Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data

Jacob J Oleson; Naresh Kumar; Brian J Smith

doi:10.1007/s10651-012-0221-4

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Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data

Journal article

Open access

Peer reviewed

Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data

Jacob J Oleson, Naresh Kumar and Brian J Smith

Environmental and ecological statistics, Vol.20(2), pp.297-314

06/01/2013

DOI: 10.1007/s10651-012-0221-4

PMCID: PMC3901316

PMID: 24470786

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https://www.ncbi.nlm.nih.gov/pmc/articles/3901316View

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Abstract

Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size, coupled with realities that come with observational data, make it difficult for all of these assumptions to be met. In particular, air quality data are very sparse across geographic space and time, due to a limited air pollution monitoring network. These “missing” values make it diffcult to incorporate most dimension reduction techniques developed for high-dimensional spatiotemporal data. This article examines aerosol optical depth (AOD), an indirect measure of radiative forcing, and air quality. The spatiotemporal distribution of AOD can be influenced by both natural (e.g., meteorological conditions) and anthropogenic factors (e.g., emission from industries and transport). After accounting for natural factors influencing AOD, we examine the spatiotemporal relationship in the remaining human influenced portion of AOD. The presented data cover a portion of India surrounding New Delhi from 2000 – 2006. The proposed method is demonstrated showing how it can handle the large spatiotemporal structure containing so much missing data for both meteorologic conditions and AOD over time and space.

temporal correlation

spatial correlation

autoregressive

AOD

Bayesian

air quality

Details

Title: Subtitle: Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data
Creators: Jacob J Oleson - Department of Geography, The University of Iowa, Iowa City, IA, USA
Naresh Kumar - Department of Geography, The University of Iowa, Iowa City, IA, USA
Brian J Smith - Department of Geography, The University of Iowa, Iowa City, IA, USA
Resource Type: Journal article
Publication Details: Environmental and ecological statistics, Vol.20(2), pp.297-314
DOI: 10.1007/s10651-012-0221-4
PMID: 24470786
PMCID: PMC3901316
NLM abbreviation: Environ Ecol Stat
ISSN: 1352-8505
eISSN: 1573-3009
Grant note: R21 ES014004 || ES / National Institute of Environmental Health Sciences : NIEHS
Language: English
Date published: 06/01/2013
Academic Unit: Biostatistics; Holden Comprehensive Cancer Center
Record Identifier: 9983997318102771

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