Developing spatially and thematically detailed backdated maps for land cover studies

作     者：Juan JoséVidal-Macua Alaitz Zabala Miquel Ninyerola Xavier Pons 

作者机构：Dep GeografiaGrumets Research GroupUniversitat Autònoma de BarcelonaBellaterraCataloniaSpain Dep Biologia AnimalVegetal i EcologiaGrumets Research GroupUniversitat Autònoma de BarcelonaBellaterraCataloniaSpain 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2017年第10卷第2期

页      面：175-206页

核心收录：

学科分类：0502[文学-外国语言文学] 050201[文学-英语语言文学] 05[文学] 0708[理学-地球物理学] 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：supported by the Spanish Ministry of Economy and Competitiveness[grant number BES-2013-063766] European Union’s Horizon 2020 Programme[ECOPOTENTIAL(641762-2)] Spanish Ministry of Economy and Competitiveness[ACAPI(CGL2015-69888-P MINECO/FEDER)],[DinaClive(CGL2012-33927)] Catalan Government[SGR2014-1491]. 

主　　题：Land cover mapping Landsat statistical classifiers backdating Iberian Peninsula 

摘      要：Global or regional land cover change on a decadal time scale can be studied at a high level of detail using the availability of remote sensing data such as that provided by Landsat.However,there are three main technical challenges in this goal.First,the generation of land cover maps without reference data is problematic(backdating).Second,it is important to maintain high accuracies in land cover change map products,requiring a reasonably rich legend within each map.Third,a high level of automation is necessary to aid the management of large volumes of data.This paper describes a robust methodology for processing time series of satellite data over large spatial areas.The methodology includes a retrospective analysis used for the generation of training and test data for historical periods lacking reference information.This methodology was developed in the context of research on global change in the Iberian Peninsula.In this study we selected two scenes covering geographic regions that are representative of the Iberian Peninsula.For each scene,we present the results of two classifications(1985-1989 and 2000-2004 quinquennia),each with a legend of 13 categories.An overall accuracy of over 92%was obtained for all 4 maps.