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UID:pretalx-soil-health-now-2026-N7PAPF@pretalx.earthmonitor.org
DTSTART;TZID=Europe/Athens:20261208T141500
DTEND;TZID=Europe/Athens:20261208T143000
DESCRIPTION:In the framework of carbon farming\, remote sensing (RS) is use
 d to produce soil property maps for the upscaling of soil carbon stocking 
 potentials\, as modeled in in-field simulations. Reducing the uncertainty 
 of the soil maps produced is a key element to obtain reliable upscaling pr
 oducts and finally calculate credible carbon credit potentials of the inte
 rested territories. The MRV4SOC project have tested the in-situ simulation
  of a RothC model in 3 demonstration sites in central-northern Italy\, to 
 calculate carbon credits of croplands and agroforestry. The soil input par
 ameters used were soil organic carbon stock of the first 30 cm depth\, and
  soil textural fractions\, clay and sand. The MRV4SOC project has tested d
 ifferent procedures to produce soil map input parameters by remote sensing
 \, such as: 1) a calibration of the bare soil composite of Europe SoilSuit
 e (SRC)\, 2) a calibration of Sentinel and ENMAP spectral libraries using 
 local field and lab-collected soil spectral libraries with VNIR spectrorad
 iometers\, and 3) a calibration of the SRC using a data augmentation strat
 egy. AI models used for each calibration cases were: for case 1) quantile 
 random forest (QRF) models\, for case 2) XGBoost models\, and for case 3) 
 QRF and convolutional neural networks (CNN). The three strategies showed h
 igh calibration performance\, but validation performance differs based on 
 the model and strategy used\, as well as the uncertainty of products.\n\nA
 uthors: Carlos Lozano Fondon\, carlos.lozanofondon@crea.gov.it\; Kevin Kü
 elh\, kevin.kuehl@dlr.de\; Dimitra Palanza\, dpalant@auth.gr\; Konstantino
 s Karyotis\, kkaryiotis@auth.gr\; Costanza Andrenelli\,  mariacostanza.and
 renelli@crea.gov.it\; Roberto Barbetti\, roberto.barbetti@crea.gov.it\; Ma
 ria Fantappiè\, maria.fantappie@crea.gov.it.
DTSTAMP:20260825T175942Z
LOCATION:Amphitheater II
SUMMARY:A comparison of model performances and uncertainty of soil remote s
 ensing products calibration for large-scale carbon farming accounting - Ma
 ria Fantappiè\, Carlos Lozano Fondón
URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/N7PAPF/
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