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author:

Xu, Zhanghua (Xu, Zhanghua.) [1] | Sun, Lei (Sun, Lei.) [2] | Zhang, Yiwei (Zhang, Yiwei.) [3] | Li, Haitao (Li, Haitao.) [4] | Yang, Yuanyao (Yang, Yuanyao.) [5] | Zhang, Chaofei (Zhang, Chaofei.) [6] | Zhang, Huafeng (Zhang, Huafeng.) [7] | Zhang, Hongbin (Zhang, Hongbin.) [8] | Guan, Fengying (Guan, Fengying.) [9]

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EI

Abstract:

To address gaps in understanding how external stresses influence remote-sensing inversion of vegetation biochemical components, a P-PROSAIL model incorporating stress factors was developed, with Shunchang County and Yanping District in Fujian Province as the study areas. The model’s effectiveness was assessed, yielding R² values of 0.7133, 0.7066, 0.6441, 0.6392, 0.6057, 0.7038, 0.5323, and 0.5149 for leaf area index (LAI), canopy dry matter content (CDMC), canopy cellulose content (CCC), canopy lignin content (CLC), canopy protein content (CPC), canopy nitrogen content (CNC), canopy tannin content (CTC), and canopy flavonoid content (CFC), respectively. While CDMC and most other components showed stable inversions, CTC and CFC exhibited uncertainties due to pest stress. This study clarified the internal and external change characteristics and mechanisms of Moso bamboo forests under Pantana phyllostachysae stress, providing empirical support for the ecological health of bamboo forests. © 2025, Author. All rights reserved.

Keyword:

Bamboo Stress analysis Vegetation

Community:

  • [ 1 ] [Xu, Zhanghua]Academy of Geography and Ecological Environment, The College of Environment and Safety Engineering, the Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Sun, Lei]Academy of Geography and Ecological Environment, The College of Environment and Safety Engineering, the Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Zhang, Yiwei]Academy of Geography and Ecological Environment, The College of Environment and Safety Engineering, the Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Li, Haitao]Academy of Geography and Ecological Environment, The College of Environment and Safety Engineering, the Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou; 350108, China
  • [ 5 ] [Yang, Yuanyao]Academy of Geography and Ecological Environment, The College of Environment and Safety Engineering, the Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou; 350108, China
  • [ 6 ] [Zhang, Chaofei]Academy of Geography and Ecological Environment, The College of Environment and Safety Engineering, the Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou; 350108, China
  • [ 7 ] [Zhang, Huafeng]Xiamen Administration Center of Afforestation, Xiamen; 361004, China
  • [ 8 ] [Zhang, Hongbin]Fujian Provincial Financial Investment Evaluation Center, Fuzhou; 350001, China
  • [ 9 ] [Guan, Fengying]International Center for Bamboo and Rattan, Key Laboratory of National Forestry and Grassland Administration, Beijing; 100102, China

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Source :

Photogrammetric Engineering and Remote Sensing

ISSN: 0099-1112

Year: 2025

Issue: 5

Volume: 91

Page: 285-297

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JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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