Vicarious calibration of the moderate-resolution imaging spectroradiometer airborne simulator thermal-infrared channels

Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU

The increase in annual wildfires in many areas of the world has triggered international efforts to deploy sensors on airborne and space platforms to map these events and understand their behaviour. During the summer of 2017, an airborne flight campaign acquired mid-wave infrared imagery over active wildfires in Northern Ontario, Canada. However, it suffered multiple position-based equipment issues, thus requiring a non-standard geocorrection methodology. This study presents the approach, which utilizes a two-step semi-automatic geocorrection process that outputs image mosaics from airborne infrared video input. The first step extracts individual video frames that are combined into orthoimages using an automatic image registration method. The second step involves the georeferencing of the imagery using pseudo-ground control points to a fixed coordinate systems. The output geocorrected datasets in units of radiance can then be used to derive fire products such as fire radiative power density (FRPD). Prior to the georeferencing process, the Root Mean Square Error (RMSE) associated with the imagery was greater than 200 m. After the georeferencing process was applied, an RMSE below 30 m was reported, and the computed FRPD estimations are within expected values across the literature. As such, this alternative geocorrection methodology successfully salvages an otherwise unusable dataset and can be adapted by other researchers that do not have access to accurate positional information for airborne infrared flight campaigns over wildfires.

A Calibration Procedure for Field and UAV-Based Uncooled Thermal Infrared Instruments

Thermal infrared cameras provide unique information on surface temperature that can benefit a range of environmental, industrial and agricultural applications. However, the use of uncooled thermal cameras for field and unmanned aerial vehicle (UAV) based data collection is often hampered by vignette effects, sensor drift, ambient temperature influences and measurement bias. Here, we develop and apply an ambient temperature-dependent radiometric calibration function that is evaluated against three thermal infrared sensors (Apogee SI-11(Apogee Electronics, Santa Monica, CA, USA), FLIR A655sc (FLIR Systems, Wilsonville, OR, USA), TeAx 640 (TeAx Technology, Wilnsdorf, Germany)). Upon calibration, all systems demonstrated significant improvement in measured surface temperatures when compared against a temperature modulated black body target. The laboratory calibration process used a series of calibrated resistance temperature detectors to measure the temperature of a black body at different ambient temperatures to derive calibration equations for the thermal data acquired by the three sensors. As a point-collecting device, the Apogee sensor was corrected for sensor bias and ambient temperature influences. For the 2D thermal cameras, each pixel was calibrated independently, with results showing that measurement bias and vignette effects were greatly reduced for the FLIR A655sc (from a root mean squared error (RMSE) of 6.219 to 0.815 degrees Celsius (℃)) and TeAx 640 (from an RMSE of 3.438 to 1.013 ℃) cameras. This relatively straightforward approach for the radiometric calibration of infrared thermal sensors can enable more accurate surface temperature retrievals to support field and UAV-based data collection efforts.

TOTAL HEMISPHERICAL EMISSIVITY OF PRE-OXIDIZED AND UN-OXIDIZED ZR-2.5Nb PRESSURE-TUBE MATERIALS AT 600 °C TO 1000 °C UNDER VACUUM

The emissivity of pre-oxidized and un-oxidized pressure-tube specimens has been measured at high temperatures under vacuum. The emissivity values of un-oxidized tube specimens decreased only slightly from 0.34 at 600 °C to 0.30 at 800 °C and changed gradually to 0.25 at 1000 °C. In comparison, the emissivity of pre-oxidized pressure-tube specimens decreased drastically from 0.70 at 600 °C to 0.35 at 800 °C, and gradually decreased to 0.25 at 1000 °C. The oxide layer of the pre-oxidized tube specimens dissolved into the metal matrix when heated to 700 °C and higher. Using these results, 2 linear correlations were obtained for emissivity with the oxide thickness measured by scanning electron microscopy and secondary ion mass spectroscopy analysis.

Analysis and rejection of systematic disturbances in hyperspectral remotely sensed images of the Earth

We discuss the appearance of systematic spatial and spectral patterns of noise in remotely sensed images as well as the possibility of mitigating the effects of these patterns on the data. We describe the structure of two simple theoretical models that predict the appearance of patterns of noise (mainly stripe noise). Moreover, two new algorithms that have been specifically developed to mitigate the noise patterns are described. The performance of the two algorithms is assessed by use of some hyperspectral images acquired by different kinds of airborne sensor. The algorithms show an unexpected ability to reject these noise patterns.