SIRIUS - Synthesized Inventory of CRitical Infrastructure and HUman-Impacted Areas in Permafrost Regions of AlaSka

The SIRIUS inventory integrates data from (i) the Sentinel-1/2 derived Arctic coastal human impact dataset (SACHI) (Bartsch et al., 2021), (ii) OpenStreetMap dataset for the infrastructure and land use information (OpenStreetMap Contributors and Geofabrik GmbH, 2018), (iii) the pan-Arctic catchments summary database (ARCADE) for the watersheds (Speetjens et al., 2022), (iv) the modeled Northern Hemisphere permafrost map by Obu et al. (2018), and (v) the contaminated sites database and reports by the State of Alaska Department of Environmental Conservation (2023) (DEC) to create a unified new dataset of critical infrastructure and human-impacted areas as well as permafrost and watershed information for Alaska.

The dataset is deployed as a GeoPackage and can be imported to spatial databases (e.g. PostgreSQL/PostGIS), a Geographic Information System (e.g. QGIS), and used within geospatial processing libraries (e.g. Python's GeoPandas). All layers can be queried either in dependence or combination with one another.

Each GeoPackage contains the following layers:

ARCADE_WatershedsDB

DEC_ContaminatedSitesAK

OSM_Point_InfrastructureHIElements

SACHI_OSM_InfrastructureHIElements

SACHI_OSM_InfrastructureHIElements_RRNetwork

UiO_MAGT

UiO_PermafrostProbability

UiO_PermafrostZones

A corresponding manuscript, including application examples and a thorough description of the individual components, was submitted to be published in an open-access journal.

Download Data

Python Scripts

01_InfrastructureDataETL: reprojects the input Shapefiles and raster datasets to a common coordinate system (EPSG:5936) and then clips datasets to the boundary of Alaska. It also includes a step for filtering the permafrost probability raster dataset based on a minimum probability threshold of 50% and rounds the values in the mean annual ground temperature raster dataset.

02_OSM-aggregation: processes the OpenStreetMap (OSM) geospatial data. It imports and merges OSM polygon and point data, cleans and extracts unique values of "fclass" and "osm_type", and aggregates these values for manual categorization, based on the OSM key-value-scheme. The script assigns Land Use/Cover Area frame Statistical Survey (LUCAS) categories to the data, filters out natural objects and places, and resolves unknown categories by identifying intersections between datasets.

03_SACHI-aggregation: assigns LUCAS categories to the SACHI dataset based on the 'Use' column.

04_SACHI-OSM_decisiontree: performs a series of geospatial operations to determine the overlap between polygonal OSM features and SACHI features and assigns LUCAS categories to the overlapping features based on certain criteria and dissolves them. The overlapping and non-overlapping features are then combined into a single dataset: the harmonized critical infrastructure and human-impacted areas dataset.

05_TextMiningNLTK-CSSites: performs text mining and data preprocessing on the reports of the DEC contaminated sites database. It extracts dates, calculates cleanup times for inactive sites, identifies contaminants based on abbreviations and text entries, and extracts information related to contaminants and the medium they are found in.

GeoPackages

PermaRisk_RRNetworkLine_v01_r00.gpkg contains the rail and road network as line geometries.

PermaRisk_RRNetworkPolygonal_v01_r00.gpkg contains the rail and road network as polygon geometries.