共查询到18条相似文献，搜索用时 109 毫秒
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以西安市长安区TM影像为例,研究关于城市建筑用地信息快速、准确提取的方法。通过对归一化差异型指数构成原理的分析,选取土壤调节植被指数（ SAVI ）、归一化水体指数（ NDWI ）和归一化差异型建筑指数（ NDBI ）来提取植被、水体和城市建筑用地专题影像,并将其构建为一幅新影像,分析新影像谱间特征,运用逻辑运算将城市建筑用地信息提取出来。本文方法总体提取效果十分有效,尤其是对于面积较大的城市建筑用地,总精度高达85．3％。综合指数法弥补了单靠某一指数提取城市建筑用地信息的不足,提取结果客观可信,是一种不经人为干预、快速有效的提取城市建筑用地的方法。 相似文献
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结合建筑指数的城市建筑用地提取与变化检测分析 总被引：1，自引：0，他引：1
利用2000,2003,2007,2009年ETM+影像,结合归一化建筑指数NDBI、新居民地提取指数NBI、差值建筑用地指数DBI等建筑物提取指数对南京市主城区建筑用地信息进行有效提取和分析,采用分类比较法检测各年份间建筑用地的变化情况,并结合近年来南京市城市规划发展现状,探究城市建筑用地变化的深层原因和变化趋势。与传统研究利用监督分类结果分析建筑用地信息不同,本研究将建筑指数与变化检测方法结合,用于城市建筑用地变化及其内在驱动力分析。实验结果证明,南京市建筑面积增加和建筑用地变化趋势直接反映了南京市城市扩张程度,且与城市化进程发展趋势一致。研究成果对比多种建筑指数,对揭示南京市城市化扩张原因、指导城镇规划、土地利用决策等具有一定的参考价值和意义。 相似文献
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基于TM图像的“增强的指数型建筑用地指数”研究 总被引：6，自引：0，他引：6
以Landsat TM/ETM+图像为数据源,研究城镇和农村建筑用地信息的提取方法.首先利用TM7,4,2波段创建归一化差值裸地与建筑用地指数(normalized difference bareness and built- up index,NDBBI);然后根据裸地在裸土指数(bare doil index,BSI)图像上的亮度值最高、在改进型归一化差值水体指数(modified normalized difference water index,MNDWI)图像的亮度值最低的特征,提出了增强型裸土指数(enhanced baresoilindex,EBSI);最后选用NDBBI,EBSI,MNDWI和SAVI( soil adjustment vegetation index,SAVI)4个指数,构建一种新型的建筑用地指数,称为“增强的指数型建筑用地指数”( enhanced index - based built - up index,EIBI),可快速地提取建筑用地信息.实验结果表明,用EIBI提取的建筑用地信息客观,人为干预少,可信度高,提取精度可达90％以上,适合于同时提取城市和农村建筑用地信息. 相似文献
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针对遥感影像只具有红（R）、绿（G）、蓝（B）3个可见光波段时无法利用归一化植被指数（NDVI）方法提取植被信息的现状,本文提出了一种基于色调饱和度亮度（HSL）模型的可见光植被提取方法。利用自主研发的系统,将影像从RGB彩色空间变换至HSL彩色空间,构建归一化色调亮度植被指数（NHLVI）,通过分析植被与非植被信息在HSL彩色空间中的特征,以及NHLVI、H、S、L、R、G、B各分量的特征,确定协同NHLVI、S分量提取植被信息,利用B分量特征剔除结果中的非植被信息,从而实现植被信息提取,并提高提取精度。研究表明,该方法在现有NHLVI指数方法基础上,加入S分量,提升了可见光植被提取的精度及方法的适用性。 相似文献
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利用遥感技术动态监测城镇扩展己成为一个重要的研究领域和应用方向。本论文基于多源多时相遥感影像和地形数据,以福建漳州市区为示范区,探讨城镇建筑用地扩张遥感动态监测的方法。作者认为基于ASTER影像,综合利用非监督分类、多时相植被指数、城镇建筑用地的地形分布等知识建立分类决策规则,可以有效提取城镇建筑用地信息,准确度不低于90%。同时提出利用城镇建筑用地时空分布知识、多时相植被指数知识,改进TM三指数城镇建筑用地提取方法的思路,最终提取的城镇建筑用地信息满足城镇建筑用地动态变化分析的精度要求。 相似文献
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针对城市热岛效应的演化规律问题,该文以2002年7月9日湖北武汉市的Landsat遥感影像和中分辨率成像光谱仪遥感影像为研究基础,采用归一化差分植被指数,归一化建筑指数,修正后归一化水体指数分别提取了武汉市的植被区域、建筑区域、水体区域,采用密度分割方法对武汉市白天和晚上的温度进行了分区,利用改进的间隙度维数对武汉市热环境白天和晚间的分布特征进行了研究。实验结果表明:对于城市特高温区,白天比晚上的面积大而且集中;对于城市特低温区,白天比晚间面积小而且分散;为研究城市白天和夜间的热岛效应变化提供了一定的参考依据。 相似文献
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基于指数分析法的西安市土地利用变化及驱动力研究 总被引：1，自引：0，他引：1
基于2000和2007年2期TM遥感影像,利用指数分析法,分别提取出归一化差异建筑指数(NDBI)、修正归一化差异水体指数(MNDWI)和归一化差异植被指数(NDVI)3种指数模型,分别代表西安市的3种最主要的土地利用类型--建筑用地、水体和植被.采用神经网络分类器进行监督分类,借助ERDAS Imagine 9.0、ENVI、ArcGIS 9.2和Matlab等软件平台,计算出西安市土地利用类型的动态转移矩阵,构建了土地利用变化动态度指数模型,定量分析西安市土地利用的时空变化.依据研究区土地利用变化的结果分析,变化的驱动力因子主要是人口增长、经济增长和政策变动. 相似文献
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JIANG Zhangyan CHEN Yunhao LI Jing 《地球空间信息科学学报》2006,9(4):293-297
IntroductionThe scientists have begun to retrieve land sur-face temperature (LST) fromsatellite data sincethe launch of TIROS-Ⅱin 60s of the 20th centu-ry . With the development of remote sensingtechnology and its application, more and moreLST retrieval … 相似文献
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Land surface temperature (LST) of Beijing area was retrieved from Landsat TM thermal band data utilizing a radiative transfer equation and the urban heat island (HUI) effects of Beijing and its relationship with land cover and normalized difference vegetation index (NDVI) were discussed. The result of LST showed that the urban LST was evidently higher than the suburban one. The average urban LST was found to 4. 5°C and 9°C higher than the suburban and outer suburban temperature, respectively, which demonstrated the prominent UHI effects in Beijing. Prominent negative correlation between LST and NDVI was found in the urban area, which suggested the low percent vegetation cover in the urban area was the main cause of the urban heat island. 相似文献
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利用改进的归一化差异水体指数（MNDWI）提取水体信息的研究 总被引：238，自引：7，他引：238
在对M cfeeters提出的归一化差异水体指数(NDWI)分析的基础上,对构成该指数的波长组合进行了修改,提出了改进的归一化差异水体指数MNDWI(M odified NDWI),并分别将该指数在含不同水体类型的遥感影像进行了实验,大部分获得了比NDWI好的效果,特别是提取城镇范围内的水体。NDWI指数影像因往往混有城镇建筑用地信息而使得提取的水体范围和面积有所扩大。实验还发现MNDWI比NDWI更能够揭示水体微细特征,如悬浮沉积物的分布、水质的变化。另外,MNDWI可以很容易地区分阴影和水体,解决了水体提取中难于消除阴影的难题。 相似文献
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This study demonstrates the use of high resolution WorldView-II satellite data in extraction of built-up land and vegetation using normalized index techniques. The PCA 1 and NIR 2 bands-based built-up index was proposed for extracting built-up land, which exhibit high accuracy. The normalized difference vegetation index based on Red Edge and NIR 2 bands of WorldView-II produced high accuracy inthe estimation of vegetation compared to the use of Red and NIR bands. The grid technique used in estimating built-up and vegetation density from precisely classified images provided better and accurate assessment of built-up and vegetation density in heterogeneous landscape of urban areas. This shows areas of very high to high built-up density are located in the central, western and southern parts, which are primarily devoid of vegetation. This study indicates possibilities of utilizing high resolution satellite data in urban landscape characterization using a grid-based technique. 相似文献
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用基于知识的决策树方法分层提取矿区土地类型——以湖北大冶为例 总被引：6，自引：0，他引：6
以湖北大冶为研究区,采用多时相陆地卫星遥感图像,通过不同波段组合,以及ironoxide指数和归一化差异植被指数(NDVI)等,详细分析了各地表地物光谱特征和空间特征,建立了研究区分类知识库表,采用决策二叉树法进行分类,得到了高精度分类结果图。基于不同时相分类结果的变化检测,通过对研究区水体污染、矿区复垦、耕地变化等分析,认为从1986～2002年,研究区水质虽有一定改善,但矿区植被退化严重,耕地大量减少,停产矿区复垦仅为20%,为合理保护矿区生态环境和科学管理采矿企业提供了有用资料。 相似文献
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Dušan Jovanović Miro Govedarica Filip Sabo Dubravka Sladić Aleksandar Ristić 《国际地球制图》2015,30(5):483-505
Main objective of this study was to establish a relationship between land cover and land surface temperature (LST) in urban and rural areas. The research was conducted using Landsat, WorldView-2 (WV-2) and Digital Mapping Camera. Normalised difference vegetation index and normalised difference built-up index were used for establishing the relation between built-up area, vegetation cover and LST for spatial resolution of 30 m. Impervious surface and vegetation area generated from Digital Mapping Camera from Intergraph and WV-2 were used to establish the relation between built-up area, vegetation cover and LST for spatial resolutions of 0.1, 0.5 and 30 m. Linear regression models were used to determine the relationship between LST and indicators. Main contribution of this research is to establish the use of combining remote sensing sensors with different spectral and spatial resolution for two typical settlements in Vojvodina. Correlation coefficients between LST and LST indicators ranged from 0.602 to 0.768. 相似文献
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Our study examines the relationships among various environmental variables in Surat city using remote sensing. Landsat Thematic Mapper satellite data were used in conjugation with geospatial techniques to study urbanization and correlation among satellite-derived biophysical parameters namely, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), normalized difference bareness index (NDBaI) and land surface temperature (LST). A modified NDWI (MNDWI) was used for extracting areas under water. Land use/land cover classification was performed using hierarchical decision tree classification technique using ERDAS IMAGINE Expert classifier with an accuracy of 90.4% for 1990 and 85% for 2009. It was found that city has expanded over 42.75 sq.km within two decades. Built-up, fallow and sediment land use classes exhibited high dynamics with increase of nearly 200% and 50% and decrease of 55% respectively from 1990 to 2009. Vegetation and water classes were less dynamic with 20% decrease and 15% increase. The transformation of land parcels from vegetation to built-up, vegetation to fallow and fallow to built-up has resulted in increase of LST by 5.5 ± 2.6°C, 6.7 ± 3°C and 3.5 ± 2.9°C, respectively. 相似文献
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Ansar Khan Soumendu Chatterjee Hashem Akbari Saad Saleem Bhatti Apurba Dinda Chandana Mitra 《国际地球制图》2019,34(5):504-527
The extraction of urban built-up areas is an important aspect of urban planning and understanding the complex drivers and biophysical mechanism of urban climate processes. However, built-up area extraction using Landsat data is a challenging task due to spatio-temporal dynamics and spatially intermixed nature of Land Use and Land Cover (LULC) in the cities of the developing countries, particularly in tropics. In the light of advantages and drawbacks of the Normalized Difference Built-up Index (NDBI) and Built-up Area Extraction Method (BAEM), a new and simple method i.e. Step-wise Land-class Elimination Approach (SLEA) is proposed for rapid and accurate mapping of urban built-up areas without depending exclusively on the band specific normalized indices, in order to pursue a more generalized approach. It combines the use of a single band layer, Normalized Difference Vegetation Index (NDVI) image and another binary image obtained through Logit model. Based on the spectral designation of the satellite image in use, a particular band is chosen for identification of water pixels. The Double-window Flexible Pace Search (DFPS) approach is employed for finding the optimum threshold value that segments the selected band image into water and non-water categories. The water pixels are then eliminated from the original image. The vegetation pixels are similarly identified using the NDVI image and eliminated. The residual pixels left after elimination of water and vegetation categories belong either to the built-up areas or to bare land categories. Logit model is used for separation of the built-up areas from bare lands. The effectiveness of this method was tested through the mapping of built-up areas of the Kolkata Metropolitan Area (KMA), India from Thematic Mapper (TM) images of 2000, 2005 and 2010, and Operational Land Imager (OLI) image of 2015. Results of the proposed SLEA were 95.33% accurate on the whole, while those derived by the NDBI and BAEM approaches returned an overall accuracy of 83.67% and 89.33%, respectively. Comparisons of the results obtained using this method with those obtained from NDBI and BAEM approaches demonstrate that the proposed approach is quite reliable. The SLEA generates new patterns of evidence and hypotheses for built-up areas extraction research, providing an integral link with statistical science and encouraging trans-disciplinary collaborations to build robust knowledge and problem solving capacity in urban areas. It also brings landscape architecture, urban and regional planning, landscape and ecological engineering, and other practice-oriented fields to bear together in processes for identifying problems and analyzing, synthesizng, and evaluating desirable alternatives for urban change. This method produced very accurate results in a more efficient manner compared to the earlier built-up area extraction approaches for the landscape and urban planning. 相似文献