%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.12.56.35
%2 sid.inpe.br/marte2/2017/10.27.12.56.36
%@isbn 978-85-17-00088-1
%F 59276
%T Assimilating leaf area index time series into a simple crop growth model to estimate effective rooting depth and soybean yield
%D 2017
%A Berger, Andres G,
%A Rossini, Pedro R,
%A Gaso, Deborah Viviana,
%@electronicmailaddress aberger@inia.org.uy
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 3073-3077
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X Soil water holding capacity is the main determinant of soybean yields in rainfed agriculture in the pampas region. Estimating water holding capacity is challenging, and the capacity to measure it over large areas is limited. The main goal of this work is in advancing in methods to estimate maximum effective root activity depth (RDMAX) as a proxy for water holding capacity based on inverse modeling of crop growth, relying on the assumption that it is the main factor accounting for variations in crop growth. For that purpose we used a simple model developed by Campbell and Diaz (1988). The model was inverted to estimate RDMAX, using TOA NDVI time series (Landsat 7 ETM+ and Landsat 8 OLI) as input while holding other parameters describing the site and crop fixed (i.e. planting, emergence and maturity dates, and dry matter water ratio). The model was also modified to estimate grain yield, assuming linear increase in harvest index and senescence driven by nitrogen remobilization from the above ground biomass. The model was tested at five fields where soybean was grown for six growing seasons. RDMAX was calibrated obtaining an estimate of RDMAX for each year and each pixel within a field independently. Comparison across years and sites suggest that general patterns are estimated correctly, in particular in normal years (not too wet, not too dry). The use of a simple model with few parameters to adjust proved useful in achieving sufficiently reliable and robust estimates of final RDMAX and grain yield.
%9 Produção e previsão agrícola
%@language en
%3 59276.pdf