scholarly journals Object-Oriented Landslide Mapping Using ZY-3 Satellite Imagery, Random Forest and Mathematical Morphology, for the Three-Gorges Reservoir, China

2017 ◽  
Vol 9 (4) ◽  
pp. 333 ◽  
Author(s):  
Tao Chen ◽  
John Trinder ◽  
Ruiqing Niu
Keyword(s):  
Random Forest ◽  
Mathematical Morphology ◽  
Satellite Imagery ◽  
Three Gorges Reservoir ◽  
Object Oriented ◽  
Three Gorges ◽  
The Three Gorges Reservoir ◽  
The Three Gorges ◽  
Landslide Mapping

Spatial prediction of landslides for the Wanzhou District (China) applying a hybrid intelligent method based on random forest and cluster algorithms

2020 ◽  
Author(s):  
Zizheng Guo ◽  
Kunlong Yin ◽  
Lixia Chen ◽  
Chao Zhou
Keyword(s):  
Random Forest ◽  
Landslide Susceptibility ◽  
Three Gorges Reservoir ◽  
Cluster Algorithm ◽  
Spatial Prediction ◽  
Three Gorges ◽  
Cluster Algorithms ◽  
The Three Gorges Reservoir ◽  
The Three Gorges ◽  
Hybrid Intelligent Method

<p>In the Three Gorges Reservoir area of China, landslides have caused considerable losses of lives, environmental and social economy during the last decade. Hence, landslide susceptibility mapping is an urgent task that could help local decision makers in disaster risk assessment and management. This study aims at generating a regional landslide susceptibility map for the Wanzhou District in the Three Gorges Reservoir (China), based on random forest (RT) and cluster algorithms. Specifically, our objectives mainly include: (i) comparing the performances among different machine learning approaches, and (ii) validating the accuracy of a novel susceptibility reclassification method which used cluster algorithm. First, nine GIS-based thematic maps presenting landslide causal factors were prepared, including elevation, slope angle, aspect, lithology, land use, topographic wetness index (TWI), distance to rivers, distance to roads, and distance to geological structures. Total 441 landslides in a landslide inventory map were divided into two subsets: 75% landslides were used as training data, and 25% landslides were validation data. To establish the hybrid intelligent method, random forest was employed to calculate the landslide occurrence probability at every raster cell whereas the cluster algorithm was used to perform landslide susceptibility zonation. The analysis results of receiver operating characteristic (ROC) curve pointed out the prediction performance of random forest was 92.8%, better than that obtained from popular artificial neural network (ANN) (81.9%) and support vector machine (84.7%) models. Meanwhile, compared with traditional GIS-based reclassification methods, in the susceptibility zonation map obtained from cluster algorithm, more historical landslides distributed in the high susceptibility zones. Hence, the proposed approach is a promising tool for spatial prediction of landslides at the study area.</p>

Seasonal variation and longitudinal distribution characters of cladocerans in the Three Gorges Reservoir

2009 ◽  
Vol 17 (5) ◽  
pp. 512
Author(s):  
Wu Hui-xian ◽  
Yao Jian-liang ◽  
Liu Yan ◽  
Xue Jun-zeng ◽  
Cai Qing-hua ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Three Gorges Reservoir ◽  
Longitudinal Distribution ◽  
Three Gorges ◽  
The Three Gorges Reservoir ◽  
The Three Gorges

Preliminary Effects of Impounding on Vegetation in Drawdown Zone of the Three Gorges Reservoir Region

2010 ◽  
Vol 30 (3) ◽  
pp. 303-314 ◽  
Author(s):  
Zhi-Jun LU ◽  
Lian-Fa LI ◽  
Han-Dong HUANG ◽  
Min TAO ◽  
Quan-Fa ZHANG ◽  
...  
Keyword(s):  
Three Gorges Reservoir ◽  
Three Gorges ◽  
The Three Gorges Reservoir ◽  
The Three Gorges ◽  
Three Gorges Reservoir Region ◽  
Drawdown Zone

scholarly journals Effects of Landscape Positions and Landscape Types on Soil Properties and Chlorophyll Content of Citrus in a Sloping Orchard in the Three Gorges Reservoir Area, China

2021 ◽  
Vol 13 (8) ◽  
pp. 4288
Author(s):  
Siyue Sun ◽  
Guolin Zhang ◽  
Tieguang He ◽  
Shufang Song ◽  
Xingbiao Chu
Keyword(s):  
Soil Properties ◽  
Chlorophyll Content ◽  
Three Gorges Reservoir ◽  
Slope Position ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Reservoir Area ◽  
The Three Gorges Reservoir ◽  
The Three Gorges ◽  
Landscape Types

In recent years, soil degradation and decreasing orchard productivity in the sloping orchards of the Three Gorges Reservoir Area of China have received considerable attention both inside and outside the country. More studies pay attention to the effects of topography on soil property changes, but less research is conducted from the landscape. Therefore, understanding the effects of landscape positions and landscape types on soil properties and chlorophyll content of citrus in a sloping orchard is of great significance in this area. Our results showed that landscape positions and types had a significant effect on the soil properties and chlorophyll content of citrus. The lowest soil nutrient content was detected in the upper slope position and sloping land, while the highest exists at the footslope and terraces. The chlorophyll content of citrus in the middle and upper landscape position was significantly higher than the footslope. The redundancy analysis showed that the first two ordination axes together accounted for 81.32% of the total variation, which could be explained by the changes of soil total nitrogen, total phosphorus, total potassium, available nitrogen, available potassium, organic matter, pH, and chlorophyll content of the citrus. Overall, this study indicates the significant influence of landscape positions and types on soil properties and chlorophyll content of citrus. Further, this study provides a reference for the determination of targeted land management measures and orchard landscape design so that the soil quality and orchard yield can be improved, and finally, the sustainable development of agriculture and ecology can be realized.

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