Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/120342
Title: Ndoi, A Novel Oil Spectral Index: Comparisons and Results
Authors: Pérez García, Ámbar 
Horstrand, Pablo 
Lopez, Jose Fco 
UNESCO Clasification: 220918 Fotometría
Keywords: Hyperspectral Imaging
Monitoring Of The Environment
Oil Spill
Remote Sensing
Spectral Indices
Issue Date: 2022
Conference: 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022 
Abstract: Spectral indices provide valuable information about oil spill characteristics, making them an essential tool to achieve effective action plans. In this work, the authors present new features that make NDOI a robust and suitable index for detecting coastal spills. Its main characteristics are that it obviates suspended sand in coastal regions and makes use of simple operations using VNIR spectral bands available in commercial sensors. The index is compared with spectral indices from the state-of-the-art and a radar image for the Deepwater Horizon accident occurred on 2010 in Mexico. An assessment is made based on the confusion matrix resulting from the k-nearest neighbours (kNN) classification, as well as the accuracy and the Fl-score metrics. The results consolidate NDOI in spill monitoring due to its balanced trade-off among its performance and its convenient implementation.
URI: http://hdl.handle.net/10553/120342
ISBN: 9781665470698
ISSN: 2158-6276
DOI: 10.1109/WHISPERS56178.2022.9955062
Source: Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing[ISSN 2158-6276],v. 2022-September, (Enero 2022)
Appears in Collections:Actas de congresos
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