Earth observations combined with other data contribute to crop monitoring to counter food insecurity, a commitment upheld by all states under Sustainable Development Goal 2, zero hunger.
GEO will advocate the value of Earth observations, engage communities and deliver data and information in support of Food Security and Sustainable Agriculture by underpinning development, management and forecasting of global food and agricultural production on land and in the water; in order to end hunger, achieve food security (including monitoring for quality, safety and correct identification) and promote sustainable agriculture adapted to climate change impacts through strengthening food production monitoring and early warning systems, and providing accurate, timely information on agricultural production status, outlook and forecasts.
Summary description of 2016 Plans
For 2016, GEO will be mainly addressing monitoring and forecasting for agriculture and fisheries.
In particular, the GEOGLAM, adopted by the G-20 in 2011, is an initiative aimed at providing transparent, timely and actionable information on crop prospects through the use of earth observations (EO). Its plans for 2016 are the following:
Food supplies depend on trends in the natural environment, including weather and climate, freshwater supplies, soil moisture and other variables.
At the same time, agriculture has a major impact on the environment. Unless they are sustainably managed, farms and pastures can cause erosion, desertification, chemicals pollution and water shortages. Similarly, fishing can deplete fish stocks and damage coastal ecosystems. These risks need to be monitored and managed.
The Group on Earth Observations is constructing the Global Earth Observation System of Systems to help farmers, fishers and policymakers maximize productivity and food security while preserving ecosystems and biodiversity.
GEO also aims to support the sustainable management of agriculture by disseminating weather forecasts, early warnings of storms and other extreme events, water pollution, long-term forecasts of likely climate change impacts, and information on water supplies.
These and other data are being integrated so that they can be used in models for simulating and predicting agricultural trends. Related activities include mapping the changing distribution of croplands around the world, advancing the accuracy of measurements of biomass (the total amount of living material in a given habitat or population), reporting agricultural statistics in a more timely manner, and improving forecasts of shortfalls in crop production and food supplies.