Mapping soil suitability using phenological information derived from MODIS time series data in a semi-arid region: A case study of Khouribga, Morocco
Maryem Ismaili,
Samira Krimissa,
Mustapha Namous,
Kamal Abdelrahman,
Abdelghani Boudhar,
Mohamed Edahbi,
Youssef Lebrini,
Abdelaziz Htitiou,
Soufiane Maimouni,
Tarik Benabdelouhab
Affiliations
Maryem Ismaili
Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco; National Agronomic Research Institute, Rabat, Morocco; Corresponding author. Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco.
Samira Krimissa
Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco
Mustapha Namous
Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco
Kamal Abdelrahman
Department of Geology & Geophysics, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia
Abdelghani Boudhar
Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco
Mohamed Edahbi
Superior School of Technology Fkih Ben Salah, Sultan Moulay Slimane University, Morocco; University of Quebec in Abitibi-Témiscamingue (UQAT), Rouyn-Noranda, J9X 5E4, QC, Canada
Youssef Lebrini
Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco
Abdelaziz Htitiou
Data4Earth Laboratory, Faculty of Sciences and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco
Soufiane Maimouni
Laboratory of Applied Geology, Geoinformatic and Environment, Department of Geology, Faculty of Sciences Ben M’sik, Hassan II University of Casablanca, B.P. 7955, Sidi Othmane, Casablanca, Morocco
Tarik Benabdelouhab
National Agronomic Research Institute, Rabat, Morocco
To address the increasing global demand for food, it is crucial to implement sustainable agricultural practices, which include effective soil management techniques for enhancing productivity and environmental conditions. In this regard, a study was conducted to assess the efficacy of utilizing phenological metrics derived from satellite data in order to map and identify suitable agricultural soil within a semi-arid region. Two distinct methodologies were compared: one based on physicochemical soil parameters and the other utilizing the phenological response of vegetation through the application of the Normalized Difference Vegetation Index (NDVI) Modis-time series. The study findings indicated that the NDVI-based approach successfully identified a specific class of soil suitability for agriculture (referred to as S1) that could not be effectively mapped using the multi-criteria analysis (MCAD) method relying on soil physicochemical parameters. This S1 class of soil suitability accounted for approximately 5 % of the total study area. These outcomes suggest that phenological-based approaches offer greater potential for spatio-temporal monitoring of soil suitability status compared to MCAD, which heavily relies on discrete observations and necessitates frequent updates of soil parameters. The approach developed to map the soil-suitability is a valuable tool for sustainable agricultural development, and it can play an effective role in ensuring food security and conducting a land agriculture assessment.
