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过程,或“灾害症状”有时具有滞后性,但高频次遥感动态监测结果对于指导森林灾害地面踏查,提高监测覆盖率和科学性,防范大面积灾害,具有积极作用。国产GF-1和GF-6 WFV遥感数据的高重访周期能为月度森林资源生长过程的监测提供坚实的数据保障,满足公顷级树叶长势退化预警监测的需要。
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-di⁃saster)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 re⁃verse growth,leaf canopy stress or loss of color in quasi-real time.The results show that although the degrada⁃tion 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 re⁃mote 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.
作者
武红敢
王成波
苗振旺
王文泉
王晓丽
米国兵
Wu Honggan;Wang Chengbo;Miao Zhenwang;Wang Wenquan;Wang Xiaoli;Mi Guobing(Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China;Laboratory of Forestry Remote Sensing and Information System,NFGA,Beijing 100091,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;Forestry and Grassland Pest Control and Quarantine Bureau of Shanxi Province,Taiyuan 300024,China;Erdaochuan Forest Farm of Guandishan state Forestry Administration,Wenshui 032199,China)
出处
《遥感技术与应用》
CSCD
北大核心
2021年第5期1121-1130,共10页
Remote Sensing Technology and Application
基金
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)。
关键词
GF⁃1
WFV
森林资源
亚健康
森林病虫害
预警
GF-1 WFV
Forest resources
Sub-health state
Forest pests and diseases
Early warning