PROGRESS IN GEOGRAPHY ›› 2014, Vol. 33 ›› Issue (11): 1556-1565.doi: 10.11820/dlkxjz.2014.09.012

• Orginal Article • Previous Articles     Next Articles

Land cover classification based on MODIS images: taking the Beijing-Tianjin-Hebei region as an example

Yushan ZUO1,2(), Wei WANG1,2(), Yanli HAO1,2, Hong LIU1,2   

  1. 1. School of Resource and Environmental Science, Hebei Normal University, Shijiazhuang 050024, China
    2. The Key Laboratory of Environment Evolution and Ecology Construction in Hebei Province, Shijiazhuang 050024, China
  • Online:2014-11-25 Published:2014-09-30


With intensifying human activities global ecological and environmental problems have become increasingly pressing. Therefore the study of global change has become more prominent. Obtaining accurate land cover information in a timely fashion is critically important for such research. With the development of remote sensing science and technology and application, numerous studies have the issue of land cover classification using remote sensing image. In this study, the Beijing-Tianjin-Hebei region was selected as a study area for land cover classification using MODIS data. The 16-day MOD13Q1/EVI data in 2013, MOD09Q1 (Band1, 2) and MOD09A1(Band3-7) products in May 2013 were used as the basic data. Harmonic analysis method was employed to remove clouds and noises of the whole year's EVI, so that it can better reflect plant phenology. Then, the processed MOD13Q1/EVI data, surface albedo of MODIS/Ref1-7, modified normalized difference water index (MNDWI), normalized difference soil brightness index (NDSI), and normalized difference water index (NDWI) were integrated to construct three schemes of CART decision tree to investigate the land cover classification of the Beijing-Tianjin-Hebei region. The three band combinations are scheme1: 23 phases of EVI of 2013; scheme2: 23 phases of EVI of 2013 plus B1-B7 of MOD09; and scheme3: scheme2+MNDWI+NDSI+NDWI. The results show that the overall classification accuracy of the three schemes reaches 86.70%, 89.98%, and 89.98% respectively. Their Kappa coefficients are 84.94%, 88.66%, and 90.20% respectively. Therefore, MODIS images with various classification characteristics, combined with the decision trees can achieve higher precision land cover classification. This proves the feasibility of the proposed method for land cover classification at the regional scale.

Key words: land cover, classification, MODIS images, harmonics analysis, CART decision tree, classification feature combination, Beijing-Tianjin-Hebei region

CLC Number: 

  • TP79