Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modelling on large scales

Renata Barão Rossoni
Leonardo Laipelt
Rodrigo Cauduro Dias De Paiva
Rodrigo Cauduro Dias De Paiva
R. C. D. Paiva
Fernando Mainardi Fan
Publication typeJournal Article
Publication date2024-11-01
scimago Q1
wos Q2
SJR0.993
CiteScore7.9
Impact factor4.5
ISSN23529385
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Rossoni R. B. et al. Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modelling on large scales // Remote Sensing Applications: Society and Environment. 2024. Vol. 36. p. 101352.
GOST all authors (up to 50) Copy
Rossoni R. B., Laipelt L., De Paiva R. C. D., Paiva R. C. D. D., Paiva R. C. D., Fan F. M. Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modelling on large scales // Remote Sensing Applications: Society and Environment. 2024. Vol. 36. p. 101352.
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TY - JOUR
DO - 10.1016/j.rsase.2024.101352
UR - https://linkinghub.elsevier.com/retrieve/pii/S2352938524002167
TI - Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modelling on large scales
T2 - Remote Sensing Applications: Society and Environment
AU - Rossoni, Renata Barão
AU - Laipelt, Leonardo
AU - De Paiva, Rodrigo Cauduro Dias
AU - Paiva, Rodrigo Cauduro Dias De
AU - Paiva, R. C. D.
AU - Fan, Fernando Mainardi
PY - 2024
DA - 2024/11/01
PB - Elsevier
SP - 101352
VL - 36
SN - 2352-9385
ER -
BibTex
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BibTex (up to 50 authors) Copy
@article{2024_Rossoni,
author = {Renata Barão Rossoni and Leonardo Laipelt and Rodrigo Cauduro Dias De Paiva and Rodrigo Cauduro Dias De Paiva and R. C. D. Paiva and Fernando Mainardi Fan},
title = {Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modelling on large scales},
journal = {Remote Sensing Applications: Society and Environment},
year = {2024},
volume = {36},
publisher = {Elsevier},
month = {nov},
url = {https://linkinghub.elsevier.com/retrieve/pii/S2352938524002167},
pages = {101352},
doi = {10.1016/j.rsase.2024.101352}
}