Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed

• Published in: International journal of applied earth observation and geoinformation 2012-02, Vol.14 (1), p.12-21
• Main Authors: Wang, Dongchuan, Gong, Jianhua, Chen, Liding, Zhang, Lihui, Song, Yiquan, Yue, Yujuan
• Format: Article
• Language: English
• Subjects: Applied geophysics; Aspect; Change trajectories; Earth sciences; Earth, ocean, space; Exact sciences and technology; Internal geophysics; Land use/cover change; Landscape metrics; RCI; River line; Slope
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2011.08.007

► Overlaying trajectories with natural factors works well in LUCC analysis. ► We found that in the study area RCI is related to the distance to the river line. ► There is a certain correlation between RCI and slope grades in the study area. ► No obvious correlation exists between RCI and aspect grades in the study area. Human-induced land use/cover change has been considered to be one of the most important parts of global environmental changes. In loess hilly and gully regions, to prevent soil loss and achieve better ecological environments, soil conservation measures have been taken during the past decades. The main objective of this study is to quantify the spatio-temporal variability of land use/cover change spatial patterns and make preliminary estimation of the role of human activity in the environmental change in Xihe watershed, Gansu Province, China. To achieve this objective, the methodology was developed in two different aspects, that is, (1) analysis of change patterns by binary image of change trajectories overlaid with different natural geographic factors, in which Relative Change Intensity (RCI) metric was established and used to make comparisons, and (2) analysis based on pattern metrics of main trajectories in the study area. Multi-source and multi-temporal Remote Sensing (RS) images (including Landsat ETM+ (30 June 2001), SPOT imagery (21 November 2003 and 5 May 2008) and CBERS02 CCD (5 June 2006)) were used due to the constraints of the availability of remotely sensed data. First, they were used to extract land use/cover types of each time node by object-oriented classification method. Classification results were then utilized in the trajectory analysis of land use/cover changes through the given four time nodes. Trajectories at every pixel were acquired to trace the history of land use/cover change for every location in the study area. Landscape metrics of trajectories were then analyzed to detect the change characteristics in time and space through the given time series. Analysis showed that most land use/cover changes were caused by human activities, most of which, under the direction of local government, had mainly led to virtuous change on the ecological environments. While, on the contrary, about one quarter of human-induced changes were vicious ones. Analysis through overlaying binary image of change trajectories with natural factors can efficiently show the spatio-temporal distribution characteristics of land use/cover change patte