Publications

Puttaswamy, Sweta Jinnagara; Nguyen, Hai M.; Braverman, Amy; Hu, Xuefei; Liu, Yang (2014). Statistical data fusion of multi-sensor AOD over the Continental United States. GEOCARTO INTERNATIONAL, 29(1), 48-64.

Abstract
This article illustrates two techniques for merging daily aerosol optical depth (AOD) measurements from satellite and ground-based data sources to achieve optimal data quality and spatial coverage. The first technique is a traditional Universal Kriging (UK) approach employed to predict AOD from multi-sensor aerosol products that are aggregated on a reference grid with AERONET as ground truth. The second technique is spatial statistical data fusion (SSDF); a method designed for massive satellite data interpolation. Traditional kriging has computational complexity O(N-3), making it impractical for large datasets. Our version of UK accommodates massive data inputs by performing kriging locally, while SSDF accommodates massive data inputs by modelling their covariance structure with a low-rank linear model. In this study, we use aerosol data products from two satellite instruments: the moderate resolution imaging spectrometer and the geostationary operational environmental satellite, covering the Continental United States.

DOI:
10.1080/10106049.2013.827750

ISSN:
1010-6049; 1752-0762