从TM影像中提取城镇建筑覆盖区专题信息的改进方法

选用TM影像作为城镇建筑覆盖区专题信息提取的数据源，在Bayes的最大似然法半自动提取城镇专题信息和建筑指数法自动提取城镇专题信息分类方法的基础上，通过二值逻辑演算，综合两种方法的分类结果，去掉不属于城镇的信息，得到真正的城镇建筑覆盖区专题信息。实验结果表明，改进后的分类方法，兼有自动与半自动的优点，其分类精度大大提高。特别是对于短期变化(如防洪区)较大、面积较大而复杂的研究区来说，这一方法的应用弥补了单一分类方法的不足。     

1990—2015年宁波市热岛效应特征与人口资源环境分析

针对目前城市中心越来越明显的城市热岛效应,基于Landsat系列数据和MODIS遥感数据,以宁波市中心城区为研究区域,运用地理信息系统技术和Pearson相关性分析方法,进行地表温度与其他因素的长时间序列的相关性变化分析。结果表明：1990-2015年间,宁波市中心城区热岛效应变化显著;其地表温度与NDVI呈负相关性,与NDBI呈正相关性;地表温度与GDP呈正相关性,并在2010年达到最大值;人口规模与城乡之间的差距不会直接导致城市热岛效应,政府的环境政策是城市热岛的主要影响因素。根据区域所处的发展水平不同,政府环境保护态度、人口规模发展与城乡差异存在复杂的影响关系。研究表明基于单窗算法的地表温度反演技术分析城市热岛效应变化的驱动因素具有一定可行性。     

基于RS和GIS的城市扩展及驱动力研究——以西安市为例

以RS和GIS技术为支撑,基于多时相Landsat遥感数据,采用监督分类、非监督分类和归一化裸露指数(NDBI)等方法提取陕西省西安市城市空间特征信息,结合地学统计方法,定量研究了城市扩张强度、紧凑度等指标。结果表明:西安市城区1988~2002年14 a间面积翻了1.6倍,年平均增长率为8.815%;城区扩展空间主要集中在南北方向;在此基础上,以影响城市扩张视角多元化为出发点,通过分析社会经济因子、人口因子、政策导向性因子和基本建设投资等因子对城区扩张的影响,政策导向性的前提下社会经济(GDP)和人口增长是其核心影响因子。     

滇池流域不透水表面扩张监测与时空过程分析

人类活动是影响和改变自然和人文环境最主要的因素,而不透水表面是反映人类活动频度与强度重要指标。近30年来,随着城镇化的不断推进,不透水表面快速扩张,同时伴随着一系列流域水环境问题产生。掌握不透水表面变化的时空过程是改善流域水环境、控制水污染的基础。为此,以滇池流域近25年来的TM影像与OLI影像为数据基础,将改进的NDBI算法及线性光谱混合分析法相结合,得到了滇池流域近25年来不透水表面的空间范围、空间分布、不透水表面指数、不透水表面覆盖度等指标。实验结果表明,本文采用的算法效果较好,0.2 m空间分辨率的航拍影像精度检验结果表明,提取精度达到85.27%;滇池流域不透水表面覆盖率达19.44%,部分子流域不透水表面覆盖率超过40%,其对流域生态系统功能和结构有直接的影响。     

Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes

Global warming has obtained more and more attention because the global mean surface temperature has increased since the late 19th century. As more than 50% of the human population lives in cities, urbanization has become an important contributor for global warming. Pearl River Delta (PRD) in Guangdong Province, southern China, is one of the regions experiencing rapid urbanization that has resulted in remarkable Urban Heat Island (UHI) effect, which will be sure to influence the regional climate, environment, and socio-economic development. In this study, Landsat TM and ETM+ images from 1990 to 2000 in the PRD were selected to retrieve the brightness temperatures and land use/cover types. A new index, Normalized Difference Bareness Index (NDBaI), was proposed to extract bare land from the satellite images. Additionally, Shenzhen, which has experienced the fastest urbanization in Guangdong Province, was taken as an example to analyze the temperature distribution and changes within a large city as its size expanded in the past decade. Results show that the UHI effect has become more prominent in areas of rapid urbanization in the PRD region. The spatial distribution of heat islands has been changed from a mixed pattern, where bare land, semi-bare land and land under development were warmer than other surface types, to extensive UHI. Our analysis showed that higher temperature in the UHI was located with a scattered pattern, which was related to certain land-cover types. In order to analyze the relationship between UHI and land-cover changes, this study attempted to employ a quantitative approach in exploring the relationship between temperature and several indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Bareness Index (NDBaI) and Normalized Difference Build-up Index (NDBI). It was found that correlations between NDVI, NDWI, NDBaI and temperature are negative when NDVI is limited in range, but positive correlation is shown between NDBI and temperature.