A Spatial-Temporal Modeling Approach to Reconstructing Land-Cover Change Trajectories from Multi-temporal Satellite Imagery

作者：Liu Desheng^*; Cai Shanshan

来源：Annals of the Association of American Geographers, 2012, 102(6): 1329-1347.

DOI：10.1080/00045608.2011.596357

• change detection
• land-cover change trajectories
• Landsat imagery
• post-classification comparison
• spatial-temporal contextual information

Temporal trajectories of land-cover change provide important information on landscape dynamics that are critical to our understanding of complex human-environment adaptive systems. The increasing availability of long time series of satellite images, especially the recent free release of multi-decadal Landsat satellite archive, presents a great opportunity to improve our ability to detect land-cover change over multiple dates and advance land change science. In this article, a spatial-temporal modeling approach is developed for reconstructing land-cover change trajectories from time series of satellite images. The change detection method represents an enhancement to the conventional post-classification comparison. The key innovation lies in the use of Markov random field theory to model spatial-temporal contextual information explicitly in the classification of time series images. When evaluated using a time series of seven Landsat images in a case study of southeast Ohio, the spatial-temporal modeling approach yielded significantly more accurate and consistent trajectories of land-cover change than conventional non-contextual approaches. The results from the case study demonstrate the effectiveness of the change detection method in reconstructing land-cover change trajectories and also highlight the utility of spatial-temporal contextual information in improving the accuracy and consistency of land-cover classifications across space and time.

• 出版日期2012