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
地理科学与资源研究所 [5]
采集方式
OAI收割 [5]
内容类型
期刊论文 [3]
SCI/SSCI论文 [2]
发表日期
2022 [2]
2020 [1]
2015 [1]
2014 [1]
学科主题
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Village-level poverty identification using machine learning, high-resolution images, and geospatial data
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 卷号: 107, 页码: 11
作者:
Hu, Shan
;
Ge, Yong
;
Liu, Mengxiao
;
Ren, Zhoupeng
;
Zhang, Xining
  |  
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2022/09/21
Poverty
High-resolution imagery
Geospatial data
Point-of-interest (POI)
OpenStreetMap (OSM)
Random forest
Village-level poverty identification using machine learning, high-resolution images, and geospatial data
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 卷号: 107, 页码: 11
作者:
Hu, Shan
;
Ge, Yong
;
Liu, Mengxiao
;
Ren, Zhoupeng
;
Zhang, Xining
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2022/09/21
Poverty
High-resolution imagery
Geospatial data
Point-of-interest (POI)
OpenStreetMap (OSM)
Random forest
A Location-and-Form-Based Distance for Geographical Analysis
期刊论文
OAI收割
ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS, 2020, 页码: 18
作者:
Zhou, Yu
  |  
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2021/03/16
form
location
location-and-form-based distance
OpenStreetMap
pattern analysis
A citizen data-based approach to predictive mapping of spatial variation of natural phenomena
SCI/SSCI论文
OAI收割
2015
作者:
Zhu A. X.
;
Zhang, G. M.
;
Wang, W.
;
Xiao, W.
;
Huang, Z. P.
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2015/12/09
spatial bias
Rhinopithecus bieti
volunteered geographic information
(VGI)
citizen data
location imprecision
volunteered geographic information
habitat suitability models
conservation priorities
species distributions
rhinopithecus-bieti
sampling bias
biodiversity
knowledge
maps
openstreetmap
Geometric-based approach for integrating VGI POIs and road networks
SCI/SSCI论文
OAI收割
2014
作者:
Lu F.
收藏
  |  
浏览/下载:39/0
  |  
提交时间:2014/12/24
VGI data
road network
spatial data integration
linear clustering
matching
geospatial data
openstreetmap
information
similarity
datasets