AKADEMIYA2063’s COVID-19 portal

Production Systems Disruption

FINDING A SOLUTION TO THE PROBLEM OF FOOD CROP PRODUCTION DATA

From effects on access to seeds and fertilizers, limited movement of goods, declining demand, to labor shortage, the disruptive impact of Covid-19 on food production systems is real. The challenge here is not only the likely extent and complexity of the disruptions but also the difficulty to identify and track them in real time. Unlike the propagation of the disease itself which can be tracked through testing and tracing, it is impossible, even in normal times, to have accurate information on cropping activities. The introduction of confinement and other measures to control the pandemic make the situation even more difficult. There is no way of knowing whether farmers have access to inputs, in time or in adequate quantities, whether they have been too sick to tend to their farmers or could work only partially. One would eventually find out at the end of the growing season from the impact of harvested quantities. One is then left to play catch up to deal with a crisis situation.

The complete lack of information about growing conditions can be overcome by using today’s digital technologies. Remotely sensed data allow to track in real time changes in vegetation cover, weather data and other parameters related to cropping activities. Recent developments in machine learning and computer modeling make it possible to track and predict crop production using these data. The benefits go far beyond the ability to overcome the obstacles to data gathering during crises. The many weaknesses hampering the access to good quality agricultural statistics also can be overcome using the same digital technologies, from measuring arable land, planted areas, crop yields to the spatial distribution of harvested quantities.
Our scientists are using these technologies to assess changes in food production systems during the pandemic and thereby provide valuable information to tackle the impact of the pandemic among local communities.

INTRODUCTION

COVID-19 is expected to have wide ranging impacts on production systems, resulting from a host of disruptions not just to health, but also transport, market and broader food systems. The difficulty of in-person data collection poses a real challenge to assessing the situation and providing an accurate picture of the crisis’ ramifications. Under this workstream, we will use innovative remote sensing, big data and computer learning methodologies to build tools that allow us to evaluate the impact on production systems at the local community level. We will track the growing season for key local staples and apply our tools to issue real time predictions of future food production at community level in a number of countries. Comparisons between predicted 2020 production levels and those of previous years as well as crop modeling techniques will be used to estimate the role of COVID-19 in production disruptions.