Airborne Thermal Infrared Data Research Articles

Response of Industrial Warm Drainage to Tide Revealed by Airborne and Sea Surface Observations

Maintaining the balance between power station operation and environmental carrying capacity in the process of cooling water discharge into coastal waters is an essential issue to be considered. Earth observations with airborne and sea surface sensors can efficiently estimate distribution characteristics of extensive sea surface temperature compared with traditional numerical and physical simulations. Data acquisition timing windows for those sensors are designed according to tidal data. The airborne thermal infrared data (Thermal Airborne Spectrographic Imager, TASI) is preprocessed by algorithms of atmospheric correction, geometric correction, strip brightness gradient removal, and noise reduction, and then the seawater temperature is inversed in association with sea surface synchronous temperature measurement data (Sea-Bird Electronics, SBE). Verification analyses suggested a satisfied accuracy of less than about 0.2 °C error between the predicted and the measured values in general. Multiple factors influence seawater temperature, i.e., meteorology, ocean current, runoff, water depth, seawater convection, and eddy current; tidal activity is not the only one. Environmental background temperature in different seasons is the governing factor affecting the diffusion effect of seawater temperature drainage according to analyses of the covariances and correlation coefficients of eight tidal states. The present study presents an efficient and quick seawater temperature monitoring technique owing to industrial warm drainage to sea by means of a complete set of seawater temperature inversion algorithms with multi-source thermal infrared hyperspectral data.

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights

AbstractSubmarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.

Noise Simulation and Correction in Synthetic Airborne TIR Data for Mineral Quantification

Rock-forming minerals (such as feldspar and quartz) can be identified and quantified from thermal infrared (TIR) laboratory spectroscopy using spectral models. This paper uses synthetic airborne TIR spectra to test whether the hyperspectral Spatially Enhanced Broadband Array Spectrograph System (SEBASS) would theoretically be able to detect quartz and feldspar minerals and quantitatively predict mineral modes in felsic igneous rocks. Data from a previous laboratory study were used to simulate TIR spectra with band locations and noise levels of the SEBASS sensor. The quantitative partial least squares regression (PLSR) models from that study were applied to newly created synthetic SEBASS data, and results were compared with the predictions from the previous study. Predicted compositions based on SEBASS band positions are nearly identical $(\rho = 0.995)$ to those based on laboratory resolution. Results are still reliable [prediction errors within 0.4% (absolute)] to the original laboratory PLSR predictions when adding up to 1% noise (about five times the SEBASS noise level) to the synthetic data. Prediction errors rapidly increase when noise levels beyond 1% are used. These results show that SEBASS' spectral resolution, spectral coverage, and signal-to-noise levels are sufficient to quantitatively predict quartz and feldspar amounts, and feldspar compositions with models based on PLSR. Spectral distortions, such as reduced spectral contrast, tilts, and vertical shifts, must be compensated for before these quantitative models are applied. A mean and standard deviation (MASD) normalization is proposed using a set of ground data for compensating systematic errors that are common to all image pixels.

Inflight straylight analysis for ASTER thermal infrared bands

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument was launched into Earth orbit on the Terra platform in late 1999. ASTER produces images of the Earth in 14 spectral bands including five bands in the thermal infrared (TIR) part of the electromagnetic spectrum (8-12 /spl mu/m). On one occasion ASTER was used to image the Moon as part of the long-term calibration strategy for instruments on the Terra platform. Analysis of the imagery revealed that the TIR band had noticeable straylight effects (ghosting), and an algorithm was developed to correct for these effects. The algorithm was applied to ASTER/TIR images acquired over a vicarious calibration (VC) site at Cold Springs Reservoir (CSR), NV. Data from CSR had been evaluated in three previous VC experiments and showed large unexplained differences between the ASTER image radiance and vicarious predicted radiance not observed in other larger, more laterally homogenous sites. After straylight correction the vicarious and image radiances were in good agreement. A further comparison with nearly simultaneous airborne TIR data acquired with the MODIS/ASTER (MASTER) sensor indicated that the ASTER straylight corrected data also agreed with the airborne data. Finally, the algorithm was applied to artificially created models. The results indicated that a radiance change caused by straylight reached 6% to 8% of a radiance contrast for a smaller square target than 10/spl times/10 pixels or a narrower line target than five pixels. Straylight in ASTER/TIR imagery may not be very large for most targets, but may become an error factor for high-radiance-contrast targets.

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.

Atmospheric corrections of single broadband channel and multidirectional airborne thermal infrared data: Application to the ReSeDA experiment

This study focused on atmospheric corrections of airborne thermal infrared remote sensing data acquired with a multidirectional and single broadband channel sensor during the ReSeDA experiment. For single channel sensors, atmospheric corrections are generally performed using atmospheric radiative transfer models such as MODTRAN 3.5 along with radiosoundings. A sensitivity study was performed using MODTRAN 3.5 simulations to assess the accuracy of the processing regarding the experimental context. It was shown that the local topography and the atmosphere spatial variability could affect significantly the radiosounding representativeness, whereas the fluctuations of the flight altitude around the nominal value induced non-negligible inaccuracies. Moreover, using a broadband sensor induced non-linear effects that required a second order correction and also the use of look-up tables to reduce computation time. A theoretical error was next proposed to account for both the sensor accuracy and the experimental uncertainties considered when performing the sensitivity study. This theoretical error was about 1°C, and agreed well with the results obtained when validating against field measurements.

Estimating silicic lava vesicularity with thermal remote sensing: a new technique for volcanic mapping and monitoring

Remote monitoring of active lava domes pro- vides insights into the duration of continued lava extru- sion and detection of potentially associated explosive activity. On inactive flows, variations in surface texture ranging from dense glass to highly vesicular pumice can be related to emplacement time, volatile content, and internal structure. Pumiceous surface textures also pro- duce changes in thermal emission spectra that are clear- ly distinguishable using remote sensing. Spectrally, the textures describe a continuum consisting of two pure end members, obsidian and vesicles. The distinct spec- tral features of obsidian are commonly muted in pu- mice due to overprinting by the vesicles, which mimic spectrally neutral blackbody emitters. Assuming that this energy combines linearly in direct proportion to the percentage of vesicles, the surface vesicularity can be estimated by modeling the pumice spectrum as a lin- ear combination of the glass and blackbody spectra. Based on this discovery, a linear retrieval model using a least-squares fitting approach was applied to airborne thermal infrared data of the Little Glass Mountain and Crater Glass rhyolite flows at Medicine Lake Volcano (California) as a case study. The model produced a ve- sicularity image of the flow with values from 0 to F70%, which can be grouped into three broad textural classes: dense obsidian, finely vesicular pumice, and coarsely vesicular pumice. Values extracted from the image compare well with those derived from SEM anal- ysis of collected samples as well as with previously re- ported results. This technique provides the means to accurately map the areal distributions of these textures, resulting in significantly different values from those de- rived using aerial photographs. If applied to actively deforming domes, this technique will provide volcano- logists with an opportunity to monitor dome-wide de- gassing and eruptive potential in near-real-time. In July 1999 such an effort will be possible for the first time when repetitive, global, multispectral thermal infrared data become available with the launch of the Advanced Spaceborne Thermal Emission and Reflectance Ra- diometer (ASTER) instrument aboard the Earth Ob- serving System satellite.