Chunyang He^a,b, Anni Wei^b, Peijun Shi^a, Qiaofeng Zhang^c, Yuanyuan Zhao^a,b

a State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China

b College of Resources Science & Technology, Beijing Normal University, Beijing 100875, China

c Department of Geosciences, Murray State University, Murray, KY 42071, USA

A b s t r a c t：Detecting land-use/land-cover (LULC) changes in rural–urban fringe areas (RUFAs) timely and accuratelyusing satellite imagery is essential for land-use planning and management in China. Although traditionalspectral-based change-vector analysis (CVA) can effectively detect LULC change in many cases, it encountersdifficulties in RUFAs because of deficiencies in the spectral information of satellite images. To detectLULC changes in RUFAs effectively, this paper proposes an extended CVA approach that incorporatestextural change information into the traditional spectral-based CVA. The extended CVA was applied tothree different pilot RUFAs in China with different remotely sensed data, including Landsat ThematicMapper (TM), China–Brazil Earth Resources Satellite (CBERS) and Advanced Land Observing Satellite(ALOS) images. The results demonstrated the improvement of the extended CVA compared to the traditionalspectral-based CVA with the overall accuracy increased between 4.66% and 8.00% and the kappacoefficient increased between 0.10 and 0.15, respectively. The advantage of the extended CVA lies inits integration of both spectral and textural change information to detect LULC changes, allowing foreffective discrimination of LULC changes that are spectrally similar but texturally different in RUFAs. Theextended CVA has great potential to be widely used for LULC-change detection in RUFAs, which are oftenheterogeneous and fragmental in nature, with rich textural information.

 

Keywords: Change-vector analysis，Land-use/land-cover change，Rural–urban fringe area，Texture information