Geo‐questionnaire: A Method and Tool for Public Preference Elicitation in Land Use Planning

Geo‐questionnaire involves an integration of sketchable maps with questions, aimed at eliciting public preferences and attitudes about land allocation and services. Respondents can link their answers with corresponding locations on a map by marking points or sketching polygon features. Geo‐questionnaires have been used to learn about perceptions and preferences of city residents for specific types of land use, place‐based services, and development projects. This article reports on results of an empirical study, in which an online geo‐questionnaire was designed and implemented to elicit preferences of residents in guiding an urban development plan. Preferences collected in the form of polygon sketches were processed using GIS operations and mapped for visual interpretation. The article focuses on aggregation and analysis of respondent preferences including the analysis of positional and attribute uncertainty. Results of the study show that geo‐questionnaire is a scalable method for eliciting public preferences with a potential for meaningfully informing land use planning.     

Understanding User Interaction Patterns within Online Systems for Public‐Participation Transportation Planning

Many research projects in public‐participation geographic information systems focused on the development of software prototypes that were conceptualized to complement traditional forms of public participation. Given the challenges introduced by the heterogeneity of their user base, system design, and decision making process, empirical evaluations of such systems based on actual use have been scarce. This article reports on a rigorous empirical assessment of human‐computer interaction of users of a web‐based system for participatory transportation planning. We devised three groups of participants with below‐average, average, and above‐average interaction duration through hierarchical cluster analysis. Subsequently, the characteristics of the clusters were subjected to logistic regression analysis to determine the significance and strength of statistical associations between duration of interaction and a host of individual‐level variables. Our results indicate a statistically significant reduction of the odds‐ratio for participants with above‐average duration of interaction in the case of no prior experience with online transportation discussions. No significant associations were found between overall duration of interaction and sociodemographic background, cognitive decision‐making style, and travel behavior. We advocate for the development of adaptable participatory systems which accommodate flexibility in terms of both the user interface and pathways of the decision making process.     

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.     

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.     

Who's Watching Your Food? A Flexible Framework for Public Health Monitoring1

By responding to potentially life‐threatening emergencies such as foodborne illnesses and water contamination, U.S. public health agencies play a vital role in promoting human health and protecting the environment. Local, state, and federal partners must collaborate to strategically plan initiatives, allocate resources, and evaluate emergency response activities. These collaborative decision‐making processes can be improved by using web‐based mapping applications for visualization and analysis. We developed a web‐based GIS framework which is applied to public health data for North Carolina's (NC) Department of Health and Human Services. The application visualizes all state‐regulated food service facilities and supports query and analysis tools crucial for food recalls or radiation contamination tracking. Built with PostgreSQL/PostGIS, GeoServer, and a customized GeoExplorer map viewer, the framework delivers a web‐based mapping tool that is flexible and Open Source. The flexibility of the framework is an important dimension of its scalability, allowing it to be customizable, modular, and portable so that it is easily configurable to support additional research and education initiatives. This approach reverses a trend toward application‐specific web mapping development in Open Source GIS. To demonstrate flexibility, we configured an additional website for forest landowner management to be used by another state agency, the NC Forest Service.     

Advancements in web‐mapping tools for land use and marine spatial planning

Land use and marine spatial planning processes are increasingly supported by systematic assessment techniques, particularly by multi‐criteria spatial analysis methods. This has been facilitated by the growing release and uptake of web‐mapping tools, which contribute to transparent, consistent, and informed planning processes and decisions. This article reviews the usability, functionality, and applicability of contemporary planning web‐mapping tools to identify the state‐of‐the‐art and future prospects. The review reveals that interfaces are increasingly available and intuitively applicable by non‐specialized users. Basic map navigation and data querying functionality is being expanded to incorporate advanced map‐making and online data geoprocessing capabilities that enable deriving new data and insights. However, the majority of published planning web tools are one‐off solutions, and a disconnect between research and practice is rendering many of these inaccessible or obsolete. Despite the significant progress made in advancing their provision in the last decade, there is a need for developing transferable interfaces that are maintained beyond project end dates, for them to effectively and consistently support planning processes.     

Improving Representation of Land‐use Maps Derived from Object‐oriented Image Classification

Object‐oriented (OO) image analysis provides an efficient way to generate vector‐format land‐cover and land‐use maps from remotely sensed images. Such image‐derived vector maps, however, are generally presented with congested and twisted polygons with step‐like boundaries. They include unclassified polygons and polygons with geometric conflicts such as unreadable small areas and narrow corridors. The complex and poorly readable representations usually make such maps not comply well with the Gestalt principle of cartography. This article describes a framework designed to improve the representation by resolving these problematic polygons. It presents a polygon similarity model integrating semantic, geometric and spectral characteristics of the image‐derived polygons to eliminate small and unclassified polygons. In addition, an outward‐inward‐buffering approach is presented to resolve the narrow‐corridor conflicts of a polygon and improve its overall appearance. A case study demonstrates that the implementation of the framework reduces the number of the polygons by 32% and the length of the polygon boundaries by 20%. At the same time, it does not cause distinct changes the distribution of land‐use types (less than 0.05%) and the overall accuracy (decreased only 0.02%) as compared with the original image‐derived land‐use maps. We conclude that the presented framework and models effectively improve the overall representation of image‐derived maps without distinct changes in their semantic characteristics and accuracy.     

Geospatial Human‐environment Simulation through Integration of Massive Multiplayer Online Games and Geographic Information Systems

This article reports on the initial development of a generic framework for integrating Geographic Information Systems (GIS) with Massive Multi‐player Online Gaming (MMOG) technology to support the integrated modeling of human‐environment resource management and decision‐making. We review Web 2.0 concepts, online maps, and games as key technologies to realize a participatory construction of spatial simulation and decision making practices. Through a design‐based research approach we develop a prototype framework, “GeoGame”, that allows users to play board‐game‐style simulations on top of an online map. Through several iterations we demonstrate the implementation of a range of design artifacts including: real‐time, multi‐user editing of online maps, web services, game lobby, user‐modifiable rules and scenarios building, chat, discussion, and market transactions. Based on observational, analytical, experimental and functional evaluations of design artifacts as well as a literature review, we argue that a MMO GeoGame‐framework offers a viable approach to address the complex dynamics of human‐environmental systems that require a simultaneous reconciliation of both top‐down and bottom‐up decision making where stakeholders are an integral part of a modeling environment. Further research will offer additional insight into the development of social‐environmental models using stakeholder input and the use of such models to explore properties of complex dynamic systems.     

Location Intelligence: An Innovative Approach to Business Location Decision‐making

As one of the leading ‘world cities’, London is particularly reliant on sources of foreign direct investment (FDI). In the face of increasing global competition and a difficult economic climate, the capital must compete effectively to encourage and support such investors. Through a collaborative study with London's official FDI promotion agency, Think London, the need for a coherent framework for data, methodologies and tools to inform business location decision‐making became apparent. This article discusses the development of a rich environment to explore, compare and rank London's business neighbourhoods. This is achieved through the development and evaluation of a model for location‐based decision support. First, we discuss the development of a geo‐business classification for London which draws upon methods and practices common in geodemographic neighbourhood classification. A geo‐business classification is developed, encapsulating relevant location variables using Principal Components Analysis into a set of composite area profiles. Second, we discuss the implementation of an appropriate Multi‐Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP), enabling the aggregation of the geo‐business classification and decision‐makers' preferences into discrete decision alternatives. Finally, we present the results of the integration of both data and model through the development and evaluation of a web‐based prototype.     

Using Pattern‐oriented Modeling (POM) to Cope with Uncertainty in Multi‐scale Agent‐based Models of Land Change

Local land‐use and ‐cover changes (LUCCs) are the result of both the decisions and actions of individual land‐users, and the larger global and regional economic, political, cultural, and environmental contexts in which land‐use systems are embedded. However, the dearth of detailed empirical data and knowledge of the influences of global/regional forces on local land‐use decisions is a substantial challenge to formulating multi‐scale agent‐based models (ABMs) of land change. Pattern‐oriented modeling (POM) is a means to cope with such process and parameter uncertainty, and to design process‐based land change models despite a lack of detailed process knowledge or empirical data. POM was applied to a simplified agent‐based model of LUCC to design and test model relationships linking global market influence to agents’ land‐use decisions within an example test site. Results demonstrated that evaluating alternative model parameterizations based on their ability to simultaneously reproduce target patterns led to more realistic land‐use outcomes. This framework is promising as an agent‐based virtual laboratory to test hypotheses of how and under what conditions driving forces of land change differ from a generalized model representation depending on the particular land‐use system and location.     

Integrated Hazards Mapping Tool

The Disaster Mitigation Act of 2000 formally establishes a national program for pre‐disaster mitigation. As part of the mitigation planning effort, state and local governments are required to perform assessments of hazards vulnerability, including the development of multi‐hazard maps. However, the number of communities possessing the technology, expertise, and time to create multi‐hazard vulnerability maps is limited due to technical and resource constraints. The use of Internet mapping technology has the potential to overcome these hurdles because it does not require users to possess a high level of GIS expertise or costly software, and it standardizes the vulnerability mapping approach. This article describes the Integrated Hazards Assessment Tool, a web‐based multi‐hazard vulnerability mapping application for local and state hazard mitigation practitioners in the state of South Carolina. The initial findings suggest the application holds strong potential as a viable decision support tool for hazard mitigation planning.     

Evaluation of Land Suitability for Urban Land‐Use Planning: Case Study Dhaka City

The aim of this research is evaluation of land suitability for urban land‐use planning. Four factors and fourteen criteria were selected for suitability analysis and land‐use planning. Factors and criteria were defined based on literature survey, experts’ opinions, local contexts and availability of data. GIS‐based Analytical Hierarchy Process (AHP) was used as a Multi‐criteria Decision Making model. The study was conducted on a selected area of Dhaka city, which is one of the fastest growing mega‐cities of the world. The research result shows that highly suitable area (13%) should be used for urban residential zone; moderately suitable area (35%) should be designated as mixed use zone; low suitable area (42%) should be reserved for agricultural use and open spaces; and not suitable area (10%) should be protected from any types of activities except agriculture. The research approached an urban land‐use planning at a regional scale.     

Incorporating sprawl and adjacency measures in land‐use forecasting model: A case study of Collin County,TX

Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.     

Spatial optimization of rural settlement relocation by incorporating inter‐village social connections under future policy scenarios

Social connections between villages can represent farmers’ interests and thus benefit participatory rural relocation planning. With rural development, however, these connections will change and may weaken the adaptation of relocation plans to future rural systems. As yet, most studies still use empirical social connections to guide relocation planning, while a few have incorporated predicted connections in the context of rural development into relocation decisions. Meanwhile, spatial optimization approaches have seldom been adopted to solve this geographical decision issue. Accordingly, our study proposes a novel spatial relocation framework that incorporates changed inter‐village social connections under future rural development scenarios. Empirical inter‐village connections and their policy‐induced changes in central China were explored using social network analysis. An integration of particle swarm optimization and geographic information systems was adopted to identify the relocation solutions with maximum inter‐village connections and maximum spatial land use compactness, and to examine how connection changes under different policy scenarios influenced relocation outcomes. The results demonstrate the significance of incorporating policy‐induced social connections into relocation plans, and most importantly, show the negative relations between changed social connections and the migration distance/direction of relocated settlements. Our study is expected to improve the adaptation of relocation plans to future rural development.     

Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles

Weather radar data play an important role in meteorological analysis and forecasting. In particular, web‐based real‐time 3D visualization will enable and enhance various meteorological applications by avoiding the dissemination of a large amount of data over the internet. Despite that, most existing studies are either limited to 2D or small‐scale data analytics due to methodological limitations. This article proposes a new framework to enable web‐based real‐time 3D visualization of large‐scale weather radar data using 3D tiles and WebGIS technology. The 3D tiles technology is an open specification for online streaming massive heterogeneous 3D geospatial datasets, which is designed to improve rendering performance and reduce memory consumption. First, the weather radar data from multiple single‐radar sites across a large coverage area are organized into a spliced grid data (i.e., weather radar composing data, WRCD). Next, the WRCD is converted into a widely used 3D tile data structure in four steps: data preprocessing, data indexing, data transformation, and 3D tile generation. Last, to validate the feasibility of the proposed strategy, a prototype, namely Meteo3D at https://202.195.237.252:82 , is implemented to accommodate the WRCD collected from all the weather radar sites over the whole of China. The results show that near real‐time and accurate visualization for the monitoring and early warning of strong convective weather can be achieved.     

协同学在可持续土地利用规划中的应用

论述了可持续发展的系统观与协同观、土地利用系统与规划的主要特征及协同学应用于可持续土地利用规划的必要性和可能性,提出了一种面向规划／决策支持的应用框架,分析了GIS与系统分析技术应用于可持续土地利用规划过程的方法与途径,并提出了今后发展的方向。     

Small‐area patch‐merging method accounting for both local constraints and the overall area balance

Small‐area patch merging is a common operation in land use data generalization. However, existing research on small‐area patch merging has mainly focused on local compatibility measures, which often lead to area imbalances among land use types from a global perspective. To address the shortcomings of previous studies by resolving local and global concerns simultaneously, this article proposes a merging method that considers both local constraints and the overall area balance. First, a local optimization model that considers three constraints—namely, the areas of neighboring patches, the lengths of shared arcs, and semantic similarity—is established. The areas of small patches are first pre‐allocated. Subsequently, in accordance with an area change threshold for individual land use types, land use types with area changes that exceed this threshold are identified. The patches corresponding to these land use types are subjected to iterative adjustments while considering the overall area balance. Based on their area splitting abilities, the split lines for small‐area patches are determined, and small‐area patches are merged. Finally, actual data from Guangdong Province are used for validation. The experimental results demonstrate that the proposed method is capable of preserving the local compatibility of patches while balancing the overall area associated with each land use type.     

Integrating a Raster Geographical Information System with Multi‐Objective Land Allocation Optimization for Conservation Reserve Design

The multi‐objective land allocation problem is to optimize the selection of land for different uses based on a set of decision objectives. For most applications, a geographical information system (GIS) is either absent or loosely coupled through file exchange. In this article the evolutionary algorithm (EA), a heuristic solution method for optimization problems, is integrated with a raster GIS to form a spatial decision support system (SDSS) for multi‐objective conservation reserve design. The SDSS effectively combines the functions of a GIS for data management, analysis, and visualization, with the optimization capability of the EA; and provides a uniform way to solve conservation reserve design problems with different types of constraints and objectives. The SDSS is demonstrated through application to the creation of conservation reserves in Bolivia to protect 17 endemic mammals.     

Knowledge Transfer for Large‐Scale Urban Growth Modeling Based on Formal Concept Analysis

Cellular automata (CA) are useful for studies on urban growth and land‐use changes. Although various methods have been developed to define transition rules, modeling urban growth of large areas remains a tough challenge owing to heterogeneous geographical features. To address the problem, we present a novel method based on the combination of Formal Concept Analysis (FCA) and knowledge transfer techniques. FCA is used to solicit association rules among cities within a large area. This method can provide a theoretical basis for the knowledge transfer process. A cutting‐edge algorithm called TrAdaBoost is then integrated with the commonly‐used Logistic‐CA as the modeling framework. The proposed method is applied to the urban growth modeling of Guangdong Province, a large region with 21 cities in China, from 2005 to 2008. Compared with traditional methods, this method can achieve better results at the provincial and local levels, according to the experiments. The combination of FCA and knowledge transfer is expected to provide a useful tool for calibrating large‐scale urban CA models.     

Web‐based GIS Approaches to Enhance Public Participation in Wind Farm Planning

Planning information pertaining to the potential visual impacts of proposed construction developments is particularly important in the case of wind farm planning, given the high levels of concern amongst members of the public regarding the perceived negative visual impacts of wind turbines on the landscape. Previous research has highlighted the shortcomings associated with traditional visualization techniques used to assess these impacts, and also the means by which such information is then disseminated to the wider public during the consultation stages of the wind farm planning process. This research is concerned with examining the potential of Web‐based mapping and digital landscape visualization techniques for addressing some of these shortcomings. This article reports the findings of a Web‐based survey study designed to evaluate the potential of online GIS‐based approaches for improving the effectiveness and dissemination of wind farm visualizations and enhancing public participation in the wind farm planning process. Results from the survey study add to the research literature by demonstrating how innovative Web‐based approaches have real potential for augmenting existing methods of information provision and public participation in the planning process. The findings of this study are also potentially transferrable to other landscape planning scenarios.