This document illustrates the ASAP methodology for the automatic calculation of the warning levels at provincial level, including the model, the data used by the system, and the way it is implemented. Version 4.0.
This document illustrates the method used to downscale the existing national level crop calendars to the sub-national level using ASAP remote sensing derived phenology.
This document describes the Water Satisfaction Index model.
Summary of climate variability and extremes and their main impacts on agricultural production in 2018.
NOTE: the tutorials illustrate an older release of ASAP. While all the key concepts are still valid, the interface has undergone important updates and may be different from what is shown in the video.
This 4 minutes video tutorial is a quick guide on how to explore the information for a single hotspot country. It summarizes the main steps to visualize the most relevant information available on the ASAP platform.
This 14 minutes video is a complete live demo of the main functionalities of the system. You will be introduced to the main information products. and to the methodology used to generate them.
Rembold F., Meroni M., Urbano F., Csak G., Kerdiles H., Perez-Hoyos A., Lemoine G., Leo O., Thierry N. (2018) "ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis" in Agricultural Systems
Rembold F., Meroni M., Urbano F., Lemoine G., Kerdiles H., Perez-Hoyos A., Csak G. (2017) "ASAP - Anomaly hot Spots of Agricultural Production, a new early warning decision support system developed by the Joint Research Centre" in proceedings of MultiTemp 2017 Conference, Bruges - Belgium
Meroni M., Rembold F., Fasbender D., Vrieling A. (2016) "Evaluation of the Standardized Precipitation Index as an early predictor of seasonal vegetation production anomalies in the Sahel" in Remote Sensing Letters
Presentation that illustrates the main features of ASAP