Assessing the potential of drone-based thermal infrared imagery for quantifying river temperature heterogeneity

© 2019 Crown copyright. Hydrological Processes © 2019 John Wiley & Sons, Ltd. Climate change is altering river temperature regimes, modifying the dynamics of temperature-sensitive fishes. The ability to map river temperature is therefore important for understanding the impacts of future warming. Thermal infrared (TIR) remote sensing has proven effective for river temperature mapping, but TIR surveys of rivers remain expensive. Recent drone-based TIR systems present a potential solution to this problem. However, information regarding the utility of these miniaturised systems for surveying rivers is limited. Here, we present the results of several drone-based TIR surveys conducted with a view to understanding their suitability for characterising river temperature heterogeneity. We find that drone-based TIR data are able to clearly reveal the location and extent of discrete thermal inputs to rivers, but thermal imagery suffers from temperature drift-induced bias, which prevents the extraction of accurate temperature data. Statistical analysis of the causes of this drift reveals that drone flight characteristics and environmental conditions at the time of acquisition explain ~66% of the variance in TIR sensor drift. These results shed important light on the factors influencing drone-based TIR data quality and suggest that further technological development is required to enable the extraction of robust river temperature data. Nonetheless, this technology represents a promising approach for augmenting in situ sensor capabilities and improved quantification of advective inputs to rivers at intermediate spatial scales between point measurements and “conventional” airborne or satellite remote sensing

A highly digital microbolometer ROIC employing a novel event-based readout and two-step time to digital converters

Uncooled infrared imaging systems are a light weight and low cost alternative to their cooled counterparts. Uncooled microbolometer IR focal plane arrays (IRFPAs) for applications such as medical imaging, thermography, night vision, surveillance and industrial process control have recently been under focus. These systems have small pixel pitches ( 250 K). Low NETD demands excellent microbolometer and readout noise performance. If sensitive analog circuits, driving long metal interconnects, are part of the predigitization readout channel, this necessitates the use of power consuming buffers, potentially in conjunction with noise cancellation circuits that result in power and area overhead. Thus re-thinking at the architectural level is crucial to meet these demands. Accordingly, in this thesis a column-parallel readout architecture for frame synchronous microbolometer imagers is proposed that enables low power operation by employing a time mode digitizer. The proposed readout circuit is based on a bridge type detector network with active and reference microbolometers and employs a capacitive transimpedance amplifier (CTIA) incorporating a novel two-step integration mechanism. By using a modified reset scheme in the CTIA, a forward ramp is initiated at the input side followed by the conventional backward integrated ramp at the output. This extends the measurement interval and improves signal-to-noise ratio (SNR). A synchronous counter based TDC measures this interval providing robust digitization. This technique also provides a way of compensating for self-heating effects. Being highly digital, the proposed architecture offers robust frontend processing and achieves a per channel power consumption of 66 µW, which is considerably lower than the most recently reported designs, while maintaining better than 10mK readout NETD

Thermographic Control of Pediatric Dental Patients During the SARS-CoV-2 Pandemics Using Smartphones

Objective: To evaluate the reliability of infrared (IR) thermal camera connected to smartphones, already used in medicine for diagnostic purposes, as an easy tool for access screening to pediatric dentistry services. Material and Methods: After the preventive telephone triage, thirty orthodontic patients (7-13 years) underwent temperature measurement in the office with two no-contact IR devices: forehead digital thermometer and thermal-camera connected to a smartphone (reference areas: forehead, inner canthi, ears). Measurements were compared and differences were statistically investigated with T student’s test (p<0.01). Results: Forehead digital thermometer temperatures were superimposable to those recorded in ear areas and inner canthi with the thermal camera connected to a smartphone. Differences were not statistically significant even in comparison between the sexes. Forehead temperature values detected with a thermal camera are lower than those detected with a digital forehead thermometer. Conclusion: Thermal camera on a smartphone could be reliable in measuring body temperature. Mobile thermographic values of ears and inner canthi areas can be used as an alternative to forehead digital thermometer measurements. Further applications in pediatric dentistry of thermography on smartphones should be examined

Performance evaluation of an uncooled infrared array camera.

This thesis describes work carried out on an uncooled pyroelectric infrared array camera with the aim of improving performance and increasing its value in commercial markets. The image processing circuitry of the camera was bypassed and replaced by a purpose built 14 bit digitiser and processing algorithms running on a PC. The constructed digitiser was shown to meet the performance needs of the detector. A model was developed for the camera's performance, taking into account the nature of the chopped pyroelectric detector, and the wavelength passband of the camera. The model suggested that placing a temperature sensor close to the chopper blade of the camera would allow radiometric measurements to be made with the camera. Experimental results verified the predicted camera behaviour and radiometric performance was found to be accurate to within +1.5K when imaging flat fields in a stable thermal environment. Significant distortion and radiometric errors were found when imaging high contrast scenes an algorithm was written to correct this distortion. The algorithm was shown to perform well, drastically reducing distortion and improving radiometric accuracy in all scenes tested. The source of the distortion was not identified, but it is thought to be unrelated to the physical behaviour of the pyroelectric array. The performance of the modified camera is discussed in relation to the current state of the art, and in relation to the performance needs of existing and emerging infrared imaging markets

Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging

Developing thermal infrared imaging systems for monitoring spatial crop temperatures for precision agriculture applications

Master of ScienceDepartment of Biological & Agricultural EngineeringAjay ShardaPrecise water application conserves resources, reduces costs, and optimizes plant performance and quality. Existing irrigation scheduling utilizes single, localized measurements that do not account for spatial crop water need; but, quick, single-point sensors are impractical for measuring discrete variations across large coverage areas. Thermography is an alternate approach for measuring spatial temperatures to quantify crop health. However, agricultural studies using thermography are limited due to previous camera expense, unfamiliar use and calibration, software for image acquisition and high-throughput processing specifically designed for thermal imagery mapping and monitoring spatial crop water need. Recent advancements in thermal detectors and sensing platforms have allowed uncooled thermal infrared (TIR) cameras to become suited for crop sensing. Therefore, a small, lightweight thermal infrared imaging system (TIRIS) was developed capable of radiometric temperature measurements. One-time (OT) and real-time (RT) radiometric calibrations methods were developed and validated for repeatable, temperature measurements while compensating for strict environmental conditions within a climate chamber. The Tamarisk® 320 and 640 analog output yielded a measurement accuracy of ±0.82°C or 0.62ºC with OT and RT radiometric calibration, respectively. The Tamarisk® 320 digital output yielded a measurement accuracy of ±0.43 or 0.29ºC with OT and RT radiometric calibration, respectively. Similarly, the FLIR® Tau 2 analog output yielded a measurement accuracy of ±0.87 or 0.63ºC with OT and RT radiometric calibration, respectively. A TIRIS was then built for high-throughput image capture, correction, and processing and RT environmental compensation for monitoring crop water stress within a greenhouse and temperature mapping aboard a small unmanned aerial systems (sUAS). The greenhouse TIRIS was evaluated by extracting plant temperatures for monitoring full-season crop water stress index (CWSI) measurements. Canopy temperatures demonstrated that CWSI explained 82% of the soil moisture variation. Similarly, validation aboard a sUAS provided radiometric thermal maps with a ±1.38°C (α=0.05) measurement accuracy. Due to the TIR cameras’ performance aboard sUAS and greenhouse platforms, a TIRIS provides unparalleled spatial coverage and measurement accuracy capable of monitoring subtle crop stress indicators. Further studies need to be conducted to produce spatial crop water stress maps at scales necessary for variable rate irrigation systems

Hyperspectral, thermal and LiDAR remote sensing for red band needle blight detection in pine plantation forests

PhD ThesisClimate change indirectly affects the distribution and abundance of forest insect pests and pathogens, as well as the severity of tree diseases. Red band needle blight is a disease which has a particularly significant economic impact on pine plantation forests worldwide, affecting diameter and height growth. Monitoring its spread and intensity is complicated by the fact that the diseased trees are often only visible from aircraft in the advanced stages of the epidemic. There is therefore a need for a more robust method to map the extent and severity of the disease. This thesis examined the use of a range of remote sensing techniques and instrumentation, including thermography, hyperspectral imaging and laser scanning, for the identification of tree stress symptoms caused by the onset of red band needle blight. Three study plots, located in a plantation forest within the Loch Lomond and the Trossachs National Park that exhibited a range of red band needle blight infection levels, were established and surveyed. Airborne hyperspectral and LiDAR data were acquired for two Lodgepole pine stands, whilst for one Scots pine stand, airborne LiDAR and Unmanned Aerial Vehicle-borne (UAV-borne) thermal imagery were acquired alongside leaf spectroscopic measurements. Analysis of the acquired data demonstrated the potential for the use of thermographic, hyperspectral and LiDAR sensors for detection of red band needle blight-induced changes in pine trees. The three datasets were sensitive to different disease symptoms, i.e. thermography to alterations in transpiration, LiDAR to defoliation, and hyperspectral imagery to changes in leaf biochemical properties. The combination of the sensors could therefore enhance the ability to diagnose the infection.Natural Environment Research Council (NERC) for funding this PhD program (studentship award 1368552) and providing access to specialist equipment through a Field Spectroscopy Facility loan (710.114). I would like to thank NERC Airborne Research Facility for providing airborne data (grant: GB 14-04) that made the PhD a challenge, to say the least. My sincere gratitude goes to the Douglas Bomford Trust for providing additional funds, which allowed for completion of the UAV-borne part of this research

Imaging by Detection of Infrared Photons Using Arrays of Uncooled Micromechanical Detectors

The objective of this dissertation was to investigate the possibility of uncooled infrared imaging using arrays of optically-probed micromechanical detectors. This approach offered simplified design, improved reliability and lower cost, while attaining the performance approaching that contemporary uncooled imagers. Micromechanical infrared detectors undergo deformation due to the bimetallic effect when they absorb infrared photons. The performance improvements were sought through changes in structural design such as modification and simplification of detector geometry as well as changes in the choice of materials. Detector arrays were designed, fabricated and subsequently integrated into the imaging system and relevant parameters, describing the sensitivity and signal-to-noise ratio, were characterized. The values of these parameters were compared to values published for other uncooled micromechanical detectors and commercial uncooled detectors. Several designs have been investigated. The first design was made of standard materials for this type of detectors - silicon nitride and gold. The design utilized changes in detector geometry such as reduction in size and featured an optical resonant cavity between the detector and the substrate on which arrays were built. This design provided decrease in levels of noise equivalent temperature difference (NETD) to as low as 500 mK. The NETD parameter limits the lowest temperature gradient on the imaged object that can be resolved by the imaging device. The second design used silicon dioxide and aluminum, materials not yet fully investigated. It featured a removed substrate beneath each detector in the array, to allow unobstructed transmission of incoming IR radiation and improve the thermal isolation of the detector. Second design also featured an amorphous silicon layer between silicon dioxide and aluminum layers, to serve as an optical resonant cavity. The NETD levels as low as 120 mK have been achieved. The only difference between the third and the second design was the modification of the geometry to minimize the noise. Successfully obtained thermal images and improved NETD values, approaching those of modern uncooled imagers (20 mK for commercial bolometer-based detectors), confirm the viability of this approach. With further improvements, this approach has a potential of becoming a lowcost alternative for uncooled infrared imaging