2012 Second International Workshop on Earth Observation and Remote Sensing Applications最新文献

{"title":"Classification of CBERS-02B high resolution image using morphological features for urban areas","authors":"Linlin Lu, Qingting Li, L. Jing, Huadong Guo, M. Pesaresi","doi":"10.1109/EORSA.2012.6261126","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261126","url":null,"abstract":"Urban landscapes represent one of the most challenging areas for remote sensing analysis due to high spatial and spectral diversities of surface materials involved. High Resolution images (HR, better than 5-m spatial resolution) have a potential for detailed and accurate mapping of urban environment. The objective of this study is to analyze the effectiveness of multi-scale morphological features in the purpose of classifying urban landscapes with panchromatic HR images. The experiment is performed using two CBERS HR scenes with urban landscapes characterized by different architectural styles, namely an apartment block and a peri-urban village surrounding Beijing City. Seven types of morphological features including opening (O), closing (C), opening by reconstruction(OR), closing by reconstruction(CR), opening by top-hat(OTH), closing by top hat(CTH) and derivative morphological profile(DMP) are assessed. A support vector machine classifier was also employed to handle the considerable amount of morphological features. The classification results show that with multi-scale morphological features it is possible to discriminate surfaces with mixed spectral characters such as roads, parking lots, and tents due to their different textures for each scene. According to the validation results, the overall accuracy can be improved from 50% with single band HR data to 80.2% and 76.3% respectively for each urban scene using HR-OC-DMP morphological sets. The classification of residential buildings with similar textual character but different gray scales is improved a lot with the supplement of OC sets. The integration of DMP and OC sets benefits the differentiation of bare soil and roads. The mixed sets combining simple, reconstruction and DMP filters provide the best performance.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121313886","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}

{"title":"Operational wildfire monitoring and disaster management support using state-of-the-art EO and Information Technologies","authors":"C. Kontoes, I. Keramitsoglou, I. Papoutsis, T. Herekakis, D. Michail, P. Xofis, Manolis Koubarakis, K. Kyzirakos, M. Karpathiotakis, C. Nikolaou, M. Sioutis, G. Garbis, S. Vassos, S. Manegold, M. Kersten, H. Pirk, M. Ivanova","doi":"10.1109/EORSA.2012.6261164","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261164","url":null,"abstract":"The National Observatory of Athens (NOA) has been established in Greece as a research institute offering, among others, operational services for disaster management of forest wildfires. In this paper the main activities of NOA related to fire monitoring and the Burn Scar Mapping damage assessment services are presented. The current capacities in delivering fire-related products and services are greatly enhanced by the integration of state-of-the-art Information Technologies, which provide the potential of refining the thematic accuracy of our products, allows the connection to other distributed databases for the generation of new and innovative added-value products, and suggest the establishment of an operational system that can be extended to include other applications related to natural disaster management.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122692253","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}

{"title":"The retrieval of land surface albedo in rugged terrain","authors":"B. Gao, L. Jia, M. Menenti","doi":"10.1109/EORSA.2012.6261131","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261131","url":null,"abstract":"Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed surface reflectance, and varies the distribution of downward irradiance, so that BRDF and angular integration will change from flat area to rugged area. This paper details an approach to take into account the topography influences on the surface reflectance, and outlines an algorithm considering the topographic factor. This algorithm makes use of a Digital Elevation Model (DEM) to correct the incidence angle and the reflection angle in a BRDF model, and performs the angular integration based on the different distribution of downward irradiance between a flat area and a rugged area. This approach was applied to HJ-1A/B data and the results were compared with the ones obtained with the algorithm designed for NASA's MODIS data.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126524101","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}

{"title":"Application of land surface temperature inversion based on emissivity mixture analysis at sub-pixel scale in geothermal exploration","authors":"Tianyu Li, Guonian Lv, Y. Wen","doi":"10.1109/EORSA.2012.6261152","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261152","url":null,"abstract":"The detection of thermal anomaly at land surface is crucial in the exploration of geothermal resources. Since field observations are costly and only limited to certain area, the requirement of land surface temperature (LST) inversion estimating accurately in geothermal exploration makes the remote sensing of LST a prevailing topic. The information about the spatial distribution of land surface emissivity (LSE) is a vital land surface temperature inversion parameter. LSE being applied to convert heat energy into radiant energy plays a key role in the measure of land surface inherent efficiency. This study proposes a new method for improving the estimation of LSE. Linear spectral mixture analysis (LSMA) model is applied to thermal infrared band data from Landsat-7 Enhanced Thematic Mapper plus (ETM+) remote sensing sensor. The effective emissivity of one single pixel is regarded as the combination of sub-pixel level emissivity and corresponding area proportion. In this paper, the first step is to conduct georeferencing and atmospheric correction on the imaging data of Nanjing in order to establish a geographic coordinate system and remove the effect of water vapor in the atmosphere. Due to the complexity of the land surface type and its physical conditions, surface pixel is assumed to be divided into three fundamental land cover components after MNF (minimum noise fraction) rotation and PPI (purity pixel indices) calculation, namely vegetation,rock and soil.This kind of dividing method is a variant of V-I-S model proposed by Ridd. The validation of LSMA showes that almost root-mean-square error (RMSE) value is less than 0.02 which can get a precise result. Representative emissivity values of three fundamental land cover are assigned to each component which is derived from ASTER Spectrum Laboratory and MODIS UCSB Emissivity Library. Following pixel effective emissivity calculation, the mono-window algorithm is used to extract LST map. Analyses and evaluations are conducted on thermal state of Tangshan area with thermal anomalies being represented by thermal field variance (TFV) index in LST map. Two possible geothermal fields are found to be located under the zone of Tangshan. Some investigations in field survey reveal a close correlation between the geothermal anomalies and the distribution of hotsprings. The feature of geothermal anomalies also indicates that the geothermal anomaly areas in Tangshan are subjected to the development of fault structure. It can be well explained that the fault structure serve as channels for thermal transmission with which the subterranean heat water can be efficiently transferred to land surface and detected as LST anomalies in thermal infrared images. This study shows that the estimation of LSE is effective and TIR remote sensing can be used in geothermal exploration accurately.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134193451","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}

{"title":"Multi-platform persistent scatterer SAR interferometry time series analyzing","authors":"Rui Zhang, Guoxiang Liu, Bing Yu, Tao Li, Hongguo Jia","doi":"10.1109/EORSA.2012.6261157","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261157","url":null,"abstract":"Exploration on persistent scatterer radar interferometry (PSI) and its applications to regional deformation monitoring has become one of the hot research topics in the radar remote sensing community. PSI analysis with time series of SAR images collected by a single side-looking mode from a single satellite platform can only reveal its own ground deformation along the direction of radar line of sight (LOS). This paper proposes the modeling and algorithm for extracting vertical deformation rate field (DRF) accurately using a multi-platform PSI (MPSI) method. Its basic strategy includes two parts. Above all, the SAR images collected by each single platform are first used to estimate LOS DRF by PSI analysis. Then, imaging geometric space relationship of different satellite platforms has been modeled. Finally, all the DRFs obtained from different platforms are combined to resolve vertical DRF by the least squares solution. For validation purpose, the northwestern part of Tianjin (China) is selected as the testing area, and 39 TerraSAR-X images, 23 ENVISAT ASAR and 16 ALOS PALSAR images collected over this area between 2007 and 2010 are used to estimate the vertical DRF. The comparison with the ground-based leveling results indicates that the vertical deformation rates derived by the combined solution can reach up to a millimeter accuracy level.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128202771","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}

{"title":"Cross-calibration of HJ-1B/CCD1 image based on Aqua/MODIS data","authors":"Lili Li, Jingxue Yang, Yunpeng Wang","doi":"10.1109/EORSA.2012.6261147","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261147","url":null,"abstract":"Cross radiometric calibration is an effective method of no-ground-site calibration of remote sensors through building the relationship between the radiance of the reference sensor with higher radiometric accuracy and the experimental sensor, which can avoid the disadvantages of ground-site calibration — higher cost and longer update cycle of calibration coefficients. In this paper, the visible and near-infrared spectral bands of HJ-1B/CCD1 are cross-calibrated through the Ray-Matching method (RM) using the corresponding bands of Aqua/MODIS with higher radiometric accuracy and the TM image at a similar time is used to validate our results. Compared with the results by the coefficients of the satellite, the cross-calibration results by RM method are desirable and the error is acceptable, showing higher accuracy and effectiveness.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124471346","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}

{"title":"Compare different levels of fusion between optical and SAR data for impervious surfaces estimation","authors":"Hongsheng Zhang, Yuanzhi Zhang, Hui Lin","doi":"10.1109/EORSA.2012.6261128","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261128","url":null,"abstract":"Impervious surfaces estimation has become very significant both in urban and environment studies. Recently, the synergistic use of optical and Synthetic Aperture Radar (SAR) data has been identified as a promising approach for accurate estimation of impervious surfaces. This paper presents a comparison study over three different levels (pixel, feature, and decision level) of fusion between optical and SAR data. Detailed fusion strategies are designed at three levels, and the support vector machine is employed as the fusion method. Results indicate that pixel level fusion (Overall accuracy: 78.27%; Kappa: 0.5654) seems not appropriate for optical-SAR fusion, as it reduces the accuracy compared to the single use of optical data (Overall accuracy: 78.47%; Kappa: 0.5694). In addition, decision level fusion obtained the best accuracy (Overall accuracy: 89.87%; Kappa: 0.7974), since it not only improves the impervious surfaces in shaded areas and but also well separates bare soils.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"2002 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129581530","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}

{"title":"The evenness degree evaluation of parkland location in the main province garden cities of Shandong Province based on 1km grid model","authors":"X. Fei, Zhiguo Zhang, Xiang-wei Gao","doi":"10.1109/EORSA.2012.6261195","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261195","url":null,"abstract":"The evenness is one of the most important evaluation indexes for urban park green space quality. In this study, four province garden cities were chosen as the study area, including Tai'an, Linyi, Dezhou, Binzhou, and Dongying in Shandong Province. First, the limit and parkland digital location map of each urban area were obtained by visual interpretation from high spatial images such as, Quickbird and Spot5. Then, using GIS technology, the 1km grid with definite start point was drawn. Based on the 1km grid, according to national garden city standards published by State Ministry of Construction, the evenness model was developed using two factors, the ratio of blind grid zone of green space in entire urban area and the standard error of ratio of green space in service grid. Using the developed model, the spatial location evenness degree (SLED) of each city was computed. The result showed that Linyi city has the largest parkland area and Per capita park green space. But the SLED is only 3. Dongying city has the best SLED, although the per capita park green space is smaller than that of Linyi city. In Binzhou and Tai'an city, the SLED is similar, although the quantity has obvious difference. Hence, the evenness evaluation based on 1km model is more comprehensive for indicating the quality of parkland space quality.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126346510","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}

{"title":"The assessment of air quality using satellite observations in coal-fired power plants","authors":"Weiling Wu, Liangfu Chen, J. Tao, L. Su, Huanhuan Yan","doi":"10.1109/EORSA.2012.6261160","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261160","url":null,"abstract":"Understanding the spatial and temporal variation of pollutant concentrations over power plant is important for optimizing emission control strategies. Remote sensing technology can help to expand the sparse ground monitoring networks into regions currently not covered. This paper use the monthly mean sulfur dioxide (SO2) and nitrogen dioxide (NO2) from Ozone Monitoring Instrument (OMI) on board NASA's Aura satellite to assess the air quality in several coal-fired power plants over the North China Plain. Our analysis indicates: 1) The inter-annual variation (2007∼2009) of SO2 and NO2 showed the implement of flue-gas desulfurization (FGD) devices in power plants was effectiveness; 2) Due to lack of NO2 national standard and the increasing NO2 emissions from automobiles, the NO2 pollutions have a trend of increment in North China Plain in the past decade; 3) By comparing the monthly mean SO2 and NO2 of several big coal-fired power plants over the mountain and plain area, we found that the power output directly affects pollutant concentrations.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127748366","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}

{"title":"Elevation accuracy assessment of a DSM and DTM generated for an urban area from the ALTM 2025 airborne laser scanning sensor","authors":"F. Leonardi, C. Almeida, Leila Maria Garcia Fonseca, L. Tomás, P. G. Albuquerque, C. Oliveira","doi":"10.1109/EORSA.2012.6261142","DOIUrl":"https://doi.org/10.1109/EORSA.2012.6261142","url":null,"abstract":"The assessment of elevation accuracy of digital elevation models (DEM), which comprise digital surface models (DSM) and digital terrain models (DTM), has become a recurrent theme in the scientific literature in the latest decades. Accuracy tests are specifically based on a 10% level of statistical significance and they comprise both trend and precision analyses. Both tests were applied to data obtained from an air survey accomplished with the ALTM 2025 laser scanning sensor for a central sector of Uberlandia city, Brazil. The statistical tests for the DSM and DTM demonstrated that the mean elevation error respectively lay around 0,41 m and 0,48 m, and the RMSE about 0,48 m and 0,47 m. In both cases, the presence of trend in the H direction was observed, revealing systematic influences in this component. This trend was further removed by means of algebraic manipulations. The precision analysis revealed that the DSM and DTM were compatible with a 1∶5,000 scale and were up to the standard of the highest cartographic accuracy category (class A - PEC).","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"89 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113971631","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}