Yuxin Cen

Dr. Yuxin Cen


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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YCYuxin Cen
Yuxin Cen
BZBin Zhang
Bin Zhang
JLJun Luo
Jun Luo
QDQingchun Deng
Qingchun Deng
HLHui Liu
Hui Liu
LWLei Wang
Lei Wang
A gully system is an important indicator that reflects the development of regional topography and landforms, and topography is one of the most important factors affecting the development of gullies. However, at present, research on the impact of topography on the development of gully systems in the mountainous area of Ningnan dry-hot valley still needs to be strengthened. In order to study the characteristics of gullies and the influence of topography on the development of gully systems, based on both the visual interpretation of remote sensing images and field investigations, five topographic factors (elevation, slope gradient, aspect, relief, and dissection) were employed and three gully erosion indexes (gully length, density, and frequency) were calculated. The geographical information system was used in this study to carry out the spatial analysis, Ward’s hierarchical clustering and correlation analysis. Results showed that the development of gully systems is greatly affected by the degree of relief and dissection, and there is a significant positive correlation (p < 0.01; p < 0.05), while elevation, slope gradient and aspect have little influence on it. Analysis of the gully systems showed that the gully erosion is the most intense in the area with an elevation of 2800–3200 m and slope gradients ≥ 38°. Furthermore, the degree of erosion on shady slopes was greater than that on sunny slopes. These results will help us to understand the spatial distribution and formation of gully systems in mountainous areas.

21 October 2024 in Sustainability
Verified
Journal Article
Open access
PDF file
YXYixian Xiao
Yixian Xiao
HLHe Li
He Li
XCXin Chen
Xin Chen
ZHZhengwei He
Zhengwei He
YLYangqi Lai
Yangqi Lai
JRJin Run
Jin Run
Ertan Hydroelectric Power Station was the first large-scale water conservancy facility in western China, and with its completion, the ecological pattern of the reservoir area has changed dramatically; however, the changes in habitat quality before and after the completion of the reservoir have not yet been systematically monitored and evaluated. In this study, we analyzed the spatial and temporal characteristics of the remote sensing ecological index (RSEI), used CA-Markov model and GeoDetector, evaluated the ecological environment of the Ertan Reservoir area in each five-year period from 1995 to 2020, simulated the ecological quality of the Ertan Reservoir area in 2025, and revealed the nine drivers and their interactions affecting ecological quality of the watershed from a geologic point of view, and finally put forward reasonable planning and targeted protection suggestions. Finally, rational planning and targeted protection recommendations were proposed. The main results were as follows: (1) After the completion of the Ertan Hydropower Station, the spatial distribution of the RSEI in the reservoir area varied significantly, with a trend of “rising-declining-rising” in time, and the area share of “good” area increased the most, by 19.83%. (2) The degree of grading of each driving factor had different degrees of influence on the size of the RSEI value, and its interaction enhanced the spatial differentiation of the RSEI. (3) The average value of the RSEI is 0.66 in 2025, and the ecological environment quality will show a steady improvement in five years. The results of the study can provide a reference for constructing RSEI indicators for large hydropower facilities.

27 December 2024 in Forests
Verified
Journal Article
Open access
PDF file
HLHe Li
He Li
YYYan Yuan
Yan Yuan
ZHZhengwei He
Zhengwei He
JPJin Pang
Jin Pang
YZYang Zhao
Yang Zhao
YXYixian Xiao
Yixian Xiao
Net primary productivity (NPP) is a key metric for evaluating ecosystem carbon sink capacity and defining vegetation. Despite extensive research on vegetation NPP, much relies on coarse spatial resolution data, which often overlooks regional spatial heterogeneity, causing inaccuracies in NPP estimates. Therefore, this study employed the improved CASA model, based on GF-SG and kNDVI methods, to estimate vegetation NPP at a 30 m spatial resolution on the Zoigê Plateau from 2001 to 2020. The effects of anthropogenic and climatic factors on NPP were quantified through residual and partial correlation analyses. These results indicated the following: (1) NDVI derived from the GF-SG fusion method aligns closely with Landsat NDVI (R2 ≈ 0.9). When contrasted with using NDVI alone, incorporating kNDVI into the CASA model enhances NPP assessment accuracy. (2) Vegetation NPP on the Zoigê Plateau has fluctuated upward by 2.09 gC·m−2·a−1 over the last two decades, with higher values centrally and lower at the edges. (3) Monthly partial correlation analysis indicates almost no temporal effects in NPP response to temperature (97.42%) but significant cumulative effects in response to precipitation (80.3%), with longer accumulation periods in the south. Annual analysis reveals that NPP correlates more strongly with temperature than precipitation. (4) NPP changes are jointly influenced by climate change (48.46%) and human activities (51.54%), with the latter being the dominant factor. This study deepens the understanding of NPP dynamics in the Zoigê Plateau and offers insights for estimating NPP at high spatial-temporal resolutions.