Digital soil mapping predicted on mid-infrared (MIR) spectroscopy measurements in North-Western Kurdistan region, Iraq (netCDF and GeoTIFF files) V2.0 - Mathias Bellat; Benjamin Glissmann; Tobias Rentschler; Paola Sconzo; Peter Pfälzner; Bekas Brifkany; Thomas Scholten (PANGAEA, 2025)
Soil information is valuable for many disciplines (e.g. agriculture, geomorphology, geology, archaeology) and can be used to produce maps or statistics on soil productivity. As part of the project CRC1070 ResourceCulture, we collected information on the soil quality in the Dohuk province of the Kurdistan region of Iraq. In total, 561 samples were collected at 136 locations in 2017, 2018, 2022, and 2023. These samples were collected at different depth increments (0 - 10, 10 - 30, 30 - 50, 50 - 70 and 70 - 100 cm) with an auger before being prepared and measured with mid-infrared (MIR) spectroscopy. Part of these samples (109) were selected to be analyzed in a laboratory, measuring texture, pH, organic and total carbon, nitrogen, sulfur, electrical conductivity, bulk density and calcium carbonate. A Cubist model was used to predict the remaining samples based on the MIR spectra. We then modelled digital soil mapping with machine learning methods (ensemble learning, linear regression, decision trees) for these soil components. Additionally, we mapped the soil depth using the information collected in the field.