Bolin Fu

Prof. Bolin Fu

Guilin University of Technology, Guilin, Guangxi, China
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

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

Representative Publications

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1 February 2017 in Ecological Indicators
Verified
Journal Article
Closed access
BFBolin Fu
Bolin Fu
YWYeqiao Wang
Yeqiao Wang
ACAnthony Campbell
Anthony Campbell
YLYing Li
Ying Li
BZBai Zhang
Bai Zhang
XJXiaomin Jin
Xiaomin Jin

1 June 2021 in Ecological Indicators
Verified
Journal Article
Open access
MLMan Liu
Man Liu
BFBolin Fu
Bolin Fu
SXShuyu Xie
Shuyu Xie
HHHongchang He
Hongchang He
FLFeiwu Lan
Feiwu Lan
DFDonglin Fan
Donglin Fan

1 October 2016 in Ecological Indicators
Verified
Journal Article
Closed access
BFBolin Fu
Bolin Fu
YLYing Li
Ying Li
YWYeqiao Wang
Yeqiao Wang
BZBai Zhang
Bai Zhang
SYShubai Yin
Shubai Yin
ZXZefeng Xing
Zefeng Xing

5 August 2023 in Ecological Indicators
Verified
Journal Article
Open access
WYWenlan Yang
Wenlan Yang
BFBolin Fu
Bolin Fu
SLSunzhe Li
Sunzhe Li
ZLZhinan Lao
Zhinan Lao
TDTengfang Deng
Tengfang Deng
ZCZhikun Chen
Zhikun Chen

Verified
Journal Article
Open access
PDF file
RWRanghu Wang
Ranghu Wang
SZShuwen Zhang
Shuwen Zhang
LPLuoman Pu
Luoman Pu
JYJiuchun Yang
Jiuchun Yang
Chaobin YangChaobin Yang
Chaobin Yang
XSXuejia Sang
Xuejia Sang
This research is focused on gully erosion mapping and monitoring at multiple spatial scales using multi-source remote sensing data of the Sancha River catchment in Northeast China, where gullies extend over a vast area. A high resolution satellite image (Pleiades 1A, 0.7 m) was used to obtain the spatial distribution of the gullies of the overall basin. Image visual interpretation with field verification was employed to map the geometric gully features and evaluate gully erosion as well as the topographic differentiation characteristics. Unmanned Aerial Vehicle (UAV) remote sensing data and the 3D photo-reconstruction method were employed for detailed gully mapping at a site scale. The results showed that: (1) the sub-meter image showed a strong ability in the recognition of various gully types and obtained satisfactory results, and the topographic factors of elevation, slope and slope aspects exerted significant influence on the gully spatial distribution at the catchment scale; and (2) at a more detailed site scale, UAV imagery combined with 3D photo-reconstruction provided a Digital Surface Model (DSM) and ortho-image at the centimeter level as well as a detailed 3D model. The resulting products revealed the area of agricultural utilization and its shaping by human agricultural activities and water erosion in detail, and also provided the gully volume. The present study indicates that using multi-source remote sensing data, including satellite and UAV imagery simultaneously, results in an effective assessment of gully erosion over multiple spatial scales. The combined approach should be continued to regularly monitor gully erosion to understand the erosion process and its relationship with the environment from a comprehensive perspective.

7 August 2023 in International Journal of Applied Earth Observation and Geoinformation
Verified
Journal Article
Open access
BFBolin Fu
Bolin Fu
YLYiyin Liang
Yiyin Liang
ZLZhinan Lao
Zhinan Lao
XSXidong Sun
Xidong Sun
SLSunzhe Li
Sunzhe Li
DFDonglin Fan
Donglin Fan