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.


    Access

    Download


    Export, share and cite



    Title :

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




    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Use of Unmanned Aerial Vehicles for Imaging and Remote Sensing

    Durmuş, Alpaslan / Duymaz, Erol | Springer Verlag | 2023


    Remote sensing unmanned aerial vehicle

    LUO YONGQI / ZHANG WEI | European Patent Office | 2024

    Free access

    Remote sensing unmanned aerial vehicle

    LI CHUNYU / TAN ZHANMING / ZHANG YUAN et al. | European Patent Office | 2021

    Free access

    Remote sensing reconnaissance system with cooperation of multiple unmanned aerial vehicles

    ZHANG CHAO / WU SHUANG / XU YING et al. | European Patent Office | 2023

    Free access