Thermal Infrared Image Data Research Articles

Mapping rock forming minerals at Boundary Canyon, Death Valey National Park, California, using aerial SEBASS thermal infrared hyperspectral image data

Aerial spatially enhanced broadband array spectrograph system (SEBASS) long-wave infrared (LWIR) hyperspectral image data were used to map the distribution of rock-forming minerals indicative of sedimentary and meta-sedimentary lithologies around Boundary Canyon, Death Valley, California, USA. Collection of data over the Boundary Canyon detachment fault (BCDF) facilitated measurement of numerous lithologies representing a contact between the relatively unmetamorphosed Grapevine Mountains allochthon and the metamorphosed core complex of the Funeral Mountains autochthon. These included quartz-rich sandstone, quartzite, conglomerate, and alluvium; muscovite-rich schist, siltstone, and slate; and carbonate-rich dolomite, limestone, and marble, ranging in age from late Precambrian to Quaternary. Hyperspectral data were reduced in dimensionality and processed to statistically identify and map unique emissivity spectra endmembers. Some minerals (e.g., quartz and muscovite) dominate multiple lithologies, resulting in a limited ability to differentiate them. Abrupt variations in image data emissivity amongst pelitic schists corresponded to amphibolite; these rocks represent gradation from greenschist- to amphibolite-metamorphic facies lithologies. Although the full potential of LWIR hyperspectral image data may not be fully utilized within this study area due to lack of measurable spectral distinction between rocks of similar bulk mineralogy, the high spectral resolution of the image data was useful in characterizing silicate- and carbonate-based sedimentary and meta-sedimentary rocks in proximity to fault contacts, as well as for interpreting some mineral mixtures.

Study of thermal IR phenomena associated with 27 February 2010 Chile Mw 8.8 earthquake using MODIS data

Stresses acting on fault systems before major earthquakes can produce thermal anomalies; these abnormalities can be observed using multi-sensor satellite data. Moderate resolution spectro-radiometer on board the terra and aqua satellites can provide thermal infrared (TIR) imaging data for land and ocean. These TIR data have recorded short-lived thermal anomaly prior to major earthquakes. It is suggested by others that these electromagnetic (EM) phenomena relate to stress build up before earthquakes. The objective of this study is to find an association between spatial extent and temporal evolution of thermal anomalies and known major earthquakes near the boundary of Nazca plate and South American plate. Our approach is to map the TIR transient fields from polar orbiting satellites and analysing those data using time series temperature plots to detect the abnormal thermal trends before the earthquake. This study concentrated on marine earthquakes to detect the changes in both land and ocean before seismic activity.

Self-Adaptive Gradient-Based Thresholding Method for Coal Fire Detection Using ASTER Thermal Infrared Data, Part I: Methodology and Decadal Change Detection

Coal fires that are induced by natural spontaneous combustion or result from human activities occurring on the surface and in underground coal seams destroy coal resources and cause serious environmental degradation. Thermal infrared image data, which directly measure surface temperature, can be an important tool to map coal fires over large areas. As the first of two parts introducing our coal fire detection method, this paper proposes a self-adaptive threshold-based approach for coal fire detection using ASTER thermal infrared data: the self-adaptive gradient-based thresholding method (SAGBT). This method is based on an assumption that the attenuation of temperature along the coal fire’s boundaries generates considerable numbers of spots with extremely high gradient values. The SAGBT method applied mathematical morphology thinning to skeletonize the potential high gradient buffers into the extremely high gradient lines, which provides a self-adaptive mechanism to generate thresholds according to the thermal spatial patterns of the images. The final threshold was defined as an average temperature value reading from the high temperature buffers (segmented by 1.0 σ from the mean) and along a sequence of extremely high gradient lines (thinned from the potential high gradient buffers and segmented within the lower bounds, ranging from 0.5 σ to 1.5 σ and with an upper bound of 3.2 σ, where σ is the standard deviation), marking the coal fire areas. The SAGBT method used the basic outer boundary of the coal-bearing strata to simply exclude false alarms. The intermediate thresholds reduced the coupling with the temperature and converged by changing the potential high gradient buffers. This simple approach can be economical and accurate in identifying coal fire areas. In addition, it allows for the identification of thresholds using multiple ASTER TIR scenes in a consistent and uniform manner, and supports long-term coal fire change analyses using historical images in local areas. This paper focuses on the introduction of the methodology. Furthermore, an improvement to SAGBT is proposed. In a subsequent paper, subtitled “Part 2, Validation and Sensitivity Analysis,” we address satellite-field simultaneous observations and report comparisons between the retrieved thermal anomalies and field measurements in different aspects to prove that the coal fires are separable by the SAGBT method. These comparisons allowed us to estimate the accuracy and biases of the SAGBT method. As an application of the SAGBT, a relationship between coal fires’ decadal variation and coal production was also examined. Our work documented a total area increase in the beginning of 2003, which correlates with increased mining activities and the rapid increase of energy consumption in China during the decade (2001–2011). Additionally, a decrease in the total coal fire area is consistent with the nationally sponsored fire suppression efforts during 2007–2008. It demonstrated the applicability of SAGBT method for long-term change detection with multi-temporal images.

Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data

Soil and vegetation component temperatures in non-isothermal pixels encapsulate more physical meaning and are more applicable than composite temperatures. The component temperatures however are difficult to be obtained from thermal infrared (TIR) remote sensing data provided by single view angle observations. Here, we present a land surface temperature and albedo (T-α) space approach combined with the mono-surface energy balance (SEB-1S) model to derive soil and vegetation component temperatures. The T-α space can be established from visible and near infrared (VNIR) and TIR data provided by single view angle observations. This approach separates the soil and vegetation component temperatures from the remotely sensed composite temperatures by incorporating soil wetness iso-lines for defining equivalent soil temperatures; this allows vegetation temperatures to be extracted from the T-α space. This temperature separation methodology was applied to advanced scanning thermal emission and reflection radiometer (ASTER) VNIR and high spatial resolution TIR image data in an artificial oasis area during the entire growing season. Comparisons with ground measurements showed that the T-α space approach produced reliable soil and vegetation component temperatures in the study area. Low root mean square error (RMSE) values of 0.83 K for soil temperatures and 1.64 K for vegetation temperatures, respectively, were obtained, compared to component temperatures measurements from a ground-based thermal camera. These results support the use of soil wetness iso-lines to derive soil surface temperatures. It was also found that the estimated vegetation temperatures were extremely close to the near surface air temperature observations when the landscape is well watered under full vegetation cover. More robust soil and vegetation temperature estimates will improve estimates of soil evaporation and vegetation transpiration, leading to more reliable the monitoring of crop water stress and drought.

Time-domain analysis of scrotal thermoregulatory impairment in varicocele

Varicocele is a common male disease defined as the pathological dilatation of the pampiniform plexus and scrotal veins with venous blood reflux. Varicocele usually impairs the scrotal thermoregulation via a hemodynamic alteration, thus inducing an increase in cutaneous temperature. The investigation of altered scrotal thermoregulation by means of thermal infrared imaging has been proved to be useful in the study of the functional thermal impairment. In this study, we use the Control System Theory to analyze the time-domain dynamics of the scrotal thermoregulation in response to a mild cold challenge. Four standard time-domain dynamic parameters of a prototype second order control system (Delay Time, Rise Time, closed poles locations, steady state error) and the static basal temperatures were directly estimated from thermal recovery curves. Thermal infrared imaging data from 31 healthy controls (HCS) and 95 varicocele patients were processed. True-positive predictions, by comparison with standard echo color Doppler findings, higher than 87% were achieved into the proper classification of the disease stage. The proposed approach could help to understand at which specific level the presence of the disease impacts the scrotal thermoregulation, which is also involved into normal spermatogenesis process.

Differential diagnosis of Raynaud’s phenomenon based on modeling of finger thermoregulation

Raynaud's phenomenon (RP) is a vasospastic disorder of small arteries, pre-capillary arteries, and cutaneous arteriovenous shunts of the extremities, typically induced by cold exposure and emotional stress. RP is either primary (PRP) or secondary to connective tissue diseases such as systemic sclerosis (SSc). Early differential diagnosis is crucial in order to set the proper therapeutic strategy. To this goal, thermal infrared imaging data from 18 healthy controls (HCs) and 48 RP patients (20 PRP, 28 SSc) were processed through a model for a second-order time-invariant system with exponential critically damped dynamic response. Subject classification on the basis of the model parameters provides 100% true-positive discrimination for RP patients (PRP and SSc) and healthy, and 90% of correct classification within the group of patients. The proposed method may provide useful hints for early differential diagnosis in the assessment of RP disease.

Plume Ascent Tracker: Interactive Matlab software for analysis of ascending plumes in image data

This paper presents Matlab-based software designed to track and analyze an ascending plume as it rises above its source, in image data. It reads data recorded in various formats (video files, image files, or web-camera image streams), and at various wavelengths (infrared, visible, or ultra-violet). Using a set of filters which can be set interactively, the plume is first isolated from its background. A user-friendly interface then allows tracking of plume ascent and various parameters that characterize plume evolution during emission and ascent. These include records of plume height, velocity, acceleration, shape, volume, ash (fine-particle) loading, spreading rate, entrainment coefficient and inclination angle, as well as axial and radial profiles for radius and temperature (if data are radiometric). Image transformations (dilatation, rotation, resampling) can be performed to create new images with a vent-centered metric coordinate system. Applications may interest both plume observers (monitoring agencies) and modelers. For the first group, the software is capable of providing quantitative assessments of plume characteristics from image data, for post-event analysis or in near real-time analysis. For the second group, extracted data can serve as benchmarks for plume ascent models, and as inputs for cloud dispersal models. We here describe the software's tracking methodology and main graphical interfaces, using thermal infrared image data of an ascending volcanic ash plume at Santiaguito volcano.

A radiometrically-accurate super-resolution approach to thermal infrared image data

Super-resolution is an image processing and analysis technique used to improve the original (or native) spatial resolution of data. Super-resolution approaches have commonly sacrificed radiometric accuracy for visual appeal or vice versa. The results presented here are a significant modification and improvement of an algorithm originally applied to the thermal infrared (TIR) data from the Earth-orbiting Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. The algorithm has been programmed in the Interactive Data Language (IDL) scripting but could be easily coded in other programming languages. The primary focus of these modifications was to adapt the algorithm for use with visible and TIR data from the Mars-orbiting Thermal Emission Imaging System (THEMIS) instrument in addition to other improvements, such as a user-defined Point Spread Function (PSF) using an alpha notation. In addition, the previous requirement for an intermediate spatial/spectral resolution dataset has been removed after determining it to be unnecessary for accurate and visually pleasing results. This super-resolution approach is now more transparent to the user, and provides data from the intermediate steps, which allows for more accurate analysis of the results. The super-resolved TIR data from both the ASTER and the THEMIS are radiometrically accurate, interpretable, reproducible and maintain an excellent qualitative appearance.

High-resolution satellite and airborne thermal infrared imaging of precursory unrest and 2009 eruption at Redoubt Volcano, Alaska

A combination of satellite and airborne high-resolution visible and thermal infrared (TIR) image data detected and measured changes at Redoubt Volcano during the 2008–2009 unrest and eruption. The TIR sensors detected persistent elevated temperatures at summit ice-melt holes as seismicity and gas emissions increased in late 2008 to March 2009. A phreatic explosion on 15 March was followed by more than 19 magmatic explosive events from 23 March to 4 April that produced high-altitude ash clouds and large lahars. Two (or three) lava domes extruded and were destroyed between 23 March and 4 April. After 4 April, the eruption extruded a large lava dome that continued to grow until at least early July 2009.

Car Detection by Using High Resolution Remote Sensing Image Based on Background Iterative Search

In the traditional Space-to-Earth car detection system,thermal infrared,radar or aerial image data are often used,while high-resolution satellite remote sensing data have rarely been employed.To solve this problem,this paper proposes a new method for car detection based on high resolution satellite images,which is named BIS(Background Iterative Search).Firstly,according to the local differences between the object and the background,the background is searched and removed,and the preliminary car detection is achieved based on the material properties of cars.Secondly,the dynamic twin peak threshold method is used to separate roads from non-roads,and roads are roughly extracted based on shape features.Lastly,the correct car objects are obtained by constraining the elementary ones with the derived road information.The BIS method was applied with IKONOS and QuikBird data and proved to be effective.

An objective method of cyclone centre determination from geostationary satellite observations

An objective method has been developed for finding the centre of a cyclone using thermal infrared (TIR) image data from geostationary satellites. The data from the Meteosat-5 TIR channel have been analysed to demonstrate the utility of the method. The minimization approach has been used to determine the centre with the assumption of a near elliptic structure in the surrounding of the central dense overcast (CDO) region of a cyclone. The ellipse fitting technique is able to estimate objectively the centre for more than 70% cases with an error of less than 50 km.

Classifying Affective States Using Thermal Infrared Imaging of the Human Face

In this paper, time, frequency, and time-frequency features derived from thermal infrared data are used to discriminate between self-reported affective states of an individual in response to visual stimuli drawn from the International Affective Pictures System. A total of six binary classification tasks were examined to distinguish baseline and affect states. Affect states were determined from subject-reported levels of arousal and valence. Mean adjusted accuracies of 70% to 80% were achieved for the baseline classifications tasks. Classification accuracies between high and low ratings of arousal and valence were between 50% and 60%, respectively. Our analysis showed that facial thermal infrared imaging data of baseline and other affective states may be separable. The results of this study suggest that classification of facial thermal infrared imaging data coupled with affect models can be used to provide information about an individual's affective state for potential use as a passive communication pathway.

Finger Thermoregulatory Model Assessing Functional Impairment in Raynaud’s Phenomenon

Raynaud's Phenomenon (RP) is a paroxysmal vasospastic disorder of small arteries, pre-capillary arteries, and cutaneous arteriovenous shunts of the extremities, typically induced by cold exposure and emotional stress. RP is either primary (PRP) or secondary to systemic sclerosis. In this study we use Control System Theory to model finger thermoregulatory processes in response to a standardized cold challenge (a diagnostic test routinely performed for differential diagnosis of RP). The proposed model is based on a homeostatic negative feedback loop, characterized by five distinct parameters which describe how the control mechanisms are activated and maintained. Thermal infrared imaging data from 14 systemic sclerosis subjects (SSc), 14 PRP, and 16 healthy control subjects (HCS) were processed. HCS presented the fastest active recovery, with the highest gain. PRP presented the slowest and weakest recovery, mostly due to passive heat exchange with the environment. SSc presented an intermediate behavior, with the longest delay of response onset. The estimated model parameters elucidated the level of functional impairment expressed in the various forms of this disease.

ARM constellation—Establishing a regional remote sensing asset

The ARM constellation has been described as fulfilling the need for regular high resolution data over Africa for resource management applications. The widespread use of high and medium resolution image data clearly demonstrates the urgent need for this kind of data in a timely manner over Africa. The user requirements of the ARM have evolved to include medium resolution imagery (<30m) and very high resolution imagery in addition to future needs identified in the form of SAR and thermal infrared image data sets. This paper explores the user requirements for satellite remote sensed data for Africa and describes one constellation solution that dramatically increases the amount of relevant remote sensed data for African priorities. Two different next generation remote sensing satellites viz. MWSat and MSMISat are considered as a baseline for the technical solution.

Detection of geothermal anomalies using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared images at Bradys Hot Springs, Nevada, USA

Surface temperature anomalies associated with geothermal activity at Bradys Hot Springs, Churchill County, Nevada were mapped using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared (TIR) image data. In order to highlight subsurface contributions of geothermal heat, the ASTER images were processed to minimize temperature variations caused by the diurnal heating effects of the sun. Surface temperature variations caused by changes in albedo were corrected with visible and near-infrared ASTER bands, and a 10-meter-smoothed Digital Elevation Model (DEM) was used to correct for topographic slope effects. Field measurements of ground surface temperatures made over 24-hour periods were used to design a thermal inertia correction incorporating day and night thermal infrared images. In the resulting processed image, background temperature variations were reduced 30–50% without reducing the intensity of geothermal anomalies, thus making it easier to distinguish geothermal activity from ‘false’ anomalies caused by non-thermal springs, topographic effects, and variable rock, soil, and vegetation compositions.

Multiscale Fusion of Visible and Thermal IR Images for Illumination-Invariant Face Recognition

This paper describes a new software-based registration and fusion of visible and thermal infrared (IR) image data for face recognition in challenging operating environments that involve illumination variations. The combined use of visible and thermal IR imaging sensors offers a viable means for improving the performance of face recognition techniques based on a single imaging modality. Despite successes in indoor access control applications, imaging in the visible spectrum demonstrates difficulties in recognizing the faces in varying illumination conditions. Thermal IR sensors measure energy radiations from the object, which is less sensitive to illumination changes, and are even operable in darkness. However, thermal images do not provide high-resolution data. Data fusion of visible and thermal images can produce face images robust to illumination variations. However, thermal face images with eyeglasses may fail to provide useful information around the eyes since glass blocks a large portion of thermal energy. In this paper, eyeglass regions are detected using an ellipse fitting method, and replaced with eye template patterns to preserve the details useful for face recognition in the fused image. Software registration of images replaces a special-purpose imaging sensor assembly and produces co-registered image pairs at a reasonable cost for large-scale deployment. Face recognition techniques using visible, thermal IR, and data-fused visible-thermal images are compared using a commercial face recognition software (FaceIt®) and two visible-thermal face image databases (the NIST/Equinox and the UTK-IRIS databases). The proposed multiscale data-fusion technique improved the recognition accuracy under a wide range of illumination changes. Experimental results showed that the eyeglass replacement increased the number of correct first match subjects by 85% (NIST/Equinox) and 67% (UTK-IRIS).

Satellite thermal IR phenomena associated with some of the major earthquakes in 1999–2003

Satellite thermal infrared (TIR) imaging data have recorded short-lived anomalies prior to major earthquakes and associations with fault systems. Others have proposed that these signals originate from electromagnetic phenomena associated with pre-seismic processes, causing enhanced IR emissions, that we are calling TIR anomalies. The purpose of this exploratory study is to verify if TIR anomalies can be found in association with known earthquakes by systematically applying satellite data analysis techniques to imagery recorded prior-to and immediately after large earthquakes. Our approach utilizes both a mapping of surface TIR transient fields from polar orbiting satellites and co-registering geosynchronous weather satellites images. The significance of these observations was explored using data sets of recent worldwide strong earthquakes (1999–2003) and the techniques used to capture the trace of TIR anomalies.

Monitoring eruptive activity at Mount St. Helens with TIR image data

Thermal infrared (TIR) data from the MASTER airborne imaging spectrometer were acquired over Mount St. Helens in Sept and Oct, 2004, before and after the onset of recent eruptive activity. Pre‐eruption data showed no measurable increase in surface temperatures before the first phreatic eruption on Oct 1. MASTER data acquired during the initial eruptive episode on Oct 14 showed maximum temperatures of ∼330°C and TIR data acquired concurrently from a Forward Looking Infrared (FLIR) camera showed maximum temperatures ∼675°C, in narrow (∼1‐m) fractures of molten rock on a new resurgent dome. MASTER and FLIR thermal flux calculations indicated a radiative cooling rate of ∼714 J/m2/s over the new dome, corresponding to a radiant power of ∼24 MW. MASTER data indicated the new dome was dacitic in composition, and digital elevation data derived from LIDAR acquired concurrently with MASTER showed that the dome growth correlated with the areas of elevated temperatures. Low SO2 concentrations in the plume combined with sub‐optimal viewing conditions prohibited quantitative measurement of plume SO2. The results demonstrate that airborne TIR data can provide information on the temperature of both the surface and plume and the composition of new lava during eruptive episodes. Given sufficient resources, the airborne instrumentation could be deployed rapidly to a newly‐awakening volcano and provide a means for remote volcano monitoring.

Surface mineral mapping at Steamboat Springs, Nevada, USA, with multi-wavelength thermal infrared images

The purpose of this study was to evaluate the use of airborne multispectral and hyperspectral thermal infrared (TIR) image data for mapping surface minerals characteristic of active geothermal systems. TIR image data from the MASTER multispectral spectrometer and the SEBASS hyperspectral spectrometer were acquired over Steamboat Springs, Nevada, USA, in September 1999. Spectral emissivity information was extracted from the data and used to generate mineral maps. Using the MASTER data it was possible to map the extent of the active geothermal area as well as silica-rich vs. clay-rich areas. Using the SEBASS data the same areas could be mapped and additionally the presence of several minerals, including opal, quartz, alunite, anorthite, albite, and kaolinite could be identified. The SEBASS data also detected previously unidentified hydrous sulfate minerals (tamarugite and alunogen) forming around active fumaroles. Laboratory spectral data and XRD analyses of field samples confirmed the dominant mineral phases identified remotely. The airborne, field and laboratory data together with temperature anomaly and fumarole location data from other studies were synthesized and linked to the surface geology to determine the diagnostic surface mineral expression that could be mapped with TIR remotely sensed data for future exploration for similar geothermal systems. Opaline sinter deposits are the most diagnostic surface expression of hot spring activity at Steamboat Springs because they represent areas of the recent geyser activity. The differentiation between opal and chalcedony deposits and the identification of hydrous sulfate minerals forming around active fumaroles are also important because chalcedony represents ancient sinter deposits and hydrous sulfate minerals indicate locations of fumaroles that may be venting diffusely with no geyser activity. The surface expression of the geothermal system at Steamboat Springs is small, which emphasizes the need for high spatial resolution airborne imagers. The 90-m pixels of ASTER TIR data over the same area were only capable of resolving the area of past and recent sinter deposits together. MASTER multispectral TIR data covered the entire area (∼12 km 2) at 5-m spatial resolution and were capable of defining the extent of the sinter deposits and zones of hydrothermally altered rocks. The SEBASS image swath was too narrow (256 m) to add significant spatial information to the overall map, but the high spectral content identified several important minerals related to the local geology and the mineralogic surface expression of the geothermal system.

The retrieval of two-dimensional distribution of the earth’s surface aerodynamic roughness using SAR image and TM thermal infrared image

After having analyzed the requirement on the aerodynamic earth’s surface roughness in two-dimensional distribution in the research field of interaction between land surface and atmosphere, this paper presents a new way to calculate the aerodynamic roughness using the earth’s surface geometric roughness retrieved from SAR (Synthetic Aperture Radar) and TM thermal infrared image data. On the one hand, the SPM (Small Perturbation Model) was used as a theoretical SAR backscattering model to describe the relationship between the SAR backscattering coefficient and the earth’s surface geometric roughness and its dielectric constant retrieved from the physical model between the soil thermal inertia and the soil surface moisture with the simultaneous TM thermal infrared image data and the ground microclimate data. On the basis of the SAR image matching with the TM image, the non-volume scattering surface geometric information was obtained from the SPM model at the TM image pixel scale, and the ground pixel surface’s equivalent geometric roughness-height standard RMS (Root Mean Square) was achieved from the geometric information by the transformation of the typical topographic factors. The vegetation (wheat, tree) height retrieved from spectrum model was also transferred into its equivalent geometric roughness. A completely two-dimensional distribution map of the equivalent geometric roughness over the experimental area was produced by the data mosaic technique. On the other hand, according to the atmospheric eddy currents theory, the aerodynamic surface roughness was iterated out with the atmosphere stability correction method using the wind and the temperature profiles data measured at several typical fields such as bare soil field and vegetation field. After having analyzed the effect of surface equivalent geometric roughness together with dynamic and thermodynamic factors on the aerodynamic surface roughness within the working area, this paper first establishes a scale transformation model to calculate the aerodynamic surface roughness from surface equivalent geometric roughness. The final result retrieved from above series of models was validated using the filed measurements. It is concluded that the proposed approach is operational and feasible to derive the aerodynamic surface roughness at the pixel scale from a combination of the SAR and TM images.