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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究... [13]
云南天文台 [1]
合肥物质科学研究院 [1]
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OAI收割 [15]
内容类型
期刊论文 [14]
专利 [1]
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2020 [1]
2019 [7]
2017 [6]
2014 [1]
学科主题
天文学 [1]
天文学::恒星与银河... [1]
天文学::恒星与银河... [1]
天文学::恒星与银河... [1]
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Asteroseismic Analyses of Slowly Pulsating B Star KIC 8324482: Ultraweak Element Mixing beyond the Central Convective Core
期刊论文
OAI收割
ASTROPHYSICAL JOURNAL, 2020, 卷号: 899, 期号: 1, 页码: 17
作者:
Wu T(吴涛)
;
Li Y(李焱)
;
Deng, Zhen-min
;
Lin GF(林桂芳)
;
Song, Han-feng
  |  
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2020/09/28
Asteroseismology
Stellar interiors
Stellar oscillations
Stellar structures
Fundamental parameters of stars
Stellar rotation
Stellar properties
B stars
Temporal and Spatial Change Monitoring of Drought Grade Based on ERA5 Analysis Data and BFAST Method in the Belt and Road Area during 1989-2017
期刊论文
OAI收割
ADVANCES IN METEOROLOGY, 2019, 卷号: 2019, 页码: 10
作者:
Xue, Changdi
;
Wu, Hua
;
Jiang, Xiaoguang
  |  
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2020/05/19
Temporal and Spatial Change Monitoring of Drought Grade Based on ERA5 Analysis Data and BFAST Method in the Belt and Road Area during 1989-2017
期刊论文
OAI收割
ADVANCES IN METEOROLOGY, 2019, 卷号: 2019, 页码: 10
作者:
Xue, Changdi
;
Wu, Hua
;
Jiang, Xiaoguang
  |  
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2020/05/19
Retrieving Atmospheric and Land Surface Parameters From At-Sensor Thermal Infrared Hyperspectral Data With Artificial Neural Network
期刊论文
OAI收割
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 卷号: 12, 期号: 7, 页码: 2409-2416
作者:
  |  
收藏
  |  
浏览/下载:69/0
  |  
提交时间:2020/03/23
Artificial neural network (ANN)
atmospheric transmittance
hyperspectral thermal infrared (TIR)
land surface emissivity (LSE)
land surface temperature (LST)
Retrieving Atmospheric and Land Surface Parameters From At-Sensor Thermal Infrared Hyperspectral Data With Artificial Neural Network
期刊论文
OAI收割
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 卷号: 12, 期号: 7, 页码: 2409-2416
作者:
Chen, Mengshuo
;
Ni, Li
;
Jiang, Xiaoguang
;
Wu, Hua
  |  
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2020/03/23
Artificial neural network (ANN)
atmospheric transmittance
hyperspectral thermal infrared (TIR)
land surface emissivity (LSE)
land surface temperature (LST)
Fast and accurate measurement of spectral emissivity with a portable field infrared spectrometer: ancillary equipment and methods
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 卷号: 40, 期号: 5-6, 页码: 1736-1749
作者:
Zhang, YuZe
;
Ni, Li
;
Wu, Hua
;
Jiang, XiaoGuang
;
Han, Ying
  |  
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2019/05/22
Fast and accurate measurement of spectral emissivity with a portable field infrared spectrometer: ancillary equipment and methods
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 卷号: 40, 期号: 5-6, 页码: 1736-1749
作者:
Zhang, YuZe
;
Ni, Li
;
Wu, Hua
;
Jiang, XiaoGuang
;
Han, Ying
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2019/05/22
Fast and accurate measurement of spectral emissivity with a portable field infrared spectrometer: ancillary equipment and methods
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 卷号: 40, 期号: 5-6, 页码: 1736-1749
作者:
Zhang, YuZe
;
Ni, Li
;
Wu, Hua
;
Jiang, XiaoGuang
;
Han, Ying
  |  
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2019/05/22
Land Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform
期刊论文
OAI收割
REMOTE SENSING, 2017, 卷号: 9, 期号: 5, 页码: 16
作者:
Zhang, Yu-Ze
;
Wu, Hua
;
Jiang, Xiao-Guang
;
Jiang, Ya-Zhen
;
Liu, Zhao-Xia
  |  
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2019/09/25
temperature and emissivity separation
hyperspectral
field-measured data
wavelet transform
Land Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform
期刊论文
OAI收割
REMOTE SENSING, 2017, 卷号: 9, 期号: 5, 页码: 16
作者:
Zhang, Yu-Ze
;
Wu, Hua
;
Jiang, Xiao-Guang
;
Jiang, Ya-Zhen
;
Liu, Zhao-Xia
  |  
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2019/09/25
temperature and emissivity separation
hyperspectral
field-measured data
wavelet transform