PERFORMANCE ANALYSIS OF THE C2RCC PROCESSOR IN ESTIMATE THE WATER QUALITY PARAMETERS IN INLAND WATERS USING OLCl/SENTINEL-3A IMAGES

Autor(es)

Alcantara, Enner ; de Andrade, Caroline Pilfer ; Gomes, Ana Carolina ; Bernardo, Nariane ; Carmo, Alisson Fernando ; Rodrigues, Thanan ; Watanabe, Fernanda ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; v. N/A, p. 4-pg., 2018-01-01.

Resumo

Remote sensing can be a powerful tool for long-teen spatial and temporal water quality monitoring if proper sets of algorithms are available. To estimate optically significant substances (OSS) by satellite images the water-leaving reflectance (pw) must be accurately estimated because it is directly related to the inherent optical properties (IOPs). For an accurate pw an effective atmospheric correction method must be used to remote the contribution of the atmospheric path radiance. The C2RCC processor has a set of algorithms capable of reduce the atmospheric path radiance, estimate the IOPs and then the OSS concentrations. But, the C2RCC was only tested using OL Cl/Sentine1-3 images for coastal areas, therefore, is of huge importance to know about their accuracy for inland waters. The results showed that the pw (with errors from 26.57 to 97.48%), IOPs (with errors from 39.77 to 99.90%) and OSS concentrations (with errors from 49.29 to 148.40%) estimated by C2RCC have no correlation with in situ data. For a long-teen use of OL Cl/Sentine1-3 images researchers must try to use another atmospheric correction and IOPs estimation methods when studying inland waters. (AU)

• Processo FAPESP: 15/21586-9 - Re-parametrização do algoritmo quase-analítico (QAA) para estimativa das propriedades ópticas inerentes nos reservatórios do Rio Tietê
• Beneficiário: Enner Herenio de Alcântara
• Modalidade de apoio: Auxílio à Pesquisa - Regular