Comparative Analysis of Gully Morphology Extraction Suitability Using Unmanned Aerial Vehicle and Google Earth Imagery

被引:4
|
作者
Zhang, Chunmei [1 ,2 ]
Wang, Chunmei [1 ,2 ]
Long, Yongqing [1 ,2 ]
Pang, Guowei [1 ,2 ]
Shen, Huazhen [1 ,2 ]
Wang, Lei [1 ,2 ]
Yang, Qinke [1 ,2 ]
机构
[1] Northwest Univ, Coll Urban & Environm Sci, Shaanxi Key Lab Earth Surface Syst & Environm Carr, Xian 710127, Peoples R China
[2] Natl Forestry & Grassland Adm, Key Lab Ecohydrol & Disaster Prevent Arid Reg, Xian 710048, Peoples R China
基金
中国国家自然科学基金;
关键词
gully; accuracy; field measurement; high-resolution remote sensing image; LOESS PLATEAU; EROSION; ACCURACY; RESOLUTION; REGION; 3D;
D O I
10.3390/rs15174302
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Gully erosion is considered to be a highly destructive form of soil erosion, often leading to the occurrence of natural calamities like landslides and mudslides. Remote sensing images have been extensively utilized in gully erosion research, and the suitability of extracting gully morphology parameters in various topographic regions needs to be clarified. Based on field measurements, this paper focuses on two widely used high-resolution remote sensing images: Unmanned Aerial Vehicle (UAV) and Google Earth (GE) imagery. It systematically examines the accuracy of gully morphological characteristic extraction using remote sensing in two regions with different terrain characteristics. The results show the following: (1) Compared to interpreting wide gullies with unclear shoulder lines, centimeter-level UAV imagery is more suitable for interpreting narrow gullies with clear shoulder lines. Conversely, the interpretability of sub-meter-level GE imagery is exactly the opposite. (2) The error in interpreting gully head points (GHPs) based on UAV images is less than 1 m, while the errors in gully length (GL), width (GW), perimeter (GP) and area (GA) are all below 3%, and these errors are hardly affected by gully morphology. (3) The error of GHPs based on GE images is concentrated within the range of 1-3 m. Meanwhile, the errors associated with GL, GP and GA are less than 10%. Conversely, the error of GW exceeds 11%. Furthermore, the aforementioned errors tend to increase as the gully width decreases and the complexity of the gully shoulder line increases. These findings shed light on the suitability of two commonly used remote sensing images for gully morphology extraction and provide valuable guidance for image selection in future research endeavors in this field.
引用
收藏
页数:20
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