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2012 IEEE International Geoscience and Remote Sensing Symposium最新文献

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Model analysis and experimental investigations of X-band backscattering sensitivity to snowpack characteristics 积雪特征对x波段后向散射灵敏度的模型分析与实验研究
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6351313
M. Brogioni, C. Xiong, P. Pampaloni, S. Pettinato, S. Paloscia, Jiancheng Shi
{"title":"Model analysis and experimental investigations of X-band backscattering sensitivity to snowpack characteristics","authors":"M. Brogioni, C. Xiong, P. Pampaloni, S. Pettinato, S. Paloscia, Jiancheng Shi","doi":"10.1109/IGARSS.2012.6351313","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6351313","url":null,"abstract":"Monitoring of snow cover is crucial in water resource management and hydrological risk prevention. Experiments have shown the ability of C-band SAR in mapping the extent of wet snow. But, detection of dry snow at this frequency is difficult due to the high transmissivity of the snowpack. A model sensitivity study, corroborated by experimental data, has demonstrated that COSMO-Skymed X-band data can give significant information for generating maps of SWE for snow depth higher than about 50-60 cm.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124754653","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: 5
Robust unsupervised nonparametric change detection of SAR images SAR图像鲁棒无监督非参数变化检测
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6351111
A. Garzelli, C. Zoppetti, B. Aiazzi, S. Baronti, L. Alparone
{"title":"Robust unsupervised nonparametric change detection of SAR images","authors":"A. Garzelli, C. Zoppetti, B. Aiazzi, S. Baronti, L. Alparone","doi":"10.1109/IGARSS.2012.6351111","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6351111","url":null,"abstract":"This paper presents an unsupervised nonparametric method for change detection in multitemporal synthetic aperture radar (SAR) imagery. The proposed method relies on a novel feature capable of capturing the structural changes between the two images and discarding almost completely the statistical changes due to speckle patterns or co-registration inaccuracies. This feature utilizes the scatterplots of the amplitude levels in the two SAR images and applies a fast version of the mean-shift (MS) algorithm to find the modes of the underlying bivariate distribution. The value of the probability density function (PDF) is translated to a value of conditional information and given to all image pixels originating such modes. Experimental results have been carried out with simulated changes and true SAR images acquired by the COSMO-SkyMed satellite constellation. The proposed feature exhibits significantly better discrimination capability than both the classical log-ratio (LR) and is particularly robust if applied to SAR images having different processing and/or acquisition angles.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123557874","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: 4
Radar altimetry of water level variability in the Inner Delta of Niger River 尼日尔河内三角洲水位变化的雷达测高
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6352422
K. Goita, A. T. Diepkilé
{"title":"Radar altimetry of water level variability in the Inner Delta of Niger River","authors":"K. Goita, A. T. Diepkilé","doi":"10.1109/IGARSS.2012.6352422","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6352422","url":null,"abstract":"This study shows that consistent long term water level time series could be established in heterogeneous medium such as the Delta, using satellite altimetry data. A correction of 89 cm was used to reduce the two satellites at the same altimetry reference system. The seventeen years of water level data is of great value for hydrologic and climate related studies in the Delta in West-Africa, where measurements gauge stations are rare. Our results show that precipitation has a major influence in the flooding process in the Delta. Further analyses are ongoing to better understand the contributions of satellite altimetry data in the study of the hydrology and climate in the Delta.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131129822","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: 6
Sensitivity of TerraSAR-X, RADARSAT-2 and ALOS satellite radar data to crop variables TerraSAR-X、RADARSAT-2和ALOS卫星雷达数据对作物变量的敏感性
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6350504
R. Fieuzal, F. Baup, C. Marais-Sicre
{"title":"Sensitivity of TerraSAR-X, RADARSAT-2 and ALOS satellite radar data to crop variables","authors":"R. Fieuzal, F. Baup, C. Marais-Sicre","doi":"10.1109/IGARSS.2012.6350504","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6350504","url":null,"abstract":"The aim of this work is to investigate the sensitivity of multi-incidence, multi-frequency and multi-polarized radar signatures over different crops (wheat, rapeseed, soybean, corn and sunflower). Time series of SAR images are acquired by TerraSAR-X (HH), RADARSAT-2 (full polarization) and ALOS (HH) over an agricultural site located in South West of France during the MCM'10 experiment synchronously with ground measurements. The angular normalization of radar signals is performed per crop type at X- and C-bands. The angular sensitivity of the backscatters decreases with the increase of the vegetation index (from 0.4 dB.°-1 over bare soils to 0.05 dB.°-1 for fully vegetated fields). Analyses of the radar time series show that X-, C- and L-bands behaviors are strongly contrasted, depending on the phenological stages of crops, highlighting the interest of using multi-frequency data. Crop height retrieval based on microwave data indicates promising results, with R2 ranging from 0.7 to 0.93.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131851242","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: 18
Scattering analysis of flat magnetic dipoles embedded in chiral multilayer structures 嵌入手性多层结构中的平面磁偶极子的散射分析
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6352289
N. R. Rabelo, S. Sant’anna, José Carlos Lacava, D. Fernandes
{"title":"Scattering analysis of flat magnetic dipoles embedded in chiral multilayer structures","authors":"N. R. Rabelo, S. Sant’anna, José Carlos Lacava, D. Fernandes","doi":"10.1109/IGARSS.2012.6352289","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6352289","url":null,"abstract":"From a model developed for the electromagnetic analysis of structures consisting of multiple chiral layers with electric and magnetic currents on the layer interfaces, this paper presents the scattering matrix for the case of magnetic dipoles embedded in a chiral layer structure. The effects of the chiral admittance and the thickness of the layer on the co- and cross-polarized polarimetric responses are considered and a comparison is made with electric dipoles at similar conditions.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121960085","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
Analysis of fisheye photography for monitoring canopy structure during larch sawfly outbreak 落叶松锯叶虫爆发时林冠结构监测的鱼眼摄影分析
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6352713
M. Kubo, S. Gavrilov, K. Muramoto, N. Kamata
{"title":"Analysis of fisheye photography for monitoring canopy structure during larch sawfly outbreak","authors":"M. Kubo, S. Gavrilov, K. Muramoto, N. Kamata","doi":"10.1109/IGARSS.2012.6352713","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6352713","url":null,"abstract":"During an outbreak of the larch sawfly in Hokkaido, Japan, it was demonstrated that hemispherical photography could detect defoliation, measured as changes in vegetation index (NDVI).","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117252380","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: 1
An initial consistency analysis of Aerosol Optical Depth retrieval from satellite data 卫星气溶胶光学深度反演的初步一致性分析
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6352397
Jia Liu, Yong Xue, Hui Xu, Yingjie Li, J. Guang, Chi Li
{"title":"An initial consistency analysis of Aerosol Optical Depth retrieval from satellite data","authors":"Jia Liu, Yong Xue, Hui Xu, Yingjie Li, J. Guang, Chi Li","doi":"10.1109/IGARSS.2012.6352397","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6352397","url":null,"abstract":"Aerosol Optical Depth (AOD) is an important index that indicates the aerosol condition. This article summarizes the efforts to explore discrepancies in the AOD retrieval process, mainly focusing on consistency analysis among multiple instruments and algorithms, and we conduct the experiments of consistency in a single instrument and algorithm of AOD retrieval based on the Synergetic Retrieval of Aerosol Properties (SRAP) model from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In this article we propose the discrepancy problem, and provide some possible solutions.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121318282","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
The retrieval and monitoring of vegetation parameters from COSMO-SkyMed images COSMO-SkyMed影像中植被参数的检索与监测
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6351952
E. Santi, G. Fontanelli, F. Montomoli, M. Brogioni, G. Macelloni, S. Paloscia, S. Pettinato, P. Pampaloni
{"title":"The retrieval and monitoring of vegetation parameters from COSMO-SkyMed images","authors":"E. Santi, G. Fontanelli, F. Montomoli, M. Brogioni, G. Macelloni, S. Paloscia, S. Pettinato, P. Pampaloni","doi":"10.1109/IGARSS.2012.6351952","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6351952","url":null,"abstract":"The capability of COSMO-SkyMed in estimating vegetation biomass has been investigated in this paper. SAR data from COSMO-SkyMed were collected on two agricultural areas in Italy in 2010 at different dates during the vegetation cycle. The performances of X-band data have been compared with accurate ground truth measurements of soil and vegetation carried out simultaneously to satellite passes. Experimental data have been compared with model simulations obtained with a discrete element radiative transfer model. Moreover, an inversion algorithm, based on an Artificial Neural Network and trained by using AIEM and the radiative transfer model, has been applied to retrieve the plant water content of wheat and sunflower crops and to generate the corresponding plant water content maps.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122426927","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: 15
Global trends in tropospheric NO2 observed from space 从太空观测对流层二氧化氮的全球趋势
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6350625
P. Schneider, A. Ronaldvander
{"title":"Global trends in tropospheric NO2 observed from space","authors":"P. Schneider, A. Ronaldvander","doi":"10.1109/IGARSS.2012.6350625","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6350625","url":null,"abstract":"Here we present results of a global trend analysis using nearly a decade of NO2 observations acquired by the SCIA-MACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) instrument onboard the Envisat satellite platform. Monthly average tropospheric NO2 column data was acquired for the period between August 2002 and August 2011. A trend analysis was subsequently performed by fitting a statistical model including a seasonal cycle and linear trend to the time series extracted at each grid cell. The linear trend component and the trend uncertainty were then mapped spatially at both regional and global scales. The results show that spatially contiguous areas of significantly increasing NO2 levels are found primarily in Eastern China. In addition, many urban agglomerations in Asia and the Middle East similarly exhibit significantly increasing trends, with Dhaka in Bangladesh being the megacity with the most rapid relative increase during the study period. In contrast, significantly decreasing trends in NO2 levels exist over large parts of Europe and the Eastern United States. The satellite-derived time series were further analysed with respect to identification of the impact of the 2008/2009 economic crisis. European trends obtained from the satellite analysis are also compared with corresponding trends computed using data of the EMEP model, as well as with NO2 trends calculated from station observations throughout Europe.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114984665","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
A wrapper feature selection for the polarimetric SAR data classification 用于极化SAR数据分类的包装器特征选择
2012 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2012-11-12 DOI: 10.1109/IGARSS.2012.6350411
Y. Maghsoudi, M. Collins, D. Leckie
{"title":"A wrapper feature selection for the polarimetric SAR data classification","authors":"Y. Maghsoudi, M. Collins, D. Leckie","doi":"10.1109/IGARSS.2012.6350411","DOIUrl":"https://doi.org/10.1109/IGARSS.2012.6350411","url":null,"abstract":"The main objective is to propose a wrapper feature selection algorithm for analyzing the polarimetric SAR data for forest mapping. The method is based on the concept of feature selection and classifier ensemble. Due to its ability to take numerous and heterogeneous features into account, the support vector machine (SVM) algorithm is used as the classifier. The limitation of SVM as the evaluation function for feature selection is its time-consuming optimization. To accelerate the SVM training process, a training sample reduction strategy based on the notion of support vectors is proposed. Two fine quad-polarized Radarsat-2 images, which were acquired in leaf-on and leaf-off seasons, were chosen for this study. A wide range of SAR parameters were derived from each PolSAR image. A combined dataset was also considered. The classification results (in terms of the overall accuracy) compared to the baseline classifiers demonstrate the effectiveness of the proposed wrapper scheme for forest mapping.","PeriodicalId":193438,"journal":{"name":"2012 IEEE International Geoscience and Remote Sensing Symposium","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131300519","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: 4
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