This case study highlights the results of one of our cocoa yield prediction projects. Let us show you how our scientific progress and unique high resolution satellite data can impact your trading strategy.
Unsurprisingly, commodity traders are more than eager to understand how they can harness the power of these Ag datasets to benefit their business. Insight and information are the only things capable of enhancing – or indeed hindering – your ability to make a profit in a market. Finding ways to create more useful insights and generate more information than other market players is exactly what VanderSat can do for commodity traders all over the world.
The data VanderSat delivers on climatic factors such as moisture, vegetation and temperature can go a long way towards predicting the final crop yield. From tropical zones to temperate zones and even irrigated land, our data provides the latest crop information. In addition to daily monitoring of conditions, we are able to supply historical data for any location on Earth. This historical data – going back to 2002 – provides an understanding of how today’s values relate to growing seasons almost two decades ago. This enables VanderSat not only to supply essential data but also to assess the impact of the situation you see today.
To understand how these changing conditions impact crop and final yield, we compare the historical VanderSat soil moisture dataset to historical production data. For one cocoa trader, we used this knowledge to develop and provide a national cocoa forecast for Ivory Coast and Ghana. We were able to deliver an absolute monthly yield forecast up to six months ahead, with a correlation of (R2) > 0.9. This improved on a previous model fed solely by pod-counting data.
VanderSat began the project by processing the satellite soil moisture data for Ghana and Ivory Coast (2002-present, see Figure 1) and researching the physical behaviour of the specific crop and its reaction to a range of climatic conditions. Does drought always have a negative impact? Can cold night-time temperatures prevent disease? Does the crop thrive when soil moisture is above a certain threshold? These initial questions helped produce a final model based on hardcore science, infinitely more reliable than the traditional ‘black box’ approach.