Mass data processing of time series Landsat imagery:pixels to data products for forest monitoring
作者机构：Integrated Remote Sensing StudioDepartment of Forest Resources ManagementUniversity of British ColumbiaVancouverBCCanada Canadian Forest Service(Pacific Forestry Centre)Natural Resources CanadaVictoriaBCCanada
出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)
年 卷 期：2016年第9卷第11期
页 面：1035-1054页
核心收录：
学科分类：08[工学] 0708[理学-地球物理学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0835[工学-软件工程] 0704[理学-天文学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：Canadian Space Agency (CSA) Government Related Initiatives Program (GRIP) Canadian Forest Service (CFS) of Natural Resources Canada
主 题：Remote sensing big data forest change monitoring image processing
摘 要：Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring ***,we summarize a project characterizing the change history of Canada’s forested ecosystems with a time series of data representing *** the Composite2Change approach,we applied spectral trend analysis to annual best-available-pixel(BAP)surface reflectance image composites produced from Landsat TM and ETM+imagery.A total of 73,544 images were used to produce 29 annual image composites,generating∼400 TB of interim data products and resulting in∼25 TB of annual gap-free reflectance composites and change *** average,10%of pixels in the annual BAP composites were missing data,with 86%of pixels having data gaps in two consecutive years or *** detection overall accuracy was 89%.Change attribution overall accuracy was 92%,with higher accuracy for standreplacing wildfire and *** were assigned to the correct year with an accuracy of 89%.Outcomes of this project provide baseline information and nationally consistent data source to quantify and characterize changes in forested *** methods applied and lessons learned build confidence in the products generated and empower others to develop or refine similar satellite-based monitoring projects.
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