文献类型：期刊文献

中文题名：森林资源亚健康状态的卫星遥感预警技术研究

英文题名：Study on Early Warning Technology of Sub-health State of Forest Resources with Spaceborne Remote Sensing

作者：武红敢[1,2] 王成波[3] 苗振旺[4] 王文泉[1,2] 王晓丽[4] 米国兵[5]

第一作者：武红敢

机构：[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

年份：2021

卷号：36

期号：5

起止页码：1121-1130

中文期刊名：遥感技术与应用

外文期刊名：Remote Sensing Technology and Application

收录：CSTPCD;;北大核心:【北大核心2020】；CSCD:【CSCD2021_2022】；

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)。

语种：中文

中文关键词：GF?1 WFV;森林资源;亚健康;森林病虫害;预警

外文关键词：GF-1 WFV;Forest resources;Sub-health state;Forest pests and diseases;Early warning

分类号：TP79

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.