Enyan Zhu

Dr. Enyan Zhu


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

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

Representative Publications

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1 January 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
EZEnyan Zhu
Enyan Zhu
JDJinsong Deng
Jinsong Deng
MZMengmeng Zhou
Mengmeng Zhou
Muye GanMuye Gan
Muye Gan
RJRuowei Jiang
Ruowei Jiang
ASAmir Reza Shahtahmassebi
Amir Reza Shahtahmassebi

1 March 2020 in Science of The Total Environment
Verified
Journal Article
Closed access
Marye Belete AlemayehuMarye Belete Alemayehu
Marye Belete Alemayehu
JDJinsong Deng
Jinsong Deng
KWKe Wang
Ke Wang
MZMengmeng Zhou
Mengmeng Zhou
EZEnyan Zhu
Enyan Zhu
YBYared Bayissa
Yared Bayissa

28 February 2020 in Land Degradation & Development
Verified
Journal Article
Closed access
PDF file
Marye Belete AlemayehuMarye Belete Alemayehu
Marye Belete Alemayehu
JDJinsong Deng
Jinsong Deng
GAGhali Abdullahi Abubakar
Ghali Abdullahi Abubakar
MZMenberu Teshome Zeleke
Menberu Teshome Zeleke
KWKe Wang
Ke Wang
AGAdam Gudo
Adam Gudo

15 August 2023 in Land Degradation & Development
Verified
Journal Article
Closed access
EZEnyan Zhu
Enyan Zhu
WLWei Li
Wei Li
LCLisu Chen
Lisu Chen
MSMei Sha
Mei Sha

5 December 2023 in Environmental Science and Pollution Research
Verified
Journal Article
Closed access
PDF file
EZEnyan Zhu
Enyan Zhu
JYJian Yao
Jian Yao
XZXinghui Zhang
Xinghui Zhang
LCLisu Chen
Lisu Chen

17 December 2018 in Forests
Verified
Journal Article
Open access
PDF file
ASAihua Shen
Aihua Shen
CWChaofan Wu
Chaofan Wu
BJBo Jiang
Bo Jiang
JDJinsong Deng
Jinsong Deng
WYWeigao Yuan
Weigao Yuan
CWChuping Wu
Chuping Wu
Biomass is a key biophysical parameter used to estimate carbon storage and forest productivity. Spatially-explicit estimation of biomass provides invaluable information for carbon stock calculation and scientific forest management. Nevertheless, there still exists large uncertainty concerning the relationship between biomass and influential factors. In this study, aboveground biomass (AGB) was estimated using the random forest algorithm based on remote sensing imagery (Landsat) and field data for three regions with different topographic conditions in Zhejiang Province, China. AGB distribution and change combined with stratified terrain classifications were analyzed to investigate the relations between AGB and topography conditions. The results indicated that AGB in three regions increased from 2010 to 2015 and the magnitude of growth varied with elevation, slope, and aspect. In the basin region, slope had a greater influence on AGB, and we attributed this negative AGB-elevation relationship to ecological forest construction. In the mountain area, terrain features, especially elevation, showed significant relations with AGB. Moreover, AGB and its growth showed positive relations with elevation and slope. In the island region, slope also played a relatively more important role in explaining the relationship. These results demonstrate that AGB varies with terrain conditions and its change is a consequence of interactions between the natural environment and anthropogenic behavior, implying that biomass retrieval based on Landsat imagery could provide considerable important information related to regional heterogeneity investigations.