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Remote Sensing Technology and Application  2021, Vol. 36 Issue (5): 1121-1130    DOI: 10.11873/j.issn.1004-0323.2021.5.1121
    
Study on Early Warning Technology of Sub-health State of Forest Resources with Spaceborne Remote Sensing
Honggan Wu1,2(),Chengbo Wang3(),Zhenwang Miao4,Wenquan Wang1,2,Xiaoli Wang4,Guobing Mi5
1.Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China
2.Laboratory of Forestry Remote Sensing and Information System,NFGA,Beijing 100091,China
3.Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China
4.Forestry and Grassland Pest Control and Quarantine Bureau of Shanxi Province,Taiyuan 300024,China
5.Erdaochuan Forest Farm of Guandishan state Forestry Administration,Wenshui 032199,China
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Abstract  

Monitoring and early warning of sub-healthy forests caused by forest diseases and insect pests and other disturbance types can not be carried out in time, resulting in a passive situation (disaster-relief /post-disaster) for a long time. Based on the multi-temporal GF-1 WFV data from May to September 2019, this paper uses the ratio vegetation index and the red-green vegetation index to monitor "disaster" information such as reverse growth, leaf canopy stress or loss of color in quasi-real time. The results show that although the degradation of chlorophyll such as withering and wilting of tree leaves and gradually transforming into lutein and red leaf pigment requires a certain process, or the "disaster symptoms" sometimes have a lag, but the high frequency remote sensing dynamic monitoring results are useful for guiding the ground inspection of forest disasters. It has a positive effect on improving monitoring coverage and scientificity, and preventing large-scale disasters. The high revisit cycle of domestic GF-1 and GF-6 WFV remote sensing data provides a solid data guarantee for the monthly monitoring of the growth process of forest resources, and meets the needs of hectare-level leaf growth and degradation early warning monitoring.

Key words:  GF-1 WFV      Forest resources      Sub-health state      Forest pests and diseases      Early warning     
Received:  18 June 2020      Published:  07 December 2021
ZTFLH:  TP79  
Corresponding Authors:  Chengbo Wang     E-mail:  wuhg@ifrit.ac.cn;wangcb@aircas.ac.cn
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Honggan Wu
Chengbo Wang
Zhenwang Miao
Wenquan Wang
Xiaoli Wang
Guobing Mi

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Honggan Wu,Chengbo Wang,Zhenwang Miao,Wenquan Wang,Xiaoli Wang,Guobing Mi. Study on Early Warning Technology of Sub-health State of Forest Resources with Spaceborne Remote Sensing. Remote Sensing Technology and Application, 2021, 36(5): 1121-1130.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2021.5.1121     OR     http://www.rsta.ac.cn/EN/Y2021/V36/I5/1121

优势树种油松柏类落叶松栎类桦类杨类灌草
小班个数9191528357375853
占比/%62.641.021.9024.332.523.953.61
Table 1  Information table of dominant tree species in Erdaochuan Forest Farm
序号12345678910
过境日期0430050905170521052906020704090409211028
传感器WFV2WFV4WFV4WFV3WFV3WFV1WFV1WFV2WFV3WFV4
Table 2  GF-1 WFV remote sensing data in 2019
Fig.1  GF-1 WFV multi-temporal composite images for research zone in 2019
植被指数健康轻度中度重度
△RGRI≤0.00-0.10.1-0.2≥0.2
△RVI≥0.00-0.1-0.1-0.25≤-0.25
Table 3  Classification of forest disturbance degree
日 期轻度中度重度所在小班数量/个平均海拔 /m
201905213.920.230.56161 534.52
201905293.790.160.56281 524.42
2019060233.140.410.00881 519.00
201910281 574.29383.479.279141 600.91
Table 4  Area statistics of discoloration stands and site conditions(Units:hm2
Fig.2  Spatial distribution map of discoloration stands
日 期轻度中度重度所在小班数量/个平均海拔/m
20190509693.32431.7429.019921 641.39
201910281 291.621 633.322 569.411 3731 610.22
Table 5  Area statistics in growth degradation stands and site conditions(Units:hm2
Fig.3  Spatial distribution of growth degradation stands
Fig.4  Discoloration forest on June 14, 2019
Fig.5  Temperature scatter diagram in Wenshui County between Apr. 25 to Jun. 2, 2019
Fig.6  Orthophoto image and Landscape photos on October 11, 2019
Fig.7  Comparison and verification in high resolution remote sensing images of GF-2
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