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A comparative study on satellite- and model-based crop phenology in West Africa

Vintrou Elodie, Bégué Agnès, Baron Christian, Saad Alexandre, Lo Seen Danny, Traoré Seydou B.. 2014. A comparative study on satellite- and model-based crop phenology in West Africa. Remote Sensing, 6 (2) : pp. 1367-1389.

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Quartile : Q1, Sujet : REMOTE SENSING

Abstract : Crop phenology is essential for evaluating crop production in the food insecure regions of West Africa. The aim of the paper is to study whether satellite observation of plant phenology are consistent with ground knowledge of crop cycles as expressed in agro-simulations. We used phenological variables from a MODIS Land Cover Dynamics (MCD12Q2) product and examined whether they reproduced the spatio-temporal variability of crop phenological stages in Southern Mali. Furthermore, a validated cereal crop growth model for this region, SARRA-H (System for Regional Analysis of Agro-Climatic Risks), provided precise agronomic information. Remotely-sensed green-up, maturity, senescence and dormancy MODIS dates were extracted for areas previously identified as crops and were compared with simulated leaf area indices (LAI) temporal profiles generated using the SARRA-H crop model, which considered the main cropping practices. We studied both spatial (eight sites throughout South Mali during 2007) and temporal (two sites from 2002 to 2008) differences between simulated crop cycles and determined how the differences were indicated in satellite-derived phenometrics. The spatial comparison of the phenological indicator observations and simulations showed mainly that (i) the satellite-derived start-of-season (SOS) was detected approximately 30 days before the model-derived SOS; and (ii) the satellite-derived end-of-season (EOS) was typically detected 40 days after the model-derived EOS. Studying the inter-annual difference, we verified that the mean bias was globally consistent for different climatic conditions. Therefore, the land cover dynamics derived from the MODIS time series can reproduce the spatial and temporal variability of different start-of-season and end-of-season crop species. In particular, we recommend simultaneously using start-of-season phenometrics with crop models for yield forecasting to complement commonly used climate data and provide a better estimate of vegetation phenological changes that integrate rainfall variability, land cover diversity, and the main farmer practices. (Résumé d'auteur)

Mots-clés Agrovoc : Modèle, Télédétection, Phénologie, Analyse d'image, Terre cultivée, Couverture végétale, Plante de culture, Facteur climatique, Zone agroclimatique, Pratique culturale, Variété, Imagerie par satellite

Mots-clés géographiques Agrovoc : Mali

Classification Agris : U30 - Research methods
U10 - Computer science, mathematics and statistics
F01 - Crops
E90 - Agrarian structure

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Vintrou Elodie, CIRAD-PERSYST-UPR AIDA (REU)
  • Bégué Agnès, CIRAD-ES-UMR TETIS (FRA)
  • Baron Christian, CIRAD-ES-UMR TETIS (FRA)
  • Saad Alexandre
  • Lo Seen Danny, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0002-7773-2109
  • Traoré Seydou B., AGRHYMET (NER)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/573921/)

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