Spatiotemporal analysis of land-use and land-cover change in the Brazilian Amazon

Abstract

This paper provides a comparative analysis of land-use and land-cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired during the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water – was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition, and rates among the three study areas and indicates the importance of analysing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g. urban expansion, roads, and land-use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates.

Acknowledgements

The authors wish to thank the National Institute of Child Health and Human Development at NIH (grant # R01 HD035811) for their support of this research, addressing population and environment reciprocal interactions in several regions of the Brazilian Amazon. Any errors are solely the responsibility of the authors and not of the funding agencies. The authors also thank the anonymous reviewers for their constructive suggestions and comments for revising this paper.