MASH : monitoring the sugarcane harvest

Software and digital applications Sustainable agriculture
Mash (Mapping Sugarcane Harvest) is a web application for mapping the progress of the sugarcane harvest using optical and radar remote sensing. It enables the observation of the sugarcane harvest in semi-real time over an entire territory, and thus optimizes the supply chain for processing units.
Cartographie du suivi de récolte de la canne à sucre à La Réunion @Mickael Mézino, Cirad

Sugarcane harvest mapping and monitoring using radar satellite imagery in La Réunion island © Mickael Mézino, CIRAD

 

A tool for optimizing sugarcane production

Mash (Mapping Sugarcane Harvest) is an application for mapping sugarcane harvest progress in semi-real time. The method consists in automatically processing free satellite images (radar and optical) acquired with high repeatability (less than 6 days). Each pixel of sugarcane plots is classified according to its harvest status. Mash produces synthetic maps of harvested area rates by plot, as well as synthetic tables by supply center, or by factory, enabling operators to visually monitor harvest progress.

The Mash chain is based exclusively on free satellite data from the European Space Agency's (ESA) Copernicus program and Open Source software. It is deployed on a Linux server. 

Development stage
TRL8 - Qualification of the complete system in an operational environment

TRL8 - Qualification of the complete system in an operational environment

Benefits for sugarcane production

Mash is a decision-support module that :

  • Gives an overview of the state of harvesting in a given geographical area;
  • Optimizes the supply chain around the sugarcane harvest;
  • Facilitates the management of manpower and field operations.

Mash, which focuses on harvesting processes, currently complements the yield estimation solution developed by our partner GeoWtach Labs to provide a better range of services.

Mash markets and applications

  • For sugarcane operators: a tool for optimizing sugarcane harvest logistics and updating harvest area forecasts. Mash provides precise information on the area of cane actually harvested and its distribution across the country
  • For the industry's institutions and economic partners on a regional scale: the harvested area rate on a regional scale is a particularly complicated piece of information to obtain, given that sugarcane production is often spread over thousands of small producers. Mash provides simple, map-based access to this information.

How to access the Mash tool and related services?

The research team that developed Mash offers :

Sugarcane millers and processors : 

Integrate the Mash application into their own logistics management tools. 

Imaging service operators: 

Transfer the technology to them, with a view to licensing it in certain countries/regions and incorporating it into their solution, as GeoWatch Labs does.

For all other requests, particularly from political and statistical institutions, please do not hesitate to contact us.
For further information: https://smartis.re/p/MASH 

The Research Team : Mash was developed within the Aïda (Agroecology and sustainable intensification of annual crops) research unit. The original approach consists in coupling optical and radar satellite observations with a geographic information system, thus providing decision-support tools for tropical agriculture in general, with the tool being adaptable as required. 

References and intellectual property

Patents and licenses : 

APP filing IDDN n° FR.001.18008.00 of April 23, 2019

The module has been transferred to GeoWatch Labs for integration into their production chain. This transfer is non-exclusive, however, and enables us to take into account additional specific requirements.

Publications

Baghdadi N., Boyer N., Todoroff P., El Hajj M., and Begue A., 2009. Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT, and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island. Remote Sensing of Environment, vol.113, Issue 8, pp. 1724-1738. http://publications.cirad.fr/une_notice.php?dk=549410

Baghdadi, N., Cresson, R., Todoroff, P., Moinet, S., 2010. Multitemporal Observations of Sugarcane by TerraSAR-X Images. Sensors 10, 8899-8919.  http://dx.doi.org/10.3390/s101008899

See also