基于SWAT模型的细河流域土地利用/覆被变化对径流影响的研究

土地利用/覆被变化对细河流域的水文过程影响显著。为研究不同土地利用/覆被情景对流域水文要素的影响情况,本文构建了适用于细河流域的SWAT分布式水文模型,并拟算出不同情景下的流域多年平均月径流量、多年平均地表径流深度、多年平均蒸发量以及多年平均土壤侧流。模拟结果显示:当流域农林用地增加时,平均月径流量增加了8.40%;当建设用地增加时,平均月径流量减少了4.11%;当旱地及其他未利用地增加时,平均月径流量减少了1.93%。综上所述,细河流域农林用地变化对径流产量的影响相对最大,其增加导致径流量增加;旱地及其他未利用对径流产量的影响相对最小,建设用地和旱地及其他未利用地的增加导致径流量减少。     

面向土地规划管理的"多规合一"信息平台建设应用初探

近年来,许多城市以开展"多规合一"信息平台建设为抓手推进"多规合一"工作,以期建立统一的空间规划体系.但是,大部分地区实践的"多规合一"信息管理平台建设侧重于多规空间数据展示和协同审批等方面,而对面向土地规划管理方面并无相关应用.本文首先尝试对土地规划管理与多规合一的关系进行探讨;进而梳理出面向土地规划管理的多规合一的信息平台建设思路;最后重点研究解决了土地集约利用管理、建设用地选址预审、土地规划实施效果评价等功能的关键技术问题.     

Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis

Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively.     

Optimization of spatial statistical approaches to identify land use/land cover change hot spots of Pune region of Maharashtra using remote sensing and GIS techniques

This study investigated land use/land cover change (LULCC) dynamics using temporal satellite images and spatial statistical cluster analysis approaches in order to identify potential LULCC hot spots in the Pune region. LULCC hot spot classes defined as new, progressive and non-progressive were derived from Gi* scores. Results indicate that progressive hot spots have experienced high growth in terms of urban built-up areas (20.67% in 1972–1992 and 19.44% in 1992–2012), industrial areas (0.73% in 1972–1992 and 3.46% in 1992–2012) and fallow lands (4.35% in 1972–1992 and ?6.38% in 1992–2012). It was also noticed that about 28.26% of areas near the city were identified as new hot spots after 1992. Hence, non-significant change areas were identified as non-progressive after 1992. The study demonstrated that LULCC hot spot mapping through the integrated spatial statistical approach was an effective approach for analysing the direction, rate, spatial pattern and spatial relationship of LULCC.     

国土资源网格化管理与服务系统的设计与实现

从地学网格的基本概念出发,提出了由网络层、数据层与应用层以及安全保障和标准化体系构成的国土资源管理与服务系统总体框架。探索了国土资源网格化管理的运行模式,明确了不同角色在网格化管理中的职责。对于网格化管理中的数据更新机制、更新流程和更新方式进行了详细的探讨。最后,文章结合东莞市的实际设计并实现了国土资源网格化管理与服务系统原型。     

基于规则库和网格算法的土地利用现状图自动数字注记

图形自动注记可极大地提高制图的工作效率。针对土地利用现状图数字注记的特点,本文从地图认知角度出发,建立注记自动配置的规则库,提出面状要素自动注记的一种新的算法——网格法。该算法最大的优点是容易实现、效率高,可方便地解决注记压盖冲突等问题。通过开发一个程序实例,对图斑要素进行了自动数字注记,实验表明95％以上的图形注记效果都较为理想。     

对新疆土地生态环境保护的思考

新疆幅员辽阔,总面积为1.6×106km2,占我国国土总面积的1/6。但新疆远离海洋,气候干燥,沙漠面积7.3×105km2,占全国沙漠总面积的2/3。生态环境脆弱,直接威胁人们的生存环境。本文叙述了新疆土地荒漠化的现状及成因和危害;开荒造田的历程;开荒造田中的经验和教训,指出了新疆土地生态环境保护中存在的主要矛盾和问题,并提出了思考和建议。     

基于遥感影像理解模型的土地利用时空变化监测——以龙口市为例

本文从遥感影像理解模型出发,探讨了遥感信息的知识发现及特征提取问题,特别针对士地利用研究领域,提出了纳入GIS信息的遥感影像综合理解模型,将GIS数据(主要包括高程和坡度)与遥感影像结合起来,从中发现知识,并将知识用于遥感影像的专题信息提取,建立了地学规律知识库,从而提高了遥感影像的分类精度。本文基于遥感影像理解模型,发现土地利用变化区域,提取变化信息,动态地监测了龙口市土地利用的时空变化情况。     

基于模糊神经网络的模糊空间对象生成方法研究

随着对GIS中的空间对象模型和自然地理特征表达的研究深入,模糊空间对象被提出。针对模糊空间对象表达的特点,提出了一种基于模糊神经网络的模糊空间对象生成方法。该方法将模糊技术与神经网络相结合,利用神经网络的学习能力调整模糊隶属函数和模糊规则,使系统具备自适应的特性。实验表明,这种基于模糊神经网络的生成模糊空间对象的方法比传统方法大大的提高了成果的精度。     

基于特征价格模型的农村土地征收价格影响因素研究

在分析我国农村土地征收市场现状和农村土地征收价格影响因素的基础上,以天津市环城3个近郊区为例,收集市场案例256宗,选择影响因素13个,采用SPSS12.0进行多元回归,构建了两种形式的特征价格模型,重点分析了影响因素对价格的作用机制。