Outlier Detection at the Parcel-Level in Wheat and Rapeseed Crops Using Multispectral and SAR Time Series

Outlier Detection at the Parcel-Level in Wheat and Rapeseed Crops Using Multispectral and SAR Time Series

This paper studies the detection of anomalous crop development at the parcel-level based on an unsupervised outlier detection technique. The experimental validation is conducted on rapeseed and wheat parcels located in Beauce (France). The proposed methodology consists of four sequential steps: (1)...

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Bibliographic Details
Main Authors: Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit, Denis Kouamé, Guillaume Rieu, Jean-Yves Tourneret
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
crop monitoring
Sentinel-1
Sentinel-2
isolation forest
anomaly detection
unsupervised
Online Access:https://www.mdpi.com/2072-4292/13/5/956

Internet

https://www.mdpi.com/2072-4292/13/5/956

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