@InProceedings{RodriguesKörtQuei:2020:CiHoTr,
author = "Rodrigues, Marcos Lima and K{\"o}rting, Thales Sehn and Queiroz,
Gilberto Ribeiro de",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Circular Hough Transform and Balanced Random Forest to Detect
Center Pivots",
booktitle = "Anais...",
year = "2020",
editor = "Carneiro, Tiago Garcia de Senna (UFOP) and Felgueiras, Carlos
Alberto (INPE)",
pages = "106--115",
organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 21. (GEOINFO)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Water management is a field related to the increased mechanization
of agriculture, mainly through center pivot irrigation systems,
therefore it is important to identify and quantify these systems.
Currently, with 6.95 million hectares, Brazil is among the 10
largest countries in irrigation areas in the world. In this study,
a combined Computer Vision and Machine Learning ap- proach is
proposed for the identification of center pivots in remote sensing
im- ages. The methodology is based on Circular Hough Transform
(CHT) to target detection and Balanced Random Forest (BRF)
classifier using vegetation indices NDVI and SAVI generated from
Landsat 8 and CBERS 4 images, being able to detect up to 90.48% of
center pivots mapped by the Brazilian National Water Agency
(ANA).",
conference-location = "On-line",
conference-year = "30 nov. a 03 dez. 2020",
issn = "2179-4847",
language = "en",
ibi = "8JMKD3MGPDW34P/43PLCP5",
url = "http://urlib.net/ibi/8JMKD3MGPDW34P/43PLCP5",
targetfile = "p10.pdf",
type = "Geoinforma{\c{c}}{\~a}o",
urlaccessdate = "11 maio 2024"
}