Water and Irrigation Management

Water and Irrigation Management

Mapping Date-palm Plantations Using Random Forest Classification and Multi-temporal in the Maroon–Jarahi Sub-basin, Khuzestan, Iran

Document Type : Research Paper

Authors
Masoud Soltani 1
Bahareh Bahman Abadi 1
Ali Mokhtaran 2
1 Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran.
2 Agricultural Engineering Research Department, Khuzestan Agricultural and Natural Resources Research and Education Center (AREEO), Ahwaz, Iran.
10.22059/jwim.2026.409960.1284
Abstract
Accurate Manitoring of date-palm plantations and reliable estimation of cultivated area are essential for water-resource management, agricultural planning and regional policy making in arid and semi-arid regions, specially in south-west of Iran. This research utilized multi-temporal, Sentinel-2, and radar, Sentinel-1 imageries and supervised classification based on random forest, to present accurate and applicable map of date-palms plantations in Maroon-Jarahi sub-basin. To address this, Sentinel-2 optical and Sentinel-1 radar time series were derieved and processed, then together with Spectral, Radar, thermal indices and collected field reference samples during the 2022-2024 agricultural seasons were applied to training process of random forest model. Classification was run based on 36 inputs including, main bands, Spectral, Radar, and thermal indices. Accuracy assessment of the Model according to independent sample test displayed that The Random Forest classifier yielded very high performance due to, overall accuracy=95%, kappa coefficient=0.94, and precision, recall and F1-score were approximately 0.99. furthermore, mapped date-palm area closely matched reference inventories, the actual area was 26197.55 ha while the mapped area was 21764.55 ha for the Random Forest result, thus approximately +1% over-estimation was derieved. The results showed that, The integration of multi-temporal and thermal indicators within a Random Forest classification framework provides an efficient, reliable and scalable method to map date-palm plantations in arid and semi-arid basins.Practically, the proposed workflow can be a validated approach for water resource management, Orchards’ health monitoring and agricultural planning in reginal and national scales.
Keywords
Classification, Date palm, Maroon&ndash
Jarahi sub-basin, Random Forest, Sentinel
Subjects
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Water and Irrigation Management
Volume 16, Issue 2
Summer 2026
Pages 371-391