Making more out of pixel-level change information: using a neighbourhood approach to improve land change characterization across large and heterogeneous areas

Abstract

The paper demonstrates two issues; (i) how a ‘moving window approach’, that translates pixel level detected changes to landscape level, can be implemented; (ii) how the approach can overcome the limitations of pixel level change information to characterize change over large areas. First we detected changes from two periods (1986 and 2010) of LULC maps. On the pixel-based changes, we ran focal statistics summation operator separately for selected window sizes (1–10 km). Further, we assessed effect of scale in depicting the pattern and amount of change. The approach is found useful to overcome major shortfalls of pixel-based change characterization. However, varying scale of analysis provide varying amount of change and differently represent change patterns. Thus, implementing the approach over complex and large areas requires multi-scale approach. Subdividing complex and large areas into homogeneous zones can help to implement the multi-scale approach and facilitate the selection of appropriate scale of analysis.