%0 Conference Proceedings
%4 sid.inpe.br/marte2/2023/04.19.19.25
%2 sid.inpe.br/marte2/2023/04.19.19.25.52
%@isbn 978-65-89159-04-9
%T Estimation of annual trophic state index distributions of a tropical reservoir using Landsat imagery time series
%D 2023
%A Wanderley, Raianny Leite do Nascimento,
%A Paulino, Rejane de Souza,
%A Maciel, Daniel de Andrade,
%A Barbosa, Cláudio Clemente Faria,
%A Novo, Evlyn Márcia Leão de Moraes,
%A Domingues, Leonardo Moreno,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade de São Paulo (USP)
%@electronicmailaddress raianny.leite.nw@gmail.com
%@electronicmailaddress rejane.paulino@inpe.br
%@electronicmailaddress daniel.maciel@inpe.br
%@electronicmailaddress claudio.barbosa@inpe.br
%@electronicmailaddress evlyn.novo@inpe
%@electronicmailaddress leomdomingues@gmail.com
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%E Sanches, Ieda DelArco,
%B Simpósio Brasileiro de Sensoriamento Remoto, 20 (SBSR)
%C Florianópolis
%8 02-05 abril 2023
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P e155818
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K Water quality, Inland waters, Landsat-8, Modelling, Random Forest.
%X The eutrophication of reservoirs significantly impacts human health and environmental security. However, in situ water quality monitoring can be expensive once it includes equipment and human resources. An effective proxy for water quality is the Trophic State Index (TSI) Chlorophyll-a (chl-a) based. Remote sensing techniques have helped the authorities and scientific community to map TSI worldwide. Then, this study aimed to develop a remote sensing-based TSI algorithm and estimate the TSI spatiotemporal distribution in a reservoir in Brazil. The chl-a concentration was used as a proxy to TSI and classified into three classes: OligoMeso, EutroSuper, and Hyper. The calibrated algorithm was applied to the Jaguari-Jacareí reservoir to obtain TSI between 2013 and 2022. Classification results achieved an overall accuracy of 75% for a validation dataset. Although the general pattern of the TSI in the reservoir is majority OligoMeso, the results indicate two patterns established according to dry and wet seasons.
%9 Sensoriamento remoto de águas interiores
%@language en
%3 155818.pdf