Development of a GIS-based decision support system for assessing land use status

IntroductionAgriculturallandusepatternsandtheirchangesaretightlyrelatedwithagriculturepolicyandfoodsecurityissuesundergrowingfooddemand,assess mentofglobalclimatechangeimpactsonagricul ture,environmentalissuesduetotheintensificationofagriculturallandusessuchaswaterpollution,soildegradation,andrecentlywaterscarcityissues.Soasustainableandholisticplanningandmanage mentoflandresourcesshouldcombineallthesere latedinformationwithefficienttoolsforassessmentandevaluationinordertopermitbroad ,interact…     

防汛会商决策支持系统实现方法

防汛会商属于风险决策和群决策,本文基于决策支持理论,结合我国防汛指挥的实际情况,详细分析论证了当今的信息技术特点和应用前景,阐述了信息领域的网络技术、地理信息系统技术、数据仓库技术和人工智能等在防汛会商决策支持系统中的实际应用。概述了防汛会商决策支持系统的总体结构和实现思路。     

高铁大临设施用地复垦利用辅助系统的设计与实现

本文根据复垦利用流程及复垦业务功能需求,结合组件式GIS集成开发技术,基于VS2008与Arc En-gine平台,采用SQL Server 2005数据库设计并开发了高速铁路大临设施用地复垦利用辅助决策系统。该系统实现了复垦方向优化过程的自动分析、复垦利用参数的动态设定、复垦工程量及投资的自动计算,并在京沪高铁江阴制梁场得到应用,取得了良好的效果。     

A GIS-based decision support system for analysis of route choice in congested urban road networks

Urban congestion patterns have become ubiquitous and complex. Traditional, “static” approaches are no longer adequate for analyzing network flows and conducting minimum cost routing. This paper reports on a GIS-based decision support tool for modeling dynamic network congestion and conducting minimum cost routing. The system predicts network flows at a detailed level of temporal resolution, capturing dynamic congestion propagation effects. A Route Planner module solves for the combined departure time and minimum cost routing required for a trip to reach its destination by a given deadline. The GIS provides effective decision support through its database management capabilities, graphical user interfaces and cartographic visualization. This supports analyses of “what-if?” scenarios for strategic planning and tactical management subject to unplanned network disturbances. Received: 1 October 1999/Accepted: 21 September 2000     

Spatial decision support system for home-delivered services

 We present a spatial decision support system for the non-profit sector, designed to assist planning in the area of home-delivered services such as meals on wheels. Using data collected from existing programs, current and forecasted demographic data, and a set of algorithmic tools, we provide a system for evaluating current meals on wheels facilities, and for making incremental facility location decisions that satisfy coverage and equity requirements. Received: 27 September 2000 / Accepted: 22 March 2001     

The development of spatial decision support system tool for marine spatial planning

A major problem associated with marine spatial planning (MSP) involves the difficult and time-consuming practice of creating a scenario that encompasses complex datasets in near real time via the use of a simple spatial analysis method. Moreover, decision-makers require a reliable, user-friendly system to quickly and accessibly acquire accurate spatial planning information. The development of national spatial data infrastructure (NSDI), which links the spatial data of a nation’s many diverse institutions, may pave the way for the development of a tool that can better utilize spatial datasets, such as a spatial decision support system (SDSS). Thus, this project aimed to develop an SDSS for MSP and to evaluate the feasibility of its integration within the NSDI framework. The seaweed culture was selected as an example due to its economic and technological acceptance by traditional fishers. Additionally, a multi-criteria analysis was used to develop the tool. Furthermore, a feasibility evaluation of its implementation within the NSDI framework was conducted based on the Delphi method. The results of the assessment indicated that the SDSS can be incorporated into the NSDI framework by addressing the policy issue – one map policy, updating custodians’ decree and data, and improve the standard and protocol.     

The framework of a geospatial semantic web-based spatial decision support system for Digital Earth

Abstract

While significant progress has been made to implement the Digital Earth vision, current implementation only makes it easy to integrate and share spatial data from distributed sources and has limited capabilities to integrate data and models for simulating social and physical processes. To achieve effectiveness of decision-making using Digital Earth for understanding the Earth and its systems, new infrastructures that provide capabilities of computational simulation are needed. This paper proposed a framework of geospatial semantic web-based interoperable spatial decision support systems (SDSSs) to expand capabilities of the currently implemented infrastructure of Digital Earth. Main technologies applied in the framework such as heterogeneous ontology integration, ontology-based catalog service, and web service composition were introduced. We proposed a partition-refinement algorithm for ontology matching and integration, and an algorithm for web service discovery and composition. The proposed interoperable SDSS enables decision-makers to reuse and integrate geospatial data and geoprocessing resources from heterogeneous sources across the Internet. Based on the proposed framework, a prototype to assist in protective boundary delimitation for Lunan Stone Forest conservation was implemented to demonstrate how ontology-based web services and the services-oriented architecture can contribute to the development of interoperable SDSSs in support of Digital Earth for decision-making.     

土地利用碳排放核算系统设计与实现

针对土地利用碳排放核算方法的参数设置烦琐、计算过程复杂等缺点,限制了碳排放核算模型广泛应用于我国土地利用/覆被变化导致的碳收支研究。本文选择了簿记模型基本原型作为核心算法,构建一套包含土地开垦/退耕、森林收获/恢复4种情景在内的土地利用碳排放核算系统。系统以地理区域为核算基本单元,可逐年并行核算多个区域土地利用活动导致的土壤和植被直接碳排放,提高了碳排放估算的效率;系统界面简洁明了、输入参数少、操作简便。     

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.     

Illegal land use change assessment using GIS and remote sensing to support sustainable land management strategies in Taiwan

Land use is changing at accelerated rates in Taiwan, and illegal land use change practices (ILP) are regularly observed within conservation areas. For this reason, we map high-potential areas of ILP within the Soil and water conservation zone (SWCZ) as an aid for effective land management and conducted an exploratory analysis of explanatory variables to evaluate their variability within ILP hot spots. We used variables relevant to hot spots to develop a logistic regression model and identified seven statistically significant variables. We re-applied the logistic regression approach to produce spatially explicit predictions of ILP. High probability areas are distributed along the coastal regions, covering 26% of the SWCZ, and their major drivers are related to accessibility and topography. The results from this research provide relevant information on the major drivers of ILP and high-potential areas, which can support officials in monitoring efforts for better planning and governance within the SWCZ.     

城市土地集约利用评价信息系统架构研究

本文在探讨模型库系统、数据库系统、人机交互系统等三大部件设计的基础上,重点研究模型库中各模型的存储、调用、管理和维护机制。本文设计并实现了模型字典库与文件库相结合的混合管理方式来对模型进行统一组织和存储;由空间数据库子系统、模型库子系统,以及人机交互子系统三个部件所组成的两两相互作用的三角式网络结构。结果表明:软件系统模型及数据组织恰当,软件结构和功能设置合理,能有效地进行城市土地集约利用评价工作。     

面向土地用途分区的空间聚类系统设计与实现

传统的土地用途分区方法存在受人为因素影响、效率低下的问题,不利于土地用途分区管制的实施,基于GIS的智能化的土地用途分区系统则可以弥补这一缺陷。本文以GIS相关理论和土地用途分区的需求分析为基础,构建了系统的逻辑框架,研究了数据库、模型库、算法库和知识库的设计方案,提出了土地用途分区过程中的空间数据整合、目标函数和分区模型的选择等问题的解决方案,并实现了面向土地用途分区的空间聚类系统。以典型地区的土地用途分区为例,验证了该空间聚类系统是一种智能、高效、科学的土地用途分区平台。     

大气污染扩散模拟评价决策支持系统的研究与开发

大气污染扩散模拟评价决策支持系统将GIS技术与环境模型相结合集成应用于大气污染扩散评价中,不仅发挥了GIS在大气污染扩散评价中强大的空间信息可视化管理和分析功能,还能将环境模型的分析预测功能直观应用于对各类污染源的宏观与微观模拟表达,实现了对大气污染综合决策分析,为工程决策者和管理人员提供了一种强有力的决策支持方案.系...     

Remote sensing-derived national land cover land use maps: a comparison for Malawi

Reliable land cover land use (LCLU) information, and change over time, is important for Green House Gas (GHG) reporting for climate change documentation. Four different organizations have independently created LCLU maps from 2010 satellite imagery for Malawi for GHG reporting. This analysis compares the procedures and results for those four activities. Four different classification methods were employed; traditional visual interpretation, segmentation and visual labelling, digital clustering with visual identification and supervised signature extraction with application of a decision rule followed by analyst editing. One effort did not report classification accuracy and the other three had very similar and excellent overall thematic accuracies ranging from 85 to 89%. However, despite these high thematic accuracies there were very significant differences in results. National percentages for forest ranged from 18.2 to 28.7% and cropland from 40.5 to 53.7%. These significant differences are concerns for both remote-sensing scientists and decision-makers in Malawi.     

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.     

An adaptive unimodal subclass decomposition (AUSD) learning system for land use and land cover classification using high-resolution remote sensing

Land use and land cover classification is an important application of remote-sensing images. The performances of most classification models are largely limited by the incompleteness of the calibration set and the complexity of spectral features. It is difficult for models to realize continuous learning when the study area is transferred or enlarged. This paper proposed an adaptive unimodal subclass decomposition (AUSD) learning system, which comprises two-level iterative learning controls: The inner loop separates each class into several unimodal Gaussian subclasses; the outer loop utilizes transfer learning to extend the model to adapt to supplementary calibration set collected from enlarged study areas. The proposed model can be efficiently adjusted according to the variability of spectral signatures caused by the increasingly high-resolution imagery. The classification result can be obtained using the Gaussian mixture model by Bayesian decision theory. This AUSD learning system was validated using simulated data with the Gaussian distribution and multi-area SPOT-5 high-resolution images with 2.5-m resolution. The experimental results on numerical data demonstrated the ability of continuous learning. The proposed method achieved an overall accuracy of over 90% in all the experiments, validating the effectiveness as well as its superiority over several widely used classification methods.     

特征提取和决策树法土地利用遥感分类

文章以安徽省淮南市为例,采用2005年Landsat-5 TM多光谱数据,分析地物谱间关系,选择改进归一化差异水体指数(MNDWI)、归一化植被指数(NDVI)、归一化建筑指数(NDBI)、TM4+ TM5、TM4+ TM5+TM7、DEM高程和坡度等特征值,构建决策树分类规则,完成研究区土地利用遥感分类.结果表明:MNDWI和TM4+TM5特征值能较好地区分水体与非水体;NDVI和NDBI可完成非水体区域植被与非植被信息分类;DEM和TM数据6波段和值可完成建筑用地、裸地和沙(旱)地分类;DEM和TM4+ TM5+ TM7能较好地解决耕地和园地混淆问题.决策树法分类总精度和Kappa系数分别为90.29％和0.87,相比较于最大似然分类法和基于特征提取波段的最大似然分类法,精度均有所提高.     

Integrating the system dynamic and cellular automata models to predict land use and land cover change

Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors.     

北京市土地资源和建设用地综合决策分析平台

本文通过对建设用地资源潜力评价体系的研究,建立了适用于北京市的建设用地资源潜力评价体系:制定了"先筛选,后评价"的建设用地评价思路和工作流程。建立了可利用建设用地筛选模型;在理论构建的基础上,综合利用GIS技术,开发建立了北京市土地资源和建设用地综合决策分析平台。研究发现只有保障了空间数据质量,可利用建设用地资源潜力评价的准确性和可持续性才能得到根本保证。