Generation and analysis of the 2005 land cover map for Mexico using 250 m MODIS data

被引:48
作者
Colditz, Rene R. [1 ]
Lopez Saldana, Gerardo [2 ]
Maeda, Pedro [1 ]
Argumedo Espinoza, Jesus [3 ]
Meneses Tovar, Carmen [4 ]
Victoria Hernandez, Arturo [3 ]
Zermeno Benitez, Carlos [4 ]
Cruz Lopez, Isabel [1 ]
Ressl, Rainer [1 ]
机构
[1] Natl Commiss Knowledge & Use Biodivers CONABIO, Mexico City 14010, DF, Mexico
[2] Inst Super Agron, Dept Forestry, P-1349017 Lisbon, Portugal
[3] Natl Inst Stat & Geog INEGI, Aguascalientes 20270, Mexico
[4] Natl Forestry Commiss CONAFOR, Zapopan, Jalisco, Mexico
关键词
Land cover; Image classification; Spatial analysis; North American Land Change Monitoring System (NALCMS); MODIS; Mexico; ACCURACY ASSESSMENT; SPATIAL-RESOLUTION; CLASSIFICATION; SURFACE; PRODUCTS; MATRIX;
D O I
10.1016/j.rse.2012.04.021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land cover plays a key role in global to regional monitoring and modeling because it affects and is being affected by climate change and thus became one of the essential variables for climate change studies. National and international organizations require timely and accurate land cover information for reporting and management actions. The North American Land Change Monitoring System (NALCMS) is an international cooperation of organizations and entities of Canada. the United States, and Mexico to map land cover change of North America's changing environment. This paper presents the methodology to derive the land cover map of Mexico for the year 2005 which was integrated in the NALCMS continental map. Based on a time series of 250 m Moderate Resolution Imaging Spectroradiometer (MOD'S) data and an extensive sample data base the complexity of the Mexican landscape required a specific approach to reflect land cover heterogeneity. To estimate the proportion of each land cover class for every pixel several decision tree classifications were combined to obtain class membership maps which were finally converted to a discrete map accompanied by a confidence estimate. The map yielded an overall accuracy of 82.5% (Kappa of 0.79) for pixels with at least 50% map confidence (71.3% of the data). An additional assessment with 780 randomly stratified samples and primary and alternative calls in the reference data to account for ambiguity indicated 83.4% overall accuracy (Kappa of 0.80). A high agreement of 83.6% for all pixels and 92.6% for pixels with a map confidence of more than 50% was found for the comparison between the land cover maps of 2005 and 2006. Further wall-to-wall comparisons to related land cover maps resulted in 56.6% agreement with the MODIS land cover product and a congruence of 49.5 with Globcover. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:541 / 552
页数:12
相关论文
共 56 条
[21]   A decision-theoretic generalization of on-line learning and an application to boosting [J].
Freund, Y ;
Schapire, RE .
JOURNAL OF COMPUTER AND SYSTEM SCIENCES, 1997, 55 (01) :119-139
[22]   Global land cover mapping from MODIS: algorithms and early results [J].
Friedl, MA ;
McIver, DK ;
Hodges, JCF ;
Zhang, XY ;
Muchoney, D ;
Strahler, AH ;
Woodcock, CE ;
Gopal, S ;
Schneider, A ;
Cooper, A ;
Baccini, A ;
Gao, F ;
Schaaf, C .
REMOTE SENSING OF ENVIRONMENT, 2002, 83 (1-2) :287-302
[23]   MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets [J].
Friedl, Mark A. ;
Sulla-Menashe, Damien ;
Tan, Bin ;
Schneider, Annemarie ;
Ramankutty, Navin ;
Sibley, Adam ;
Huang, Xiaoman .
REMOTE SENSING OF ENVIRONMENT, 2010, 114 (01) :168-182
[24]  
GCOS, 2006, GCO107
[25]   Land cover mapping of Greater Mesoamerica using MODIS data [J].
Giri, Chandra ;
Jenkins, Clinton .
CANADIAN JOURNAL OF REMOTE SENSING, 2005, 31 (04) :274-282
[26]  
GTOS, 2009, GTOS64
[27]   Global land cover classification at 1km spatial resolution using a classification tree approach [J].
Hansen, MC ;
Defries, RS ;
Townshend, JRG ;
Sohlberg, R .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2000, 21 (6-7) :1331-1364
[28]   Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets [J].
Herold, M. ;
Mayaux, P. ;
Woodcock, C. E. ;
Baccini, A. ;
Schmullius, C. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (05) :2538-2556
[29]   The spatiotemporal form of urban growth: measurement, analysis and modeling [J].
Herold, M ;
Goldstein, NC ;
Clarke, KC .
REMOTE SENSING OF ENVIRONMENT, 2003, 86 (03) :286-302
[30]   Development of a 2001 National Land-Cover Database for the United States [J].
Homer, C ;
Huang, CQ ;
Yang, LM ;
Wylie, B ;
Coan, M .
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2004, 70 (07) :829-840