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Predictive mapping of air pollution involving sparse spatial observations
Jeremy E. Diem,
Andrew C. Comrie
Arid Lands Resources Sciences - GIDP
Community, Environment and Policy
Entomology / Insect Science - GIDP
Hydrology and Atmospheric Science
Remote Sensing / Spatial Analysis - GIDP
Statistics - GIDP
Geography, Development and Enviroment, School of
Global Change - GIDP
Research output
:
Contribution to journal
›
Article
›
peer-review
39
Scopus citations
Overview
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Medicine & Life Sciences
Ozone
95%
Air Pollution
88%
Linear Models
29%
Geographic Information Systems
16%
Spatial Analysis
16%
Forests
15%
Engineering & Materials Science
Ozone
95%
Air pollution
86%
Linear regression
25%
Geographic information systems
12%
Interpolation
10%
Availability
8%
Composite materials
7%
Earth & Environmental Sciences
atmospheric pollution
59%
ozone
59%
ground-level ozone
26%
ozone precursor
25%
metropolitan area
18%
geographic information system
16%
interpolation
16%
need
10%
chemical
9%
Chemical Compounds
Air Pollution
100%
Ozone
76%
Error
9%
Composite Material
6%