Spatio-temporal Analysis and Optimization of Land Use/Cover Change : Shenzhen as a Case Study

This book concentrates on developing a set of innovative models to address land use challenges. It subsequently applies them by analysing and optimizing the land use in SEZ, Shenzhen, China. Within the logistic regression framework, it firstly proposes three spatio-temporal logit models for land use change analysis, namely, GTWLM, ST-PLM and GSTLM for short. All of these have extended or improved the existing model in various aspects. The book also describes a MOO-based two-level spatial planning model of land use, which aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels.

This book proposes a method to solve land use problems, and has made some significant contributions to the land use analysis and optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted logit model (GTWLM), spatio-temporal panel logit model (ST-PLM) and generalized spatio-temporal logit model (GSTLM), are proposed. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temporal framework by proposing a spatiotemporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model. By integrating GTWLM and ST-PLM, the GSTLM explores spatio-temporal non-stationarity and correlations simultaneously, whilst considering their individual effects to construct an integrated model.

Secondly, a MOO-based two-level spatial planning of land use is proposed. The spatial planning aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels. In spatial planning, GIS and Remote Sensing are used to evaluate, analyze, and measure environmental, economic and social issues. The quantitative relationships between these objectives and spatial land use allocation are then used as rules in the MOO process to simulate environmental conditions under different spatial land use allocation scenarios. The book features a case study of Shenzhen city, the most important Special Economic Zone in China.

This book will be of interest to academics and professionals in the fields of urban planning, land resource management, remote sensing and geographic information systems.