The data in feature service include points, lines and polygon areas within South Carolina that the Council of Governments identified as priority areas

The towns of Connecticut (CT) Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2022 are part of a zipped file containing two items: CT parcels in geodatabases organized by COGs and associated CAMA files. The parcel information includes 169 out of 169 town organized with geodatabases for each of the 9 Council of Governments. Most of the parcel data sets can be linked to the CAMA data which has attribute information (e.g. value of house, number of bedrooms) about real property. The parcel features for each town are in shape files, feature classes, or within a geodatabase. Most parcels are organized by town and COG and placed within a geodatabases. The CAMA data sets have information about real property within the towns of CT. It may be linked to the parcels using a join process within a GIS package like ArcGIS Pro or QGIS. 154 out of 169 towns have complete CAMA information. Of the remaining 15 towns, four have no information and the remaining have some limited information mixed into the parcel attribute tables. These files were gathered from the CT towns by the COGs and then submitted to CT OPM. Town data is organized by COG. Attribute names, primary key, secondary key, naming conventions, and file formats are not fully consistent but some cleaning and reorganization was conducted to improve quality. This file was created on 03/08/2023 from data collected in 2021-2022.

A public feature layer view used in the Performance Management and Performance Management Mobile dashboards to monitor key performance indicators (KPIs).

Councils of Government (COG) boundaries for the state of Oklahoma.

Overview:
The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters.

The Copernicus DEM for Europe at 1000 meter resolution (EU-LAEA projection) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/).

Processing steps:
The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in VRT format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized:

gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt

In order to reproject the data to EU-LAEA projection while reducing the spatial resolution to 1000 m, bilinear resampling was performed in GRASS GIS (using r.proj and the pixel values were scaled with 1000 (storing the pixels as Integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using r.relief, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.

Projection + EPSG code:
ETRS89-extended / LAEA Europe (EPSG: 3035)

Spatial extent:
north: 6874000
south: -485000
west: 869000
east: 8712000

Spatial resolution:
1000 m

Pixel values:
meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)

Software used:
GDAL 3.2.2 and GRASS GIS 8.0.0 (r.proj; r.relief)

Original dataset license:
https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf

Processed by:
mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM for Europe at 30 meter resolution (EU-LAEA projection) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/). Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in https://gdal.org/drivers/raster/vrt.html format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt In order to reproject the data to EU-LAEA projection, bilinear resampling was performed in GRASS GIS (using r.proj) and the pixel values were scaled with 1000 (storing the pixels as Integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using r.relief, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files. Note that GLO-30 Public provides limited coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs.

Data set includes polygons depicting an area’s General Plan designation with a table providing General Plan codes (abbreviations), legends, type descriptions as well as area, acreage and perimeter values.

This archive contains all spatial data from the 2017 Forest Atlas of the Congo.

This archive contains all spatial data from the 2016 Forest Atlas of the Congo.

This metadata record describes a set of raster maps representing soil carbon content in agricultural areas of Andalusia, Spain. The dataset includes values for both organic carbon (COS) and inorganic carbon (CIC) at two depth intervals: 0–30 cm and 30–60 cm. These maps were generated using digital soil mapping techniques based on field sampling (684 locations) and a range of environmental predictors (e.g., climate, land use, topography, vegetation indices). Machine learning models (QRF, MLR, AML) were applied to produce high-resolution predictions (90 m). The data are provided in Cloud Optimized GeoTIFF (COG) format, allowing efficient access, visualization, and download via HTTP range requests. The service is maintained within the GIS infrastructure of LifeWatch ERIC and integrated in the Andalusian Environmental Information Network (REDIAM).

GlendaleOne provides access to non-emergency services and city services information to Glendale residents. For every service that can be requested through GlendaleOne the responsible department has established the time frame that a standard request type should take to be completed. If the service is not completed within that time the request is automatically escalated to the next level of supervision. This escalation pattern continues until the request reaches the City Manager's office. This data set shows the number of days/hours until the first escalation will occur. Requests that are placed on hold will not escalate until the hold is removed.

This archive contains all spatial data from the 2011 Interactive Forest Atlas of the Congo.

This dataset demarcates the municipal boundaries in Allegheny County. Data was created to portray the boundaries of the 130 Municipalities in Allegheny County the attribute table includes additional descriptive information including Councils of Government (COG) affiliation (regional governing and coordinating bodies comprised of several bordering municipalities), School District, Congressional District, FIPS and County Municipal Code and County Council District.

This dataset is harvested on a weekly basis from Allegheny County’s GIS data portal. The full metadata record for this dataset can also be found on Allegheny County's GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the "Explore" button (and choosing the "Go to resource" option) to the right of the "ArcGIS Open Dataset" text below.

Category: Civic Vitality and Governance

Department: Geographic Information Systems Group; Department of Administrative Services

This dataset contains statewide CAMA information for the parcels in Connecticut, created by the GIS office in accordance with CGS Sec. 4d-90-92 and 7-100L. It is part of the 2024 data collection effort, which involved gathering CAMA data from all municipalities through the Council of Governments. The parcel layer is provided as a zipped folder containing a File Geodatabase, encompassing information from all 169 towns organized into a seamless parcel layer. The CAMA dataset include details about real property within Connecticut towns, which can be linked to the parcel data using a GIS software. The linking is facilitated through a designated column called ‘link’ that contains unique codes for each town and the designated values provided by the assessors and COGs. While the data was gathered from Connecticut towns and submitted to CT OPM by the COGs, it’s important to note that not all towns adhered to the established schema. As a result, some attribute names, primary and secondary keys, naming conventions, and file formats were inconsistent. Cleaning and reorganization were performed to align the data with the state schema, though some limitations remain. This file was generated on 09/28/2024 from data collected throughout 2024. Additional Note: Some towns were unable to verify which entries were suppressed pursuant to Connecticut General Statute Sec. 1-217. As a result, all related information has been fully suppressed. The owner and co-owner fields have been replaced with "Current Owner" and "Current Co-Owner," respectively, and the mailing address has been updated to reflect the location address.

The sixteen regional councils in North Carolina serve their member governments through a broad range of services. Some of those are traditional: delivery of federal and state programs in aging, transportation planning, workforce development, community planning – GIS mapping services and convening of regional leaders for problem solving. A more robust range of services has emerged through member demand for administrative and financial services, interim executive management, financial administration, human services program delivery and economic development.For more informaiton, visit https://www.ncregions.org/regional-councils/

The State of Indiana Geographic Information Office (GIO) has published a State-wide Digital Aerial Imagery Catalog consisting of orthoimagery files from 2016-2019 in Cloud-Optimized GeoTIFF (COG) format on the AWS Registry of Open Data Account. These COG formatted files support the dynamic imagery services available from the GIO ESRI-based imagery solution. The Open Data on AWS is a repository of publicly available datasets for access from AWS resources. These datasets are owned and maintained by the Indiana GIO. These images are licensed by Creative Commons 0 (CC0). Cloud Optimized GeoTIF behaves as a GeoTIFF in all products; however, the optimization becomes apparent when incorporating them into web services.

City of Glendale Recycling boundaries, schedule, contact information and website: https://www.glendaleaz.com/sanitation/

The Web Map Name Is:Performance ManagementThe Layers in this app are:Couldn't get the list

City of Glendale Zoning polygons, maintained by Development Services.

In an effort to integrate information from a wide range of data sets into a single spatially referenced grid that can be used as an annotated spatial index of data layers, facilitate data discovery, and enhance research, personnel at the Kansas Biological Survey at the University of Kansas developed the Nested Hexagon Framework (NHFv2). The NHFv2 is comprised of four nested spatial scale mapping units (1 km2 Hexagons, 7 km2 Cogs, 49 km2 Wheels, and 343 km2 Rings) and currently covers all of North and Central America, with the potential to be expanded to other global extents due to its unique hierarchical number system and spatial tiling based around 5 degree by 5 degree latitude and longitude tiles. Data can be referenced to any of the spatial scales (hex, cog, wheel, ring) depending on the spatial precision and/or sensitivity of the data. The NHFv2 allows for the sharing of information without revealing the raw spatial data or precise spatial locations so that users can quickly get a summary of the features and conditions present in a given cell. The original version of the NHF had a similar nested structure, but was based around mapping cells using miles instead of kilometers. To be better suited for scientific integration and international applications, the process framework was rebuilt around a one square kilometer hexagon grid and renamed as NHFv2 to keep it distinct.