中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研... [175]
遥感与数字地球研究... [45]
成都山地灾害与环境... [32]
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A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface
期刊论文
OAI收割
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 卷号: 62, 页码: 18
作者:
He, Min
;
Wen, Jianguang
;
Wu, Shengbiao
;
Meng, Lei
;
Lin, Xingwen
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/03/01
Forestry
Reflectivity
Indexes
Surface topography
Biological system modeling
Atmospheric modeling
Vegetation mapping
Bidirectional reflectance
effective leaf area index (LAI)
geometrical optical model (GOM)
remote sensing
radiative transfer (RT)
scattering by arbitrarily inclined leaves (SAIL)
topography
Future variation of land surface temperature in the Yangtze River Basin based on CMIP6 model
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 卷号: 16, 期号: 1, 页码: 2776-2796
作者:
Liu, Jinlian
;
Tang, Hanya
;
Yan, Fengqin
;
Liu, Shiwei
;
Tang, Xuguang
  |  
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2023/09/07
Temporal and spatial changes
Delta downscaling
Random forest
Global warming
>
Identifying Outliers of the MODIS Leaf Area Index Data by Including Temporal Patterns in Post-Processing
期刊论文
OAI收割
REMOTE SENSING, 2023, 卷号: 15, 期号: 20, 页码: 5042
作者:
Ma, Baibing
;
Xu, Ming
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2023/12/04
MODIS LAI
outliers
temporal patterns
inter-quartile range
post-processing
基于多源遥感指数监测山区植被动态及其驱动因子的不确定性分析——以尼泊尔地区为例
期刊论文
OAI收割
环境生态学, 2023, 卷号: 5, 期号: 08, 页码: 15-24
作者:
刘子源
;
周德成
;
郝璐
;
樊江文
;
张良侠
  |  
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2023/10/08
遥感
山区
植被动态
不确定性
尼泊尔
Evaluation of perennial reference evapotranspiration (ET o ) over a typical dryland using satellite images: A case study from Uzbekistan
期刊论文
OAI收割
ECOHYDROLOGY & HYDROBIOLOGY, 2023, 卷号: 23, 期号: 3, 页码: 484-497
作者:
Makhmudova, Umida
;
Khasanov, Sayidjakhon
;
Karimov, Akmal
;
Abdurakhmonov, Sarvar
  |  
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2023/10/09
Air temperature
Solar irradiance
Leaf area index
Land cover change
Evapotranspiration
Agricultural land
Hargreaves-Samani
NDVI
SAVI
Climate change
Karakalpakstan
Mapping bamboo forest and expansion intensity in China by coupling vegetation phenology and C-band SAR with Sentinel-1 and Sentinel-2 images
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2023, 卷号: 121, 页码: 16
作者:
Li, Saibo
;
He, Shaoyang
;
Yue, Tianxiang
;
Du, Zhengping
;
Zhao, Na
  |  
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2024/03/01
Bamboo forest
Expansion intensity
Vegetation phenology
SAR
Google Earth Engine
How is the performance of satellite-based product suites in monitoring long-term dynamics of vegetation photosynthesis over global mountainous areas?
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2023, 卷号: 119, 页码: 14
作者:
Xie, Xinyao
;
Li, Ainong
  |  
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2023/10/09
Terrestrial photosynthesis
Global mountainous areas
Moderate -resolution Imaging
Spectroradiometer (MODIS)
Global LAnd Surface Satellite (GLASS)
Global Inventory Modeling and Mapping
Studies (GIMMS)
Evaluation of the High-Resolution MuSyQ LAI Product over Heterogeneous Land Surfaces
期刊论文
OAI收割
REMOTE SENSING, 2023, 卷号: 15, 期号: 5, 页码: 1238
作者:
Li, Dandan
;
Huang, Yajun
;
Xiao, Yao
;
He, Min
;
Wen, Jianguang
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/01/04
leaf area index (LAI)
MuSyQ LAI product
GF-1
validation
UAV image
Retrieving global leaf chlorophyll content from MERIS data using a neural network method
期刊论文
OAI收割
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2022, 卷号: 192, 页码: 66-82
作者:
Xu, Mingzhu
;
Liu, Ronggao
;
Chen, Jing M.
;
Shang, Rong
;
Liu, Yang
  |  
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2022/09/26
Global mapping
Machine learning
Leaf pigment
Leaf biochemical parameter
Phenology
Estimation of Vegetation Leaf-Area-Index Dynamics from Multiple Satellite Products through Deep-Learning Method
期刊论文
OAI收割
REMOTE SENSING, 2022, 卷号: 14, 期号: 19, 页码: 17
作者:
Liu, Tian
;
Jin, Huaan
;
Li, Ainong
;
Fang, Hongliang
;
Wei, Dandan
  |  
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2022/11/09
time series
leaf-area index
long short-term memory
deep learning