Mapping global land cover in 2001 and 2010 with spatial-temporal consistency at 250 m resolution

作者:Wang, J (Wang, Jie)[ 1 ] ; Zhao, YY (Zhao, Yuanyuan)[ 2 ] ; Li, CC (Li, Congcong)[ 3 ] ; Yu, L (Yu, Le)[ 2 ] ; Liu, DS (Liu, Desheng)[ 4 ] ; Gong, P (Gong, Peng)[ 1,2,5,6 ]

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

卷: 103  页: 38-47

DOI: 10.1016/j.isprsjprs.2014.03.007

出版年: MAY 2015

摘要

Global land cover types in 2001 and 2010 were mapped at 250 m resolution with multiple year time series Moderate Resolution Imaging Spectrometer (MODIS) data. The map for each single year was produced not only from data of that particular year but also from data acquired in the preceding and subsequent years as temporal context. Slope data and geographical coordinates of pixels were also used. The classification system was derived from the finer resolution observation and monitoring of global land cover (FROM-GLC) project. Samples were based on the 2010 FROM-GLC project and samples for other years were obtained by excluding those changed from 2010. A random forest classifier was used to obtain original class labels and to estimate class probabilities for 2000-2002, and 2009-2011. The overall accuracies estimated from cross validation of samples are 74.93% for 2001 and 75.17% for 2010. The classification results were further improved through post processing. A spatial-temporal consistency model, Maximum a Posteriori Markov Random Fields (MAP-MRF), was first applied to improve land cover classification for each 3 consecutive years. The MRF outputs for 2001 and 2010 were then processed with a rule-based label adjustment method with MOD44B, slope and composited EVI series as auxiliary data. The label adjustment process relabeled the over-classified forests, water bodies and barren lands to alternative classes with maximum probabilities. (C) 2014 International Society for Photogrammetiy and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.

通讯作者地址: Gong, P (通讯作者)

Tsinghua Univ, Ctr Earth Syst Sci, Beijing 100084, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Tsinghua Univ, Ctr Earth Syst Sci, Key Lab Earth Syst Modeling, Minist Educ, Beijing 100084, Peoples R China

[ 3 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

[ 4 ] Ohio State Univ, Dept Geog, Columbus, OH 43210 USA

[ 5 ] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA

[ 6 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China