ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis

• Published in: Agricultural systems Vol. 168; pp. 247 - 257
• Main Authors: Rembold, Felix, Meroni, Michele, Urbano, Ferdinando, Csak, Gabor, Kerdiles, Hervé, Perez-Hoyos, Ana, Lemoine, Guido, Leo, Olivier, Negre, Thierry
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01-01-2019; Elsevier Applied Science [etc.]
• ISSN: 0308-521X; 1873-2267
• DOI: 10.1016/j.agsy.2018.07.002

Monitoring crop and rangeland conditions is highly relevant for early warning and response planning in food insecure areas of the world. Satellite remote sensing can obtain relevant and timely information in such areas where ground data are scattered, non-homogenous, or frequently unavailable. Rainfall estimates provide an outlook of the drivers of vegetation growth, whereas time series of satellite-based biophysical indicators at high temporal resolution provide key information about vegetation status in near real-time and over large areas. The new early warning decision support system ASAP (Anomaly hot Spots of Agricultural Production) builds on the experience of the MARS crop monitoring activities for food insecure areas, that have started in the early 2000's and aims at providing timely information about possible crop production anomalies. The information made available on the website (https://mars.jrc.ec.europa.eu/asap/) directly supports multi-agency early warning initiatives such as for example the GEOGLAM Crop Monitor for Early Warning and provides inputs to more detailed food security assessments that are the basis for the annual Global Report on Food Crises. ASAP is a two-step analysis framework, with a first fully automated step classifying the first sub-national level administrative units into four agricultural production deficit warning categories. Warnings are based on rainfall and vegetation index anomalies computed over crop and rangeland areas and are updated every 10 days. They take into account the timing during the crop season at which they occur, using remote sensing derived phenology per-pixel. The second step involves the monthly analysis at country level by JRC crop monitoring experts of all the information available, including the automatic warnings, crop production and food security-tailored media analysis, high-resolution imagery (e.g. Landsat 8, Sentinel 1 and 2) processed in Google Earth Engine and ancillary maps, graphs and statistics derived from a set of indicators. Countries with potentially critical conditions are marked as minor or major hotspots and a global overview is provided together with short national level narratives.
•Earth Observation based global monitoring of crop and rangeland conditions for food security analysis•Timely early warning thanks to frequent updates (10 days for climate anomalies, 30 days for agricultural hotspot analysis)•Public online webGIS with downloadable information•Country level agricultural production hotspot identification and short narratives for non-remote sensing experts