PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data

Thermal-infrared remote sensing is used to monitor and study hazardous volcanic phenomena. Thermal cameras are often used by monitoring centers and laboratories. A physical comprehension of their behavior is needed to perform quantitative measurements, which are strongly dependent on camera features...

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Main Authors: Benedetta Calusi, Daniele Andronico, Emilio Pecora, Emilio Biale, Matteo Cerminara
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/24/4056
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spelling doaj-6d81cc1f9325468fa46cd61f9da1e25b2020-12-12T00:03:47ZengMDPI AGRemote Sensing2072-42922020-12-01124056405610.3390/rs12244056PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera DataBenedetta Calusi0Daniele Andronico1Emilio Pecora2Emilio Biale3Matteo Cerminara4Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, 56125 Pisa, ItalyIstituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, 95032 Catania, ItalyIstituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, 95032 Catania, ItalyIstituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, 95032 Catania, ItalyIstituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, 56125 Pisa, ItalyThermal-infrared remote sensing is used to monitor and study hazardous volcanic phenomena. Thermal cameras are often used by monitoring centers and laboratories. A physical comprehension of their behavior is needed to perform quantitative measurements, which are strongly dependent on camera features and settings. This makes it possible to control the radiance measurements related to volcanic processes and, thus, to detect thermal anomalies, validate models, and extract source parameters. We review the theoretical background related to the camera behavior beside the main features affecting thermal measurements: Atmospheric transmission, object emissivity and reflectivity, camera characteristics, and external optics. We develop a Python package, PythTirCam-1.0, containing pyTirTran, a radiative transfer model based on the HITRAN database and the camera spectral response. This model is compared with the empirical algorithm implemented into a commercial camera. These two procedures are validated using a simple experiment involving pyTirConv, an algorithm developed to recover the radiometric thermal data from compressed images collected by monitoring centers. Python scripts corresponding to the described methods are provided as open-source code. This study can be applied to a wide variety of applications and, specifically, to different volcanic processes, from earth and space.https://www.mdpi.com/2072-4292/12/24/4056volcano monitoringimage processingthermal imagingeruption dataatmospheric transmissionHITRAN database
collection DOAJ
language English
format Article
sources DOAJ
author Benedetta Calusi
Daniele Andronico
Emilio Pecora
Emilio Biale
Matteo Cerminara
spellingShingle Benedetta Calusi
Daniele Andronico
Emilio Pecora
Emilio Biale
Matteo Cerminara
PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data
Remote Sensing
volcano monitoring
image processing
thermal imaging
eruption data
atmospheric transmission
HITRAN database
author_facet Benedetta Calusi
Daniele Andronico
Emilio Pecora
Emilio Biale
Matteo Cerminara
author_sort Benedetta Calusi
title PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data
title_short PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data
title_full PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data
title_fullStr PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data
title_full_unstemmed PyTirCam-1.0: A Python Model to Manage Thermal Infrared Camera Data
title_sort pytircam-1.0: a python model to manage thermal infrared camera data
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-12-01
description Thermal-infrared remote sensing is used to monitor and study hazardous volcanic phenomena. Thermal cameras are often used by monitoring centers and laboratories. A physical comprehension of their behavior is needed to perform quantitative measurements, which are strongly dependent on camera features and settings. This makes it possible to control the radiance measurements related to volcanic processes and, thus, to detect thermal anomalies, validate models, and extract source parameters. We review the theoretical background related to the camera behavior beside the main features affecting thermal measurements: Atmospheric transmission, object emissivity and reflectivity, camera characteristics, and external optics. We develop a Python package, PythTirCam-1.0, containing pyTirTran, a radiative transfer model based on the HITRAN database and the camera spectral response. This model is compared with the empirical algorithm implemented into a commercial camera. These two procedures are validated using a simple experiment involving pyTirConv, an algorithm developed to recover the radiometric thermal data from compressed images collected by monitoring centers. Python scripts corresponding to the described methods are provided as open-source code. This study can be applied to a wide variety of applications and, specifically, to different volcanic processes, from earth and space.
topic volcano monitoring
image processing
thermal imaging
eruption data
atmospheric transmission
HITRAN database
url https://www.mdpi.com/2072-4292/12/24/4056
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