Assessment of Slope Indicators for Agricultural Lands with Complex Terrain
Musurmankulova Shaxlo Axmedovna , Republic of Uzbekistan, Tashkent “Uzdavyerloyikha” State Scientific-Design Institute Doctoral Studies Student, UzbekistanAbstract
This study assesses slope indicators of agricultural lands with complex terrain in the Tashkent region of Uzbekistan using GIS and remote sensing technologies. The Perfect Slope web platform was developed by integrating digital elevation models, Sentinel-2 imagery, precipitation, and land-cover data within the ArcGIS Pro environment. To evaluate the platform's accuracy, field measurements were conducted at 200 geodetic points, including slope observations at 100 locations, and compared with remotely derived data. The results showed a strong correlation between field and remote measurements (r ≥ 0.94), while the maximum slope estimation error did not exceed 1.2°. Statistical evaluation using MSE, RMSE, and R² confirmed high accuracy for gentle slopes and acceptable performance for steeper terrain. The developed platform provides a reliable tool for slope assessment, land suitability analysis, and sustainable agricultural land management in areas with complex relief.
Keywords
Degree of slope, agricultural areas, platform
References
K. A. Al-Gaadi, E. Tola, R. Madugundu, and R. Fulleros, “Sentinel-2 Images for Effective Mapping of Soil Salinity in Agricultural Fields,” Curr. Sci., vol. 121, p. 0384, Aug. 2021, doi: 10.18520/cs/v121/i3/384-390.
B. Alikhanov, S. Alikhanova, R. Oymatov, Z. Fayzullaev, and A. Pulatov, “Land cover change in Tashkent province during 1992-2018,” presented at the IOP Conference mSeries: Materials Science and Engineering, 2020. doi: 10.1088/1757-899X/883/1/012088.
I. Aslanov et al., “Applying remote sensing techniques to monitor green areas in Tashkent Uzbekistan,” E3S Web Conf., vol. 258, p. 04012, Jan. 2021, doi:10.1051/e3sconf/202125804012.
B. Sh. Matyakubov, Z. J. Mamatkulov, R. K. Oymatov, U. N. Komilov, and G. E.Eshchanova, “Assessment of the reclamation conditions of irrigated areas by geospatial analysis and recommendations for their improvement,” presented at the InterCarto, InterGIS, 2020, pp. 229–239. doi: 10.35595/2414-9179-2020-3-26-229-239.
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Applied Sciences
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