%0 Journal Article %1 Bernardo2017 %A Bernardo, Nariane Marselhe Ribeiro %A de Alcântara, Enner Herenio %D 2017 %J Modeling Earth Systems and Environment %K imported sertie %N 1 %P 19 %R 10.1007/s40808-017-0285-0 %T Comparing proximal remote sensing and orbital images to estimate the total suspended matter in inland water %V 3 %X The main purpose of this work was to improve the remote sensing reflectance (R rs ) applications to estimate the total suspended matter (TSM) concentrations, since several studies using R rs retrieved from atmospherically corrected images did not match with in situ radiometric measurements. The goal was achieved by comparing two R rs datasets: one from atmospherically corrected image from Operational Land Imager (OLI)/ Landsat-8 and the R rs surface created by non-deterministic statistical approach. The R rs used to create the surface was computed by using samples gathered out in situ on 13--16 October 2014, and the OLI image used was taken in the first day of fieldwork. A reference surface from in situ TSM concentrations was also created to compare the estimates from both datasets (from statistical approach and image atmospherically corrected). The TSM estimates were made using empirical model, and the results demonstrate that non-statistical methods provide lowest errors to estimate the TSM concentration if compared to atmospheric corrected images.

@article{Bernardo2017, abstract = {The main purpose of this work was to improve the remote sensing reflectance (R rs ) applications to estimate the total suspended matter (TSM) concentrations, since several studies using R rs retrieved from atmospherically corrected images did not match with in situ radiometric measurements. The goal was achieved by comparing two R rs datasets: one from atmospherically corrected image from Operational Land Imager (OLI)/ Landsat-8 and the R rs surface created by non-deterministic statistical approach. The R rs used to create the surface was computed by using samples gathered out in situ on 13--16 October 2014, and the OLI image used was taken in the first day of fieldwork. A reference surface from in situ TSM concentrations was also created to compare the estimates from both datasets (from statistical approach and image atmospherically corrected). The TSM estimates were made using empirical model, and the results demonstrate that non-statistical methods provide lowest errors to estimate the TSM concentration if compared to atmospheric corrected images.}, added-at = {2017-07-31T17:28:59.000+0200}, author = {Bernardo, Nariane Marselhe Ribeiro and de Alcântara, Enner Herenio}, biburl = {https://www.bibsonomy.org/bibtex/26b6a9c858c0b42cffbfae93a87665242/alisondocarmo}, day = 23, doi = {10.1007/s40808-017-0285-0}, interhash = {56f81eb24ebdabdf867a259ed1e4fc6a}, intrahash = {6b6a9c858c0b42cffbfae93a87665242}, issn = {2363-6211}, journal = {Modeling Earth Systems and Environment}, keywords = {imported sertie}, month = feb, number = 1, pages = 19, timestamp = {2017-07-31T17:28:59.000+0200}, title = {Comparing proximal remote sensing and orbital images to estimate the total suspended matter in inland water}, volume = 3, year = 2017 }