Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells

Hasi Bagan, Yoshiki Yamagata

Research output: Contribution to journalArticlepeer-review

101 Citations (Scopus)


Global urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities' fundamental characteristics and processes, and of the impact of changing land-cover on potential carbon storage. We present a grid square approach using multi-temporal Landsat data from around 1985-2010 to monitor the spatio-temporal land-cover dynamics of 50 global cities. The maximum-likelihood classification method is applied to Landsat data to define the cities' urbanized areas at different points in time. Subsequently, 1 km2 grid squares with unique cell IDs are designed to link among land-cover maps for spatio-temporal land-cover change analysis. Then, we calculate land-cover category proportions for each map in 1 km2 grid cells. Statistical comparison of the land-cover changes in grid square cells shows that urban area expansion in 50 global cities was strongly negatively correlated with forest, cropland and grassland changes. The generated land-cover proportions in 1 km2 grid cells and the spatial relationships between the changes of land-cover classes are critical for understanding past patterns and the consequences of urban development so as to inform future urban planning, risk management and conservation strategies.

Original languageEnglish
Article number064015
JournalEnvironmental Research Letters
Issue number6
Publication statusPublished - 2014 Jun 1
Externally publishedYes


  • Landsat
  • change analysis
  • grid cells
  • land cover
  • urban growth

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • General Environmental Science
  • Public Health, Environmental and Occupational Health


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