scholarly journals Vine copula ensemble downscaling for precipitation projection over the Loess Plateau based on high‐resolution multi‐RCM outputs

2020 ◽  
Author(s):  
Chaoxing Sun ◽  
Guohe Huang ◽  
Yurui Fan ◽  
Xiong Zhou ◽  
Chen Lu ◽  
...  
Keyword(s):  
High Resolution ◽  
Loess Plateau ◽  
The Loess Plateau ◽  
Precipitation Projection ◽  
Vine Copula

scholarly journals OBIA-Based Extraction of Artificial Terrace Damages in the Loess Plateau of China from UAV Photogrammetry

2021 ◽  
Vol 10 (12) ◽  
pp. 805
Author(s):  
Xuan Fang ◽  
Jincheng Li ◽  
Ying Zhu ◽  
Jianjun Cao ◽  
Jiaming Na ◽  
...  
Keyword(s):  
High Resolution ◽  
Loess Plateau ◽  
Water Conservation ◽  
Ground Truth ◽  
Field Investigation ◽  
The Loess Plateau ◽  
Flow Process ◽  
Local Flow ◽  
Object Based ◽  
Damage Mapping

Terraces, which are typical artificial landforms found around world, are of great importance for agricultural production and soil and water conservation. However, due to the lack of maintenance, terrace damages often occur and affect the local flow process, which will influence soil erosion. Automatic high-accuracy mapping of terrace damages is the basis of monitoring and related studies. Researchers have achieved artificial terrace damage mapping mainly via manual field investigation, but an automatic method is still lacking. In this study, given the success of high-resolution unmanned aerial vehicle (UAV) photogrammetry and object-based image analysis (OBIA) for image processing tasks, an integrated framework based on OBIA and UAV photogrammetry is proposed for terrace damage mapping. The Pujiawa terrace in the Loess Plateau of China was selected as the study area. Firstly, the segmentation process was optimised by considering the spectral features and the terrains and corresponding textures obtained from high-resolution images and digital surface models. The feature selection was implemented via correlation analysis, and the optimised segmentation parameter was achieved using the estimation of scale parameter algorithm. Then, a supervised k-nearest neighbourhood classifier was used to identify the terrace damages in the segmented objects, and additional geometric features at the object level were considered for classification. The comparison with the ground truth, as delineated by the image and field survey, showed that proposed classification can be adequately performed. The F-measures of extraction on three terrace damages were 92.07% (terrace sinkhole), 81.95% (ridge sinkhole), and 85.17% (collapse), and the Kappa coefficient was 85.34%. Finally, the potential application and spatial distribution of the terrace damages in this study were determined. We believe that this work can provide a credible framework for mapping terrace damages in the Loess Plateau of China.

scholarly journals Accuracy Assessment of the Planar Morphology of Valley Bank Gullies Extracted with High Resolution Remote Sensing Imagery on the Loess Plateau, China

2019 ◽  
Vol 16 (3) ◽  
pp. 369 ◽  
Author(s):  
Yixian Chen ◽  
Juying Jiao ◽  
Yanhong Wei ◽  
Hengkang Zhao ◽  
Weijie Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Loess Plateau ◽  
Satellite Image ◽  
Gully Erosion ◽  
Chinese Loess Plateau ◽  
Vegetation Coverage ◽  
The Loess Plateau ◽  
Remote Sensing Imagery ◽  
Shape Complexity

Gully erosion is a serious environmental problem worldwide, causing soil loss, land degradation, silting up of reservoirs and even catastrophic flooding. Mapping gully features from remote sensing imagery is crucial for assisting in understanding gully erosion mechanisms, predicting its development processes and assessing its environmental and socio-economic effects over large areas, especially under the increasing global climate extremes and intensive human activities. However, the potential of using increasingly available high-resolution remote sensing imagery to detect and delineate gullies has been less evaluated. Hence, 130 gullies occurred along a transect were selected from a typical watershed in the hilly and gully region of the Chinese Loess Plateau, and visually interpreted from a Pleiades-1B satellite image (panchromatic-sharpened image at 0.5 m resolution fused with 2.0 m multi-spectral bands). The interpreted gullies were compared with their measured data obtained in the field using a differential global positioning system (GPS). Results showed that gullies could generally be accurately interpreted from the image, with an average relative error of gully area and gully perimeter being 11.1% and 8.9%, respectively, and 74.2% and 82.3% of the relative errors for gully area and gully perimeter were within 15%. But involving field measurements of gullies in present imagery-based gully studies is still recommended. To judge whether gullies were mapped accurately further, a standard adopting one-pixel tolerance along the mapped gully edges was proposed and proved to be practical. Correlation analysis indicated that larger gullies could be interpreted more accurately but increasing gully shape complexity would decrease interpreting accuracy. Overall lower vegetation coverage in winter due to the withering and falling of vegetation rarely affected gully interpreting. Furthermore, gully detectability on remote sensing imagery in this region was lower than the other places of the world, due to the overall broken topography in the Loess Plateau, thus images with higher resolution than normally perceived are needed when mapping erosion features here. Taking these influencing factors (gully dimension and shape complexity, vegetation coverage, topography) into account will be favorable to select appropriate imagery and gullies (as study objects) in future imagery-based gully studies. Finally, two linear regression models were built to correct gully area (Aip, m2) and gully perimeter (Pip, m) visually extracted, by connecting them with the measured area (Ams, m2) and perimeter (Pms, m). The correction models were Ams=1.021Aip+0.139 and Pms=0.949Pip+ 0.722, respectively. These models could be helpful for improving the accuracy of interpreting results, and further accurately estimating gully development and developing more effective automated gully extraction methods on the Loess Plateau of China.

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