

Senegal prototype
Optimizing the survey protocol in Senegal, Nioro
Over the last decade, food security has become one of the world’s greatest challenges. To effectively address this challenge, a wide range of timely data and information on food production, agricultural practices and natural resources is required to be available, analyzed and understood. Agricultural monitoring at national scale is a prerequisite for assessing and analyzing the agricultural resources by mandated authorities, usually the agricultural National Statistical Offices (NSOs). Recognizing the limitations of the current agricultural data collection, the potential of satellite Earth Observation for agricultural statistics is more and more emphasized by key international bodies and UN agencies. The objective of the Sen4Stat project is to facilitate the uptake of EO information by the NSOs through the development and demonstration of EO products and best practices coupling EO and survey data in order to support the agricultural statistics.
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It is associated with statistical modules to integrate these EO products with statistical surveys and support improved agricultural statistics. Sen4Stat is an open source operational solution for national processing and for local applications, in near real-time along the satellite data acquisition or off-line, on the cloud or locally. It is easily configurated through a graphical user interface to launch the production and monitor the
Our system is designed to be versatile, whether you want to use it locally or on the cloud. You can download the necessary package for free and start exploring it right away!
System download (~8Gb)Using EO data in a statistical framework to maximize the statistics accuracy (i.e. low variance) at low cost (free data, «simple» methods)
Using EO data to allow statistics disaggregation at over smaller administrative areas (e.g. province, county).
Using EO data to support the building of an area sampling frame and to find the optimal samples size and segments size.
Using EO data to forecast statistics before the official publication and possibly, provide seasonal estimates.
Using EO data to support the calculation of specific indicators of interest for the SDG’s reporting.
Using EO data to contribute to increasing the quality of the ground data collected through official agricultural surveys..
Optimizing the survey protocol in Senegal, Nioro
See the latest articles related to the ESA Sen4Stat projet including meeting, etc.
The project was marred by a daunting challenge: the reinforcement of the input dataset prior to crop mapping. This step was a make-or-break moment for the project, as the accuracy and completeness of the input data were vital to the success of the mapping.
Increasing sustainable agricultural productivity is the number one challenge of the “The Future of Food and Agriculture” report of the Food and Agriculture Organization in response to a projected increase in demand for food by 50% between 2012 and 2050.
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