2009 Joint Urban Remote Sensing Event最新文献_第7页

3D laser omnimapping for 3D reconstruction of large-scale scenes 用于大尺度场景三维重建的三维激光测绘

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137584

Shaoxing Hu, Aiwu Zhang

引用次数: 5

Research on evolution of land subsidence induced by nature and human activity by utilizing remote sensing technology 基于遥感技术的自然与人类活动引起的地面沉降演变研究

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137693

Zhu Lin, G. Huili, Jing Lingling, S. Yaoming, Li Xiaojuan, Jiang Jun

{"title":"Research on evolution of land subsidence induced by nature and human activity by utilizing remote sensing technology","authors":"Zhu Lin, G. Huili, Jing Lingling, S. Yaoming, Li Xiaojuan, Jiang Jun","doi":"10.1109/URS.2009.5137693","DOIUrl":"https://doi.org/10.1109/URS.2009.5137693","url":null,"abstract":"In Northern China, main water supply is groundwater. In recent years, as the city's construction and development, long-term over-exploitation of groundwater has induced land subsidence which endangers the safety of human lives and properties. Because Beijing is a region seriously lack of water, five water sources for emergent events were built in order to meet the demand for urban water supply. Groundwater in such sources has been exploited in large-scale, high-intensity and concentratively, which will change groundwater system and result in related environmental-induced geological disasters. Shunyi District, as the place in which China's largest and most advanced Capital International Airport locates, meets more and more geological disasters such as land subsidence and ground fissure. Nature-human coupled factors impact on land subsidence progressing is focused in Shunyi District, the selected study area in this research. In the study, multi-scale remotely sensed imageries are utilized to extract human activity impact factors, especially in built-up areas. Hydrologic data is collected, and precipitation is defined as one of the natural factors. Comparison is made on relations between intensity change of accumulative ground subsidence and factors including precipitation, shallow groundwater exploitation amount, and land use in the period of 1990 to 2006. Meanwhile, contribution of nature-human impact factors on land subsidence is determined by AHP, and a Grey model is constructed in this research to forecast the intensity of ground subsidence in order to provide reference for prevention, control and slowdown on land subsidence.","PeriodicalId":154334,"journal":{"name":"2009 Joint Urban Remote Sensing Event","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128042128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Evaluation of urban heat environment using multi-algorithm and multi-scale images 基于多算法和多尺度图像的城市热环境评价

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137662

L. Pei, Du Peijun, Cao Wen, Xia Junshi

{"title":"Evaluation of urban heat environment using multi-algorithm and multi-scale images","authors":"L. Pei, Du Peijun, Cao Wen, Xia Junshi","doi":"10.1109/URS.2009.5137662","DOIUrl":"https://doi.org/10.1109/URS.2009.5137662","url":null,"abstract":"Remote sensing of Urban Heat Islands (UHIs) usually used Land Use and Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), normalized difference built-up index (NDBI) and Vegetation-Impervious Surface Area (ISA)-Soil (V-I-S) model separately in the past. The purpose of this paper is to examine the relationship between surface thermal patterns with land cover types, NDVI and VIS model as a whole. LST was derived using three different algorithms from remotely sensed images at two different scales and LUCC map was obtained by SVM classification method. The results demonstrate that LST retrieval from Landsat ETM+ image by improved MWA algorithm is more suitable for analyzing relationship between urban structures with urban heat islands in Xuzhou. By analyzing the relationship between LST and land cover type, it also indicated that SVM classified result and VIS have a good uniformity. The analytical correlation between UHIs and different indices indicated that correlation between indices with UHIs change slightly among the different fraction in different city structures. The special distribution of heat island shows that building area, bare land, semi-bare land and land under development are warmer than other surface type, and higher temperature in the UHIs was related to certain land cover types and distributed with a scattered pattern. By making an integration analysis of NDVI, NDBI and LST, it was confirmed that strong positive correlations between LST and NDBI existed, as with negative correlations between LST and NDVI.","PeriodicalId":154334,"journal":{"name":"2009 Joint Urban Remote Sensing Event","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128560416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

The utilization of SAR remote sensing and GIS technology to delineate urban extent in North China 利用SAR遥感和GIS技术对华北城市范围进行圈定

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137600

Biao Deng, Huadong Guo, Yueping Nie

引用次数: 0

InSAR interferogram detail-compensating filtering method based on the stationary wavelet transform 基于平稳小波变换的InSAR干涉图细节补偿滤波方法

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137554

Liang Chang, Xiufeng He

引用次数: 1

Spatial pattern of thermal and ecological environment in Shanghai 上海市热环境与生态环境空间格局

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137669

Cui Lin-li, Zhou Hongmei, Yang Yinming, Shi Jun, T. Jianguo

{"title":"Spatial pattern of thermal and ecological environment in Shanghai","authors":"Cui Lin-li, Zhou Hongmei, Yang Yinming, Shi Jun, T. Jianguo","doi":"10.1109/URS.2009.5137669","DOIUrl":"https://doi.org/10.1109/URS.2009.5137669","url":null,"abstract":"Shanghai has experienced rapid urbanization over the past three decades. With the rapid development and expansion of city, the physical characteristics (such as land cover types, surface albedo and so on) and property of the urban underlying surface are undergoing substantially changes, which significantly impact the climate and ecological environment. Based on the Landsat TM remote sensing imagery, with the remote sensing (RS) and geographic information system (GIS) spatial analysis techniques, spatial pattern of land surface temperature (LST), land use type, vegetation coverage, surface albedo and the relationship between LST and vegetation was analyzed in this study. The results indicate that LST in urban and suburban areas is higher than that in exurban areas of Shanghai. The dominant land use type in urban areas is residential land, but in exurban areas, farmland is the main land use type. From urban to exurban areas, the vegetation coverage and surface albedo increase gradually. In urban, suburban and exurban areas, the mean vegetation coverage is 0.01, 0.078 and 0.126 respectively, and the mean surface albedo is 0.067, 0.083 and 0.189 respectively. The distribution of LST is well corresponding with the land use types in Shanghai, with residential areas and buildings have higher LST. LST possesses a negative correlation with the vegetation coverage and normalized difference vegetation index (NDVI) for all land cover types, and in the urban areas, the low vegetation coverage is the important contributor of the higher LST. The change in urban albedo has significant impact on the evolution of LST.","PeriodicalId":154334,"journal":{"name":"2009 Joint Urban Remote Sensing Event","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121847702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation of at sensor signals over urban area: two cases study 城市上空at传感器信号的模拟:两个案例研究

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137507

S. Doz, X. Briottet, S. Lachérade, D. Boldo

引用次数: 1

Advanced interferometric techniques for monitoring urban areas 用于监测城市地区的先进干涉测量技术

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137569

M. Bonano, G. Fornaro, R. Lanari, M. Manunta, D. Reale, F. Serafino

引用次数: 0

An object-based two-stage method for a detailed classification of urban landscape components by integrating airborne LiDAR and color infrared image data: A case study of downtown Houston 基于机载激光雷达和彩色红外图像数据的基于目标的两阶段城市景观成分详细分类方法——以休斯顿市中心为例

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137543

Bailang Yu, Hongxing Liu, L. Zhang, Jianping Wu

{"title":"An object-based two-stage method for a detailed classification of urban landscape components by integrating airborne LiDAR and color infrared image data: A case study of downtown Houston","authors":"Bailang Yu, Hongxing Liu, L. Zhang, Jianping Wu","doi":"10.1109/URS.2009.5137543","DOIUrl":"https://doi.org/10.1109/URS.2009.5137543","url":null,"abstract":"By exploiting high resolution airborne LiDAR data along with color infrared aerial photographs, this research aims to quantify the urban landscape components using an object-based two-stage method in the case of downtown Houston, Texas, USA. The urban landscape components will be identified and classified by integrating spectral information from color infrared aerial photograph and surface geometric information from airborne LiDAR data. In first stage, the color near-infrared aerial photographs are used to segment the scene into image objects. Then, these objects are classified into three broad categories - impervious surface, vegetation, and water surface, based on their spectral and two-dimensional spatial attributes. In the second stage, the normalized Digital Surface Model derived from airborne LiDAR data is introduced into analysis. Two indicators, relative height and roughness, of each vegetation object from the first stage are calculated, and the threshold values are determined to separate vegetation into lawns, shrubs/hedges, and trees. Next, a series of image processing steps are applied to the nDSM to further classify the impervious surface objects into skyscrapers, high-rise buildings, ordinary buildings, streets, highways, and open spaces. The overall classification accuracy is evaluated as high as 94.10%, and the Kappa coefficient is 92.91%. This research suggests that the combination of morphological information of LiDAR data and spectral information from image data renders a powerful tool for a detailed investigation of urban landscape structure.","PeriodicalId":154334,"journal":{"name":"2009 Joint Urban Remote Sensing Event","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122374901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Urban expansion monitoring and driving forces analysis: A case study of Jiangsu Province, China 城市扩张监测与驱动力分析——以江苏省为例

2009 Joint Urban Remote Sensing Event Pub Date : 2009-05-20 DOI: 10.1109/URS.2009.5137718

Xu Jinyong, Zhang Zeng-xiang, Wang Changyou, Zhao Xiaoli, L. Bing, Y. Ling

引用次数: 4