机构

• 地理科学与资源研究所 [2]
• 遥感与数字地球研究所 [2]
• 中国科学院大学 [1]

采集方式

• OAI收割 [4]
• iSwitch采集 [1]

内容类型

• SCI/SSCI论文 [2]
• 会议论文 [2]
• 期刊论文 [1]

发表日期

• 2011 [1]
• 2010 [3]
• 2008 [1]

学科主题

筛选

浏览/检索结果: 共5条，第1-5条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Flower Species Identification and Coverage Estimation Based on Hyperspectral Remote Sensing Data in Hulunbeier Grassland SCI/SSCI论文  OAI收割 2011 Gai Y. Y.; Fan W. J.; Xu X. R.; Yan B. Y.; Wang H. J.; Liu Y. 收藏  |  浏览/下载：28/0  |  提交时间：2012/06/08 Hulunbeier grassland  Species diversity  Florescense  Spectral  characteristics extraction  Mixed spectra unmixing   Hyperspectral remote sensing monitoring of grassland degradation 期刊论文  iSwitch采集 Spectroscopy and spectral analysis, 2010, 卷号: 30, 期号: 10, 页码: 2734-2738 作者:  Wang Huan-jiong;  Fan Wen-jie;  Cui Yao-kui;  Zhou Lei;  Yan Bin-yan 收藏  |  浏览/下载：38/0  |  提交时间：2019/05/10 Hyperspectral  Grassland degradation  Spectral characteristics  Mixed spectra unmixing   The Land Cover Mapping with Airborne Hyperspectral Remote Sensing Imagery in Yanhe River Valley 会议论文  OAI收割 2010 18th International Conference on Geoinformatics, New York Zhang, Lianpeng; Liu, Qinhuo; Lin, Hui; Sun, Huasheng; Chen, Shicheng 收藏  |  浏览/下载：26/0  |  提交时间：2014/12/07 Land cover  Projection pursuit  Spectra unmixing  PROJECTION PURSUIT ALGORITHM   Hyperspectral Remote Sensing Monitoring of Grassland Degradation SCI/SSCI论文  OAI收割 2010 Wang H. J.; Fan W. J.; Cui Y. K.; Zhou L.; Yan B. Y.; Wu D. H.; Xu X. R. 收藏  |  浏览/下载：29/0  |  提交时间：2012/06/08 Hyperspectral  Grassland degradation  Spectral characteristics  Mixed  spectra unmixing  vegetation  xilinhot  china   Remote chlorophyll-a retrieval in eutrophic inland waters by concentration classification Taihu Lake case study 会议论文  OAI收割 International Conference on Earth Observation Data Processing and Analysis, ICEODPA,, Wuhan, China, December 28, 2008 - December 30,2008 Du, Cong; Wang, Shixin; Zhou, Yi; Yan, Fuli 收藏  |  浏览/下载：32/0  |  提交时间：2014/12/07 In order to improve the precision of phytoplankton chlorophyll-a (chla) concentration retrieval  this study classified the data into two groups (the high and the low) by chla concentration with the threshold of 50gA&bullL-1. And then build the statistical models for each group. Particularly  a modifying factor OSS/TSS was used to unmixing the spectra in the low model to improve the low relationship between spectral reflectance and chla concentrations. As a result  the concentration classification model allowed estimation of chla with a root mean square error (RMSE) of 21.12gA&bullL-1 and the determination coefficient (R2) was 0.92  comparing with RMSE of chla estimation was 35.72gA&bullL-1 and R2=0.72 in the traditional model. It shows that concentration classification is a helpful method for accurate remote chla retrieval in eutrophic inland waters. 2008 SPIE.