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Journal of Environmental Biology

pISSN: 0254-8704 ; eISSN: 2394-0379 ; CODEN: JEBIDP
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    Abstract - Issue Sep 2022, 43 (5)                                     Back


nstantaneous and historical temperature effects on a-pinene

Seasonal variations of forest leaf area index

and its thermal effect on water-eroded areas in 2000–2014 using remote sensing imageries

 

D.L. Li1,2, Z.J. Gu3*, X.X. Wu2, H. Yue4, S.Y. Peng4 and X.L. Wang2

1School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, Jiangsu Province, 221 116, P.R China

2School of Environmental Science, Nanjing Xiaozhuang University, Nanjing, 211 171, P.R China

3Pearl River Water Resources Research Institute,Guangzhou, 510 380, P.R China

4Changting Bureau of Soil and Water Conservation, Changting, Fujian, Province, 366 399, P.R China

*Corresponding Author Email : zhujungu@163.com

 

Received: 04.10.2021                                                                                                Revised: 08.03.2022                                                                                  Accepted: 14.05.2022

 

 

Abstract

Aim: To analyze the spatiotemporal distribution of forest vegetation and its relationship with ground temperature in severe water erosion areas in Southern China.

Methodology: The spatiotemporal variations of leaf area index (LAI) at a seasonal scale of the study area, Changting County in Fujian Province, China, were derived and compared with ground temperature (T) in 2000-2014 through remote sensing imageries.

Results: Average seasonal LAI of central towns (< 2.3) were less than those of other towns, and negative correlations were found between LAI and T in 2000 and 2014. The R squares of the LAI–T relationship models were > 0.4 in 2000 and < 0.4 in 2014.

Interpretation: This study demonstrated that more factors were involved in the thermal effect with the increase of LAI and the multi-year conservation management. Conservation measures should be prioritized in the central and south-eastern areas of the county with intense erosion.

Key words: County, Leaf area index, Remote sensing, Seasonal variations, Soil erosion grade

 

 

 

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