Forecasting Regional Sugarcane Yield Based on Time Integral and Spatial Aggregation of MODIS NDVI

Betty Mulianga,Agnès Bégué,Pierre Todoroff,Margareth Simoes

doi:10.3390/rs5052184

Abstract

This study explored the suitability of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectrometer (MODIS) obtained for six sugar management zones, over nine years (2002–2010), to forecast sugarcane yield on an annual and zonal base. To take into account the characteristics of the sugarcane crop management (15-month cycle for a ratoon, accompanied with continuous harvest in Western Kenya), the temporal series of NDVI was normalized through an original weighting method that considered the growth period of the sugarcane crop (wNDVI), and correlated it with historical yield datasets. Results when using wNDVI were consistent with historical yield and significant at P-value = 0.001, while results when using traditional annual NDVI integrated over the calendar year were not significant. This correlation between yield and wNDVI is mainly drawn by the spatial dimension of the data set (R2 = 0.53, when all years are aggregated together), rather than by the temporal dimension of the data set (R2 = 0.1, when all zones are aggregated). A test on 2012 yield estimation with this model realized a RMSE less than 5 t·ha−1. Despite progress in the methodology through the weighted NDVI, and an extensive spatio-temporal analysis, this paper shows the difficulty in forecasting sugarcane yield on an annual base using current satellite low-resolution data. This is particularly true in the context of small scale farmers with fields measuring less than the size of MODIS 250 m pixel, and in the context of a 15-month crop cycle with no seasonal cropping calendar. Future satellite missions should permit monitoring of sugarcane yields using image resolutions that facilitate extraction of crop phenology from a group of individual plots.

Highlights

IntroductionSugarcane (Saccharum Spp. Hybrids) is a graminae of the tribe of Andropogonae and Poaceae family
When the whole data set (6 zones and 9 years) is used, the analysis shows that the annual Normalized Difference Vegetation Index (NDVI) is not strongly related to the sugarcane yield (p = 0.1; (Figure 4(a))
This research has investigated the influence of cropping practices and environmental conditions on yield at zone scale through two approaches

Summary

Introduction

Sugarcane (Saccharum Spp. Hybrids) is a graminae of the tribe of Andropogonae and Poaceae family. Hybrids) is a graminae of the tribe of Andropogonae and Poaceae family It is defined as a tropical semi perennial crop which is harvested through the manual system in. Re-growth of sugarcane, known as ratooning, matures at different periods, introducing spatio-temporal variability in the sugarcane landscape. In Kenya where sugarcane is rain fed, this variability is exacerbated with an unspecified cropping calendar and diversification of the cropping system both at spatial (sugar management zone) and temporal (inter-annual) levels, presenting a heterogeneous sugarcane landscape. Sugarcane being the second largest contributor to Kenya’s agricultural growth saves the country in excess of USD 229,885,057 annually in foreign exchange, while contributing to poverty reduction and national development [1]

Objectives

Results

Conclusion