Article (Scientific journals)
Advancing Blackmore’s methodology to delineate management zones from Sentinel 2 images
Lenoir, Arthur; Vandoorne, Bertrand; Siah, Ali et al.
2024In Precision Agriculture
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Keywords :
Management zones; NDVI; Sentinel-2; Spatio-temporal delineation; Winter-wheat; Agricultural and Biological Sciences (all); General Agricultural and Biological Sciences
Abstract :
[en] Improving agricultural nitrogen management is one of the key objectives of the recent Green Deal in Europe. Current technological developments in agriculture offer new opportunities to improve nitrogen fertilization practices. The aim of this study was to adapt to Sentinel-2 data a proven delineation method initially developed for yield maps, in order to facilitate precise nitrogen management by farmers. The study was conducted in two steps. Firstly, an analysis at annual level was conducted to assess the relationship between vegetation indices and yield at the subfield scale, for different sensing period. The second step consisted in performing a pluri- annual analysis through the delineation of management zones and compare the results achieved from yield maps and from NDVI maps. Among different vegetation indices, NDVI proved to be an interesting candidate for subfield detection of yield variation, specifically when the index was sensed was sensed around the second half of May. In this area, this period usually corresponds to phenological development between the flag leaf stage and heading stage, just prior the initiation of winter wheat flowering. Using NDVI maps within Blackmore’s delineation approach instead of yield maps. Allowed to reach an accuracy of 69% on zone classification. However, as yields and NDVI distribution do not respond to similar statistical distributions, we considered that the delineation threshold used to differentiate high from low yielding zones had to be adapted. The adaptation of the “performance threshold” in favor of the median NDVI, made it possible to achieve a higher accuracy (71%) of the delineation. But above all, the improvement lies also in a more robust satellite-based delineation.
Disciplines :
Agriculture & agronomy
Author, co-author :
Lenoir, Arthur  ;  Université de Liège - ULiège > TERRA Research Centre
Vandoorne, Bertrand;  Joint Research Unit 1158 BioEcoAgro, Junia, Université de Lille, Université de Liège, UPJV, Université d’Artois, ULCO, INRAE, Lille Cedex, France
Siah, Ali;  Joint Research Unit 1158 BioEcoAgro, Junia, Université de Lille, Université de Liège, UPJV, Université d’Artois, ULCO, INRAE, Lille Cedex, France
Dumont, Benjamin  ;  Université de Liège - ULiège > TERRA Research Centre > Plant Sciences
Language :
English
Title :
Advancing Blackmore’s methodology to delineate management zones from Sentinel 2 images
Alternative titles :
[fr] Adapter la méthodologie de Blackmore pour délimiter des zones de management à partir d'images satellites Sentinel 2
Publication date :
February 2024
Journal title :
Precision Agriculture
ISSN :
1385-2256
eISSN :
1573-1618
Publisher :
Springer
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 15 March 2024

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