Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany

The dataset consists of particulate matter pollution concentration, measured in three localities - Hermsdorf, Charlottenburg and Adlershof, in Berlin, Germany.

pm25_summer_rd_30s.geojson shows the observed PM2.5 concentration in a 30 second interval.

pm25_summer.geojson shows the concentrations shown is the local concentration (observed concentration - background concentration) in a 30 second interval. The background concentration is calculated as the lowest 5 percentile of the measured concentration for each measurement round. 

PM2.5_lc_max.geojson contains the information from pm25_summer.geojson in a 25m resolution. Additionally, it contains the land use information for each coordinate.

The original publication providing all necessary background information on study sites, methodology and data processing is the following: Venkatraman Jagatha, J., T. Sauter, C. Schneider (2024): Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany. MDPI Sensors, 24(13), 4193, DOI: 10.3390/s24134193. The paper is fully open access and can be downloaded at https://doi.org/10.3390/s24134193.

Information on working with geojson file can be found under GeoJSON .