Skip header navigation
×

Conference Paper

Data Fusion of Remote-sensing and In-lake chlorophyll a Data Using Statistical Downscaling

Citation
Wilkie CJ, Scott EM, Miller C, Tyler AN, Hunter PD & Spyrakos E (2015) Data Fusion of Remote-sensing and In-lake chlorophyll a Data Using Statistical Downscaling. Spatial Statistics conference 2015, Avignon, France, 09.06.2015-12.06.2015. Procedia Environmental Sciences, 26, pp. 123-126. https://doi.org/10.1016/j.proenv.2015.05.014

Abstract
Chlorophyll a is a green pigment, used as an indirect measure of lake water quality. Its strong absorption of blue and red light allows for quantification through satellite images, providing better spatial coverage than traditional in-lake samples. However, grid-cell scale imagery must be calibrated spatially using in-lake point samples, presenting a change-of-support problem. This paper presents a method of statistical downscaling, namely a Bayesian spatially-varying coefficient regression, which assimilates remotely-sensed and in-lake data, resulting in a fully calibrated spatial map of chlorophyll a with associated uncertainty measures. The model is applied to a case study dataset from Lake Balaton, Hungary.

Keywords
statistical downscaling; Bayesian spatially-varying coefficients; chlorophyll a; spatial calibration; MCMC;

Journal
Procedia Environmental Sciences: Volume 26

StatusPublished
Author(s)Wilkie, Craig J; Scott, E Marian; Miller, Claire; Tyler, Andrew N; Hunter, Peter D; Spyrakos, Evangelos
FundersNatural Environment Research Council
Publication date31/12/2015
Publication date online05/06/2015
Date accepted by journal15/12/2015
URLhttp://hdl.handle.net/1893/30513
PublisherElsevier BV
ISSN1878-0296
eISSN1878-0296
ConferenceSpatial Statistics conference 2015
Conference locationAvignon, France
Dates
Scroll back to the top