Mapping bare ground in New Zealand hill-country agriculture and forestry for soil erosion risk assessment: An automated satellite remote-sensing method

North, Heather; Amies, Alexander C.; Dymond, J. R.; Belliss, S.E.; Pairman, D.; Drewry, John; Schindler, Jan; Shepherd, James D.

doi:10.1016/j.jenvman.2021.113812

Cited by 11 publications

(1 citation statement)

References 35 publications

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“…Several studies have resulted in fast and accurate outputs when using UAV for erosional feature modeling and mapping in remote and complex regions [32][33][34][35][36][37][38][39]. Although UAV data have recently been used to calculate erosional landforms [8,40], these studies calculated soil losses using three different images.…”

Section: Introductionmentioning

confidence: 99%

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

Kariminejad,

Kazemi Garajeh,

Hosseinalizadeh

et al. 2023

Drones

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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.

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