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Remote Sens. 2013, 5(3), 1091-1116; doi:10.3390/rs5031091

Enhanced Processing of 1-km Spatial Resolution fAPAR Time Series for Sugarcane Yield Forecasting and Monitoring

Monitoring Agricultural Resources (MARS) Unit, Institute for Environment and Sustainability (IES), European Commission Joint Research Centre, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy
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Received: 5 January 2013 / Revised: 26 February 2013 / Accepted: 27 February 2013 / Published: 1 March 2013
(This article belongs to the Special Issue Advances in Remote Sensing of Agriculture)
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Abstract

A processing of remotely-sensed Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) time series at 1-km spatial resolution is established to estimate sugarcane yield over the state of São Paulo, Brazil. It includes selecting adequate time series according to the signal spatial purity, using thermal time instead of calendar time and smoothing temporally the irregularly sampled observations. A systematic construction of various metrics and their capacity to predict yield is explored to identify the best performance, and see how timely the yield forecast can be made. The resulting dataset not only reveals a strong spatio-temporal structure, but is also capable of detecting both absolute changes in biomass accumulation and changes in its inter-annual variability. Sugarcane yield can thus be estimated with a RMSE of 1.5 t/ha (or 2%) without taking into account the strong linear trend in yield increase witnessed in the past decade. Including the trend reduces the error to 0.6 t/ha, correctly predicting whether the yield in a given year is above or below the trend in 90% of cases. The methodological framework presented here could be applied beyond the specific case of sugarcane in São Paulo, namely to other crops in other agro-ecological landscapes, to enhance current systems for monitoring agriculture or forecasting yield using remote sensing.
Keywords: sugarcane; yield; SPOT-VEGETATION; fAPAR; thermal time; regional scale; São Paulo sugarcane; yield; SPOT-VEGETATION; fAPAR; thermal time; regional scale; São Paulo
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Duveiller, G.; López-Lozano, R.; Baruth, B. Enhanced Processing of 1-km Spatial Resolution fAPAR Time Series for Sugarcane Yield Forecasting and Monitoring. Remote Sens. 2013, 5, 1091-1116.

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