20.500.12556/RUL-169951 Hyperspectral soil heavy metal prediction via privileged-informed residual correction This study integrates hyperspectral remote sensing with chemical and pedological data to estimate Zn, Pb, and Cd concentrations in the upper soil layers. Conducted in agricultural fields east and northeast of Celje, Slovenia, an area impacted by past industrial activities such as zinc ore smelting, the research integrates remote sensing and soil sampling to rapidly identify and map soil pollution over large surfaces. A multi-sensor approach was employed, combining two hyperspectral cameras (VNIR and SWIR, aerial), laboratory spectrometry, soil parameters, and content of chemical covariates measured with portable XRF and ICP-OES with a direct comparison of both techniques for this specific purpose. Accurate atmospheric and signal transformations were performed to improve modeling. The importance of covariates was thoroughly evaluated using conditional permutations to assess their contribution to the prediction of metal concentrations. The proposed framework utilizes spectral data and privileged information during training, improving prediction accuracy through a multi-stage model architecture. Here, a base model trained on spectral data is corrected using privileged information. During inference, the model functions without relying on privileged data providing a scalable and cost-effective solution for large-scale environmental monitoring. Our model achieved a reduction of predicted RMSE for Zn and Cd maps in comparison to the baseline models, translating to more precise identification of possibly polluted zones. However, for Pb, no improvements were observed, potentially due to variability in the data, including spectral issues or imbalances in the training and test datasets. hyperspectral imagery aerial remote sensing imaging spectroscopy digital soil mapping pedometric mapping onesnaženost tal environmental monitoring residual modeling hiperspektralni posnetki daljinsko zaznavanje iz zraka slikovna spektroskopija digitalno kartiranje tal pedometrično kartiranje onesnaženost tal okoljsko spremljanje modeliranje ostankov true false true Angleški jezik Slovenski jezik Članek v reviji 2025-06-26 08:46:09 2025-06-26 08:46:11 2025-06-27 03:54:55 0000-00-00 00:00:00 2025 0 0 32 str. iss. 12, art. 1987 Vol. 17 Jun 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 504 2072-4292 10.3390/rs17121987 240480259 remotesensing-17-01987-v2.pdf remotesensing-17-01987-v2.pdf 1 9C3FD552E1D02285CBEEAFBA1FF8231E 1b8543bc9e845918d57ee3c03f372506d2c6e56ef62f9b0703d8bb2b11866cfe fc4bec56-5257-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211775 https://www.mdpi.com/2072-4292/17/12/1987 1 5ff4006e-5257-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211774 Fakulteta za gradbeništvo in geodezijo Fakulteta za kemijo in kemijsko tehnologijo Biotehniška fakulteta 0 0 0