Assessing the capability of MODIS to monitor mixed pastures with high-intensity grazing at a fine-scale

Author(s)

da Silva, Yane de Freitas ; Aparecida Dos Reis, Aliny ; Sampaio Werner, Joao Paulo ; Vasconcelos Valadares, Rafael ; Campbell, Eleanor E. ; Augusto Camargo Lamparelli, Rubens ; Magalhaes, Paulo Sergio Graziano ; Figueiredo, Gleyce Kelly Dantas Araujo

• Document type: Journal article
• Source: GEOCARTO INTERNATIONAL; v. 37, n. 20, p. 19-pg., 2021-05-07.

Abstract

MODIS time series carries valuable long-term data essential to support several studies such as biogeochemical modelling. However, there is a lack of validation studies applying MODIS data at a fine-scale to monitor pasture management practices. In this study, we assessed the potential of MODIS sensor in monitoring at a fine-scale four intensively managed mixed-pastures fields located in Sao Paulo State, Brazil. The MODIS spectral response was compared with Sentinel-2, and the ability of the two sensors in predicting aboveground biomass (AGB) and canopy height (CH) was assessed using the Random Forest algorithm. EVI images from MODIS and Sentinel-2 were correlated with field measurements of AGB and CH. The prediction performance of AGB (R-2: Sentinel-2 = 38%; MODIS = 42%) and CH (R-2: Sentinel-2 = 69%; MODIS = 85%) models was superior using EVI data from MODIS than Sentinel-2, highlighting MODIS ability to monitor small and intensively managed pasture fields. (AU)

• FAPESP's process: 18/24707-0 - Assessing the effects of integrated crop-livestock systems and associated management practices on soil carbon and nitrogen cycling processes using the Daycent model
• Grantee: Rafael Vasconcelos Valadares
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 18/24985-0 - Methodology for mapping and monitoring different pasture-based Livestock management and Mixed Crop-Livestock systems with remote sensing
• Grantee: Aliny Aparecida dos Reis
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 17/50205-9 - Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production - towards low carbon agriculture
• Grantee: Paulo Sergio Graziano Magalhães
• Support Opportunities: Research Projects - Thematic Grants