An Efficient Graph-based Method for Long-term Land-use Change Statistics

Abstract

Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency.

Determining Changes in Land Use Structure in Małopolska Using Statistical Methods

“…Modelling is an important technique for determining land use status, assessing dynamics and trends in land use [12,16], and searching for primary directions in planning [4,17]. Thus, statistical analysis of land use change is increasingly more important for sustainable land management and is attracting ever more attention in scientific circles [18][19].…”