Harnessing the Power of Remote Sensing and Unmanned Aerial Vehicles: A Comparative Analysis for Soil Loss Estimation on the Loess Plateau

Author:

Kariminejad Narges1,Kazemi Garajeh Mohammad2ORCID,Hosseinalizadeh Mohsen3ORCID,Golkar Foroogh4,Pourghasemi Hamid Reza5ORCID

Affiliation:

1. Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz 71441-13131, Iran

2. Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, 00138 Rome, Italy

3. Department of Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan 49138-15739, Iran

4. Department of Water Engineering & Oceanic and Atmospheric Research Center, College of Agriculture, Shiraz University, Shiraz 71441-13131, Iran

5. Department of Soil Science, College of Agriculture, Shiraz University, Shiraz 71441-13131, Iran

Abstract

This study explored the innovative use of multiple remote sensing satellites and unmanned aerial vehicles to calculate soil losses in the Loess Plateau of Iran. This finding emphasized the importance of using advanced technologies to develop accurate and efficient soil erosion assessment techniques. Accordingly, this study developed an approach to compare sinkholes and gully heads in hilly regions on the Loess Plateau of northeast Iran using convolutional neural network (CNN or ConvNet). This method involved coupling data from UAV, Sentinel-2, and SPOT-6 satellite data. The soil erosion computed using UAV data showed AUC values of 0.9247 and 0.9189 for the gully head and the sinkhole, respectively. The use of SPOT-6 data in gully head and sinkhole computations showed AUC values of 0.9105 and 0.9123, respectively. The AUC values were 0.8978 and 0.9001 for the gully head and the sinkhole using Sentinel-2, respectively. Comparison of the results from the calculated UAV, SPOT-6, and Sentinel-2 data showed that the UAV had the highest accuracy for calculating sinkhole and gully head soil features, although Sentinel-2 and SPOT-6 showed good results. Overall, the combination of multiple remote sensing satellites and UAVs offers improved accuracy, timeliness, cost effectiveness, accessibility, and long-term monitoring capabilities, making it a powerful approach for calculating soil loss in the Loess Plateau of Iran.

Funder

College of Agriculture, Shiraz University

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

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