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科研机构
地理科学与资源研... [255]
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SCI/SSCI... [255]
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Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites
SCI/SSCI论文
2016
作者:
Zhang L.
;
Mao, J. F.
;
Shi, X. Y.
;
Ricciuto, D.
;
He, H. L.
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2016/12/16
Community land model
ChinaFLUX
Eddy covariance
Carbon flux
air co2 enrichment
global vegetation models
leymus-chinensis steppe
net ecosystem exchange
earth system models
cycle feedbacks
forest
ecosystems
use efficiency
coniferous plantation
uncertainty analysis
Greening of the Earth and its drivers
SCI/SSCI论文
2016
作者:
Zhu Z. C.
;
Piao, S. L.
;
Myneni, R. B.
;
Huang, M. T.
;
Zeng, Z. Z.
收藏
  |  
浏览/下载:101/0
  |  
提交时间:2016/12/16
terrestrial carbon-cycle
photosynthetic capacity
nitrogen deposition
forests
co2
deforestation
productivity
temperature
models
trends
Dependence of trends in and sensitivity of drought over China (1961-2013) on potential evaporation model
SCI/SSCI论文
2016
作者:
Zhang J.
;
Sun, F. B.
;
Xu, J. J.
;
Chen, Y. N.
;
Sang, Y. F.
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2016/12/16
PDSI drought
potential evaporation
Penman-Monteith
california drought
climate
risk
variability
Effects of precipitation and restoration vegetation on soil erosion in a semi-arid environment in the Loess Plateau, China
SCI/SSCI论文
2016
作者:
Zhou J.
;
Fu, B. J.
;
Gao, G. Y.
;
Lu, Y. H.
;
Liu, Y.
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2016/12/16
Soil erosion
Restoration vegetation
The Loess Plateau
Structure
equation modelling
rainfall interception
storage capacity
land uses
water
runoff
ecosystem
dynamics
forest
models
resistance
Distribution characteristics and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in the Liao River drainage basin, northeast China
SCI/SSCI论文
2016
作者:
Hu J.
;
Liu, C. Q.
;
Zhang, G. P.
;
Zhang, Y. L.
;
Li, S. L.
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2017/11/09
Liao River drainage basin
PAHs
Emission sources
Diagnostic ratio
surface-water
particulate matter
bed sediments
bay
contamination
emissions
hangzhou
estuary
tianjin
taiwan
Estimating High-Resolution Urban Surface Temperature Using a Hyperspectral Thermal Mixing (HTM) Approach
SCI/SSCI论文
2016
作者:
Liu K.
;
Su, H. B.
;
Li, X. K.
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2017/11/09
High-resolution land surface temperature (LST)
hyperspectral remote
sensing
multiple endmember spectral mixture analysis (SMA) (MESMA)
urban application
spectral mixture analysis
sensible heat-flux
impervious surface
endmember selection
analysis mesma
imagery
aster
area
disaggregation
separation
Mineral resources prospecting by synthetic application of TM/ETM plus , Quickbird and Hyperion data in the Hatu area, West Junggar, Xinjiang, China
SCI/SSCI论文
2016
作者:
Liu L.
;
Zhou, J.
;
Jiang, D.
;
Zhuang, D. F.
;
Mansaray, L. R.
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2017/11/09
hydrothermally altered rocks
spaceborne thermal emission
reflection
radiometer aster
remote-sensing data
eo-1 hyperion
images
satellite
region
etm+
iran
Niche modeling predictions of the potential distribution of Marmota himalayana, the host animal of plague in Yushu County of Qinghai
SCI/SSCI论文
2016
作者:
Lu L.
;
Ren, Z. P.
;
Yue, Y. J.
;
Yu, X. T.
;
Lu, S.
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2017/11/09
Marmota himalayana
Niche modeling
LST
GDEM
NDVI
Soil type
ecological niche
china
mongolia
risk
The Effect of Vegetation on the Remotely Sensed Soil Thermal Inertia and a Two-Source Normalized Soil Thermal Inertia Model for Vegetated Surfaces
SCI/SSCI论文
2016
作者:
Zhang R. H.
;
Tian, J.
;
Mi, S. J.
;
Su, H. B.
;
He, H. L.
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2017/11/09
Remote sensing
soil moisture
soil thermal inertia (STI)
vegetated
surface
southern great-plains
evapotranspiration estimation
temperature
observations
canopy temperature
triangle method
heat-flux
moisture
index
evaporation
retrieval
Wavelet-Based Hydrological Time Series Forecasting
SCI/SSCI论文
2016
作者:
Sang Y. F.
;
Singh, V. P.
;
Sun, F. B.
;
Chen, Y. N.
;
Liu, Y.
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2017/11/09
Hydrological forecasting
Artificial intelligence modeling
Wavelet
analysis
Temporal scale
Hydrological time series analysis
Statistical
significance
neural-network models
practical guide
streamflow
trends
rivers
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