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Monitoring of cropping pattern changes using Sentinel-2 Imagery and GIS applications: A case study of Varamin plain, Iran
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Jafar Kambouzia   , Azade Ghanbarzade Ghasabe , Fateme Sadat Aghamir Mohamadali |
| Environmental Sciences Research Institute Shahid Beheshti University, Tehran, Iran |
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Abstract: (37 Views) |
Introduction: In recent decades, arid and semi-arid regions of the world have experienced considerable shifts in agricultural land use, driven by chaging climate and resources limitations. In Iran, particularly in Varamin plain these transformations have included significant changes in cropping patterns, especially the conversion of rainfed fields into orchard. The primary motivations behind this change include increasing resilience to water scarcity, economic incentives, and government support programs.
Materials and Methods: This research used Sentinel-2 satellite imagery and the NDVI (Normalized Difference Vegetation Index) to monitor agricultural land-use changes from 2016 to 2022. NDVI profiles were calculated on a monthly basis and aggregated annually to reduce the effects of clouds and short-term variability. Supervised classification was performed using the Support Vector Machine (SVM) algorithm in ENVI software. Accuracy assessments were carried out for each year, using ground reference data and official agricultural reports.
Results: The findings revealed substantial declines in irrigated lands following the severe drought of 2017 (from 47% in 2016 to less than 8% in 2018), leading to a rapid increase in orchard areas, especially pistachio plantations (from 16% in 2016 to over 48% in 2018). However, a severe frost in winter 2020 led to major damage in newly established orchard, particularly those that were still young trees. Consequently, by 2022, orchard area declined sharply to approximately 17%, and rainfed cropping resurged. Classification accuracies were consistently above 80% for all years, with the highest accuracy observed in 2018 (Kappa= 0.77).
Conclusion: This study provides a spatiotemporal analysis of cropping pattern changes in Varamin plain. The findings highlight the dynamic nature of land use in response to climatic events such as drought and frost, underscoring the importance of flexible, climate-resilient planning in cropping systems. The integration of remote sensing and machine learning tools proved effective for monitoring land use trends over time.
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| Keywords: Climate change, Cropping pattern, Rainfed cropping and Remote sensing |
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Full-Text [PDF 820 kb]
(24 Downloads)
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Type of Study: Scientific & Research |
Subject:
Special
Received: 2025/07/24 | Accepted: 2025/10/14 | Published: 2026/03/30
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