How well do EO-based food security warning systems for food security agree? Comparison of NDVI-based vegetation anomaly maps in West Africa

Bégué Agnès, Madec Simon, Lemettais Louise, Leroux Louise, Interdonato Roberto, Becker-Reshef Inbal, Barker Brian, Justice Christina, Kerdiles Hervé, Meroni Michele. 2023. How well do EO-based food security warning systems for food security agree? Comparison of NDVI-based vegetation anomaly maps in West Africa. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16 : 1641-1653.

https://doi.org/10.1109/JSTARS.2023.3236259

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Résumé : The GEOGLAM crop monitor for early warning is based on the integration of the crop conditions assessments produced by regional systems. Discrepancies between these assessments can occur and are generally attributed to the interpretation of the vegetation and climate data. The premise of this article is that other sources of discrepancy related to the data themselves must also be considered. We conducted a comparative experiment of the growth vegetation anomalies routinely produced by four operational crop monitoring systems in West Africa [FEWSNET, GIEWS, ASAP, VAM] for the 2010–2020 period. We collected a set of normalized differences vegetation index-based indicators (% mean, % median, and Z -score) and proposed original methods to analyze and compare the spatio-temporal variations of these indices using Hovmöller representation, statistics, and spatial analysis. To facilitate systems comparison, a classification scheme based on the percentile rank values of anomaly indicators was applied to produce 3-class alarm maps (negative, absence, and positive anomalies). Results show that, on an annual basis, the per-pixel similarity is relatively low between the four systems [24.5%–34.1%], and that VAM and ASAP are the most similar (70%). The reasons of the products discrepancies come mainly from different preprocessing methods, especially the choice of the reference period used to calculate the anomaly. The negative alarm agreement classes show no eco-climatic zoning influence, but negative alarms hot-spots were locally observed. The negative alarm agreement maps can be a useful tool for early warning as they synthesize the information provided by the different systems, with a confidence level.

Mots-clés Agrovoc : télédétection, système de culture, sécurité alimentaire, système d'alerte rapide, cartographie, surveillance des cultures, végétation, cartographie de l'utilisation des terres

Mots-clés géographiques Agrovoc : Afrique occidentale, Sahel

Mots-clés libres : Remote Sensing, Food Security, Vegetation anomalies, Satellite Image Time Series, Africa, NDVI

Classification Agris : S01 - Nutrition humaine - Considérations générales
S40 - Programmes alimentaires

Champ stratégique Cirad : CTS 3 (2019-) - Systèmes alimentaires

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