The QMUL underGround Re-IDentification (GRID) dataset contains 250 pedestrian image pairs. Each pair contains two images of the same individual seen from different camera views. All images are captured from 8 disjoint camera views installed in a busy underground station. The figures beside show a snapshot of each of the camera views of the station and sample images in the dataset. The dataset is challenging due to variations of pose, colours, lighting changes; as well as poor image quality caused by low spatial resolution.

A 2.5 kilometer Bouguer anomaly grid for the state of Idaho. Number of columns is 215 and number of rows is 320. The order of the data is from the lower left to the right and then up one row.

# FiN: A Smart Grid and Powerline Communication Dataset

Within the Fühler-im-Netz (FiN) project 38 BPL modems were distributed in three different areas of a German city with about 150.000 inhabitants. Over a period of 22 months, an SNR spectrum of each connection between adjacent BPL modems was generated every quarter of an hour. The availability of this data from actual practical use opens up new possibilities to face the increasing complex challenges in smart grids.

~~ For detailed information we would like to refer to the full paper. ~~

Attributs | FiN 1
-------- | --------
SNR measurements | 3.3 Mio
Timespan | ~2.5yrs
*Metadata* |
Sleeve count per section | ☑
Cable length, typ, cross section | ☑
Number of conductors | ☑
Year of installation | ☑
Weather by openweather | ☑

## Paper abstract
The increasing complexity of low-voltage networks poses a growing challenge for the reliable and fail-safe operation of power grids. The reasons for this are, for example, a more decentralized energy generation (photovoltaic systems, wind power, ...) and the emergence of new types of consumers (e-mobility, domestic electricity storage, ...). At the same time, the low-voltage grid is largely unmonitored and local power failures are sometimes detected only when consumers report the outage. To end the blind flight within the low voltage network, the use of a broadband over power line (BPL) infrastructure is a possible solution. In addition to the purpose of establishing a communication infrastructure, BPL also offers the possibility of evaluating the cables themselves, as well as the connection quality between individual cable distributors based on their Signal-to-Noise-Ratio (SNR). Within the Fühler-im-Netz pilot project 38 BPL modems were distributed in three different areas of a German city with about 100.000 inhabitants. Over a period of 21 months, an SNR spectrum of each connection between adjacent BPL modems was generated every quarter of an hour. The availability of this data from actual practical use opens up new possibilities to react agilely to the increasingly complex challenges.

# FiN-Dataset release 1.0

### Content
- 68 data .npz files
- 3 weather csv files
- 2 metadata csv files
- this readme

### Summary
The dataset contains ~3.7B SNR measurements divided into 68 1-to-1 connections. Each of the 1-to-1 connections can split into additional segments, e.g. if part of a cable was replaced due to a cable break.
All 68 connections are formed by 38 different nodes distributed over three different locations. Due to data protection regulations, the exact location of the nodes cannot be given. Therefore, each of the 38 nodes is uniquely identified by an ID.

### Data
The filename specifies the location, the ID of the source node and the destination ID.
Example: "loc03_from26_to27.npz"
-> Node is in lcation 3
-> Source node is 26
-> Destination node is 27

The .npz file contains a Python dict that is structured as follows:

data_dict = {"timestamps": np.array(...), --> Nx1 Timestamps
"spectrum_rx": np.array(...), --> Nx1536 SNR assesments on 1536 channels in RX directions. Range is 0.00dB...40.00dB
"tonemap_rx": np.array(...), --> Nx1536 Tonemaps in RX directions. Range is 0...7
"tonemap_tx": np.array(...)} --> Nx1536 Tonemaps in TX directions. Range is 0...7

### Weather
In addition to the measured data, we add weather data provided by https://openweathermap.org for all three locations. The weather data is stored in CSV format and contains many different weather attributes. Detailed information on the weather data can be found in the official documentation: https://openweathermap.org/history-bulk

### Metadata
--> nodes.csv
Contains in overview of all nodes, their id, corresponding location and voltage level.

--> connections.csv
Contains all available metadata for the 68 1-to-1 connections and their individual segements.

+ year_of_installation -> year in which the cable was installed
+ year_approximated -> Indicates whether the year was approximated or not (e.g. due to missing records)
+ cable_section -> identifies the segment or section described by the metadata
+ length -> length in meters
+ number_of_conductors -> identifier for the conductor structure in the cable
+ cross-section -> cross-section of the conductors
+ voltage_level -> identifier for the voltage level (MV=mid voltage; LV=low voltage)
+ t_sleeves -> number of T-sleeves installed within a section
+ type -> cable type
+ src_id -> id of the source node
+ dst_id -> id of the destination node

ArcGIS and QGIS map packages, with ESRI shapefiles for the DSM2 Model Grid. These are not finalized products. Locations in these shapefiles are approximate.

Monitoring Stations - shapefile with approximate locations of monitoring stations.

DSM2 v8.2.0, calibrated version:

• dsm2_8_2_grid_map_calibrated.mpkx - ArcGIS Pro map package containing all layers and symbology for the calibrated grid map.
• dsm2_8_2_grid_map_calibrated.mpk - ArcGIS Desktop map package containing all layers and symbology for the calibrated grid map.
• dsm2_8_2_0_calibrated_grid_map_qgis.zip - QGIS map package containing all layers and symbology for the calibrated grid map.
• dsm2_8_2_0_calibrated_gridmap_shapefiles.zip - A zip file containing all the shapefiles used in the above map packages:
• dsm2_8_2_0_calibrated_channels_centerlines - channel centerlines, follwing the path of CSDP centerlines
• dsm2_8_2_0_calibrated_network_channels - channels represented by straight line segments which are connected the upstream and downstream nodes
• dsm2_8_2_0_calibrated_nodes - DSM2 nodes
• dsm2_8_2_0_calibrated_dcd_only_nodes - Nodes that are only used by DCD
• dsm2_8_2_0_calibrated_and_dcd_nodes - Nodes that are shared by DSM2 and DCD
• dsm2_8_2_0_calibrated_and_smcd_nodes - Nodes that are shared by DSM2 and SMCD
• dsm2_8_2_0_calibrated_gates_actual_loc - The approximate actual locations of each gate in DSM2
• dsm2_8_2_0_calibrated_gates_grid_loc - The locations of each gate in the DSM2 model grid
• dsm2_8_2_0_calibrated_reservoirs - The approximate locations of the reservoirs in DSM2
• dsm2_8_2_0_calibrated_reservoir_connections - Lines showing connections from reservoirs to nodes in DSM2

DSM2 v8.2.1, historical version:

• DSM2 v8.2.1, historical version grid map release notes (PDF), updated 7/12/2022
• DSM2 v8.2.1, historical version grid map, single zoom level (PDF)
• DSM2 v8.2.1, historical version grid map, multiple zoom levels (PDF) - PDF grid map designed to be printed on 3 foot wide plotter paper.
• DSM2 v8.2.1, historical version map package for ArcGIS Desktop: A map package for ArcGIS Desktop containing the grid map layers with symbology.
• DSM2 v8.2.1, historical version grid map shapefiles (zip): A zip file containing the shapefiles used in the grid map.

Change Log

7/12/2022: The document "DSM2 v8.2.1, historical version grid map release notes (PDF)" was corrected by removing section 4.4, which incorrectly stated that the grid included channels 710-714, representing the Toe Drain, and that the Yolo Flyway restoration area was included.

The Key Map Grid Index dataset contains rectangular features representing index pages within Montgomery County, Texas. Each index page is proportioned to fit a letter-sized map and is assigned a unique identifier for reference purposes. This dataset facilitates the organization and retrieval of key map grids, with 24 key map grids fitting within a single index page. The index pages are numbered sequentially, and the key map grids within each index page are lettered accordingly, excluding the letters "I" and "O" to avoid confusion with numbers. The Key Map Grid Index was created by the Houston Map Company, which covers multiple counties in the Houston metropolitan area including Harris, Fort Bend, Galveston, Brazoria, Liberty, Waller, and Montgomery Counties. More information can be found on the Houston Map Company's website at www.keymaps.com.Data Fields Included:Index Page ID: Unique identifier assigned to each index pageBoundary Polygon: Rectangle representing the proportionate index page

Chimera medium-size grid for HIRENASD. Two files, fort.501 for grid for wing, fuselage, and 'world' zones, fort.503 for collar zone. File format is plot3d, unstructured, double precision, multi-zone.

The Montgomery County-Owned Facilities Map with Alpha Numeric Grid offers an enhanced visualization of county-owned facilities along with a custom grid system and facility table. Key features of the map include:Custom Alpha Numeric Grid: An alphanumeric grid surrounding the map frame, with letters along the top and numbers along the left side, providing a reference for locating facilities on the map.Facility Table: A table adjacent to the map frame, listing each county-owned facility by name, address, and grid ID. Users can quickly search for a facility by name in the table and locate its position on the map using the corresponding grid ID.Facility Labels: Each county-owned facility is labeled on the map with its corresponding grid ID, enhancing spatial awareness and navigation.Map Insets: Map insets for areas with a high concentration of facilities within a small area, ensuring clarity and detail for densely populated regions.The Montgomery County-Owned Facilities Map with Alpha Numeric Grid is optimized for printing at Arch E size (36x48 inches) and is available in Adobe PDF format. Users may need Adobe Acrobat for viewing and printing.Data Sources:Facility Locations: Montgomery County Property Management DepartmentGrid System: Customized grid system developed by Montgomery County GIS DepartmentAccess Requirements: Access to the Montgomery County-Owned Facilities Map with Alpha Numeric Grid is open to the public and stakeholders interested in county-owned properties and facilities.

Power Grid Inspection

## Overview

Power Grid Inspection is a dataset for classification tasks - it contains Transformers Towers Powercables annotations for 1,624 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This MIDAS object contains all the data inputs and code necessary to replicate the findings presented in NIST TN2137 using the statistical software Stata.

In the Great Lakes, grid systems defined by latitude and longitude minutes have been used for a number of decades as a fishery standard for data reporting. The Michigan Department of Natural Resources (MDNR) Fisheries Division created this GIS layer in 2019 to depict the MDNR Michigan Great Lakes grid (v3.2) standard for Fisheries Division applications for the waters of the State of Michigan, and for Canadian waters in the St. Clair Detroit River System (SCDRS), as of June 2019. This GIS layer was created by incorporating grid boundaries and ID values from a number of existing grid standards. This layer is a composite grid that incorporates grid boundaries and ID values from the following GIS data standards for different areas of the Great Lakes: 1) 10-minute grids for Lakes Huron, Michigan, Superior and the St. Mary’s River came from the Institute for Fisheries Research (IFR) version 1 (v1) of the 10-minute grids. 2) 10-minute grids for Lake Erie came from version 2 of the IFR 10-minute grids created by the Great Lakes GIS (GLGIS) project, and 3) 5-minute grids for SCDRS came from 5-minute grids developed by the GLGIS project. Version 1 of the IFR 10-minute grids were created in 1998, and only covered Lakes Huron, Michigan, and Superior, and the St. Mary’s River. This is the GIS dataset that was used as the grid standard for the 2000 consent decree. The grid boundaries and ID values in v1 were based off of the paper maps depicted in the 1989 Status of the Fisheries Resource Report (Technical Review Committee, 1989) with some very minor grid boundary differences likely caused by bringing the paper map into a digital GIS format. In v1, 10-minute grids do not always have rectangular boundaries where each side represents 10-minutes of latitude and longitude, especially near the shoreline. In order to create the v3.2 composite layer, some features in the v1 GIS dataset that were missing ID values were assigned ID values based on historical creel maps or nearby grid ID values. Version 2 of the IFR 10-minute grids was created in 2006 and provides coverage forall five Great Lakes, but only partial coverage in the connecting channels, with no coverage in SCDRS. In contrast to v1, 10-minute grids in this dataset are true 10-minute grids with rectangular sides that strictly follow 10-minute latitude and longitude lines (along with some cases where two true 10-minute grids were combined into one grid cell with one ID value). Due to the differences in grid boundaries, there are some different ID values across v1 and v2. The GLGIS 5-minute grid GIS dataset was created in 2006 at IFR. This layer contains rectangular 5-minute grids that are true 5-minute grids, with each side of every grid representing 5-minutes of latitude or longitude. 5-minute grids were used for SCDRS in v3.2 to align with historical data reporting standards in the region, and because there are no 10-minute grids that fully cover SCDRS. 5-minute grids created by the GLGIS only exist for SCDRS, Lake Erie, and Lake Huron, and the reason for this is unknown. SCDRS grids on the Canadian side of the basin are included in v3.2 for Fisheries Division data reporting needs that may include Canadian areas of SCDRS, but these grids in Canadian waters may not represent the standard that is actively used by Canadian agencies. In order to create the v3.2 composite, grid cells from the various GIS data sources were merged together for water bodies as specified above. In v3.2 the grids are almost exactly as they appear in the source data (with minor edits such as edge matching) except where 10-minute grids 602 and 603 in Lake Erie from Version 2 were replaced with GLGIS 5-minute grids. These grids cover the transition between the Detroit River and Lake Erie, where 10-minute grids are too large for some fisheries data reporting purposes. Therefore in v3.2, the two 10-minute grids were replaced with four 5-minute grids from the GLGIS 5-minute grid dataset. ID values were kept from the 5-minute grids for the two northern cells but the two southern grids cells retain ID values from the GLGIS v2 10-minute grids (602 and 603). This was done to allow continuity with historical data that has been recorded for 10-minute grids 602 and 603, but users need to be aware that these ID values in v3.2 are now associated with 5-minute grids instead of 10-minute grids. Version 3.2 was subsequently slightly altered to create Version 3.3, which replaced the shoreline in Northern Lake Huron and slightly altered the shoreline near the Soo Locks in the St. Mary's River to match zones, closures, etc. described in the Consent Decree that were depicted with a more detailed shoreline than the v3.2 shoreline. This was done so that those zones, closures, etc. could be depicted along with the Michigan Great Lakes Grids and have alligning shoerline depictions (see Figures 13, 12 & 16 for examples of the more detailed shoreline). GIS layer was last updated 10/01/2019. Metadata last updated 10/02/2019.

Dataset

This dataset was created by Jiahua Chen

Contents

Data Summary: US states grid mask file and NOAA climate regions grid mask file, both compatible with the 12US1 modeling grid domain. Note:The datasets are on a Google Drive. The metadata associated with this DOI contain the link to the Google Drive folder and instructions for downloading the data. These files can be used with CMAQ-ISAMv5.3 to track state- or region-specific emissions. See Chapter 11 and Appendix B.4 in the CMAQ User's Guide for further information on how to use the ISAM control file with GRIDMASK files. The files can also be used for state or region-specific scaling of emissions using the CMAQv5.3 DESID module. See the DESID Tutorial and Appendix B.4 in the CMAQ User's Guide for further information on how to use the Emission Control File to scale emissions in predetermined geographical areas. File Location and Download Instructions: Link to GRIDMASK files Link to README text file with information on how these files were created File Format: The grid mask are stored as netcdf formatted files using I/O API data structures (https://www.cmascenter.org/ioapi/). Information on the model projection and grid structure is contained in the header information of the netcdf file. The output files can be opened and manipulated using I/O API utilities (e.g. M3XTRACT, M3WNDW) or other software programs that can read and write netcdf formatted files (e.g. Fortran, R, Python). File descriptions These GRIDMASK files can be used with the 12US1 modeling grid domain (grid origin x = -2556000 m, y = -1728000 m; N columns = 459, N rows = 299). GRIDMASK_STATES_12US1.nc - This file containes 49 variables for the 48 states in the conterminous U.S. plus DC. Each state variable (e.g., AL, AZ, AR, etc.) is a 2D array (299 x 459) providing the fractional area of each grid cell that falls within that state. GRIDMASK_CLIMATE_REGIONS_12US1.nc - This file containes 9 variables for 9 NOAA climate regions based on the Karl and Koss (1984) definition of climate regions. Each climate region variable (e.g., CLIMATE_REGION_1, CLIMATE_REGION_2, etc.) is a 2D array (299 x 459) providing the fractional area of each grid cell that falls within that climate region. NOAA Climate regions: CLIMATE_REGION_1: Northwest (OR, WA, ID) CLIMATE_REGION_2: West (CA, NV) CLIMATE_REGION_3: West North Central (MT, WY, ND, SD, NE) CLIMATE_REGION_4: Southwest (UT, AZ, NM, CO) CLIMATE_REGION_5: South (KS, OK, TX, LA, AR, MS) CLIMATE_REGION_6: Central (MO, IL, IN, KY, TN, OH, WV) CLIMATE_REGION_7: East North Central (MN, IA, WI, MI) CLIMATE_REGION_8: Northeast (MD, DE, NJ, PA, NY, CT, RI, MA, VT, NH, ME) + Washington, D.C.* CLIMATE_REGION_9: Southeast (VA, NC, SC, GA, AL, GA) *Note that Washington, D.C. is not included in any of the climate regions on the website but was included with the “Northeast” region for the generation of this GRIDMASK file.

A 2 kilometer terrace-density grid for the Idaho batholith study area. Number of columns is 331 and number of rows is 285. The order of the data is from the lower left to the right and then up one row.

Dr. Chwalowski, We just generated a modified version of the coarse node centered grid with split walls. Here the red and green sections you highlighted in the email have been merged. Please let me know if it is good so we can generate the rest of the grids and upload them. Thanks,

• Rajiv

National Grid - Nilai saat ini, data historis, perkiraan, statistik, grafik dan kalender ekonomi - Feb 2025.Data for National Grid including historical, tables and charts were last updated by Trading Economics this last February in 2025.

This dataset represents the Census data source used to produce the GPW v4.11 populations estimates. Pixels that have the same value reflect the same data source, most often a country or territory. General Documentation The Gridded Population of World Version 4 (GPWv4), Revision 11 models the distribution of global human population for the years 2000, 2005, 2010, 2015, and 2020 on 30 arc-second (approximately 1 km) grid cells. Population is distributed to cells using proportional allocation of population from census and administrative units. Population input data are collected at the most detailed spatial resolution available from the results of the 2010 round of censuses, which occurred between 2005 and 2014. The input data are extrapolated to produce population estimates for each modeled year.

Many geometrical schemes – or map projections – are used to represent the curved surface of the Earth on map sheets.Canada uses the Universal Transverse Mercator (UTM) system. It is called transverse because the strips run north-south rather than east-west along the equator.This data class shows a 10 km x 10 km coordinate system based on the UTM projection using the North American Datum 83 (NAD83) grid.It includes:Military Grid Reference- identifies a specific military grid reference system grid cellFire Base Map identifier- five digit identifier used by MNR’s Aviation and Forest Fire Management Program to identify a fire basemapAtlas identifier – identifies a specific grid cellUTM Map Sheet Number – ID number of a UTM mapsheetAdditional DocumentationUTM Grid - User Guide (Word)UTM 10Km Grid - Data Description (PDF)UTM 10Km Grid - Documentation (Word)StatusCompleted: production of the data has been completedMaintenance and Update FrequencyAs needed: data is updated as deemed necessaryContactOffice of the Surveyor General, landtenuremapping@ontario.ca

This dataset shows the tiling grid and their IDs for Sentinel 2 satellite imagery. The tiling grid IDs are useful for selecting imagery of an area of interest.

Sentinel 2 is an Earth observation satellite developed and operated by the European Space Agency (ESA). Its imagery has 13 bands in the visible, near infrared and short wave infrared part of the spectrum. It has a spatial resolution of 10 m, 20 m and 60 m depending on the spectral band.

Sentinel-2 has a 290 km field of view when capturing its imagery. This imagery is then projected on to a UTM grid and made available publicly on 100x100 km2 tiles. Each tile has a unique ID. This ID scheme allows all imagery for a given tile to be located.

Provenance:

The ESA make the tiling grid available as a KML file (see links). We were, however, unable to convert this KML into a shapefile for deployment on the eAtlas. The shapefile used for this layer was sourced from the Git repository developed by Justin Meyers (https://github.com/justinelliotmeyers/Sentinel-2-Shapefile-Index).

Why is this dataset in the eAtlas?:

Sentinel 2 imagery is very useful for the studying and mapping of reef systems. Selecting imagery for study often requires knowing what the tile grid IDs are for the area of interest. This dataset is intended as a reference layer. The eAtlas is not a custodian of this dataset and copies of the data should be obtained from the original sources.

Data Dictionary:

• Name: UTM code associated with each tile. For example 55KDV

National Grid - Nilai saat ini, data historis, perkiraan, statistik, grafik dan kalender ekonomi - Mar 2025.Data for National Grid including historical, tables and charts were last updated by Trading Economics this last March in 2025.

Global vector grid at 5deg x 5deg resolution