A global soil spectral grid based on space sensing
2025
Demattê, José A.M. | Rizzo, Rodnei | Rosin, Nícolas Augusto | Poppiel, Raul Roberto | Novais, Jean Jesus Macedo | Amorim, Merilyn Taynara Accorsi | Rodriguez-Albarracín, Heidy Soledad | Rosas, Jorge Tadeu Fim | Bartsch, Bruno dos Anjos | Vogel, Letícia Guadagnin | Minasny, Budiman | Grunwald, Sabine | Ge, Yufeng | Ben-Dor, Eyal | Gholizadeh, Asa | Gomez, Cécile | Chabrillat, Sabine | Francos, Nicolas | Fiantis, Dian | Belal, Abdelaziz | Tsakiridis, Nikolaos | Kalopesa, Eleni | Naimi, Salman | Ayoubi, Shamsollah | Tziolas, Nikolaos | Das, Bhabani Sankar | Zalidis, George | Francelino, Marcio Rocha | Mello, Danilo Cesar De | Hafshejani, Najmeh Asgari | Peng, Yi | Ma, Yuxin | Coblinski, João Augusto | Wadoux, Alexandre, M. J.-C. | Savin, Igor | Malone, Brendan | Karyotis, Konstantinos | Milewski, Robert | Vaudour, Emmanuelle | Wang, Changkun | Salama, Elsayed Said Mohamed | Shepherd, Keith | Universidade de São Paulo = University of São Paulo (USP) | Sydney Institute of Agriculture ; The University of Sydney | University of Florida [Gainesville] (UF) | University of Nebraska–Lincoln ; University of Nebraska System | Tel Aviv University (TAU) | Czech University of Life Sciences Prague (CZU) | Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH) ; Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) | Indo-French Cell for Water Sciences = Cellule Franco Indienne de Recherche en Science de l’Eau (IFCWS = CEFIRSE) ; Indian Institute of Science [Bangalore] (IISc Bangalore) | German Research Centre for Geosciences - Helmholtz-Centre Potsdam (GFZ) | Leibniz Universität Hannover = Leibniz University Hannover | Andalas University | National Authority for Remote Sensing and Space Sciences (NARSS) | Aristotle University of Thessaloniki | University of Isfahan | Indian Institute of Technology Kharagpur (IIT Kharagpur) | Universidade Federal de Viçosa [Brasil] = Federal University of Viçosa [Brazil] = Université fédérale de Viçosa [Brésil] (UFV [Brésil]) | Institute of Soil Science ; Chinese Academy of Sciences [Beijing] (CAS) | Department of Science and Technology and Climate Change of China Meteorological Administration ; China Meteorological Administration (CMA) | Institute of Soil Science and Plant Cultivation (IUNG) | Dokuchaev Soil Science Institute (SSI) ; Russian Academy of Agricultural Sciences | CSIRO Agriculture and Food (CSIRO AF) ; Commonwealth Scientific and Industrial Research Organisation [Australia] (CSIRO) | Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS) ; AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Université russe de l'amitié des peuples = People's Friendship University of Russia = Rossijskij universitet družby narodov [Moscou] (RUDN) | Innovative Solutions for Decision Agriculture | First Author ackowledge the CNPq for a researcher scholarship. The authors would like to express their gratitude to the S˜ao Paulo ResearchFoundation (FAPESP) for the financial support provided through grant number 2021/05129-8. The authors also wish to thank researchers andinstitutions in other countries for providing data. We thank the GeoCiS research group https://esalqgeocis.wixsite.com/english for technical support.
International audience
Show more [+] Less [-]English. Soils provide a range of essential ecosystem services for sustaining life, including climate regulation. Advanced technologies support the protection and restoration of this natural resource. We developed the first fine-resolution spectral grid of bare soils by processing a spatiotemporal satellite data cube spanning the globe. Landsat imagery provided a 30 m composite soil image using the Geospatial Soil Sensing System (GEOS3), which calculates the median of pixels from the 40-year time series (1984–2022). The map of the Earth's bare soil covers nearly 90 % of the world's drylands. The modeling resulted in 10 spectral patterns of soils worldwide. Results indicate that plant residue and unknown soil patterns are the main factors that affect soil reflectance. Elevation and the shortwave infrared (SWIR2) band show the highest importance, with 78 and 80 %, respectively, suggesting that spectral and geospatial proxies provide inference on soils. We showcase that spectral groups are associated with environmental factors (climate, land use and land cover, geology, landforms, and soil). These outcomes represent an unprecedented information source capable of unveiling nuances on global soil conditions. Information derived from reflectance data supports the modeling of several soil properties with applications in soil-geological surveying, smart agriculture, soil tillage optimization, erosion monitoring, soil health, and climate change studies. Our comprehensive spectrally-based soil grid can address global needs by informing stakeholders and supporting policy, mitigation planning, soil management strategy, and soil, food, and climate security interventions
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