New Functionalities and Regional/National Use Cases of the Anomaly Hotspots of Agricultural Production (ASAP) Platform

Author:

Rembold Felix1,Meroni Michele1,Otieno Viola2,Kipkogei Oliver2,Mwangi Kenneth2,de Sousa Afonso João Maria3ORCID,Ihadua Isidro Metódio Tuleni Johannes3,José Amílcar Ernesto A.3,Zoungrana Louis Evence4ORCID,Taieb Amjed Hadj4,Urbano Ferdinando1,Dimou Maria1,Kerdiles Hervé1,Vojnovic Petar1,Zampieri Matteo15,Toreti Andrea1

Affiliation:

1. Joint Research Centre (JRC), European Commission, Via E. Fermi 2749, I-21027 Ispra, VA, Italy

2. Intergovernmental Authority on Development (IGAD) Climate Prediction and Applications Centre (ICPAC), Nairobi P.O. Box 10304-00100, Kenya

3. Instituto Nacional de Meteorologia e Geofísica de Angola (INAMET), Rua 21 de Janeiro, Rotunda do Gamek à Direita, S/N-RC, Luanda 1323, Angola

4. GIS and Remote Sensing Unit, Observatoire du Sahara et du Sahel (OSS), P.O. Box 31, Boulevard du Leader Yasser Arafat, Tunis 1080, Tunisia

5. Department of Physical Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia

Abstract

The Anomaly hotSpots of Agricultural Production (ASAP) Decision Support System was launched operationally in 2017 for providing timely early warning information on agricultural production based on Earth Observation and agro-climatic data in an open and easy to use online platform. Over the last three years, the system has seen several methodological improvements related to the input indicators and to system functionalities. These include: an improved dataset of rainfall estimates for Africa; a new satellite indicator of biomass optimised for near-real-time monitoring; an indicator of crop and rangeland water stress derived from a water balance accounting scheme; the inclusion of seasonal precipitation forecasts; national and sub-national crop calendars adapted to ASAP phenology; and a new interface for the visualisation and analysis of high spatial resolution Sentinel and Landsat data. In parallel to these technical improvements, stakeholders and users uptake was consolidated through the set up of regionally adapted versions of the ASAP system for Eastern Africa in partnership with the Intergovernmental Authority on Development (IGAD) Climate Prediction and Applications Centre (ICPAC), for North Africa with the Observatoire du Sahara et du Sahel (OSS), and through the collaboration with the Angolan National Institute of Meteorology and Geophysics (INAMET), that used the ASAP system to inform about agricultural drought. Finally, ASAP indicators have been used as inputs for quantitative crop yield forecasting with machine learning at the province level for Algeria’s 2021 and 2022 winter crop seasons that were affected by drought.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference41 articles.

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