Spatio-temporal Analysis and Optimization of Land Use/Cover Change

Shenzhen as a Case Study

Biao Liu, Bo Huang, Wenting Zhang

• Publisher: CRC Press
• Year: 2017
• Print ISBN: 9780367885755
• eBook ISBN: 9781351966733
• Topic: Biological Sciences
• Subtopic: Environmental Science
• Index: Biological Sciences

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.

Part I

Introduction

Chapter 1

Introduction

Due to the drastic changes in land use, irrespective of their quantity or pattern, they have a profound influence on the people’s daily lives. Unfortunately, because of the lack of scientific land use analysis and planning, there are bad influences which we do not accept. As a result, especially during the last half century, the importance of these two research fields has attracted the interests of researchers around the world. Although there have been numerous studies relating to them, this book analyzes and lists their several problems. Land use analysis and planning can often be studied respectively, but a combination of them is more and more closely sought.

So, in this introductory chapter, the detailed background of LUCC analysis and land use planning is introduced at the outset. Section 1.2 proposes several problems of the contemporary studies. And the objectives of this book are stated at the end of this chapter, in the hope of solving all the problems considered in the preceding sections.

1.1 Background

The 20th century has witnessed significant changes in land use patterns. During the last three centuries, almost 1.2 million km² of forest and woodland and 5.6 million km² of grassland and pasture have been converted to other uses, globally (Ramankutty & Foley, 1999; Alexander Popp et al., 2016). Meanwhile, the impacts of land use change are escalating to threatening proportions around the globe. Many environmental problems can be traced back to land use change (Wolter et al., 2015; Yao et al., 2015): these include desertification, eutrophication, acidification, climate change, eustatic sea-level rise, greenhouse effect, and biodiversity loss. The study of land use change has, therefore, received a great deal of attention from policy-makers, planners, and developers who are seeking a sustainable land use plan (Turner & Meyer, 1991; Lambin et al., 2003; Rindfuss et al., 2004; Pontius et al., 2007; Huang et al., 2009a; Nicolas et al., 2016). Both the International Geosphere-Biosphere Programme (IGBP) and the International Human Dimensions Programme (IHDP) have proposed a Land Use and Cover Change (LUCC) Core Project/Research Programme.

For the cities, one of the main factors of LUCC is urbanization. Urbanization is a common worldwide trend that is caused by population growth and economic development. In the urbanization process, social conflicts result in the mass movement of people, which undermine the operational systems of land access (Silberstein & Maser, 2000; Ngai et al., 2016). Urbanization causes land degradation and uncontrolled natural resource use. China has witnessed astonishing economic growth and urban development during the past three decades. The rapid urban sprawl triggered by increased economic activity and population growth has caused numerous problems, such as the loss of open space, excessive carbon emission, severe soil erosion, and other environmental deterioration problems (Romero & Ordenes, 2004; Stone et al., 2010; Ma et al., 2016; Vanwalleghem et al., 2017). Moreover, the competition of local, national, and international users with various socio-economic statuses and powers to achieve economic growth, and nature conservation, increases the difficulty of land use management. Therefore, both a scientific model to properly analyze land use change and a proactive plan to properly structure and allocate land use are required.

Land use change models aim to understand the causes and consequences of land use dynamics. Currently, several modeling approaches with different outcomes for land use change simulation and exploration are available. Such approaches offer possibilities for experiments to test our understanding of the key processes, thus allowing the model to describe the sensitivity of quantitative changes and provide alternative pathways into the future.

Earlier studies in land use modeling involve dividing the study area into grid cells and describing it by a pre-determined set of biophysical and socio-economic variables. Based on this, methods such as cellular automata (CA) (Clarke & Gaydos, 1998; Wu, 1998; Wu, 2002; Ahangaran, 2017), agent (Kohler & Gumerman, 2000; Gimblett, 2002), Markov chain analysis (Lopez et al., 2001; Bielecki et al., 2016), and logistic regression (Wu & Yeh, 1997; Cheng & Masser, 2003; Morotti & Grandi, 2016) are employed. The causal factors and the main models (CA, agent, regression, etc.) used for LUCC change analysis are described in the following sections.

Since land use change modeling endeavors to explore the relationship between causal factors and land use patterns or changes (multi-temporal land use patterns), the analysis of causal factors is an indispensable part in land use change modeling.

Land use change is a complex process influenced by a number of factors. As is evident from earlier studies, no single set of factors can explain the changes. Researchers (Turner, 1995; Bicik et al., 2001) have provided a summarization of the causal factors. They have mentioned two kinds of factors: (1) natural factors, such as climate change, soil, hydrology and nature disasters, and (2) human factors, such as population, technology level, economic growth, and technology level. The IHDP report (Nunes et al., 1999) also summarizes the causal factors into natural and human factors.

Initially, most researchers focused on natural factors, which were treated as the determinants to land use change. Crow et al. (1999) and Naveh (1995) considered the impact from climate change, soil, and DEM. Climate change was considered to be a major causal factor to land use change on a large spatial and temporal scale. The influence of natural factors on land use change is realized over a long time scale. However, human factors play a key role in land use change over a short time scale. Hence, more attention has been paid to the study of human factors. Many researchers consider economic growth as a very important factor (Bingham et al., 1995; Houghton, 1994; Fischer et al., 2001; Bicik et al., 2001). Also the impact from population growth, political regimen, and technology development is studied (Reid et al., 2000; Bicik et al., 2001; Houghton, 1994). Nowadays, due consideration is given to both human and natural factors.

The important parameters that influence land use changes are as follows.

(1) demographic factors (population size, population growth, and population density) are widely treated as major causal factors of land use change (Verburg et al., 2001);

(2) accessibility is also often viewed as a significant driver for land use change through its effect on the cost of transportation and ease of settlem...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Content
• Preface
• PART I: Introduction
• PART II: Spatio-temporal Analysis Model
• PART III: Land Use Multi-objective Optimization
• PART IV: Summary and Contributions
• References