Development and testing of crop monitoring methods to improve global agricultural monitoring in support of GEOGLAM

Abstract:

The SIGMA project (Stimulating Innovation for Global Monitoring of Agriculture) is funded through the EC FPY7 Research programme with the particular aim to contribute to the GEOGLAM Research Agenda. It is a partnership of globally distributed expert organizations, focusses on developing innovative techniques and datasets in support of agricultural monitoring and its impact on the environment in support of GEOGLAM.

SIGMA has 3 generic objectives which are: (i) develop and test methods to characterize cropland and assess its changes at various scales; (ii) develop and test methods to assess changes in agricultural production levels; and; (iii) study environmental impacts of agriculture. Firstly, multi-scale remote sensing data sets, in combination with field and other ancillary data, are used to generate an improved (global) agro-ecological zoning map and crop mask. Secondly, a combination of agro-meteorological models, satellite-based information and long-term time series are be explored to better assess crop yield gaps and shifts in cultivation. The third research topic entails the development of best practices for assessing the impact of crop land and cropping system change on the environment. In support of the GEO JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative, case studies in Ukraine, Russia, Europe, Africa, Latin America and China are carried out in order to explore possible methodological synergies and particularities according to different cropping systems. This presentation will report on the progress made with respect to the three topics above.