IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium最新文献_第10页

Object-Oriented Classification for Change Detection with Different Spatial Resolution Images 面向对象的不同空间分辨率图像变化检测分类

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779519

Yongdae Gweon, Yun Zhang

引用次数: 3

Doppler Parameter Estimation for Single-Channel SAR Moving Target based on a Novel Model in Complex Image Domain 基于复像域新模型的单通道SAR运动目标多普勒参数估计

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779567

Yuanyuan Zuo, Jia Xu, Yingning Peng

引用次数: 2

Data Dimension Reduction and Band Selection using Canopy Spectral Invariants (CSI) Concept 基于冠层光谱不变量(CSI)概念的数据降维和波段选择

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779987

Dianzhong Wang, G. Sun, Shengli Wu, Y. Pang, Zhifeng Guo

{"title":"Data Dimension Reduction and Band Selection using Canopy Spectral Invariants (CSI) Concept","authors":"Dianzhong Wang, G. Sun, Shengli Wu, Y. Pang, Zhifeng Guo","doi":"10.1109/IGARSS.2008.4779987","DOIUrl":"https://doi.org/10.1109/IGARSS.2008.4779987","url":null,"abstract":"In this paper, we carried out a case study with a multidirectional and hyperspectral data, CHRIS (the Compact High Resolution Imaging Spectrometer) on board platform PROBA (Project for On Board Autonomy). After orthocorrection and atmospheric correction, we analyzed the directional reflectance (HDRF) of a dense conifer forest to get two CSI, i.e. effective value of re-collision probability, pr, and escape probability R1 at different angles. These two invariants at all five angles were regressed to LVIS_H100 data, which is relevant to canopy height, and demonstrated a comparable statistics to the regression with spectral reflectances. In this sense, CSI method can act as an effective tool to reduce the dimension of hyperspectral remote sensing data by a ratio of N/2 (N is the number of spectral bands). Re-collision probability, pr, and escape probability R1 can be understood as two principle components in PCA, however, they are superior to principle components because the transformation is based on radiation transfer physics and reduction result have explicit interpretation. In similar consideration to reduce the redundancy as above, we also calculated the deviation of each spectral band to the fitted value from pr and R1 and make a statistics for all the sampling pixels. We picked out the best fitted bands, as most of them locate in NIR range, we employed statistics to determine which to supplement in visible range, and discussed the potential of these bands to be selected as optimal VNIR bands combination of future vegetation sensor design.","PeriodicalId":237798,"journal":{"name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125760266","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

Error Analysis of Soil Roughness Parameters Estimated from Measured Surface Profile Data 基于实测地表剖面数据估算土壤粗糙度参数的误差分析

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779094

M. Nishimoto

引用次数: 8

Monitoring water constituents and salinity variations of saltwater using EO-1 Hyperion satellite imagery in the Pearl River Estuary, China 利用EO-1 Hyperion卫星图像监测珠江口海水成分和盐度变化

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4778889

Ligang Fang, Shuisen Chen, Hongli Li, C. Gu

{"title":"Monitoring water constituents and salinity variations of saltwater using EO-1 Hyperion satellite imagery in the Pearl River Estuary, China","authors":"Ligang Fang, Shuisen Chen, Hongli Li, C. Gu","doi":"10.1109/IGARSS.2008.4778889","DOIUrl":"https://doi.org/10.1109/IGARSS.2008.4778889","url":null,"abstract":"to detect water constituents' concentrations and salinity of the Pearl River Estuary (PRE), we analyzed the spectral properties of water constituents and investigated the relationships between field water reflectance spectra and water constituents' concentrations based on the synchronous in-situ hyper-spectral data analysis. Two strong relationships were discovered (two linear fit described respectively the positive correlation), one between in-situ reflectance ratio R680/R527 and total suspended sediment concentrations (TSS) (R2=65%) and the other between chlorophyll-a concentrations and the reflectance ratio R704/R513 (R2=78%); however, the result also showed that the absorption coefficient of color dissolved organic matter (CDOM) was not tightly correlated with reflectance. In addition, we also observed the significant relationships (R2=79%) between TSS and surface salinity. Finally, we were able to develop a novel method to detect water constituents' concentrations and surface salinity of river estuary waters from the calibrated EO-1 Hyperion reflectance data in the PRE. The EO-1 Hyperion derived surface salinity and water constituents' concentrations were validated using in-situ data that were collected on December 21, 2006, and synchronous with EO-1 Hyperion satellite imagery acquisition. The results showed that the semi-empirical relationships are capable of predicting salinity and water constituents' concentrations from EO-1 Hyperion imagery.","PeriodicalId":237798,"journal":{"name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126007099","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

Spaceborne Hyperspectral Image Generation based on Airborne Hyperspectral Image 基于机载高光谱图像的星载高光谱图像生成

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779707

Junping Zhang, W. Zhang, Haibin Jiao, Ye Zhang

引用次数: 2

Detection of Wooded Hedgerows in High Resolution Satellite Images using an Object-Oriented Method 基于面向对象方法的高分辨率卫星图像中树篱的检测

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779826

C. Vannier, L. Hubert‐Moy

引用次数: 27

Theoretical Model of SAR Altimeter over Water Surfaces 水面SAR高度计的理论模型

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779328

C. Martin-Puig, G. Ruffini, J. Márquez, D. Cotton, M. Srokosz, P. Challenor, Keith R. Raney, J. Benveniste

引用次数: 14

The High Resolution Radar Image Simulation of Target on Rough Surface 粗糙表面目标的高分辨率雷达图像仿真

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779938

Xiaoyang Wen, Chao Wang, Yanzhao Wu, Hong Zhang

引用次数: 0

Decomposition of Polarimetirc Scattering of Paddy Rice 水稻极化散射分解研究

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2008-07-07 DOI: 10.1109/IGARSS.2008.4779923

J. Susaki, Y. Kawatani

{"title":"Decomposition of Polarimetirc Scattering of Paddy Rice","authors":"J. Susaki, Y. Kawatani","doi":"10.1109/IGARSS.2008.4779923","DOIUrl":"https://doi.org/10.1109/IGARSS.2008.4779923","url":null,"abstract":"This paper reports the effects of the probability distribution of the target shape to the results of four-component decomposition. The four-component decomposition method decomposes polarimetric microwave data into four components, i.e. surface scattering, double bounce scattering, volume scattering and helix scattering. Prior to the present research, three dimensional structure of the rice was measured and modeled. The model was used to calculate the probability density function of the rice leaves at a viewpoint of arbitrary zenith and azimuth angles. With this probability density function, a covariance matrix of volume scattering for the rice was developed. This covariance matrix was embedded in the four-component decomposition, and it was applied for the polarimetric X-band scattering data of rice, measured in an anechoic radio wave chamber in Niigata Univ. during September 25 to 26, 2007. It was found that the proposed four-component decomposition produced more volume scattering and less surface scattering than the results produced by the standard four-component analysis. As a result, it is concluded that the probability distribution to the target shape should be considered.","PeriodicalId":237798,"journal":{"name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115809971","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