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科研机构
地理科学与资源研究... [15]
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SCI/SSCI论... [10]
期刊论文 [5]
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2021 [1]
2019 [1]
2018 [2]
2016 [5]
2015 [2]
2014 [1]
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专题:地理科学与资源研究所
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Mapping China's Electronic Power Consumption Using Points of Interest and Remote Sensing Data
期刊论文
REMOTE SENSING, 2021, 卷号: 13, 期号: 6, 页码: 17
作者:
Jin, Cheng
;
Zhang, Yili
;
Yang, Xuchao
;
Zhao, Naizhuo
;
Ouyang, Zutao
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2021/07/09
electric power consumption
points of interest
nighttime light
random forests
China
Spatiotemporal variations in cropland abandonment in the Guizhou-Guangxi karst mountain area, China
期刊论文
JOURNAL OF CLEANER PRODUCTION, 2019, 卷号: 238, 页码: 15
作者:
Han, Ze
;
Song, Wei
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2020/03/23
Abandoned cropland (ACL)
MODIS time series
Random forests classifier
Multi-level analysis
Guizhou-guangxi karst mountain area (GGKMA)
China
Spatiotemporal patterns of PM10 concentrations over China during 2005-2016: A satellite-based estimation using the random forests approach
期刊论文
ENVIRONMENTAL POLLUTION, 2018, 卷号: 242, 页码: 605-613
作者:
Chen, Gongbo
;
Wang, Yichao
;
Li, Shanshan
;
Cao, Wei
;
Ren, Hongyan
收藏
  |  
浏览/下载:43/0
  |  
提交时间:2019/05/23
PM10
AOD
Random forests
China
A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information
期刊论文
SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 卷号: 636, 页码: 52-60
作者:
Chen, Gongbo
;
Li, Shanshan
;
Knibbs, Luke D.
;
Hamm, N. A. S.
;
Cao, Wei
收藏
  |  
浏览/下载:49/0
  |  
提交时间:2019/05/23
PM2.5
Aerosol optical depth
Random forests
Machine learning
China
A Spatial Downscaling Algorithm for Satellite-Based Precipitation over the Tibetan Plateau Based on NDVI, DEM, and Land Surface Temperature
SCI/SSCI论文
2016
作者:
Jing W. L.
;
Yang, Y. P.
;
Yue, X. F.
;
Zhao, X. D.
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2017/11/09
precipitation
spatial downscaling
land surface temperature
random
forests
SVM
cover classification
random forests
machine
china
rain
variability
vegetation
networks
scales
Refining Time-Activity Classification of Human Subjects Using the Global Positioning System
SCI/SSCI论文
2016
作者:
Hu M. G.
;
Li, W.
;
Li, L. F.
;
Houston, D.
;
Wu, J.
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2017/11/09
random forests
physical-activity
air-pollution
accelerometer data
ultrafine particles
gps tracking
los-angeles
exposure
travel
location
A Comparison of Different Regression Algorithms for Downscaling Monthly Satellite-Based Precipitation over North China
SCI/SSCI论文
2016
作者:
Jing W. L.
;
Yang, Y. P.
;
Yue, X. F.
;
Zhao, X. D.
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2017/11/09
TRMM
precipitation
downscaling
land surface temperature
machine
learning
artificial neural-networks
land-surface temperature
rain-gauge
networks
vegetation dynamics
tibetan plateau
random forests
great-plains
variability
ndvi
classification
Climate envelope predictions indicate an enlarged suitable wintering distribution for Great Bustards (Otis tarda dybowskii) in China for the 21st century
SCI/SSCI论文
2016
作者:
Mi C. R.
;
Falk, H.
;
Guo, Y. M.
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2017/11/09
Climate change
Species distribution models (SDMs)
Great Bustard (Otis
tarda dybowskii)
Random Forest
China
species distribution models
habitat models
random forests
regression
impacts
area
Predicting Grassland Leaf Area Index in the Meadow Steppes of Northern China: A Comparative Study of Regression Approaches and Hybrid Geostatistical Methods
SCI/SSCI论文
2016
作者:
Li Z. W.
;
Wang, J. H.
;
Tang, H.
;
Huang, C. Q.
;
Yang, F.
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2017/11/09
leaf area index
grassland
predict
geostatistics
regression
remote
sensing
artificial neural-networks
airborne hyperspectral imagery
support
vector regression
modis-lai product
squares regression
random
forests
vegetation indexes
satellite data
spatial-distribution
aboveground biomass
Mapping Urban Areas with Integration of DMSP/OLS Nighttime Light and MODIS Data Using Machine Learning Techniques
SCI/SSCI论文
2015
作者:
Jing W. L.
;
Yang, Y. P.
;
Yue, X. F.
;
Zhao, X. D.
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2015/12/09
urban areas
DMSP-OLS
MODIS
SVM
random forests
urbanization dynamics
land-use
china cities
time-series
imagery
classification
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