The role of Landsat and Sentinel-2 data harmonization in monitoring agricultural dynamics on smallholder farming regions.

Vista sencilla de ítem
dc.contributorTAYA CRISTO PARREIRAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; EDSON LUIS BOLFE, CNPTIA.
dc.creatorPARREIRAS, T. C.
dc.creatorBOLFE, E. L.
dc.date2026-03-31T13:52:34Z
dc.date2026-03-31T13:52:34Z
dc.date2026-03-31
dc.date2025
dc.date.accessioned2026-07-07T04:18:43Z
dc.descriptionThis study explores the potential of Harmonized Landsat Sentinel-2 (HLS) data for detailed agricultural mapping in diversified farming regions of São Paulo, Brazil. Focusing on Casa Branca and Caconde, the research integrates multitemporal HLS imagery (2021–2024) to perform crop classifications at multiple levels. In Caconde, high-resolution temporal data (2–4 day revisit) enabled strong performance in distinguishing perennial crops, particularly coffee, which achieved an average sensitivity of 0.97 and specificity of 0.91. Phenological stages of coffee, such as Producing and Newly Planted, were reliably mapped, while Stumping and Skeletoning showed lower consistency. In Casa Branca, six field campaigns supported the construction of a robust training dataset across up to nine growing seasons. Integrating Landsat 9 into the HLS collection more than doubled temporal resolution over the study period, enhancing model accuracy and phenological tracking. Future work will focus on model transferability across time and space and on evaluating the relative performance of HLS versus individual Landsat and Sentinel data.
dc.descriptionOrganização: 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.
dc.identifierIn: WORKSHOP CIENTÍFICO DO CENTRO DE CIÊNCIA PARA O DESENVOLVIMENTO EM AGRICULTURA DIGITAL – SEMEAR DIGITAL, 2., 2025, Campinas. Anais [...]. Piracicaba: ESALQ/USP, 2025. p. 397-404.
dc.identifier978-85-86481-94-9
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1185940
dc.identifier.urihttp://hdl.handle.net/123456789/457430
dc.languageeng
dc.rightsopenAccess
dc.subjectAprendizado de máquina
dc.subjectDiversidade de culturas
dc.subjectProdção de café
dc.subjectHarmonized Landsat Sentinel-2
dc.subjectMachine learning
dc.subjectCrop diversity
dc.subjectCoffee production
dc.subjectAgricultura
dc.subjectIrrigação
dc.subjectAgriculture
dc.subjectIrrigation
dc.titleThe role of Landsat and Sentinel-2 data harmonization in monitoring agricultural dynamics on smallholder farming regions.
dc.typeArtigo em anais e proceedings

Archivos

Colecciones

Embrapa Agricultura Digital (CNPTIA)