基于GIS的农用地定级数据处理浅探

阐述了农用土地定级的意义,主要论述了GIS在农用土地定级中的应用,并以新疆巴音郭楞蒙古自治州尉犁县农用土地定级为例,探讨了利用GIS进行定级数据处理的过程和方法。进一步说明了利用GIS进行农用土地定级的优势——将定量和定位结合起来,使定级结果精确科学又能显示土地的空间属性。     

基于GIS的城镇土地定级信息系统建模方法探讨

基于GIS的城镇土地定级信息系统在建设过程中,定级方法确定、定级单元大小确定和定级因素/子权重值的生成是关键,且三者都具有不同的确定方法,因此选择什么样的方法决定了系统建立的优劣。本文着重归纳、总结了城镇土地定级信息系统定级方法,通过对比分析,探讨了最优定级方法、最优网格单元大小划分方法和最优因素/子权重值计算方法。     

GIS在城区土地定级中的应用

城区土地定级研究是进行城区地价评估的基础.运用特尔菲法选取定级因素、因子并确定权重;借助GIS强大的空间数据和属性数据管理、分析功能,计算影响因素、因子的分值和定级单元的分值,并进一步对土地级别进行了划分;通过GIS的制图功能对定级结果以图形化的方式输出.     

基于GIS的城镇土地定级估价方法研究

根据城镇土地定级估价的工作特点，研究基于ＧＩＳ技术的城镇土地定级估价方法。在较为系统地分析了我国现行城镇土地定级估价方法的基础上，提出了在ＧＩＳ支持下进行城镇土地定级和基准地价评估的基本方法和步骤，并以ＡｒｃＣＡＤ为支撑软件，进行了城镇土地定级估价软件的设计研制。用于自动完成定级估价因素／子分值计算。土地级别确定、基准地价测算及成果输入等，并以浙江城镇为例进行了应用实验。     

基于空间聚类的城镇土地定级方法研究

分析了多因素综合评定法、级差收益测算法等城镇土地定级方法的不足，提出了基于空间聚类的地价分区定级法的主要思想和主要步骤，并以石狮市土地定级为例，验证了此方法。     

基于GIS的土地定级技术研究

城镇土地定级是评价土地质量的必要手段,也是土地管理的一项基本工作。本文以四川某县县城综合用地定级为例,利用GIS技术划分定级单元,采用多因素评定法对定级影响因素进行分析与统计,再依据定级单元的分值对该县的综合用地级别进行了合理的划分。     

GIS在土地适宜性评价中的应用研究

土地适宜性评价是指某块土地针对特定利用方式是否适宜，同时确定其适宜程度，并作出相应等级的评定，是土地潜力评价的进一步发展。GIS技术应用到土地适宜性评价中，可以大大提高评价的效率，保持评价定级的科学性、现势性和准确性，具有很好的应用前景。本文对GIS在土地适宜性评价中应用的方法、模型、空间数据库的建立等问题进行了研究和讨论。     

基于GIS的城镇土地分等定级研究

基于GIS空间技术,采用Delphy法进行评价因素、因子的选取及权重的确定,运用空间分析模型确定土地分等定级单元,并加权得到各单元的总分值,最后采用总分值频率直方图法进行土地等级的综合评定.     

可动态定制的城镇土地定级系统开发技术研究

土地定级数据、指标(因素、因子)及指标计算方法在空间、时间上存在差异性,而传统的城镇土地定级系统伴随着具体的定级工作研发,具有量身定制的特点,缺乏对数据、指标(因素、因子)及指标计算方法时空动态演变的支持。基于组件的框架技术面向特定领域,提供了支持领域内变化性特征的处理机制,使软件具有了动态演化能力。本文从设计角度对框架模型及框架扩展机制进行了分析,在此基础上对土地定级进行业务建模,把业务中相对稳定部分实现为系统主框架,把易变的指标、方法、数据规整、抽象为扩展点,并提供了基于XML+多级菜单的易变特征动态配置、基于动态解析的易变特征动态加载方案,建立了支持时空演变的可动态定制的城镇土地定级系统。     

基于GIS的威海环翠区城市土地适宜性评价

选取威海市环翠区为评价区域,结合土地适宜性评价的相关方法和理论,应用地理信息系统(GIS)技术、层次分析法(AHP)和多因子综合权重叠加分析法确定每个指标的权重及作用分值,划分评价单元并计算评价总分值,根据评价总分值对该区域进行土地适宜性分等定级。最终绘制出环翠区土地适宜性分级地图,为城市建设选址、城市规划等提供科学的指导。     

基于栅格数据空间分析的城镇土地定级研究

以四川省达州市城区土地定级为例,论述了栅格数据空间分析方法在城镇土地定级中的运用,如定级单元的划分、定级过程中各种距离的求取、定级单元各要素作用分及总作用分的计算以及各定级要素作用分等值线的绘制。结果表明,基于栅格数据的空间分析方法在城镇土地定级中有十分重要的作用,有广泛的应用前景。     

Evaluating the compatibility of multi-functional and intensive urban land uses

This research is aimed at developing a model for assessing land use compatibility in densely built-up urban areas. In this process, a new model was developed through the combination of a suite of existing methods and tools: geographical information system, Delphi methods and spatial decision support tools: namely multi-criteria evaluation analysis, analytical hierarchy process and ordered weighted average method. The developed model has the potential to calculate land use compatibility in both horizontal and vertical directions. Furthermore, the compatibility between the use of each floor in a building and its neighboring land uses can be evaluated. The method was tested in a built-up urban area located in Tehran, the capital city of Iran. The results show that the model is robust in clarifying different levels of physical compatibility between neighboring land uses. This paper describes the various steps and processes of developing the proposed land use compatibility evaluation model (CEM).     

Characterizing bi-temporal patterns of land surface temperature using landscape metrics based on sub-pixel classifications from Landsat TM/ETM+

Landscape patterns in a region have different sizes, shapes and spatial arrangements, which contribute to the spatial heterogeneity of the landscape and are linked to the distinct behavior of thermal environments. There is a lack of research generating landscape metrics from discretized percent impervious surface area data (ISA), which can be used as an indicator of urban spatial structure and level of development, and quantitatively characterizing the spatial patterns of landscapes and land surface temperatures (LST). In this study, linear spectral mixture analysis (LSMA) is used to derive sub-pixel ISA. Continuous fractional cover thresholds are used to discretize percent ISA into different categories related to urban land cover patterns. Landscape metrics are calculated based on different ISA categories and used to quantify urban landscape patterns and LST configurations. The characteristics of LST and percent ISA are quantified by landscape metrics such as indices of patch density, aggregation, connectedness, shape and shape complexity. The urban thermal intensity is also analyzed based on percent ISA. The results indicate that landscape metrics are sensitive to the variation of pixel values of fractional ISA, and the integration of LST, LSMA. Landscape metrics provide a quantitative method for describing the spatial distribution and seasonal variation in urban thermal patterns in response to associated urban land cover patterns.     

城市用地空间信息分类与数字重建——以长春百年城市内部用地变化为例

针对单一应用遥感影像难以进行城市内部用地结构分类以及高精度城市内部用地多期空间数据叠置分析中位置误差问题建立了基于"分层分类"与"对象分割"的城市内部用地空间信息数字重建方法。实现对特大城市产业用地(住宅、商业、工业等)以及交通、水系、生态绿地等不同功能结构用地的高精度监测以及历史演变过程的重建。综合集成SPOT5,1︰1万地形图、历史地图及城市规划图等辅助信息对长春城市1905年以来城市用地信息进行分类。研究表明,在专家知识参与下人—机交互解译,集成多源空间信息对实现高精度城市用地空间信息重建具有较高的应用价值,该方法不仅能提高城市用地分类精度而且能提高城市用地空间信息提取效率以及多期空间数据叠置分析的定位精度。     

利用主成分分析改善土地利用变化的遥感监测精度——以珠江三角洲城市用地扩张为例

近年来,珠江三角洲由于经济的快速发展,城市用地急剧增加,利用多时相的遥感图,可以定量地监测这种城市化的现象。但理,由一般的遥感动态监测方法所得的结果往往夸大变化的程度,以及获得一些不合理的结论．该文提出主成分分析的方法来改善遥感动态监测的精度。将该方法应用应用于珠江三角洲发展最快的东莞市,获得了较满意的结果。     

遥感技术在“一张图”实施监督系统中的应用

结合国土空间规划“一张图”实施监督信息系统的开发,详细阐述了卫星遥感技术在规划实施评估、国土空间开发适宜性评价和规划监测预警这几个模块中的应用案例,对应用的内容、方法及效果进行了总结和探讨。分析表明,遥感技术能为国土空间规划“一张图”提供众多的基础数据,对于评估城市发展动态、合理规划城市用地具有非常重要的作用。     

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.     

An Evaluation of Four Different Wavelet Decomposition Procedures for Spatial Feature Discrimination in Urban Areas

Texture or spatial arrangement of neighborhood objects and features plays an important role in the human visual system for pattern recognition and image classification. The traditional spectral–based image processing techniques have proven inadequate for urban land use and land cover mapping from images acquired by the current generation of fine–resolution satellites. This is because of the high frequency spatial arrangements or complex nature of urban features. There is a need for an effective algorithm to digitally classify urban land use and land cover categories using high–resolution image data. Recent studies using wavelet transforms for texture analysis have generally reported better accuracy. Based on a high–resolution ATLAS image, this study illustrates four different wavelet decomposition procedures – the standard, horizontal, vertical, and diagonal decompositions – for urban land use and land cover feature extraction with the use of 33×33 pixel samples. The standard decomposition approach was found to be the most efficient approach in urban texture analysis and classification. For comparison purposes and to better evaluate the accuracy of wavelet approaches in image classification, spatial autocorrelation techniques (Moran's I and Geary's C ) and the spatial co–occurrence matrix method were also examined. The results suggest that the wavelet transform approach is superior to all other approaches.     

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。     

Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area,China

Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.