An integrated spatio-temporal classification method for urban fringe change detection analysis

Yetao Yanga*, Qiming Zhoub, Jianya Gongc & Yi Wanga a Institute of Geophysics and Geomatics, China University of Geosciences , Wuhan, 430074, PR China b Department of Geography , Hong Kong Baptist University , Kowloon, 9999, Hong Kong c State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing , Wuhan University , Wuhan, PR China * E-mail: yetao.yang@gmail.com The urban fringe is the transition zone between urban land use and rural land use. It represents the most active part of the urban expansion process. Change detection using multi-temporal imagery is proven to be an efficient way to monitor land-use/land-cover change caused by urban expansion. In this study, we propose a new multi-temporal classification method for change detection in the urban fringe area. The proposed method extracts and integrates spatio-temporal contextual information into multi-temporal image classification. The spatial information is extracted by object-oriented image segmentation. The temporal information is modelled with temporal trajectory analysis with a two-step calibration. A probabilistic schema that employs a global membership function is then used to integrate the spectral, spatial and temporal information. A trajectory accuracy measurement is proposed to assist the comparison on the performances of the integrated spatio-temporal method and classical pixel- and ‘snapshot’-based classification methods. The experiment shows that the proposed method can significantly improve the accuracies of both single scene classification and temporal trajectory analysis.