{"title":"Multi-polarization scatterometer measurements of long surface gravity wave breaking","authors":"M. Gade, T. Grobelny, D. Stammer","doi":"10.1109/IGARSS.2014.6947022","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947022","url":null,"abstract":"The possibility of detecting breaking long surface gravity waves in S-band radar backscatter measurements is being investigated using multi-polarization scatterometer measurements. To detect breaking waves the change in the spectral shape of the radar Doppler spectra was analyzed with respect to possible indicators for wave breaking events. They are identified here using the ratio of the second and fourth spectral moments after normalization by the squared radar frequency. A comparison with simultaneous estimates of the fractional area of whitecaps suggests that a normalized spectral moment ratio might be used as one indicator for events of breaking surface gravity waves.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129946066","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":"Object based building extraction by QuickBird image for population estimation: A case study of the City of Waterloo","authors":"Wei Li, Shiqian Wang, Jonathan Li","doi":"10.1109/IGARSS.2014.6947152","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947152","url":null,"abstract":"This paper used QuickBird high resolution image to estimate the population of the city of Waterloo, ON, Canada. Two approaches of object based classification were compared to extract buildings from the original image. One is rule based classification and the other is example based classification. We chose two districts which are Lakeshore and Columbia as our testing areas. Rule based result is better than example based. The overall accuracy of rule based classification in Lakeshore District and Columbia District are 92.5% and 85.5%. With census data, the average area per person is about 38.8 m2 and the estimated population of the city of Waterloo is about 109589.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128484892","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":"Analysis of surface wind retrieval in coastal areas from SAR","authors":"G. Carvajal, L. Eriksson","doi":"10.1109/IGARSS.2014.6947339","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947339","url":null,"abstract":"There are different parameters inherent to coastal areas that can affect the backscattering of the ocean surface detected by Synthetic Aperture Radar (SAR). The parameters include the influence of land, the influence of the SAR acquisition geometry, and the influence of backscattering features not directly related to wind variations. This work focuses on the study of the influence of those parameters for the performance of surface wind retrieval with C-band SAR data in coastal areas.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128549485","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":"Computing the magnetic polarizability of thin conducting sheets using an eigenvalue decomposition","authors":"J. Gabbay, W. Scott","doi":"10.1109/IGARSS.2014.6947008","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947008","url":null,"abstract":"The ability to detect and dispose of buried mines requires effective means by which to discriminate between hazardous targets and benign clutter. In that regard, wide-band electromagnetic induction (EMI) sensors have shown significant promise in their ability to classify buried metallic objects based on their response to illumination by a time-varying magnetic field. A target's scattered response may be expressed compactly in its magnetic polarizability dyadic, a form that describes the reaction of the scatterer to an arbitrary magnetic field. The magnetic polarizability dyadic may be written in terms of the eddy currents that are induced in the target. The method described in this paper uses a scalar stream function as a basis for the eddy currents that are induced in the target. This approach is powerful since the solenoidality of the current density is enforced trivially and its boundary conditions may be enforced elegantly. By setting up the eddy current equation as a generalized eigenvalue problem we arrive at a modal decomposition of the polarizability dyadic. Distribution A: Approved for public release.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128718197","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":"Developing remote sensing methodology to distinguish urban built-up areas and bare land in Mafikeng town, South Africa","authors":"L. Palamuleni, N. Ndou","doi":"10.1109/IGARSS.2014.6946906","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6946906","url":null,"abstract":"Application of remote sensing technologies in mapping urban land cover still poses a challenge among urban planners. The aim of this study was to develop remote sensing methodology for distinguishing bare surface and built-up area in Mafikeng, South Africa. Several indices were developed to depict various urban features including NDVI, NDBAI, NDISI, NDWI and NDSI using Landsat 8-OLI data. Different supervised classification algorithms were independently tested to determine their ability in extracting the urban land cover classes. Field survey was conducted to gather ground truth data for accuracy assessment. The classification results proved that KNN was effective in not only increasing the classification accuracy, but also in making the classification of urban land cover features more visible and distinguishable than the other classifiers. The results demonstrate the potential of KNN classifier and combination of several indices to accurately map urban land cover features that can be used as input to land management and urban policy planning decisions.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129019943","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 ensemble-based systems for snow-mapping using NOAA-AVHRR data over Eastern Canada","authors":"S. Roberge, K. Chokmani, D. D. Sève","doi":"10.1109/IGARSS.2014.6947358","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947358","url":null,"abstract":"Common operational snow cover products based on optical or passive microwave sensors (IMS, MODIS SNOWMAP, NOAA GOES+SSM/I, etc.) provide maps of the snow cover extent or fractional snow cover maps. These snow cover products do not provide the probability of observing snow and its uncertainty. This information is crucial in the context of forecasting water supplies to support efficient electricity. This study's objective is to develop probability maps with ensemble-based systems, where probabilities could be used to flag the onset of spring melt. To achieve this, bagging and majority voting were implemented in the snow-mapping procedure using AVHRR-KLM data of Eastern Canada. This consists in generating 100 versions based on a random variation of the six empirical threshold parameters included in the procedure. The probability of a pixel corresponds to the number of times it was identified as snow, no-snow or cloud.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124655479","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":"Design and ground validation technique of HY-2Ascatterometer","authors":"Xiaoning Wang, Jun Yu Li, Lixia Liu, Xu Jin, Wenxin Chen","doi":"10.1109/IGARSS.2014.6947664","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947664","url":null,"abstract":"The HY-2A satellite was first launched in August of 2011, the microwave scatterometer as one of the main loads, is primarily applied in sea surface wind observation. HY-2A scatterometer used two pencil beam conical scan system, and the radar worked in Ku band. The characteristics of scatterometer are tested in laboratory used the Echo Wave simulator and function validation are performed by airborne experiment. System composition and main performance requirements are presented in this paper, and airborne experiment validation scheme and its results are also introduced. On-orbit test results show that expected measurement requirements are achieved.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129476186","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}
Zhongling Gao, Q. Qin, Yuejun Sun, Xiao-po Zheng, Lingjing Wu, Nan Wang
{"title":"Improvement of TVDI for soil moisture estimation","authors":"Zhongling Gao, Q. Qin, Yuejun Sun, Xiao-po Zheng, Lingjing Wu, Nan Wang","doi":"10.1109/IGARSS.2014.6947173","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947173","url":null,"abstract":"In the paper, we developed a novel method of soil moisture estimation in vegetated area base on the simulation result of Cupid model[1], and it was found that LAI and land surface temperture (Ts) appeared in logarithmic relation rather than linear traditionally TVDI (Temperature Vegetation Dryness Index) assumed. Then the soil moisture in vegetated area was calculated through a look-up table. The validation result shown that R2 of the novel method was better than TVDI.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130375809","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":"Enhanced mapping and monitoring of mine tailings based on Landsat ETM+ and SPOT 5 fusion in the North of Tunisia","authors":"N. Mezned, Nada Mechrgui, S. Abdeljaoued","doi":"10.1109/IGARSS.2014.6947568","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947568","url":null,"abstract":"Mine tailings constitute an alarming source of pollution that threatens soils, vegetation and human health around Jebel Hallouf-Bouaouane mine site. Because of their widespread geographical distribution; their location and extent, the characterization of mine tailings using traditional field work alone is both costly and inefficient. In this study, we explore remote sensing techniques based on multispectral and multisensory data fusion. Our contribution consists in enhanced mine tailing map generation using both SPOT 5 panchromatic and Landsat ETM+ multispectral data. Results of the linear spectral unmixing of the resulting hybrid image tend to field truth. The inter-comparison of unmixing results indicates that this methodology can be applied successfully to multispectral data for multi-temporal monitoring of mine tailings.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130391333","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":"Quantitative flood assessment: Case study of floods in Germany","authors":"C. Dumitru, S. Cui, M. Datcu","doi":"10.1109/IGARSS.2014.6947238","DOIUrl":"https://doi.org/10.1109/IGARSS.2014.6947238","url":null,"abstract":"In this paper, we present a quantitative analysis for a rapid mapping scenario that performs a damage assessment of the 2013 floods in Germany. The scenario is created using pre-disaster and post-disaster TerraSAR-X images and an automated annotation system. Our data set is tiled into patches and Gabor filters are used as a primitive feature method applied to each patch separately. An active learning system based on support vector machine is implemented in order to group the features into categories. Once all categories are identified, these are semantically annotated using reference data as ground truth. In our evaluation 7 categories were retrieved with their specific taxonomies defined using our previous hierarchical annotation scheme. We show that the system supports rapid mapping scenarios (e.g., floods, tsunami, earthquake, etc.) and interactive mapping generation. In addition, with the help of this system, quantitative assessment of disasters can be carried out.","PeriodicalId":385645,"journal":{"name":"2014 IEEE Geoscience and Remote Sensing Symposium","volume":"403 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126676740","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}