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森林资源亚健康状态的卫星遥感预警技术研究
引用本文:武红敢,王成波,苗振旺,王文泉,王晓丽,米国兵. 森林资源亚健康状态的卫星遥感预警技术研究[J]. 遥感技术与应用, 2021, 36(5): 1121-1130. DOI: 10.11873/j.issn.1004-0323.2021.5.1121
作者姓名:武红敢  王成波  苗振旺  王文泉  王晓丽  米国兵
作者单位:1.中国林业科学研究院资源信息研究所,北京 100091;2.国家林业和草原局林业遥感与信息技术实验室,北京 100091;3.中国科学院空天信息创新研究院,北京 100101;4.山西省林业和草原有害生物防治检疫局,山西 太原 030024;5.关帝山国有林管理局二道川林场,山西 文水 032199
基金项目:中国林业科学研究院中央级公益性科研院所基本科研业务费专项资金项目“基于北斗的林业野外多业务综合巡护协同技术研究”(CAFYBB2017ZC001)
摘    要:森林病虫害等扰动类型造成的亚健康林木监测预警工作不能及时到位,导致防治工作长期处于灾后救灾的被动局面.基于2019年5~9月份的多时相GF-1 WFV数据,应用比值植被指数和红绿植被指数,准实时地监测逆生长、叶冠胁迫或失色等"灾害"信息.结果 表明:虽然树木叶片枯黄、萎蔫等叶绿素降解并逐渐转化成叶黄素和叶红素需要一定的...

关 键 词:GF-1 WFV  森林资源  亚健康  森林病虫害  预警
收稿时间:2020-06-18

Study on Early Warning Technology of Sub-health State of Forest Resources with Spaceborne Remote Sensing
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[J]. Remote Sensing Technology and Application, 2021, 36(5): 1121-1130. DOI: 10.11873/j.issn.1004-0323.2021.5.1121
Authors:Honggan Wu  Chengbo Wang  Zhenwang Miao  Wenquan Wang  Xiaoli Wang  Guobing Mi
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.
Keywords:GF-1 WFV  Forest resources  Sub-health state  Forest pests and diseases  Early warning  
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