Spatio‐temporal land use multi‐objective optimization: A case study in Central China

Much effort has been applied to the study of land use multi‐objective optimization. However, most of these studies have focused on the final land use scenarios in the projected year, without considering how to reach the final optimized land use scenario. To fill this gap, a spatio‐temporal land use multi‐objective optimization (STLU‐MOO) model is innovatively proposed in this research to determine possible spatial land use solutions over time. The STLU‐MOO is an extension of a genetic land use multi‐objective optimization model (LU‐MOO) in which the LU‐MOO is generally carried out in different years, and the solutions at year T will affect the solutions at year T + 1. We used the Wuhan agglomeration (WHA) as our case study area. The STLU‐MOO model was employed separately for the nine cities in the WHA, and social, economic, and environmental objectives have been considered. The success of the experiments in the case study demonstrated the value and novelty of our proposed STLU‐MOO model. In addition, the results also indicated that the objectives considered in the case study were in conflict. According to the results, the optimal land use plan in 2050 can be traced back to 2040, 2030, and 2020, providing a series of Pareto solutions over the years which can provide spatio‐temporal land use multi‐objective optimization solutions to support the land use planning process.     

Design Considerations and Evaluation of a Collaborative, Spatio-Temporal Decision Support System

Collaborative spatial decision support systems (C‐SDSS) have been used to help groups of stakeholders understand data and search for opportunities at resolving local and regional decision problems in various domains including land use, trans‐ portation, and water resources. The key issue in designing an effective C‐SDSS is the anticipation of user information needs. Knowledge of user information needs can guide system designers in achieving a C‐SDSS that fits the decision process. In this paper we present a design approach that is informed by stakeholder concerns, as part of a user needs assessment. The approach is based on the premise that knowing stakeholders’ concerns can help anticipate user information needs and consequently lead to a more usable C‐SDSS. We demonstrate the approach with the example of a spatio‐temporal decision problem involving conjunctive water administration in the Boise River Basin in southwestern Idaho. The spatial dimension of the decision task involves delineating the areas of conjunctive water administration while the temporal dimension involves selecting the year in which a given area will start to be administered. We show how the elicitation of stakeholder concerns leads to functional specification of a collaborative spatio‐temporal decision support system.     

空间决策支持系统及其支撑软件的设计与应用

本文讨论了SDSS的概念和基本理论,以决策支持为目标,面向半结构化和非结构化问题,用模型驱动的SDSS,是GIS未来的发展方向。在技术上用C语言实现了SDSS支撑软件的设计,并应用于国家科技攻关课题“三川河流域区域治理与开发信息系统”,取得了良好效果;同时对SDSS开发中存在问题作了讨论。     

面向游客旅游决策支持系统的设计与实现——以西安翠华山国家地质公园为例

本文对GIS与SDSS的集成在旅游业的应用进行了研究,采用原型法和面向对象相结合的系统设计方法对面向游客决策支持系统部分功能进行了设计和实现,对Dijkstra最短路径选择算法进行改进,并应用于该系统的动态规划模型。该系统在体现以游客为主体及动态指导方面实现效果良好,可为游客进行景区游览提供动态决策支持和科学指导。展现了GIS和SDSS在旅游业应用的广阔前景。     

An open source GIS‐based Planning Support System: Application to the land use plan of La Troncal,Ecuador

Planning Support Systems (PSS) comprise a wide variety of geo‐technological tools related to GIS and spatial modeling aimed at addressing land planning processes. This article describes the OpenRules system, a PSS based on a previous system called RULES. Among OpenRules new features are its architecture, based exclusively on free and open source software, and its applicability to all land use types, including rural and urban uses. In addition, OpenRules incorporates an unlimited number of land evaluation factors and a new objective in land use spatial allocation. OpenRules has been programmed in Java and implemented as a module of the free GIS software gvSIG, with full integration between the GIS and the decision support tools. Decision support tools include multicriteria evaluation, multiobjective linear programming and heuristic techniques, which support three basic stages of land use planning processes, namely land suitability evaluation, land use area optimization and land use spatial allocation. The application of OpenRules to the region of La Troncal, Ecuador, demonstrates its capability to generate alternative and coherent solutions through a scientific and justified procedure at low cost in terms of time and resources.     

Spatial optimization for land acquisition problems: A review of models,solution methods,and GIS support

This article reviews the interdisciplinary research field of spatial optimization for land acquisition problems. We start with a theoretical framework to identify three categories of spatial optimization models: problems with aspatial constraints, location models, and problems with topological constraints. Exact, heuristic, and metaheuristic approaches to solving these problems are critically discussed. Tools that are available in commercial and open‐source GIS packages are reviewed from four aspects. We first survey the off‐the‐shelf support and then the development environments in these packages. A case study of the one‐center problem is used to illustrate the computational performance of different solution methods. Finally the advantages and disadvantages of current GIS data models are discussed. The article concludes with challenges and future directions for solving spatial optimization problems for land acquisition.     

空间决策支持系统开发平台及其应用实例

空间决策支持系统（Ｓｐａｔｉａｌ Ｄｅｃｉｓｉｏｎ Ｓｕｐｐｏｒｔ Ｓｙｓｔｅｍ ＳＤＳＳ）作为在地理信息系统（ＧＩＳ）和决策支持系统（ＤＳＳ）基础上发展起来的一个新光科学技术领域,自本世纪８０年代中后期后来,在国内外已引起越来越广泛的关注和重视。通过大量文献的分析表明：对这种系统目前尚有许多不同的理解和认识。作者认为只有那些能够帮助决策者生成、比较和选择空间决策方案的信息系统才能纳入ＳＤＳＳ的范     

基于GIS的城镇土地估价空间决策支持系统的设计研究

将空间决策支持系统的概念和理论引入到城镇土地佑价中,基于GIS平台建立了城镇土地估价空间决策支持系统.对该系统设计目标与需求分析、系统结构、数据库设计等进行了阐述,并介绍了该系统的功能.通过城镇土地估计空间决策支持系统的建立使城镇土地佑价工作更加科学化、系统化、信息化.     

Accounting for Spatial Uncertainty in Optimization with Spatial Decision Support Systems

Spatial decision support systems (SDSS) are designed to make complex resource allocation problems more transparent and to support the design and evaluation of allocation plans. Recent developments in this field focus on the design of allocation plans using optimization techniques. In this paper we analyze how uncertainty in spatial (input) data propagates through, and affects the results of, an optimization model. The optimization model calculates the optimal location for a ski run based on a slope map, which is derived from a digital elevation model (DEM). The uncertainty propagation is a generic method following a Monte Carlo approach, whereby realizations of the spatially correlated DEM error are generated using 'sequential Gaussian simulation'. We successfully applied the methodology to a case study in the Austrian Alps, showing the influence of spatial uncertainty on the optimal location of a ski run and the associated development costs. We also discuss the feasibility of routine incorporation of uncertainty propagation methodologies in an SDSS.     

Land Cover and Vegetation Change in the Yellow River Delta Nature Reserve Analyzed with Landsat Thematic Mapper Data

Abstract

Coastal wetland is a major part of wetlands in the world. Land cover and vegetation mapping in a deltaic lowland environment is complicated by the rapid and significant changes of geomorphic forms. Remote sensing provides an important tool for coastal land cover classification and landscape analysis. The study site in this paper is the Yellow River Delta Nature Reserve (YRDNR) at the Yellow River mouth in Shangdong province, China. Yellow River Delta is one of the fastest growing deltas in the world. YRDNR was listed as a national level nature reserve in 1992. The objectives of this paper are two fold: to study the land cover status of YRDNR, and to examine the land cover change since it was declared as a nature reserve. Land cover and vegetation mapping in YRDNR was developed using multi‐spectral Landsat Thematic Mapper (TM) imagery acquired in 1995. Land cover and landscape characteristics were analyzed with the help of ancillary GIS. Land use investigation data in 1991 were used for comparison with Landsat classification map. Our results show that YRDNR has experienced significant landscape change and environmental improvement after 1992.     

建立面向区域农业可持续发展的空间决策支持系统的方法探讨

在解决诸如工业选址的空间问题时，空间决策支持系统避免了流行的商用ＧＩＳ软件在空间信息的分析评价，时空分布，预测和模拟以及决策等模型分析功能的不足，该文提出了建立ＳＤＳＳ的两种基本途径；一是利用现有ＧＩＳ与分析决策模型进行集成联结生成ＳＤＳＳ；另一种途径是自行开发具有空间数据管理和分析决策模型的一体化ＳＤＳＳ。     

Selecting conservation reserves using species-covering models: Adapting the ARC/INFO GIS

Conflicts between human development of the landscape and conservation of biodiversiry will continue to grow. Given this reality, there have been a number of attempts to model the optimal selection of conservation reserve sites such that maximum biodiversity protection can be attained within a limited budget for land acquisition. Here we adapt the Location-Allocation module of ARC/INFO to solve the problem of representing, or covering, as many species as possible in a fixed number of selected reserve sites. Resident ARC/INFO solution routines are applied to an innovative 'logical' network that converts the problem of optimal reserve selection into a problem of optimal facility placement, which the Location-Allocation module can recognize and solve. Use of this unique logical network structure as input to ARC/INFO's internal solvers makes possible, compared to previous methods, a much tighter integration of spatial optimization tools with mapping and database tools, all of which are internal to the GIS and accessed via a menu-driven interface. The main advantage is that users of public domain data (such as the US Gap Analysis data) can conduct their own explorations of possible reserve systems without having to acquire and master optimization packages and reformat model output data for GIS display and post-analysis of solutions. Our sample application uses species data from south-western California. We also present a second major form of species-covering model grounded in the same logical network. This enhanced modcl accommodates weighting of species by their conservation importance, thus allowing reserve systems to be designed around the protection of the most threatened or vulnerable biota.     

Developing a web-based spatial decision support system for geothermal exploration at the Olkaria geothermal field

ABSTRACT

Geothermal exploration is a complex process that spans a number of disciplines. Before a decision is made to drill a geothermal well, there is need for an extensive exploration process to determine the most suitable location. The process of evaluating and analyzing data from individual scientific disciplines can be complex and tedious. Attempts have been made at solving this problem using GIS-based tools but the uptake of these tools is often hindered by the limited knowledge of GIS by decision makers. This paper presents an approach for solving the geothermal exploration question through a web-based spatial decision support system (SDSS) that incorporates the various geosciences through a multi-criteria spatial decision analysis model. The results reveal a decision-making gap that is to be filled using a novel, automated exploration SDSS. This approach hypothesizes an easier and faster decision-making process. The research focuses on Olkaria, an active geothermal area in Kenya, East Africa and highlights a pragmatic approach to identifying priority areas for drilling. It evaluates contributions made by many disciplines in identifying potential sites ideal for harnessing geothermal energy and the gaps that emerge in an effort to synergize the results from the different disciplines.     

Evaluation and development of sustainable urban land use plans through spatial optimization

Along with rapid global urbanization, cities are challenged by environmental risks and resource scarcity. Sustainable urban planning is central to address the dilemma of economic growth and ecosystem protection, where the use of land is critical. Sustainable land use patterns are spatially explicit in nature, and can be structured and addressed using spatial optimization integrating GIS and mathematical models. This research discusses prominent sustainability concerns in land use planning and suggests a generalized multi‐objective spatial optimization model to facilitate conventional planning. The model is structured to meet land use demand while satisfying the requirements of the physical environment, society and economy. Unlike existing work relying on raster data, due to its simple data structure and ease of spatial relationship evaluation, this research develops an approach for identifying land use solutions based on vector data that better reflects the actual shape and spatial layout of land parcels as well as the ways land use information is managed in practice. An evolutionary algorithm is developed to find the set of efficient (Pareto) solutions given the complexity of vector‐based representations of space. The proposed approach is applied in an empirical study of Dafeng, China in order to support local urban growth and development. The results demonstrate that spatial optimization can be a powerful tool for deriving effective and efficient land use planning strategies. A comparison to results using a raster data approach supports the superiority of land use optimization using vector data as part of planning practice.     

A Genetic Algorithm for Tributary Selection with Consideration of Multiple Factors

Drainage systems are important components in cartography and Geographic Information Systems (GIS), and achieve different drainage patterns based on the form and texture of their network of stream channels and tributaries due to local topography and subsurface geology. The drainage pattern can reflect the geographical characteristics of a river network to a certain extent. To preserve the drainage pattern during the generalization process, this article proposes a solution to deal with many factors, such as the tributary length and the order in river tributary selection. This leads to a multi‐objective optimization problem solved with a Genetic Algorithm. In the multi‐objective model, different weights are used to aggregate all objective functions into a fitness function. The method is applied on a case study to evaluate the importance of each factor for different types of drainage and results are compared with a manually generalized network. The result can be controlled by assigning different weights to the factors. From this work, different weight settings according to drainage patterns are proposed for the river network generalization.     

天津市土地整理储备管理信息系统总体设计

土地整理储备工作涵盖了土地计划、土地收购、土地整理储备和土地供应等多个环节,具有业务过程复杂,持续周期长等特点,迫切需要利用信息化手段提升管理效率。结合天津市土地整理储备工作现状,探讨了土地整理储备信息化的实现方法与技术,设计了天津市土地整理储备管理信息系统总体架构,开发了集业务协同、过程监控、宏观统筹管理和辅助决策支持功能于一体的管理系统,并对系统功能作了详尽的介绍。     

GIS- and RS-based spatial decision support: structure of a spatial environmental information system (SEIS)

Abstract

The development of spatial decision support for environmental resource management, e.g. forest and agroecosystem management, biodiversity conservation, or hydrological planning, started in the 1980s and was the focus of many research groups in the 1990s. The combined availability of spatial data and communication, computing, positioning, geographic information system (GIS)- and remote sensing (RS)-technologies has been responsible for the implementation of complex SDSS since the late 1990s. The regional GIS-based modelling of environmental resources, and therefore ecosystems in general, requires setting-up an extensive geo and model database. Spatial data on topography, soil, climate, land use, hydrology, flora, fauna and anthropogenic activities have to be available. Therefore, GIS- and RS-technologies are of central importance for spatial data handling and analysis. In this context, the structure of spatial environmental information systems (SEIS) is introduced. In SEIS, the input data for environmental resource management are organised in at least seven sub-information systems: base geodata information system (BGDIS), climate information system (CIS), soil information system (SIS), land use information system (LUIS), hydrological information system (HIS), spatial/temporal biodiversity information system (STBIS), forest/agricultural management information system (FAMIS). The major tasks of a SEIS are to (i) provide environmental resource information on a regional level, (ii) analyse the impact of anthropogenic activities and (iii) simulate scenarios of different impacts.     

空间决策支持系统通用软件工具的试验研究

空间决策支持系统（ＳＤＳＳ）是近年来在常规决策支持系统（ＤＳＳ）和地理信息系统（ＧＩＳ）相结合的基础上，发展起来的一种新型的信息系统。在本文中，作者简要地论述了ＳＤＳＳ的技术特点及其与ＧＩＳ、专家系统的差异，ＳＤＳＳ通用软件工具的设计思想及其原型系统的总体结构以及建立ＳＤＳＳ通用软件工具原型系统的关键技术问题及其解决办法。在开发ＳＤＳＳ通用软件工具的过程中，引入了应用框架生成及其实例化的概念，为ＳＤＳＳ的发展和应用开拓了一条有效的途径。     

Enhancing a GIS Cellular Automata Model of Land Use Change: Bayesian Networks, Influence Diagrams and Causality

Cellular Automata (CA) models at present do not adequately take into account the relationship and interactions between variables. However, land use change is influenced by multiple variables and their relationships. The objective of this study is to develop a novel CA model within a geographic information system (GIS) that consists of Bayesian Network (BN) and Influence Diagram (ID) sub‐models. Further, the proposed model is intended to simplify the definition of parameter values, transition rules and model structure. Multiple GIS layers provide inputs and the CA defines the transition rules by running the two sub‐models. In the BN sub‐model, land use drivers are encoded with conditional probabilities extracted from historical data to represent inter‐dependencies between the drivers. Using the ID sub‐model, the decision of changing from one land use state to another is made based on utility theory. The model was applied to simulate future land use changes in the Greater Vancouver Regional District (GVRD), Canada from 2001 to 2031. The results indicate that the model is able to detect spatio‐temporal drivers and generate various scenarios of land use change making it a useful tool for exploring complex planning scenarios.     

A GIS‐based Vehicle Mobility Estimator for Operational Contexts

A vehicle mobility estimator has been developed to produce decision aid maps for projecting civil or military forces on operational theatres. Based on the exploitation of classical geographical sources (e.g. digital elevation models, optical images, and vector databases) and thematic sources (e.g. climate, meteorological, pedological and land cover databases), the system computes speed maps for different kinds of vehicles moving both on‐road and off‐road. Such computations are realized through a ground‐vehicle interaction module that estimates the vehicle performance from experimental results, numerical simulations and empirical relationships. The system's architecture is built using a GIS interface that manages the data, the computation and the presentation layers. An operational version of this tool has been tested and validated on several operational theatres in France and in northern Africa. The results show good agreement between the predicted mobility performance of various vehicles and those observed on the field. A case study is presented to illustrate the mobility maps and demonstrate their relevance in the decision‐making chain depending on different climate contexts. A short application to itinerary optimization is presented as a promising future application.