Title:	Estimating forage mass of a crop-livestock system (icl) using satellite images and climate data.
Authors:	NOGUEIRA, S. F. SILVA, G. B. S. da ADAMI, M. SANTOS, P. M. PEZZOPANE, J. R. M. NUÑEZ, D. GREGO, C. R. TEIXEIRA, A. H. SKAKUN, S. ROLISOLA, I.
Affiliation:	SANDRA FURLAN NOGUEIRA, CNPMA; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPMA; MARCOS ADAMI, National Institute for Space Research (INPE); PATRICIA MENEZES SANTOS, CPPSE; JOSE RICARDO MACEDO PEZZOPANE, CPPSE; DANIEL NUÑEZ, Unibras; CELIA REGINA GREGO, CNPTIA; ANTÔNIO HERIBERTO TEIXEIRA, UNIVERSIDADE FEDERAL DE SERGIPE; SERGII SKAKUN, University of Maryland; ISA ROLISOLA, CNPQ.
Date Issued:	2021
Citation:	In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS: 100% DIGITAL, 2., 2021. WCCLF 2021 proceedings. Campo Grande, MS: Embrapa Gado de Corte, 2021.
Pages:	p.804-809.
Description:	The Simple Algorithm for Evapotranspiration Retrieving (SAFER) was used to estimate forage mass in a beef cattle production system, in São Carlos (SP), Brazil. Harmonized Landsat-8 and Sentinel-2 (HLS) surface reflectance bands were used with daily weather data from a station adjacent to the experimental area and from a INMET station (OMM: #86845). The experimental area is a crop-livestock system (iCL) with pasture managed under rotational stocking in rotation with corn for silage during pasture renewal. Monthly field campaigns in 2018 and 2019 were conducted and aimed to estimate ground-measured forage mass. A bootstrapped linear least-squares regression was employed for evaluating the results for model validation. SAFER is a feasible tool to estimate forage mass in a crop-livestock system (iCL), as around 73% of the variability in forage mass was explained through the integration of HLS surface reflectance images, groundmeasured data, and cattle management, in an agrometeorological modeling approach. The methodology will assist farmers and policymakers to estimate forage availability to improve decision-making on pasture management. Future works will discriminate estimated forage mass in intensive and extensive pasture systems
NAL Thesaurus:	Agrometeorology Remote sensing
Keywords:	Digital agriculture
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CNPMA)