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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Mapping inland water carbon content with Landsat 8 data

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Author(s):
Kutser, Tiit ; Pascual, Gema Casal ; Barbosa, Claudio ; Paavel, Birgot ; Ferreira, Renato ; Carvalho, Lino ; Toming, Kaire
Total Authors: 7
Document type: Journal article
Source: International Journal of Remote Sensing; v. 37, n. 13, p. 2950-2961, 2016.
Web of Science Citations: 8
Abstract

Landsat 8 is the first Earth observation satellite with sufficient radiometric and spatial resolution to allow global mapping of lake CDOM and DOC (coloured dissolved organic matter and dissolved organic carbon, respectively) content. Landsat 8 is a multispectral sensor however, the number of potentially usable band ratios, or more sophisticated indices, is limited. In order to test the suitability of the ratio most commonly used in lake carbon content mapping, the green-red band ratio, we carried out fieldwork in Estonian and Brazilian lakes. Several atmospheric correction methods were also tested in order to use image data where the image-to-image variability due to illumination conditions would be minimal. None of the four atmospheric correction methods tested, produced reflectance spectra that matched well with in situ measured reflectance. Nevertheless, the green-red band ratio calculated from the reflectance data was in correlation with measured CDOM values. In situ data show that there is a strong correlation between CDOM and DOC concentrations in Estonian and Brazilian lakes. Thus, mapping the global CDOM and DOC content from Landsat 8 is plausible but more data from different parts of the world are needed before decisions can be made about the accuracy of such global estimation. (AU)

FAPESP's process: 11/23594-8 - Remote sensing applications for modeling human impacts on the ecological properties of wetland and aquatic environments in the Solimões/Amazon floodplain
Grantee:Evlyn Márcia Leão de Moraes Novo
Support Opportunities: Regular Research Grants