GIS and remote sensing integration for environmental applications

Abstract

The combined use of remotely-sensed images and vector GIS data has received considerable interest in recent years. This review article discusses the historical move towards closer integration of remote sensing and GIS technologies and the requirements of integrated software systems to enable remotely-sensed data to be combined with vector datasets for maximum effect. The benefits of integration to users of both GIS and remote sensing for environmental applications are reviewed and some thoughts are given on terminology and future directions in this field.     

Combination of drainage, water supply and environmental protection as well as rational distribution of water resource in Zhengzhou mining district

It is forecasted that before the 2050s, coal would still make up 50%-60% of once energy constitution in China, but unfortunately, in most part of our coal districts and peripheral regions, we generally face the contradiction and conflict among the threat of water hazard, shortage of water resource and environmental protection, which are becoming more and more serious especially with a gradual increase in mining depth of the shaft and recovery of lower coal beds. The concrete expression is as f…     

基于认知的模糊地理要素建模——以中关村为例

地理空间中的地理要素往往具有模糊性,这种模糊源于人对现实世界的概念化过程,因此具有主观特性.基于模糊集理论,尽管有很多途径对模糊地理要素对应的隶属度函数进行探讨,但是基于认知实验的方法最直接的反映了人们对相应要素的概念化过程中的模糊性.以中关村地区为例,设计了基于地标的问卷调查,并计算每个地标属于"中关村地区"这一概念的隶属度,进而采用支持向量回归方法,得到该要素的隶属度函数.该方法具有实验实施简单,结果便于管理的特点.最后,我们分析了中关村的隶属度函数的一些空间分布特征及其原因.     

基于Vague集的建筑物地震倒塌率研究

介绍了相似度量及地震事件的建筑物破坏相似因素分析,并在此基础上建立了基于相似度量的建筑物地震倒塌率的预测函数.最后,以历史地震事件统计数据为基础,根据假设检验理论得出了预测误差与相似度量的关系.     

基于粗糙集的不确定区域RCC拓扑关系研究

基于粗糙集定义了粗糙区域和粗糙区域的上、下近似区域,提出两种基于上、下近似区域表示粗糙区域拓扑关系的方法。一种方法用上、下近似区域的连接关系表达粗糙区域拓扑关系,得出两个粗糙区域之间的6种拓扑关系,并进一步利用上、下近似区域的RCC5关系表达粗糙区域之间的拓扑关系,得出两个粗糙区域之间的51种拓扑关系,然后分析两种表达之间的联系。另一种方法扩展RCC5模型,首先定义三值逻辑的部分关系≤和补运算~,然后用三值逻辑三元组(X≤Y,X≤~Y,Y≤X)描述两个粗糙区域X和Y的拓扑关系,并给出可能的8种拓扑关系。     

基于多源兴趣点的模糊地名空间范围划分方法

由于人类对现实世界进行认知和概念化的过程存在模糊性,许多人们在日常生活中使用的地名往往是没有明确边界范围的模糊区域。大数据时代的开启,为模糊地名空间范围的确定与表达提供了新思路。本文提出由k最邻近(k NN)离群点检测算法结合高斯混合模型(GMM)的方法,基于多源兴趣点(POI)数据获取模糊地名空间范围边界。该方法具有能有效识别离群点数据、参数敏感度低的特点。最后,分析了多源POI数据的应用对结果的影响。     

Generating vague neighbourhoods through data mining of passive web data

Neighbourhoods have been described as ‘the building blocks of public services society’. Their subjective nature, however, and the resulting difficulties in collecting data, means that in many countries there are no officially defined neighbourhoods either in terms of names or boundaries. This has implications not only for policy but also business and social decisions as a whole. With the absence of neighbourhood boundaries many studies resort to using standard administrative units as proxies. Such administrative geographies, however, often have a poor fit with those perceived by residents. Our approach detects these important social boundaries by automatically mining the Web en masse for passively declared neighbourhood data within postal addresses. Focusing on the United Kingdom (UK), this research demonstrates the feasibility of automated extraction of urban neighbourhood names and their subsequent mapping as vague entities. Importantly, and unlike previous work, our process does not require any neighbourhood names to be established a priori.     

基于粗糙模型的模糊地理对象空间拓扑关系研究

在粗糙集的基本概念上,基于上、下近似集定义了二维离散空间中的粗糙区域和粗糙模型,用粗糙模型描述二维离散空间中的模糊地理对象,并给出了粗糙区域的3种类型:确定—确定类型、确定—模糊类型、模糊—模糊类型。在离散空间的空间连接计算理论RCC-D-5的基础上,定义了模糊地理对象拓扑关系之间的拓扑约束关系,并依据概念临近推演和拓扑约束关系,研究得出二维离散空间中简单模糊地理对象之间的73种全拓扑关系,并基于4×4相交包含矩阵进行了描述,使得复杂的拓扑关系在计算机中描述和表达成为可能。