2007 IEEE International Geoscience and Remote Sensing Symposium最新文献_第2页

Sun glint and sea surface salinity remote sensing 太阳闪烁与海面盐度遥感

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4423052

E. Dinnat, P. D. Matthaeis, D. Vine

引用次数: 0

Three dimensional groundwater virtual reality system and its spatial database 三维地下水虚拟现实系统及其空间数据库

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4423919

G. Huili, Hu Zhuowei, Zhao Wenji, Li Xiaojuan, Wang Yanhui, Gong Zhaoning, Zhan Songmei

{"title":"Three dimensional groundwater virtual reality system and its spatial database","authors":"G. Huili, Hu Zhuowei, Zhao Wenji, Li Xiaojuan, Wang Yanhui, Gong Zhaoning, Zhan Songmei","doi":"10.1109/IGARSS.2007.4423919","DOIUrl":"https://doi.org/10.1109/IGARSS.2007.4423919","url":null,"abstract":"The current policy in the work of groundwater exploitation and management was paying attention to the questions of overall situation, long-term requirement and the holistic development of hydrological geology. Under this framework, the work of groundwater scientific management had some new characteristics. The outstanding representation was the combination with spatial information technology and virtual reality technology. Our research work was founded on the basis of field monitoring and surveying. To correctly reveal and express the actual spatial structure of groundwater and its storage environment, by using stratum generalization, spatial analysis, data interpolation and some other methodologies, a suit of 3D data structure was designed out and realized by C++ programming language to store and express the underground spatial information. Based on the database technology, an independent 3D spatial data engine interfaces was developed to make the following works more convenient. Taking the 3D virtual demonstration, arbitrary section analysis, dynamic changing simulation, and land subsidence simulation as the main objectives of developing, an integrated 3D groundwater virtual reality system (TDGVRS) was accomplished. We selected visual C++ as the main programming tool and OpenGL as the 3D graphic rendering tool. Now, the system is practically running in some operational departments. Feedbacks from the user show that the effect of visualization was good, the operation is flexible, the analysis functions are powerful and the result is credible. TDGVRS is now providing important technical supports to relative groundwater management works.","PeriodicalId":284711,"journal":{"name":"2007 IEEE International Geoscience and Remote Sensing Symposium","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063436","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

Identification of generalized self-similar principal components of single image for image filtering and pattern decomposition 单幅图像广义自相似主成分的识别，用于图像滤波和模式分解

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4422787

Q. Cheng

{"title":"Identification of generalized self-similar principal components of single image for image filtering and pattern decomposition","authors":"Q. Cheng","doi":"10.1109/IGARSS.2007.4422787","DOIUrl":"https://doi.org/10.1109/IGARSS.2007.4422787","url":null,"abstract":"Scale and resolution are critical parameters in utilization of any maps including remotely sensed imagery. With information techniques such as image processing and GIS software, digital images can be easily visualized at multiple scales. Due to the dimensional property (fractality) of objects on the ground or the dimensional properties (multifractalities) of mixing objects, the changing regularities of image patterns observed at different scales or resolutions can be quantified in terms of self- similarity or generalized self-similarity. A newly developed method is introduced for identifying self-similar principal components from a single image so that self-similar components can be utilized for purposes of image filtering and image decomposing. The self-similarity of principal components introduced in this paper is characterized by power-law relations observed from the frequency distributions of the eigenvalues or eigenvectors calculated from a single image. Different groups of self-similar components can be identified and used for image decomposing. The case study for validation is chosen from a DEM at 30 meter resolution in the Greater Toronto Area,Canada.","PeriodicalId":284711,"journal":{"name":"2007 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117245237","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

Frequency domain imaging algorithm for spaceborne/airborne hybrid bistatic SAR 星载/机载混合双基地SAR频域成像算法

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4422928

Zhe Liu, Jianyu Yang, Xiaoling Zhang, Y. Pi

引用次数: 4

ASCAT scatterometer ocean calibration ASCAT散射计海洋校正

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2008.4780074

J. Verspeek, A. Stoffelen, M. Portabella, A. Verhoef, J. Vogelzang

引用次数: 9

Advances in real time lidar spectroscopy 实时激光雷达光谱学研究进展

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4424048

B. Lienert, Shiv k. Sharma, T. Chen, J. Madey

引用次数: 0

Development and testing of the GISMOS instrument GISMOS仪器的开发和测试

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4424010

J. Garrison, M. A. Walker, J. Haase, T. Lulich, F. Xie, B. D. Ventre, M. Boehme, Ben Wilmhoff, S. Katzberg

引用次数: 17

Estimation of height measurement accuracy for ALOS PRISM triplet images ALOS PRISM三重图像高度测量精度估计

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4423442

M. Maruya, Hiroshi Ohyama

引用次数: 6

A neural netwotk based approach for multi-spectral snowfall detection and estimation 一种基于神经网络的多光谱降雪检测与估计方法

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4423295

Y. Mejia, H. Ghedira, S. Mahani, R. Khanbilvardi

{"title":"A neural netwotk based approach for multi-spectral snowfall detection and estimation","authors":"Y. Mejia, H. Ghedira, S. Mahani, R. Khanbilvardi","doi":"10.1109/IGARSS.2007.4423295","DOIUrl":"https://doi.org/10.1109/IGARSS.2007.4423295","url":null,"abstract":"The principal intent of this research is to: (a) investigate the potential of passive microwave data from AMSU in detecting snowfall events and in measuring their intensity, and (b) evaluate the effect of both land cover and atmospheric conditions on the retrieval accuracy. Additional information such as cloud cover and air temperature were added to the process to reduce misidentified snowfall pixels. Two products retrieved from AMSU brightness temperatures were used to estimate surface temperature and to map the snow cover extent. In this project, a neural-network-based model has been developed and has shown a great potential in detecting and estimating the intensity of snowfall events. This algorithm has been applied for different snow storms occurred between 2002 and 2003 in three different locations in the North-East of United States. These locations were selected because of the high amount of snowfall every year. Only pixels with cloud cover and falling within a specific range of temperature are presented to the snowfall detection model. Surface temperature collected from ground station-based observations archived by the National Climatic Data Center (NCDC) were used for this test. Different heavy storm events and non-snowfall observations that occurred at the same time as AMSU acquisition were selected. Hourly snow accumulation data collected by the NCDC were used as truth data to train and validate the model. To reduce the risk of erroneous identification of snowfall pixels, only storms lasting more than three hours were selected. Such criteria will undoubtedly increase the level of confidence that snowfall coincides with AMSU acquisition time. The neural network based snowfall product was compared with the snowfall detection algorithm over land developed in 2003 by Kongoli et al [1]. The preliminary results indicate that the neural-network-based model provides a significant improvement in snowfall detection accuracy over existing satellite-based methods.","PeriodicalId":284711,"journal":{"name":"2007 IEEE International Geoscience and Remote Sensing Symposium","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125118316","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

Provision of snow water equivalent from satellite data and the hydrological model PROMET using data assimilation techniques 利用数据同化技术从卫星数据和PROMET水文模型中提供雪水当量

2007 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2007-07-23 DOI: 10.1109/IGARSS.2007.4423779

F. Appel, H. Bach, Natalie Ohl, W. Mauser

{"title":"Provision of snow water equivalent from satellite data and the hydrological model PROMET using data assimilation techniques","authors":"F. Appel, H. Bach, Natalie Ohl, W. Mauser","doi":"10.1109/IGARSS.2007.4423779","DOIUrl":"https://doi.org/10.1109/IGARSS.2007.4423779","url":null,"abstract":"Information on snow cover and snow properties is an important factor for hydrology and runoff modelling. Frequent updates of snow cover information can help to improve water balance and discharge calculations. Within the frame of polar view, snow products from multisensoral satellite data are operationally provided to control and update water balance models for large parts of Southern Germany. Optical AVHRR sensors of the NOAA satellite are used for snow mapping and snow line delineation. Although these acquisitions are available several times per day, cloud cover hinders frequent updates of snow cover maps. As an additional remote sensing data source microwave data from ASAR on ENVISAT is used. Since C-band SAR sensors are only sensitive to snow with a high content of liquid water, the application of ASAR is limited to the melting periods. However under these conditions the developed procedure allows not only to delineate the snow cover in a comparable way as from optical data, also the additional information where the snow is melting is provided. In order to demonstrate how the remote sensing products can be used for improved water balance modelling, an application example for the watershed of the Upper Danube will be presented. This testsite is the research area of the integrative research project GLOWA-DANUBE that is conducted by the University of Munich. Model results using the PROMET-model of snow distributions with and without data assimilation of the remote sensing products will be given. Developed data assimilation concepts will be presented. Through data assimilation, the modelled snow cover agrees better with the mapped snow cover information from satellite. The optimised model provides maps of snow water equivalent, that can not directed be assessed by remote sensing. The impact of data assimilation on the modelled runoff will thus further be analysed.","PeriodicalId":284711,"journal":{"name":"2007 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125817627","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