Software and digital applications - Sustainable agriculture - Food and agrifood technology - Natural resources and territories
MASH : sugarcane harvest mapping and monitoring using radar satellite imagery
The sugar sector often lacks geographic information on the sugarcane fields to optimize the crop production and the delivery to the mills. In particular the harvest status of the fields is seldom accurately known in countries where the production is in the hand of thousands of growers.
On the other hand satellite radar images are of significant interest in tropical regions because they can be used when optical sensors are inoperative (clouds,haze) to deliver near real-time information. MASH is a signal processingalgorithm applied to radar images time series, to monitor the sugarcane Harvest by identifying the harvested fields and compute the ratio of cut/uncut areas at different geographical scales. The main innovation is based on the analysis ofthe signal backscattering, which is sensitive to the development of crop.
How to get an single look upon sugar cane Harvest?
1. To optimize the Harvest logistics by mapping the sugarcane fields harvest status
2. To optimize workforce and inputs by confirming and adjusting the harvest forecast during the campaign.
Pierre Todoroff and his team of Aida Research Unit based at Réunion Island work on an original approach which consists in coupling satelitte earth observations and geographical information system, to provide to decision support tools fortropical agriculture in general, and the sugarcane sector in particular. Theyhave developed MASH and offer to:
1. Adapt it to local conditions and to the interested partner / sugarcane processor’s spécifications in view of transferring the technology (training and application transfer).
2. Transfer the technology to an imagery service operator, with possible licensing for a country or a region during the campaign.