Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1185892
Title: Integration of the SAR and optical sensors of the Sentinel constellation for land use classification in Lagoinha (SP).
Authors: NASCIMENTO, A. C. V. do
GAVA, G. J. de C.
DE MARIA, I. C.
ROMANI, L. A. S.
MORAES, J. F. L. de
Affiliation: ANA CAROLINA VIDAL DO NASCIMENTO; GLAUBER JOSÉ DE CASTRO GAVA, INSTITUTO AGRONÔMICO DE CAMPINAS; ISABELLA CLERICI DE MARIA, INSTITUTO AGRONÔMICO DE CAMPINAS; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; JENER FERNANDO LEITE DE MORAES, INSTITUTO AGRONÔMICO DE CAMPINAS.
Date Issued: 2025
Citation: In: WORKSHOP CIENTÍFICO DO CENTRO DE CIÊNCIA PARA O DESENVOLVIMENTO EM AGRICULTURA DIGITAL – SEMEAR DIGITAL, 2., 2025, Campinas. Anais [...]. Piracicaba: ESALQ/USP, 2025. p. 26-32.
Description: Information on land use and coverage is necessary to assist in the management process and assertive decision-making. Thus, the present study aimed to evaluate the fusion of Sentinel-1 (S1) and Sentinel-2 (S2) data in the mapping of land use and coverage of the municipality of Lagoinha (SP) using the Random Forest method. Three scenarios were tested for classification: data from (S1), (S2) and fusion of (S2+S1). To evaluate the accuracy of the classification, high-resolution images from Google Earth and S2 software were used. The overall accuracy of the classification from the combination of S2+S1 data was 94%, and the Kappa index was equal to 0.9. For the isolated images of S2 and S1, overall accuracies of 80% and 50% and Kappas index of 0.71 and 0.50 were obtained, respectively. The fusion of S1+S2 data showed high accuracy in mapping.
Thesagro: Sensoriamento Remoto
Radar
Uso da Terra
NAL Thesaurus: Remote sensing
Sensors (equipment)
Land use
Keywords: Fusão de sensores
Aprendizado de máquina
Machine learning
ISBN: 978-85-86481-94-9
Notes: Na publicação: Luciana Alvim Romani. Organização: Silvia Maria Fonseca Silveira Massruhá, Durval Dourado Neto, Luciana Alvim Santos Romani, Jayme Garcia Arnal Barbedo, Édson Luis Bolfe, Ivan Bergier, Maria Angelica de Andrade Leite, Vitor Del Alamo Guarda, Catarina Barbosa Careta.
Type of Material: Artigo em anais e proceedings
Access: openAccess
Appears in Collections:Artigo em anais de congresso (CNPTIA)

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