Título:	Developing and applying an Agro-environmental Quality Index (AQI) for Caconde-SP, Brazil: a first approximation using remote sensing and Google Earth Engine.
Autoria:	KLINKE NETO, G. CASTRO, V. H. M. e de C. PARREIRAS, T. C. BOLFE, E. L. BERGIER, I.
Afiliação:	GUSTAVO KLINKE NETO, UNIVERSIDADE ESTADUAL DE CAMPINAS; VICTÓRIA HELLENA MATUSEVICIUS E DE CASTRO, UNIVERSIDADE ESTADUAL DE CAMPINAS; TAYA CRISTO PARREIRAS; EDSON LUIS BOLFE, CNPTIA; IVAN BERGIER TAVARES DE LIMA, CNPTIA.
Ano de publicação:	2025
Referência:	In: WORKSHOP CIENTÍFICO DO CENTRO DE CIÊNCIA PARA O DESENVOLVIMENTO EM AGRICULTURA DIGITAL – SEMEAR DIGITAL, 2., 2025, Campinas. Anais [...]. Piracicaba: ESALQ/USP, 2025. p. 196-204.
Conteúdo:	Continuous environmental quality monitoring is crucial for sustainability, particularly given the increased food production demanded by population growth. Smallholder farmers, responsible for a significant portion of global and Brazilian agricultural output, require practical tools to assess and enhance the agro-environmental sustainability of their activities. In this context, orbital remote sensing and platforms such as the Google Earth Engine (GEE) offer efficient solutions for deriving biophysical (NDVI, NDWI, BSI, LST) and topographic (slope) indicators, which are essential for constructing Agro-environmental Quality Indices (AQI). This study developed and applied a methodology for the monthly monitoring of AQI in the municipality of Caconde-SP, Brazil, utilizing Sentinel-2, Landsat 8, and SRTM data processed within GEE for the period between 2021 and 2023. NDVI, NDWI, BSI, LST, and slope were calculated, normalized, and combined through a weighted sum to generate the AQI, subsequently classified into five levels. The results demonstrate the feasibility of this approach, with GEE efficiently processing multi-sensor data and enabling continuous monitoring. The proposed AQI, although preliminary and requiring further validation and refinement, presents itself as a promising tool for environmental diagnostics at the municipal scale. This methodology contributes to agro-environmental monitoring by introducing a replicable and cost-effective approach with potential for adaptation to other regions.
Thesagro:	Sensoriamento Remoto
NAL Thesaurus:	Remote sensing
Palavras-chave:	Índice de qualidade agroambiental Projeto Semear Digital Google Earth Engine
ISBN:	978-85-86481-94-9
Notas:	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.
Tipo do material:	Artigo em anais e proceedings
Acesso:	openAccess
Aparece nas coleções:	Artigo em anais de congresso (CNPTIA)