Retrieving chlorophyll content and equivalent water thickness of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework - Details

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Abstract：

Biochemical　components　of　Moso　bamboo　(Phyllostachys　pubescens)　are　critical　to　physiological　and　ecological　processes　and　play　an　important　role　in　the　material　and　energy　cycles　of　the　ecosystem.　The　coupled　PROSPECT　with　SAIL　(PROSAIL)　radiative　transfer　model　is　widely　used　for　vegetation　biochemical　component　content　inversion.　However,　the　presence　of　leaf-eating　pests,　such　as　Pantana　phyllostachysae　Chao　(PPC),　weakens　the　performance　of　the　model　for　estimating　biochemical　components　of　Moso　bamboo　and　thus　must　be　considered.　Therefore,　this　study　considered　pest-induced　stress　signals　associated　with　Sentinel-2A/B　images　and　field　data　and　established　multiple　sets　of　biochemical　canopy　reflectance　look-up　tables　(LUTs)　based　on　the　PROSAIL　framework　by　setting　different　parameter　ranges　according　to　infestation　levels.　Quantitative　inversions　of　leaf　area　index　(LAI),　leaf　chlorophyll　content　(LCC),　and　leaf　equivalent　water　thickness　(LEWT)　were　derived.　The　scale　conversions　from　LCC　to　canopy　chlorophyll　content　(CCC)　and　LEWT　to　canopy　equivalent　water　thickness　(CEWT)　were　calculated.　The　results　showed　that　LAI,　CCC,　and　CEWT　were　inversely　related　with　PPC-induced　stress.　When　applying　multiple　LUTs,　the　p-values　were　<0.01;　the　R2　values　for　LAI,　CCC,　and　CEWT　were　0.71,　0.68,　and　0.65　with　root　mean　square　error　(RMSE)　(normalized　RMSE,　NRMSE)　values　of　0.38　(0.16),　17.56　μg·cm‒2　(0.20),　and　0.02　cm　(0.51),　respectively.　Compared　to　the　values　obtained　for　the　traditional　PROSAIL　model,　for　October,　R2　values　increased　by　0.05　and　0.10　and　NRMSE　decreased　by　0.09　and　0.02　for　CCC　and　CEWT,　respectively　and　RMSE　decreased　by　0.35　μg·cm‒2　for　CCC.　The　feasibility　of　the　inverse　strategy　for　integrating　pest-induced　stress　factors　into　the　PROSAIL　model,　while　establishing　multiple　LUTs　under　different　pest-induced　damage　levels,　was　successfully　demonstrated　and　can　potentially　enhance　future　vegetation　parameter　inversion　and　monitoring　of　bamboo　forest　health　and　ecosystems.　©　2023　The　Authors

Keyword：

Chlorophyll content Equivalent water thickness Moso bamboo Multiple LUTs Pantana phyllostachysae Chao PROSAIL model Sentinel-2A/B images

Community：

[ 1 ] [Xu, Z.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 2 ] [Xu, Z.]Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization, Sanming, 365004, China
[ 3 ] [Xu, Z.]Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China
[ 4 ] [He, A.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 5 ] [Zhang, Y.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 6 ] [Hao, Z.]Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization, Sanming, 365004, China
[ 7 ] [Hao, Z.]College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
[ 8 ] [Li, Y.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 9 ] [Xiang, S.]Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China
[ 10 ] [Li, B.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 11 ] [Chen, L.]Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China
[ 12 ] [Yu, H.]Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China
[ 13 ] [Shen, W.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 14 ] [Huang, X.]College of Environment and Safety Engineering, Academy of Geography and Ecological Environment, Fuzhou University, Fuzhou, 350108, China
[ 15 ] [Huang, X.]International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
[ 16 ] [Guo, X.]Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization, Sanming, 365004, China
[ 17 ] [Li, Z.]Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization, Sanming, 365004, China

Reprint 's Address：

[Xu, Z.]College of Environment and Safety Engineering, China

Email：

fzucar@fzu.edu.cn

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Related Keywords：

Retrieving chlorophyll content and equivalent water thickness of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework
2023，FOREST ECOSYSTEMS
Revealing early pest source points and spreading laws of Pantana phyllostachysae Chao in Moso bamboo ( Phyllostachys pubescens ) forests from Sentinel-2A/B images
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PROSAIL Modeling Coupled with Environmental Stress: Remote Sensing Retrieval of Multiple Dry Matters in the Canopy of Moso Bamboo Forests under the Stress of Pantana phyllostachysae Chao
2025，PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
Monitoring the Severity of Pantana phyllostachysae Chao Infestation in Moso Bamboo Forests Based on UAV Multi-Spectral Remote Sensing Feature Selection
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Mapping aboveground biomass of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress using Sentinel-2 imagery
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Source ：

Forest Ecosystems

ISSN： 2095-6355

Year： 2023

Volume： 10

3 . 8

JCR@2023

3 . 8 0 0

JCR@2023

ESI HC Threshold：18

JCR Journal Grade：1

CAS Journal Grade：1

Cited Count：

WoS CC Cited Count：

SCOPUS Cited Count： 1

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 2

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