@article{fdi:010062440, title = {{T}oward a satellite-based system of sugarcane yield estimation and forecasting in smallholder farming conditions : a case study on {R}eunion {I}sland}, author = {{M}orel, {J}. and {T}odoroff, {P}. and {B}egue, {A}. and {B}ury, {A}. and {M}artine, {J}. {F}. and {P}etit, {M}ichel}, editor = {}, language = {{ENG}}, abstract = {{E}stimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on {R}eunion {I}sland. {W}e used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1) an empirical relationship method with a growing season-integrated {N}ormalized {D}ifference {V}egetation {I}ndex {NDVI}, (2) the {K}umar-{M}onteith efficiency model, and (3) a forced-coupling method with a sugarcane crop model ({MOSICAS}) and satellite-derived fraction of absorbed photosynthetically active radiation. {T}hese models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. {R}esults showed that the linear empirical model produced the best results ({RMSE} = 10.4 t.ha(-1)). {B}ecause this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. {T}he main limitation is the acquisition of a minimum of five satellite images. {T}he upcoming open-access {S}entinel-2 {E}arth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.}, keywords = {sugarcane ; yield estimation ; model ; remote sensing ; {REUNION}}, booktitle = {}, journal = {{R}emote {S}ensing}, volume = {6}, numero = {7}, pages = {6620--6635}, ISSN = {2072-4292}, year = {2014}, DOI = {10.3390/rs6076620}, URL = {https://www.documentation.ird.fr/hor/fdi:010062440}, }