Título:	Integrating NDVI and multisensor data with digital agriculture tools for crop monitoring in southern Brazil.
Autoria:	FURUYA, D. E. G. BOLFE, E. L. PARREIRAS, T. C. SOARES, V. B. GEBLER, L.
Afiliação:	DANIELLE ELIS GARCIA FURUYA; EDSON LUIS BOLFE, CNPTIA; TAYA CRISTO PARREIRAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; VICTÓRIA BEATRIZ SOARES, UNIVERSIDADE ESTADUAL DE CAMPINAS; LUCIANO GEBLER, CNPUV.
Ano de publicação:	2026
Referência:	AgriEngineering, v. 8, n. 2, 48, Feb. 2026.
Conteúdo:	Abstract. The monitoring of perennial and annual crops requires different analytical approaches due to their contrasting phenological dynamics and management practices. This study investigates the temporal behavior of the Normalized Difference Vegetation Index (NDVI) derived from Harmonized Landsat and Sentinel-2 (HLS) imagery to characterize apple, grape, soybean, and maize crops in Vacaria, Southern Brazil, between January 2024 and April 2025. NDVI time series were extracted from cloud-free HLS observations and analyzed using raw, interpolated, and Savitzky–Golay, smoothed data, supported by field reference points collected with the AgroTag application. Distinct NDVI temporal patterns were observed, with apple and grape showing higher stability and soybean and maize exhibiting stronger seasonal variability. Descriptive statistics derived from 112 observation dates confirmed these differences, highlighting the ability of HLS-based NDVI time series to capture crop-specific phenological patterns at the municipal scale. Complementary analysis using the SATVeg platform demonstrated consistency in long-term vegetation trends while evidencing scale limitations of coarse-resolution data for small perennial plots. Overall, the findings demonstrate that the NDVI enables robust monitoring of mixed agricultural landscapes, with complementary spatial resolutions and analytical tools enhancing crop-specific phenological analysis.
Thesagro:	Maçã Uva Soja Milho Sensoriamento Remoto
NAL Thesaurus:	Apples Grapes Soybeans Remote sensing Time series analysis Normalized difference vegetation index
Palavras-chave:	Maize Rio Grande do Sul Harmonized Landsat and Sentinel-2 (HLS)
Digital Object Identifier:	https://doi.org/10.3390/agriengineering8020048
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CNPTIA)