The spatial planning of land use is the process of allocating different uses or activities to specific areas in a region and is the core content of land use planning systems. Land use planning is increasingly becoming complex because of the multifaceted problems it faces, such as guaranteeing economic growth, maintaining social equity, and preserving the environment. These objectives present conflicting demands from various land use groups and interest groups. The increased inclusion of objectives leads to different demands on the expected results. Moreover, the increased complexity of land use planning problems is influenced by the involvement and definition of multiple objectives. These objectives may be unstructured, nonlinear, and difficult to handle. Within this context, computer-based techniques have been developed to assist planners in decision making. Among all of the techniques, multi-objective optimization (MOO) approaches are the most well-known techniques in addressing multi-objective problems in land use planning. MOO approaches have successfully accomplished significant achievements. However, literature shows that some spatially-related environmental objectives, such as carbon emission, non-point source pollution, and soil erosion, are missing because of the difficulty in evaluating, analyzing, and measuring such complex land use objectives. / The land use planning process in China is divided into a series of land use plans at different levels. Among these plans, the municipal overall land use plan and the urban master plan are involved in managing the land use resources in a city. The municipal overall land use plan administers the urban and non-urban areas in an administrative scope, whereas the urban master plan focuses only on the development of urban areas. These two types of land use plans are conducted by two different government departments. These plans are usually inconsistent, particularly in terms of space. / Considering the spatial inconsistency between the municipal overall land use plan and urban master plan in China, a MOO-based two-level spatial planning of land use is conducted. 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, the geographic information system (GIS) and remote sensing (RS) are used to evaluate, analyze, and measure environmental, economic, and social issues with regard to the spatial land use change. 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. / Shenzhen, a rapidly developing city in China, is selected as the case study area to validate the proposed approach. The objectives and constraints in the spatial planning of land use are defined at two different levels based on the land use principles, local and national policies in China, and characteristics of Shenzhen. At the first level, nine objectives are proposed, namely, maximizing economic benefit, maximizing ecosystem services value, minimizing soil erosion, minimizing non-point source pollution, minimizing carbon emission, maximizing compatibility, minimizing change cost, maximizing accessibility, and minimizing landslide susceptibility. The objectives of spatial planning of land use at the urban level are subsequently proposed, as follows: maximizing housing capacity, maximizing employment capacity, minimizing changing cost, minimizing pollution from industrial lands, maximizing mixed land uses, maximizing green space, maximizing accessibility, maximizing compatibility, and maximizing spatial equity. The proposed spatial-related objectives are quantified by GIS. / Results indicated that the MOO-based two-level spatial planning can create trade-offs among the conflicting objectives, and a set of Pareto solutions is provided as options for decision makers or planners. Moreover, the MOO-based two-level spatial planning can generate a consistent land use planning system for Shenzhen. / 土地利用空間規劃通過對土地的空間位置及結構的調配以達到土地資源的合理利用.一個良好的土地利用規劃需滿足各方面的要求及目標,例如確保經濟增長的同時,保證社會公平,同時也保護環境的可持續發展.但由於社會各界對土地利用有不同的利益訴求,導致規劃中出現眾多相互衝突但不矛盾的目標.此外,土地利用規劃目標常常是空間相關的,這些空間相關目標具有非結構性,非線性的特點,使得整個土地利用規劃過程更加複雜.在這種情況下,電腦支援技術成為實際規劃中不可或缺的工具之一.在所有技術中,多目標優化模型已經被廣泛的應用于解決土地利用規劃中的多目標問題.多目標優化模型已經在土地利用規劃領域取得了大量有意義的成果.然後,現有研究往往關注土地利用結構,而忽視複雜而難以定義的土地空間問題,例如城市熱島,非點源污染,土壤侵蝕. / 在中國,土地利用規劃系統由一系列不同空間層次的規劃組成.在中國土地利用規劃系統中,市(地)級土地利用總體規劃和城市總體規劃主要關注某個城市的土地資源配置佈局問題.市(地)級土地利用總體規劃管理整個市(地)行政範圍內的土地資源,包括城市用地及非城市用地;然而城市總體規劃僅關注建成區及規劃區範圍內的土地資源.同時,這兩種規劃由不同的政府部門設定並統籌實施,這導致了兩規劃在空間範圍的不一致性. / 考慮到市(地)級土地利用總體規劃和城市總體規劃在空間上的不一致性,本研究提出了一個基於多目標優化的兩層土地利用空間規劃模型,並主要關注土地資源的空間佈局.在空間規劃中,地理資訊系統及遙感技術被用來評價,分析和衡量在土地利用變化下的環境目標.不同目標與空間土地利用變化之間的量化模型將作為多目標優化模型中的規則,用以類比不同土地利用情景下的各種目標實現情況. / 深圳作為一個高速發展並經歷土地利用迅速變化的城市被選為本研究的案例研究區.深圳市土地利用空間規劃的目標和限制條件被分為兩個層次,一個市(地)級土地利用總體規劃層次和另一個城市總體規劃層次.這些目標和限制條件基於已有的土地利用規劃方法,中國土地利用相關法律法規及深圳市發展背景來確定.在市(地)級土地利用總體規劃層次,定義了九個目標,分別是經濟利益最大化,生態服務價值最大化,土壤侵蝕最小,非點源污染最小,碳排放最小,地塊之間相容性最大,土地利用變化最小,可達性最大及滑坡危害最小. 在城市總體規劃層次,定義了如下目標:住房最大化,就業最大化,綠地最大化,可達性最大,城市土地利用地塊見相容性最大,公平性最大.所有這些目標可通過統計模型,地理資訊系統技術實現其量化. / 研究結果表明,本研究所提出的兩層次土地利用規劃能夠協調各個相互衝突的目標,並且為決策者和規劃師提供一系列Pareto解.同時,基於多目標優化的兩層次空間土地利用規劃能夠為深圳提供一個保持一致性的土地利用系統. / Zhang, Wenting. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 169-184). / Abstracts also in Chinese. / Title from PDF title page (viewed on 16, November, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

Based on the models, a case study is performed on multi-temporal land use change analysis in the Special Economic Zone (SEZ), Shenzhen. The results show that all the proposed models outperform the traditional logistic regression model: multinomial logit model (MNLM), which overlooks the aforementioned issues. Compared with MNLM, GTWLM and ST-PLM increased the percentage of correctly predicted (PCP) values from 74.1% to 82.3% and 79.4%, respectively. McNamara's test shows that the differences between those models are significant. The kappa coefficients reveal that the GTWLM and ST-PLM are better than MNLM. In particular, the GSTLM yields a considerably higher PCP of 85.9%. The Kappa coefficients also indicate that the GSTLM is the most optimal model. Furthermore, the GTWLM allows the model parameters to vary across space and time, which provides deep insights into the spatio-temporal variations of the land use pattern. Assisted with the visual results, the spatio-temporal land use distribution patterns in Shenzhen are analyzed and the results presented thereafter. / Research focusing on land use change analysis is of tremendous importance in global change studies. Land use change modeling, which is a prerequisite to understanding the complexity of land use dynamics, is an effective way to describe the change patterns and delve into the causes for the changes. Despite the development of many models in the past, several important issues still remain to be addressed such as spatio-temporal non-stationarity, spatio-temporal correlation, and individual effect. The primary objective of this research is to make improvements on.the traditional logistic models to suit the characteristics and requirements of land use change modeling. Specifically, three enhancements have been made. The first enhancement deals with spatio-temporal non-stationarity, the second improvement aims to incorporate spatio-temporal autocorrelation, and the third includes individual effect. / 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 accordingly to deal with the aforementioned issues. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temproal framework by proposing a spatio-temporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model, where spatio-temporal correlation is considered in the random individual effect with an assumption that the correlation between such components is inversely proportional to the spatio-temporal distance. 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. / Liu, Biao. / Adviser: Huang Bo. / Source: Dissertation Abstracts International, Volume: 73-01, Section: A, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 124-132). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Hu Tianxin. / "August 2003." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (p. 206-220). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.