Mapping and Monitoring Spatio-Temporal Patterns of Rainfed Agriculture Lands of North Darfur State, Sudan, Using Earth Observation Data

Mohammed B. Altoom (), Elhadi Adam and Khalid Adem Ali
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Mohammed B. Altoom: Faculty of Science, School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South Africa
Elhadi Adam: Faculty of Science, School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South Africa
Khalid Adem Ali: Faculty of Science, School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South Africa

Land, 2023, vol. 12, issue 2, 1-21

Abstract: Rainfed agriculture in Northern Darfur is influenced by erratic seasonal and decadal rainfall patterns and frequent droughts. Understanding the spatio-temporal variation in rainfed agriculture is crucial for promoting food security, socio-economic stability and protecting the vulnerable ecosystem. This study aimed to investigate the spatio-temporal dynamics of rainfed agriculture in North Darfur State from 1984–2019 using multitemporal Landsat observation data. Using the random forest technique, the multitemporal images were classified into common land use/land cover classes and rainfed agriculture on goz (sandy) and wadi (seasonal river) lands. Overall accuracies were assessed using a confusion matrix. Overall accuracies were assessed using a confusion matrix has ranging between 94.7% and 96.9%, while the kappa statistics were greater than 0.90. The results showed that the high spatial variability in goz land used for rainfed agriculture increased of (889,622.46 ha) over 1994–1999, while it decreased (658,568.61 ha) over 2004–2009 south of the 232.9 mm isohyet. Rainfed cultivation of wadi lands expanded significantly of (580,515.03 ha) over 2014–2019 and decreased (182,701.8 ha) over 1994–1999, especially in the 362.8–477.2 mm isohyets (beyond the climate-adapted 500 mm isohyet agronomic dry limit). These spatial trends need further investigation as they may exacerbate both regional land degradation and disputes among farmers over scarce wadi lands. This study provides essential spatial data which are lacking owing to ongoing conflicts; this can help decision-makers formulate sustainable land use monitoring systems.

Keywords: remote sensing; Sudan; change detection; random forest classifier; land cover (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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