A broad-area method for the Diurnal characterisation of upwelling medium wave infrared radiation

Hally, B, Wallace, L, Reinke, K and Jones, S 2017, 'A broad-area method for the Diurnal characterisation of upwelling medium wave infrared radiation', Remote Sensing, vol. 9, no. 2, 167, pp. 1-16.

Document type: Journal Article
Collection: Journal Articles

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Title A broad-area method for the Diurnal characterisation of upwelling medium wave infrared radiation
Author(s) Hally, B
Wallace, L
Reinke, K
Jones, S
Year 2017
Journal name Remote Sensing
Volume number 9
Issue number 2
Article Number 167
Start page 1
End page 16
Total pages 16
Publisher MDPI
Abstract Fire detection from satellite sensors relies on an accurate estimation of the unperturbed state of a target pixel, from which an anomaly can be isolated. Methods for estimating the radiation budget of a pixel without fire depend upon training data derived from the location's recent history of brightness temperature variation over the diurnal cycle, which can be vulnerable to cloud contamination and the effects of weather. This study proposes a new method that utilises the common solar budget found at a given latitude in conjunction with an area's local solar time to aggregate a broad-area training dataset, which can be used to model the expected diurnal temperature cycle of a location. This training data is then used in a temperature fitting process with the measured brightness temperatures in a pixel, and compared to pixel-derived training data and contextual methods of background temperature determination. Results of this study show similar accuracy between clear-sky medium wave infrared upwelling radiation and the diurnal temperature cycle estimation compared to previous methods, with demonstrable improvements in processing time and training data availability. This method can be used in conjunction with brightness temperature thresholds to provide a baseline for upwelling radiation, from which positive thermal anomalies such as fire can be isolated.
Subject Photogrammetry and Remote Sensing
Keyword(s) Fire detection
Upwelling radiation
Diurnal variation
Training data
Geostationary sensors
DOI - identifier 10.3390/rs9020167
Copyright notice © 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
ISSN 2072-4292
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