{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T09:38:56Z","timestamp":1775381936067,"version":"3.50.1"},"reference-count":99,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,20]],"date-time":"2022-08-20T00:00:00Z","timestamp":1660953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Quickly and correctly mapping soil nutrients significantly impact accurate fertilization, food security, soil productivity, and sustainable agricultural development. We evaluated the potential of the new PRISMA hyperspectral sensor for mapping soil organic matter (SOM), available soil phosphorus (P2O5), and potassium (K2O) content over a cultivated area in Khouribga, northern Morocco. These soil nutrients were estimated using (i) the random forest (RF) algorithm based on feature selection methods, including feature subset evaluation and feature ranking methods belonging to three categories (i.e., filter, wrapper, and embedded techniques), and (ii) 107 soil samples taken from the study area. The results show that the RF-embedded method produced better predictive accuracy compared with the filter and wrapper methods. The model for SOM showed moderate accuracy (Rval2 = 0.5, RMSEP = 0.43%, and RPIQ = 2.02), whereas that for soil P2O5 and K2O exhibited low efficiency (Rval2 = 0.26 and 0.36, RMSEP = 51.07 and 182.31 ppm, RPIQ = 0.65 and 1.16, respectively). The interpolation of RF-residuals by ordinary kriging (OK) methods reached the highest predictive results for SOM (Rval2 = 0.69, RMSEP = 0.34%, and RPIQ = 2.56), soil P2O5 (Rval2 = 0.44, RMSEP = 44.10 ppm, and RPIQ = 0.75), and soil K2O (Rval2 = 0.51, RMSEP = 159.29 ppm, and RPIQ = 1.34), representing the best fitting ability between the hyperspectral data and soil nutrients. The result maps provide a spatially continuous surface mapping of the soil landscape, conforming to the pedological substratum. Finally, the hyperspectral remote sensing imagery can provide a new way for modeling and mapping soil fertility, as well as the ability to diagnose nutrient deficiencies.<\/jats:p>","DOI":"10.3390\/rs14164080","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T01:56:40Z","timestamp":1661133400000},"page":"4080","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Using PRISMA Hyperspectral Satellite Imagery and GIS Approaches for Soil Fertility Mapping (FertiMap) in Northern Morocco"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3538-111X","authenticated-orcid":false,"given":"Anis","family":"Gasmi","sequence":"first","affiliation":[{"name":"Center for Remote Sensing Application (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2986-430X","authenticated-orcid":false,"given":"C\u00e9cile","family":"Gomez","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Etude des Interactions entre Sol-Agrosyst\u00e8me-Hydrosyst\u00e8me (LISAH), University of Montpellier, INRAE, IRD, Montpellier SupAgro, 34060 Montpellier, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0270-1690","authenticated-orcid":false,"given":"Abdelghani","family":"Chehbouni","sequence":"additional","affiliation":[{"name":"Center for Remote Sensing Application (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco"},{"name":"International Water Research Institute (IWRI), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco"},{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re (CESBIO), Institut de Recherche pour le D\u00e9veloppement (IRD), CNES, CNRS, INRAE, UPS, Universit\u00e9 de Toulouse, CEDEX 09, 31401 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8431-9649","authenticated-orcid":false,"given":"Driss","family":"Dhiba","sequence":"additional","affiliation":[{"name":"International Water Research Institute (IWRI), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco"}]},{"given":"Mohamed","family":"El Gharous","sequence":"additional","affiliation":[{"name":"Agricultural Innovation and Technology Transfer Center (AITTC), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,20]]},"reference":[{"key":"ref_1","unstructured":"Marschner, H. 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