A spatial-temporal modeling approach to reconstructing land-cover change trajectories from multi-temporal satellite imagery

Auteur(s) et Affiliation(s)



Description :
A spatial-temporal modeling approach is developed here 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 7 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. These results also highlight the utility of spatial-temporal contextual information in improving the accuracy and consistency of land-cover classifications across space and time.


Type de document :
Article de périodique

Source :
Annals of the Association of American Geographers, issn : 0004-5608, 2012, vol. 102, n°. 6, p. 1329-1347, nombre de pages : 19, Références bibliographiques : 2 p.

Date :
2012

Editeur :
Pays édition : Etats-Unis, Washington, DC, Association of American Geographers