Giancarlo Brugnara Chelotti, Jean-Michel Martinez, H. Roig, Diogo Olivietti
{"title":"Space-Temporal analysis of suspended sediment in low concentration reservoir by remote sensing","authors":"Giancarlo Brugnara Chelotti, Jean-Michel Martinez, H. Roig, Diogo Olivietti","doi":"10.1590/2318-0331.241920180061","DOIUrl":null,"url":null,"abstract":"ABSTRACT The study of small reservoirs with low suspended sediment concentration (CSS) is still a challenge for remote sensing. In this work we estimate CSS from the optical properties of water and orbital imagery. Campaigns were carried out at selected dates according to the calendar of sensor passages, rainfall seasonality and hydrograph of the reservoir for the collection of surface water samples and field spectroradiometry. The calibration between CSS and spectral behavior generated CSS estimation models from MODIS and Landsat 8 data, allowing investigation of their temporal and spatial behavior. The MODIS model generated a time series of CSS from 2000 to 2017, presenting R2 = 0.8105 and RMSE% = 39.91%. The Landsat 8 model allowed the spatial analysis of CSS, with R2 = 0.8352 and RMSE% = 15.12%. The combination of the proposed models allowed the temporal and spatial analysis of the CSS and its relationships with the rainfall regime and the quota variation of the Descoberto reservoir (DF). The results showed that the use of orbital data complements the CSS information obtained by the traditional methods of collecting and analyzing water quality in low CSS reservoirs.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/2318-0331.241920180061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
ABSTRACT The study of small reservoirs with low suspended sediment concentration (CSS) is still a challenge for remote sensing. In this work we estimate CSS from the optical properties of water and orbital imagery. Campaigns were carried out at selected dates according to the calendar of sensor passages, rainfall seasonality and hydrograph of the reservoir for the collection of surface water samples and field spectroradiometry. The calibration between CSS and spectral behavior generated CSS estimation models from MODIS and Landsat 8 data, allowing investigation of their temporal and spatial behavior. The MODIS model generated a time series of CSS from 2000 to 2017, presenting R2 = 0.8105 and RMSE% = 39.91%. The Landsat 8 model allowed the spatial analysis of CSS, with R2 = 0.8352 and RMSE% = 15.12%. The combination of the proposed models allowed the temporal and spatial analysis of the CSS and its relationships with the rainfall regime and the quota variation of the Descoberto reservoir (DF). The results showed that the use of orbital data complements the CSS information obtained by the traditional methods of collecting and analyzing water quality in low CSS reservoirs.