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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Landsat 9 Thermal Infrared Sensor 2 Characterization Plan Overview
摘要： Landsat 9 will continue the Landsat data record into its fifth decade with a near-copy build of Landsat 8 with launch scheduled for December 2020. The two instruments on Landsat 9 are Thermal Infrared Sensor-2 (TIRS-2) and Operational Land Imager-2 (OLI-2). TIRS-2 is a two-channel pushbroom imager with a 15-degree field of view that will have a 16-day measurement cadence from its nominal 705-km orbit altitude. Its carefully developed instrument performance requirements and associated characterization plan will result in stable and well-understood science-quality imagery that will be used for environmental, economic and legal applications. This paper will present a summary of the plan for TIRS-2 prelaunch characterization at the component, subsystem, and instrument level.
关键词： prelaunch characterization,calibration,Landsat 9,thermal infrared remote sensing,TIRS-2
更新于2025-09-23 15:22:29
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Hot monkey, cold reality: surveying rainforest canopy mammals using drone-mounted thermal infrared sensors
摘要： Animals of the rainforest canopies are often endangered by deforestation or hunting but are difficult to survey and study because of the inaccessibility of the treetops, combined with the visual camouflage of many species. Drone-based thermal sensors have the potential to overcome these hurdles by rapidly scanning large forested areas from above, detecting and mapping wildlife based on the contrast between their warm body temperatures and the cool tree canopies. We tested this concept by flying a drone-mounted thermal infrared radiometric sensor over the wildlife-rich rainforests of Barro Colorado Island, Panama. Arboreal mammals had body temperatures around 27°C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (23–25°C), but were difficult to detect by mid-morning, by which time the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone, but could be recognized from synchronized visual images taken during the daytime. Simultaneous drone and ground-based surveys of the same area proved that the aerial thermal camera did detect high-canopy species missed by the terrestrial observer, but that substantially more animals were detected by the human than by the drone. Because animal detection was so much better at night, when species ID was difficult, we suggest that future work could combine automated detection of animals from thermal infrared imagery with flash photography or IR illumination to enable species ID during nocturnal surveys. We conclude by discussing various logistical challenges that limit the utility of drone-based thermal infrared today, but that could be overcome by continued improvement of technology and collaboration with permitting agencies.
关键词： drone,mammals,wildlife surveys,thermal infrared sensors,rainforest canopy
更新于2025-09-23 15:21:21
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Temperature and Emissivity Inversion Accuracy of Spectral Parameter Changes and Noise of Hyperspectral Thermal Infrared Imaging Spectrometers
摘要： The emergence of hyperspectral thermal infrared imaging spectrometers makes it possible to retrieve both the land surface temperature (LST) and the land surface emissivity (LSE) simultaneously. However, few articles focus on the problem of how the instrument?s spectral parameters and instrument noise level affect the LST and LSE inversion errors. In terms of instrument development, this article simulated three groups of hyperspectral thermal infrared data with three common spectral parameters and each group of data includes tens of millions of simulated radiances of 1525 emissivity curves with 17 center wavelength shift ratios, 6 full width at half maximum (FWHM) change ratios and 6 noise equivalent differential temperatures (NEDTs) under 15 atmospheric conditions with 6 object temperatures, inverted them by two temperature and emissivity separation methods (ISSTES and ARTEMISS), and analyzed quantitatively the effects of the spectral parameters change and noise of an instrument on the LST and LSE inversion errors. The results show that: (1) center wavelength shifts and noise affect the inversion errors strongly, while FWHM changes affect them weakly; (2) the LST and LSE inversion errors increase with the center wavelength shift ratio in a quadratic function and increase with FWHM change ratio slowly and linearly for both the inversion methods, however they increase with NEDT in an S‐curve for ISSTES while they increase with NEDT slightly and linearly for ARTEMISS. During the design and development of a hyperspectral thermal infrared instrument, it is highly recommended to keep the potential center wavelength shift within 1 band and keep NEDT within 0.1K (corresponding LST error < 1K and LSE error < 0.015) for normal applications and within 0.03K (corresponding LST error < 0.5K and LSE error < 0.01) for better application effect and level.
关键词： inversion error,hyperspectral thermal infrared,FWHM change,instrument noise,center wavelength shift,temperature and emissivity separation
更新于2025-09-23 15:21:01
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[IEEE 2019 Sixteenth International Conference on Wireless and Optical Communication Networks (WOCN) - Bhopal, India (2019.12.19-2019.12.21)] 2019 Sixteenth International Conference on Wireless and Optical Communication Networks (WOCN) - WIMAX Smart Grid Communication network for a Substation
摘要： This multidisciplinary paper reports on a research application-led study for predicting atmospheric attenuation, and tries to bridge the knowledge gap between applied engineering and atmospheric sciences. As a useful comparative baseline, this paper focuses specifically on atmospheric attenuation under pristine conditions, over the extended terahertz spectrum. Three well-known simulation software packages (‘HITRAN on the Web’, MODTRAN R(cid:13)4, and LBLRTM) are compared and contrasted. Techniques used for modeling atmospheric attenuation have been applied to investigate the resilience of (ultra-)wide fractional bandwidth applications to the effects of molecular absorption. Two extreme modeling scenarios are investigated: horizontal path links at sea level and Earth-space path links. It is shown by example that a basic software package (‘HITRAN on the Web’) can give good predictions with the former, whereas sophisticated simulation software (LBLRTM) is required for the latter. Finally, with molecular emission included, carrier-to-noise ratio fade margins can be calculated for the effects of line broadening due to changes in macroscopic atmospheric conditions with sub-1-THz ultra-narrow fractional bandwidth applications. Outdoors can be far from pristine, with additional atmospheric contributions only briefly introduced here; further discussion is beyond the scope of this paper, but relevant references have been cited.
关键词： molecular emission,atmospheric attenuation,carrier-to-noise,MODTRAN R(cid:13),THz Torch,HITRAN,thermal infrared,transmittance,THz,LBLRTM,molecular absorption
更新于2025-09-23 15:19:57
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Assessing the potential of drone-based thermal infrared imagery for quantifying river temperature heterogeneity
摘要： 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 is 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.
关键词： river temperature,thermal infrared,temperature heterogeneity,drones,unoccupied aerial systems,TIR,remote sensing,climate change
更新于2025-09-19 17:15:36
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Validation of low-cost smartphone-based thermal camera for diabetic foot assessment
摘要： Infrared thermal imaging (IR) is not yet routinely implemented for early detection of diabetic foot ulcers (DFU), despite proven clinical effectiveness. Low-cost, smartphone-based IR-cameras are now available and may lower the threshold for implementation, but the quality of these cameras is unknown. We aim to validate a smartphone-based IR-camera against a high-end IR-camera for diabetic foot assessment. Methods: We acquired plantar IR images of feet of 32 participants with a current or recently healed DFU with the smartphone-based FLIR-One and the high-end FLIR-SC305. Contralateral temperature differences of the entire plantar foot and nine pre-specified regions were compared for validation. Intra-class correlations coefficient (ICC(3,1)) and Bland-Altman plots were used to test agreement. Clinical validity was assessed by calculating statistical measures of diagnostic performance. Results: Almost perfect agreement was found for temperature measurements in both the entire plantar foot and the combined pre-specified regions, respectively, with ICC values of 0.987 and 0.981, Bland-Altman plots’ mean Δ=-0.14 and Δ=-0.06. Diagnostic accuracy showed 94% and 93% sensitivity, and 86% and 91% specificity. Conclusions: The smartphone-based IR-camera shows excellent validity for diabetic foot assessment.
关键词： Smartphone,Thermal Infrared,Diabetes Mellitus,Diabetic Foot,Foot Ulcer,Temperature
更新于2025-09-19 17:15:36
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Thermal face segmentation based on circular shortest path
摘要： Recently, research on thermal infrared human face analysis grows rapidly. However, due to the low contrast and limited information, human face in thermal infrared images is difficult to segment precisely. To overcome these shortcomings of thermal images, we propose an improved circular shortest path method in this paper. In our method, the proposed gradient based cost function enhances the gradient information and extracts detail of the original image. In addition, we propose a shape constraint by using ellipse derivative in the cost function. The constraint helps the contour to conform to the real human face. Moreover, the proposed certainty penalty term and straight path penalty term restrain the effect of the local minima regions and improve the robustness of our method. Our method could effectively extract the precise human face contour and thus segment the complete human face. Experimental results show that our method performs well for thermal infrared face segmentation, in both visual and quantitative ways.
关键词： thermal infrared face segmentation,shape constraint,Image segmentation,circular shortest path
更新于2025-09-19 17:15:36
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Hierarchical spatial-aware Siamese network for thermal infrared object tracking
摘要： Most thermal infrared (TIR) tracking methods are discriminative, treating the tracking problem as a classification task. However, the objective of the classifier (label prediction) is not coupled to the objective of the tracker (location estimation). The classification task focuses on the between-class difference of the arbitrary objects, while the tracking task mainly deals with the within-class difference of the same objects. In this paper, we cast the TIR tracking problem as a similarity verification task, which is coupled well to the objective of the tracking task. We propose a TIR tracker via a Hierarchical Spatial-aware Siamese Convolutional Neural Network (CNN), named HSSNet. To obtain both spatial and semantic features of the TIR object, we design a Siamese CNN that coalesces the multiple hierarchical convolutional layers. Then, we propose a spatial-aware network to enhance the discriminative ability of the coalesced hierarchical feature. Subsequently, we train this network end to end on a large visible video detection dataset to learn the similarity between paired objects before we transfer the network into the TIR domain. Next, this pre-trained Siamese network is used to evaluate the similarity between the target template and target candidates. Finally, we locate the candidate that is most similar to the tracked target. Extensive experimental results on the benchmarks VOT-TIR 2015 and VOT-TIR 2016 show that our proposed method achieves favorable performance compared to the state-of-the-art methods.
关键词： Thermal infrared tracking,Similarity verification,Spatial-aware,Siamese convolutional neural network
更新于2025-09-19 17:15:36
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Thermal Infrared Imagery Integrated with Terrestrial Laser Scanning and Particle Tracking Velocimetry for Characterization of Landslide Model Failure
摘要： A laboratory model test is an effective method for studying landslide risk mitigation. In this study, thermal infrared (TIR) imagery, a modern no-contact technique, was introduced and integrated with terrestrial laser scanning (TLS) and particle tracking velocimetry (PTV) to characterize the failure of a landslide model. The characteristics of the failure initiation, motion, and region of interest, including landslide volume, deformation, velocity, surface temperature changes, and anomalies, were detected using the integrated monitoring system. The laboratory test results indicate that the integrated monitoring system is expected to be useful for characterizing the failure of landslide models. The preliminary results of this study suggest that a change in the relative TIR signal (?TIR) can be a useful index for landslide detection, and a decrease in the average value of the temperature change (?TIR) can be selected as a precursor to landslide failure.
关键词： landslide failure,thermal infrared imagery,terrestrial laser scanning,particle tracking velocimetry
更新于2025-09-16 10:30:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Long-Wave Hyperspectral Imaging for Lithological Mapping: A Case Study
摘要： Hyperspectral long-wave infrared imaging (LWIR HSI) adds a promising complement to visible, near infrared, and shortwave infrared (VNIR and SWIR) HSI data in the field of mineral mapping. It enables characterization of rock-forming minerals such as silicates and carbonates, which show no detectable or extremely weak features in VNIR and SWIR. In the last decades, there has been a steady increase of publications on satellite, aerial, and laboratory LWIR data. However, the application of LWIR HSI for ground-based, close-range remote sensing of vertical geological outcrops is sparsely researched and will be the focus of the current study. We present a workflow for acquisition, mosaicking, and radiometric correction of LWIR HSI data. We demonstrate the applicability of this workflow using a case study from a gravel quarry in Germany. Library spectra are used for spectral unmixing and mapping of the main lithological units, which are validated using sample X-ray diffraction (XRD) and thin section analysis as well as FTIR point spectrometer data.
关键词： thermal infrared,mineral mapping,hyperspectral,long wave infrared
更新于2025-09-10 09:29:36