Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV) on the Chinese Loess Plateau
Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV) on the Chinese Loess Plateau
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DOI：
10.3390/ijgi5120238
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发表时间：
2016-12
期刊：
影响因子：
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通讯作者：
Kai Liu;Hu Ding;G. Tang;J. Na;Xiaoli Huang;Zhengguang Xue;Xin Yang;Fayuan Li
中科院分区：
文献类型：
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作者：
Kai Liu;Hu Ding;G. Tang;J. Na;Xiaoli Huang;Zhengguang Xue;Xin Yang;Fayuan Li
黄土高原是一个集自然和人为因素于一体的流域，沟蚀严重。沟壑区检测是该地区沟壑侵蚀评价与监测的基础工作。首次应用无人机对该地区的沟壑特征进行了提取。选取长武和安塞两个典型小流域分别代表黄土塬区和黄土丘陵区。使用配备有非公制相机的高功率四轴飞行器（md 4 -1000）进行图像采集。InPho和MapMatrix应用于半自动工作流程，包括空中三角测量和模型生成。基于立体成像和地面控制点，生成高精度的数字高程模型（DEM）和正射镶嵌图。随后，一个基于对象的方法结合随机森林分类器的设计，以检测冲沟影响的地区。通过两个实验研究了分割策略和特征选择对图像分割效果的影响。结果表明，垂直和水平均方根误差分别小于0.5和0.2米，这是理想的黄土高原地区。长武和安塞的总体提取精度分别为84.62%和86.46%，这表明了所提出的工作流程提取沟壑特征的潜力。研究表明，无人机技术可以弥补野外测量与卫星遥感之间的差距，在流域尺度沟蚀研究中实现分辨率与效率的平衡。
The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully-affected areas detection is the basic work in this region for gully erosion assessment and monitoring. For the first time, an unmanned aerial vehicle (UAV) was applied to extract gully features in this region. Two typical catchments in Changwu and Ansai were selected to represent loess tableland and loess hilly regions, respectively. A high-powered quadrocopter (md4-1000) equipped with a non-metric camera was used for image acquisition. InPho and MapMatrix were applied for semi-automatic workflow including aerial triangulation and model generation. Based on the stereo-imaging and the ground control points, the highly detailed digital elevation models (DEMs) and ortho-mosaics were generated. Subsequently, an object-based approach combined with the random forest classifier was designed to detect gully-affected areas. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The overall extraction accuracy in Changwu and Ansai achieved was 84.62% and 86.46%, respectively, which indicated the potential of the proposed workflow for extracting gully features. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.