linework and the island data provided by the State Department to polygons. The LSIB Admin 0 world polygons (Admin 0 polygons) were created by conflating the following datasets: Eurasia_Oceania_LSIB7a_gen_polygons, Africa_Americas_LSIB7a_gen_polygons, Africa_Americas_LSIB7a, Eurasia_LSIB7a, additional updates from LSIB8, WVS shoreline data, and other shoreline data from United States Government (USG) sources. The two simplified polygon shapefiles were merged, dissolved, and converted to lines to create a single global coastline dataset. The two detailed line shapefiles (Eurasia_LSIB7a and Africa_Americas_LSIB7a) were merged with each other and the coastlines to create an international boundary shapefile with coastlines. The dataset was reviewed for the following topological errors: must not self overlap, must not overlap, and must not have dangles. Once all topological errors were fixed, the lines were converted to polygons. Attribution was assigned by exploding the simplified polygons into multipart features, converting to centroids, and spatially joining with the newly created dataset. The polygons were then dissolved by country name. Another round of QC was performed on the dataset through the data reviewer tool to ensure that the conversion worked correctly. Additional errors identified during this process consisted of islands shifted from their true locations and not representing their true shape; these were adjusted using high resolution imagery whereupon a second round of QC was applied with SRTM digital elevation model data downloaded from USGS. The same procedure was performed for every individual island contained in the islands from other USG sources.
After the island dataset went through another round of QC, it was then merged with the Admin 0 polygon shapefile to form a comprehensive world dataset. The entire dataset was then evaluated, including for proper attribution for all of the islands, by the Office of the Geographer.

Displacement risk indicator showing the number of housing units subject to conversion into condominiums summarized at the census tract level; available for every year from 2004 through the most recent year of available data.

This index enables users to identify the extent of the relationship grids provided on LDS, which are used to convert heights provided in terms of one of 13 historic local vertical datums to NZVD2016.

The polygons comprising the index show the extent of the conversion grids.

Users can view the following polygon attributes: Shape_VDR: Vertical Datum Relationship grid area LVD: Local Vertical Datum Control: Number of control marks used to compute the relationship grid Mean: Mean vertical datum relationship value at control points Std: Standard deviation of vertical datum relationship value at control points Min: Minimum vertical datum relationship value at control points Max: Maximum vertical datum relationship value at control points Range: Range of vertical datum relationship value at control points Ref: Reference control mark for the local vertical datum Ref_value: Vertical datum relationship value at the reference mark Grid: Formal grid id

Users should note that the values represented in this dataset have been calculated with the outliers excluded. These same outliers were excluded during the computation of the relationship grids, but were included when calculating the 95% confidence intervals More information on converting heights between vertical datums can be found on the LINZ website.

The NPR62-NZGD2000 grid enables the conversion of normal-orthometric heights from the Napier 162 ocal vertical datum directly to New Zealand Geodetic Datum 2000 (NZGD2000) ellipsoidal heights.

NPR62-NZGD2000 is published on a one arc-minute grid (approximately 1.8 kilometres) extending over the benchmarks that nominally define the extent of the Napier 1962 vertical datum (175.6° E to 177.9° E, 38.6° S to 40.6° S).

The conversion value is represented by the attribute “delta”, in metres.

This grid is a combination of New Zealand Quasigeoid 2016 NZGeoid2016 and the NPR62-NZVD2016 height conversion grid. Where NZGeoid2016 is the reference surface for the New Zealand Vertical Datum 2016 (NZVD2016), while the NPR62-NZVD2016 grid models the difference between the Napier 1962 vertical datum and NZVD2016 using the LINZ GPS-levelling marks.

More information on converting heights between vertical datums can be found on the LINZ website.

Warning: This raster is a grid of a floating-point values; not a surface. To derive an accurate height transformation value, this raster grid must be downloaded in terms of NZGD2000 and then converted into a surface using bilinear interpolation.

The Moturiki 1953 to NZVD2016 Conversion Raster provides users with a two arc-minute (approximately 3.6 kilometres) raster image of the conversion of normal-orthometric heights from the Moturiki 1953 local vertical datum to the New Zealand Vertical Datum 2016 (NZVD2016).

The conversion value is represented by the attribute “O”, in metres. This conversion and NZVD2016 are formally defined in the LINZ standard LINZS25009.

The height conversion grid models the difference between the Moturiki 1953 vertical datum and NZVD2016 using the LINZ GPS-levelling marks. From the GPS-levelling marks the expected accuracy is better than 2 centimetres (95% Confidence interval).

More information on converting heights between vertical datums can be found on the LINZ website.

Metadata & Projection Standards, Data Development Methods, State Engineer's Office E-Permit Instructions, Permit conversion Tool (Version 2, 2019)

The Fiber Optic Current Transformer (FOCT) system market is experiencing robust growth, projected to reach a market size of $287 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.1% from 2025 to 2033. This expansion is fueled by several key factors. The increasing demand for enhanced accuracy and reliability in power grid monitoring, particularly within substations and converter stations, is a primary driver. FOCT systems offer significant advantages over traditional current transformers, including superior accuracy, immunity to electromagnetic interference, and inherent safety due to their optical isolation. Furthermore, the rising adoption of smart grids and the need for advanced grid management solutions are bolstering market growth. The integration of FOCT systems into Geographic Information Systems (GIS) is also gaining traction, further driving market adoption. Growth is expected across all regions, with North America and Asia-Pacific anticipated to be major contributors due to substantial investments in grid modernization and renewable energy infrastructure. However, the relatively high initial investment cost of FOCT systems compared to traditional solutions could act as a restraint on market penetration, especially in developing regions. Nevertheless, the long-term benefits in terms of improved efficiency, reduced maintenance costs, and enhanced safety are expected to outweigh this initial hurdle, leading to continued market expansion throughout the forecast period. The segmentation of the FOCT system market reveals a significant focus on applications within substations and converter stations, reflecting their crucial role in ensuring grid stability and efficiency. The 'Independent Pillar Type' and 'GIS Integrated Type' segments are also prominent, showcasing the diverse installation options available to meet various grid infrastructure needs. Key players like ABB, GE Grid Solutions, and NR Electric are at the forefront of innovation and market competition, driving technological advancements and expanding product portfolios to cater to evolving market demands. Geographical analysis indicates a strong presence across North America, Europe, and Asia-Pacific, mirroring the global trend toward grid modernization and the integration of renewable energy sources.

This shapefile represents annual average sea surface temperature recordings.

The sea surface temperature is the temperature of the warm water source used by an OTEC plant. This is defined to be near the sea surface at a depth of 20 m, the approximate depth of a warm water intake pipe.

Data were processed and converted to shapefile format by NREL for the Ocean Thermal Extractable Energy Visualization

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data.

Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data. Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

The Auckland 1946 to NZVD2016 Conversion Raster provides users with a two arc-minute (approximately 3.6 kilometres) raster image of the conversion of normal-orthometric heights from the Auckland 1946 local vertical datum to the New Zealand Vertical Datum 2016 (NZVD2016).

The conversion value is represented by the attribute “O”, in metres. This conversion and NZVD2016 are formally defined in the LINZ standard LINZS25009.

The height conversion grid models the difference between the Auckland 1946 vertical datum and NZVD2016 using the LINZ GPS-levelling marks. From the GPS-levelling marks the expected accuracy is better than 2 centimetres (95% Confidence interval).

More information on converting heights between vertical datums can be found on the LINZ website.

This layer shows the District Boundary of Hong Kong. It is a set of data made available by the Home Affairs Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://GEODATA.GOV.HK/ ("Hong Kong Geodata Store"). The source data has been processed and then 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 Geodata Store at https://geodata.gov.hk/.

The GSB26-NZGD2000 grid enables the conversion of normal-orthometric heights from the Gisborne 1926 local vertical datum directly to New Zealand Geodetic Datum 2000 (NZGD2000) ellipsoidal heights.

GSB26-NZGD2000 is published on a one arc-minute grid (approximately 1.8 kilometres) extending over the benchmarks that nominally define the extent of the Gisborne 1926 vertical datum (177.0° E to 178.6° E, 37.4° S to 39.0° S).

The conversion value is represented by the attribute “delta”, in metres.

This grid is a combination of New Zealand Quasigeoid 2016 NZGeoid2016 and the GSB26-NZVD2016 height conversion grid. Where NZGeoid2016 is the reference surface for the New Zealand Vertical Datum 2016 (NZVD2016), while the GSB26-NZVD2016 grid models the difference between the Gisborne 1926 vertical datum and NZVD2016 using the LINZ GPS-levelling marks.

More information on converting heights between vertical datums can be found on the LINZ website.

This shapefile represents seasonal winter average net power estimates.

The OTEC Plant model predicts the net power production at a specific location, given three inputs: surface temperature (°C), depth (m), and difference between warm surface water temperature and cold deep sea water temperature (ΔT in °C) at the given depth, relative to the surface temperature.

In order to normalize values for the purposes of visualization of the OTEC resource around the world, a baseline plant design was used. The baseline 100MW Net Power design has been optimized for conditions indicative of the Hawai‘i OTEC resource. As such, power output as described by the results of this study is not optimized for local conditions (except in parts of Hawai’i), but does provide guidance for site selection. Given the nominal plant power output of 100MW based on a competitive cost of electricity (Hawai’i), any output exceeding this value represents significant potential. A large area of predicted 100 MW+ net power exists in many locations around the world, especially in areas with high energy costs.

Data were processed and converted to shapefile format by NREL for the Ocean Thermal Extractable Energy Visualization

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data.

Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data. Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

The USDA-ARS Southwest Watershed Research Center (SWRC) operates the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona as an outdoor laboratory for studying semiarid rangeland hydrologic, ecosystem, climate, and erosion processes. Since its establishment in 1953, the SWRC in Tucson, Arizona, has collected, processed, managed, and disseminated high-resolution, spatially distributed hydrologic data in support of the center’s mission. Data management at the SWRC has evolved through time in response to new computing, storage, and data access technologies. In 1996, the SWRC initiated a multiyear project to upgrade rainfall and runoff sensors and convert analog systems to digital electronic systems supported by data loggers. This conversion was coupled with radio telemetry to remotely transmit recorded data to a central computer, thus greatly reducing operational overhead by reducing labor, maintenance, and data processing time. A concurrent effort was initiated to improve access to SWRC data by creating a system based on a relational database supporting access to the data via the Internet. An SWRC team made up of scientists, IT specialists, programmers, hydrologic technicians, and instrumentation specialists was formed. This effort is termed the Southwest Watershed Research Center Data Access Project (DAP). The goal of the SWRC DAP is to efficiently disseminate data to researchers; land owners, users, and managers; and to the public. Primary access to the data is provided through a Web-based user interface. In addition, data can be accessed directly from within the SWRC network. The first priority for the DAP was to assimilate and make available rainfall and runoff data collected from two instrumented field sites, the WGEW near Tombstone, Arizona, and the Santa Rita Experimental Range (SRER) south of Tucson, Arizona. This web map describes the associated GIS layers. Resources in this dataset: Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/fe4ac74f13484a169899b166159e0bb5

The GSB26-NZVD2016 grid enables the conversion of normal-orthometric heights from the Gisborne 1926 local vertical datum to the New Zealand Vertical Datum 2016 (NZVD2016).

The conversion value is represented by the attribute “O”, in metres.

This conversion and NZVD2016 are formally defined in the LINZ standard LINZS25009.

GSB26-NZVD2016 is published on a two arc-minute grid (approximately 3.6 kilometres) extending over the benchmarks that nominally define the extent of the Gisborne 1926 vertical datum (177.0° E to 178.6° E, 37.4° S to 39.0° S).

The height conversion grid models the difference between the Gisborne 1926 vertical datum and NZVD2016 using the LINZ GPS-levelling marks. From the GPS-levelling marks the expected accuracy of GSB26-NZVD2016 is better than 2 centimetres (95% Confidence interval).

More information on converting heights between vertical datums can be found on the LINZ website.

The Fiber Optic Current Transformer (FOCT) system market is experiencing robust growth, projected to reach a substantial market size with a Compound Annual Growth Rate (CAGR) of 5.1% between 2019 and 2033. This expansion is fueled by several key factors. The increasing demand for improved accuracy and reliability in power grid monitoring and protection is a significant driver. FOCT systems offer superior performance compared to conventional current transformers, particularly in high-voltage applications such as substations and converter stations. The inherent advantages of FOCTs, including immunity to electromagnetic interference, enhanced safety due to their optical isolation, and ease of installation and maintenance, are further contributing to market growth. The growing adoption of smart grids and the need for advanced grid management solutions are also bolstering market demand. Segmentation reveals strong growth in both the Independent Pillar Type and GIS Integrated Type FOCT systems across various applications, with substation and converter station applications leading the way. Geographically, North America and Europe currently hold significant market share, but regions like Asia-Pacific are showing rapid growth potential due to ongoing infrastructure development and increasing electricity demand. The competitive landscape includes established players like ABB, GE Grid Solutions, and newer entrants. These companies are focusing on technological advancements, strategic partnerships, and geographic expansion to gain a larger market share. While challenges remain, such as the initial higher cost of FOCT systems compared to traditional alternatives, the long-term benefits in terms of operational efficiency and reduced maintenance costs are overcoming this barrier. The market is poised for continued growth, driven by ongoing technological innovation and the increasing need for reliable and efficient power grid management worldwide. The consistent adoption across diverse applications and regions indicates a promising outlook for the FOCT system market in the coming years. Further market penetration will likely be driven by decreasing prices, increased awareness of the benefits, and government initiatives supporting smart grid deployments.