Regional land cover mapping and change detection in Central Asia using MODIS time-series

被引:162
作者
Klein, Igor [1 ]
Gessner, Ursula [2 ]
Kuenzer, Claudia [2 ]
机构
[1] Univ Wurzburg, Dept Remote Sensing, D-97074 Wurzburg, Germany
[2] German Remote Sensing Data Ctr DFD, German Aerosp Ctr DLR, D-82234 Oberpfaffenhofen, Wessling, Germany
关键词
Regional land cover classification; Central Asia; MODIS; Decision tree; C5.0; Land cover change; CLASSIFICATION ACCURACY; VEGETATION INDEX; EAST-AFRICA; NDVI; PRECIPITATION; RAINFALL; CLIMATE; TEMPERATURE; VARIABILITY; ALGORITHMS;
D O I
10.1016/j.apgeog.2012.06.016
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
In Central Asia major alterations in land use and land cover occurred in the past decades due to political collapse of the Soviet Union, human forces, and climate change. In this context accurate land cover information for the region of Central Asia is important. In this study we present a classification approach with implemented C5.0 algorithm addressing regional land cover characteristics of Central Asia. The classification is performed on seasonal features derived from MODIS time-series for the years 2001 and 2009, which allows us to analyse possible land cover and land use changes. Training and validation are based on a reference dataset collected from high resolution remote sensing data. The overall accuracy of both classifications is above 90%. The results show some significant changes between both years in different land cover classes. Human induced alterations of water bodies, variability in sparsely vegetated areas due to seasonal precipitation and forest loss caused by forest fires and logging are exemplarily depicted and discussed in this study. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:219 / 234
页数:16
相关论文
共 83 条
[1]   Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data [J].
Abd El-Kawy, O. R. ;
Rod, J. K. ;
Ismail, H. A. ;
Suliman, A. S. .
APPLIED GEOGRAPHY, 2011, 31 (02) :483-494
[2]  
Aguiar MR, 2005, GRASSLANDS: DEVELOPMENTS OPPORTUNTIES PERSPECTIVES, P261
[3]   Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico [J].
Aguirre-Gutierrez, Jesus ;
Seijmonsbergen, Arie C. ;
Duivenvoorden, Joost F. .
APPLIED GEOGRAPHY, 2012, 34 :29-37
[4]  
[Anonymous], ENCY ENV HLTH
[5]  
[Anonymous], 2009, ASSESSING ACCURACY R
[6]  
[Anonymous], 2014, C4. 5: programs for machine learning
[7]  
[Anonymous], INT FOR FIRE NEWS IF
[8]  
Arino O, 2008, ESA BULL-EUR SPACE, P24
[9]  
Arkhipov V, 2000, INT FOREST FIRE NEWS, V22, P40
[10]   Analyzing the agricultural transition in Mato Grosso, Brazil, using satellite-derived indices [J].
Arvor, Damien ;
Meirelles, Margareth ;
Dubreuil, Vincent ;
Begue, Agnes ;
Shimabukuro, Yosio E. .
APPLIED GEOGRAPHY, 2012, 32 (02) :702-713