Thermal Infrared Multispectral Scanner Research Articles

Use of Thermal Infrared Multispectral Scanner (TIMS) imagery to investigate upslope particle size controls on arid piedmont morphology

Geomorphic differences between slopes backing two distinct desert piedmont types provide a proxy indicator for the kind of landform developed at the corresponding mountain base. Here, the term ‘bedrock pediment’ describes subaerial bedrock platforms that emanate from a mountain base while ‘alluvial slope’ describes suballuvial bedrock platforms that extend from the mountain. Mountain slopes backing bedrock pediments have been demonstrated to be mantled by larger clast sizes than corresponding slopes backing alluvial slopes in the Phoenix region, Arizona, USA. The present research focuses on using the disparate particle sizes between slopes backing bedrock pediments and alluvial slopes as an indicator for the piedmont form developed at the mountain base, and uses high-resolution remotely sensed digital data as a medium for quantitative landform assessments. A gravel + bedrock versus soil index developed from airborne midinfrared multispectral imagery acquired by the Thermal Infrared Multispectral Scanner (TIMS) indicates the presence of slopes mantled with larger particle sizes versus slopes mantled with smaller particle sizes and greater soil coverage. Two test areas confirm the applicability of this method and further demonstrate the usefulness of high-resolution midinfrared multispectral imagery as a geomorphic tool in arid regions.

Thermal infrared data analyses of Meteor Crater, Arizona: Implications for Mars spaceborne data from the Thermal Emission Imaging System

Thermal infrared (TIR) data from the Earth‐orbiting Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument are used to identify the lithologic distribution of the Meteor Crater ejecta blanket. Thermal emission laboratory spectra were obtained for collected samples, and spectral deconvolution was performed on ASTER emissivity data using both image and sample end‐members. Comparison of the spaceborne ASTER data to the airborne Thermal Infrared Multispectral Scanner (TIMS) data was used to validate the ASTER end‐member analyses. The ASTER image end‐member analysis agrees well with past studies considering the effects of resolution degradation. The work at Meteor Crater has direct bearing on the interpretation of Thermal Emission Imaging System (THEMIS) data currently being returned from Mars. ASTER and THEMIS have similar spatial and spectral resolutions, and Meteor Crater serves as an analog for similar‐sized impact sites on Mars. These small impact craters have not been studied in detail owing to the low spatial resolution of past orbiting TIR instruments. Using the same methodology as that applied to Meteor Crater, THEMIS TIR data of a provisionally named Winslow Crater (∼1 km) impact crater in Syrtis Major are analyzed. The crater rim and ejecta blanket were found to contain larger block sizes and a lower albedo than the surrounding ejecta‐free plain, indicating a young impact age. The composition of the rim, ejecta, and surrounding plain is determined to be dominated by basalt; however, potential stratigraphy has also been identified. Results of this work could be extended to future investigations using THEMIS data.

Validation of temperature-emissivity separation and split-window methods from TIMS data and ground measurements

Land surface temperature retrieved with temperature-emissivity separation (TES) and split-window (SW) algorithms from six-channel Thermal Infrared Multispectral Scanner (TIMS) data in the HAPEX-Sahel experiment agreed with contemporaneous ground temperature measurements to within ±1 °C (TES and SW with channels at 10.8 and 11.7 μm, or SW-56). The SW algorithm used with TIMS channels at 8.4 and 8.7 μm (SW-12) underestimated ground temperatures by 2–5 °C. The TES method required atmospheric correction of at-sensor radiances, which was done with local radiosonde data and MODTRAN 4, and an empirical relationship between the spectral range of emissivity and its minimum value. Emissivity data required for the SW algorithms were obtained using vegetation cover estimates from near-coincident reflective remote sensing data. The temperature underestimation of the SW-12 algorithm could be caused by errors in the emissivity inputs calculated from the vegetation cover. Such errors were due to the high variability of surface emissivity in the 8–9-μm waveband, which was much larger than in the 10–12-μm region. This was checked using TES derived emissivities as inputs of the SW algorithms, and comparing the resulting temperatures with the TES temperatures. In this case, both the SW-56 and SW-12 temperatures agreed with TES within ±1 °C for all sites and scenes.

Spectroscopic study of the Moses Lake dune field, Washington: Determination of compositional distributions and source lithologies

Source lithologies and transport histories of materials within the Ephrata Fan are investigated. Data were collected using a variety of remote‐sensing, laboratory spectroscopic, and field observations and techniques. Laboratory thermal emission spectra were collected of bedrock within the Grand Coulee, dune samples, and clast deposits. Factor analysis, target transformation, and end‐member recovery techniques were applied to the set of dune samples as well as a set of grain size fractions. The dune sample spectra are composed of three components that represent basalt, granodiorite, and clay compositions. The basalt and granodiorite components are similar to spectra of clast and bedrock samples from the Grand Coulee and the Ephrata Fan. The clay component is similar to weathering surfaces located within the dune field. The same components were recovered from the set of grain size fractions from a single dune sample demonstrating a relatively higher basalt concentration with grain sizes greater than ∼250 μm. Thermal Infrared Multispectral Scanner (TIMS) data display significant intradune compositional variation and no discernable interdune compositional variation, indicating that the basalt and granodiorite components were likely deposited simultaneously and subsequently separated by wind based on grain size. Basalt and granodiorite bedrock units within the Channeled Scablands are source materials for the deposits within the Ephrata Fan and Moses Lake dune field. The Columbia River, located 20 km west of the dune field, is not a likely source of material.

Ejecta distribution patterns at Meteor Crater, Arizona: On the applicability of lithologic end-member deconvolution for spaceborne thermal infrared data of Earth and Mars

[1] A spectral deconvolution using a constrained least squares approach was applied to airborne thermal infrared multispectral scanner (TIMS) data of Meteor Crater, Arizona. The three principal sedimentary units sampled by the impact were chosen as end-members, and their spectra were derived from the emissivity images. To validate previous estimates of the erosion of the near-rim ejecta, the model was used to identify the areal extent of the reworked material. The outputs of the algorithm reveal subtle mixing patterns in the ejecta, identified larger ejecta blocks, and were used to further constrain the volume of Coconino Sandstone present in the vicinity of the crater. The availability of the multialtitude data set also provided a means to examine the effects of resolution degradation and quantify the subsequent errors on the model. These data served as a test case for the use of image-derived lithologic end-members at various scales, which is critical for examining thermal infrared data of planetary surfaces. The model results indicate that the Coconino Ss. reworked ejecta is detectable over 3 km from the crater. This was confirmed by field sampling within the primary ejecta field and wind streak. The areal distribution patterns of this unit imply past erosion and subsequent sediment transport that was low to moderate compared with early studies and therefore places further constraints on the ejecta degradation of Meteor Crater. It also provides an important example of the analysis that can be performed on thermal infrared data currently being returned from Earth orbit and expected from Mars in 2002.

Temperature and emissivity separation from multispectral thermal infrared observations

Knowledge of the surface emissivity is important for determining the radiation balance at the land surface. For heavily vegetated surfaces, there is little problem since the emissivity is relatively uniform and close to one. For arid lands with sparse vegetation, the problem is more difficult because the emissivity of the exposed soils and rocks is highly variable. With multispectral thermal infrared (TIR) observations, it is possible to estimate the spectral emissivity variation for these surfaces. We present data from the TIMS (Thermal Infrared Multispectral Scanner) instrument, which has six channels in the 8- to 12-μm region. TIMS is a prototype of the TIR portion of the ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) instrument on NASA's Terra (EOS-AM1) platform launched in December 1999. The Temperature Emissivity Separation (TES) algorithm, developed for use with ASTER data, is used to extract the temperature and six emissivities from the six channels of TIMS data. The algorithm makes use of the empirical relation between the range of observed emissivities and their minimum value. This approach was applied to the TIMS data acquired over the USDA/ARS Jornada Experimental Range in New Mexico. The Jornada site is typical of a desert grassland where the main vegetation components are grass (black grama) and shrubs (primarily mesquite) in the degraded grassland. The data presented here are from flights at a range of altitudes from 800 to 5000 m, yielding a pixel resolution from 3 to 12 m. The resulting spectral emissivities are in qualitative agreement with laboratory measurements of the emissivity for the quartz rich soils of the site. The derived surface temperatures agree with ground measurements within the standard deviations of both sets of observations. The results for the 10.8- and 11.7-μm channels show limited variation of the emissivity values over the mesquite and grass sites indicating that split window approaches may be possible for conditions like these.

Recovery of spectral emissivity from Thermal Infrared Multispectral Scanner imagery acquired over a mountainous terrain: A case study from Mount Etna Sicily

The estimation of ground radiance and emissivity from Thermal Infrared Multispectral Scanner (TIMS) data is strongly dependent on the atmospheric correction applied to these data. Since such corrections are a function of the atmospheric path between the sensor and ground, correction techniques that do not consider the topographic variations within a scene can introduce appreciable error in the estimation of the atmosphere effects. In this paper, we describe the development and application of a variable-elevation atmospheric correction procedure. Our objective was to incorporate changes in target altitude into a general atmosphere correction strategy. This procedure was tested on a TIMS data set acquired over Mt. Etna, Italy in July 1986. The methodology adopted in this study is based on the use of the LOWTRAN radiative transfer code and a digital elevation model (DEM) registered to the image data. The image data are divided into a series of layers, based on elevation, and a separate atmosphere correction is applied to each layer. Maps of emissivity estimates derived with the variable-elevation approach were compared with geologic maps of the Etna flow fields. Prior to the variable-elevation correction, the emissivity spectra of long lava flows appeared to vary with elevation. Following the variable-elevation correction, many of these spectral artifacts were removed from the emissivity maps. In addition, the variable-elevation correction increased our ability to discriminate individual lava flows.

MONITORING OF ACTIVE VOLCANOES ON KAMCHATKA FROM THERMAL INFRARED SCANNER AND RADAR IMAGERY

On the basis of data recorded by a thermal infrared multispectral scanner (TIMS) carried on board an aircraft laboratory, maps of volcanic regions in Russia were compiled on which portions of lava dating to different periods were identified. SIR-C (Shuttle) data, processed by computer, made it possible to obtain distinct boundaries of lava flows with cross-polarization. A three-dimensional digital model of the Northern Fissure of the Great Tolbachik Fissure Eruption, on which TIMS, Zeiss, and SIR-C data were plotted, was constructed. A lineament analysis was made it possible to genetically classify cinder cones on the eastern slope of the Klyuchevskoy volcano, and a zone of areal volcanism was defined.

A Diurnal Animation of Thermal Images from a Day–Night Pair

Interpretation of thermal images is often complicated because the physical property information is contained in both the spatial and temporal variations of the data and thermal models are necessary to extract and display this information. A linearized radiative transfer solution to the surface flux has been used to derive a function that is invariant with respect to thermal inertia. This relationship makes it possible to predict the temperature variation at any time in the diurnal cycle using only two distinct measurements (e.g., noon and midnight). An animation can then be constructed from a pair of day–night images to view both the spatial and temporal temperature changes throughout the diurnal cycle. A more complete solution for the invariant function, using the method of Laplace transforms and based on the linearized solution, was introduced. These results indicate that the linear model does not provide a sufficiently accurate estimate. Using standard conditions (latitude 30°, solar declination 0°, acquisition times at noon and midnight), this new relationship was used to predict temperature throughout the diurnal cycle to an rms error of 0.2°C, which is close to the system noise of most thermal scanners. The method was further extended to include the primary effects of topographic slope with similar accuracy. The temperature was computed at 48 equally spaced times in the diurnal cycle with this algorithm using a co-registered day and night TIMS (Thermal Infrared Multispectral Scanner) data pair (330 pixels, 450 lines) acquired of the Carlin, Nevada, area and a co-registered DEM (Digital Elevation Model). (Any reader can view the results by downloading the animation file from an identified ftp site.) The results illustrate the power of animation to display subtle temporal and spatial temperature changes, which can provide clues to structural controls and material property differences. This `visual change' approach could significantly increase the use of thermal data for environmental, hazard, and resource studies.

An investigation of the geological and geomorphological features of Fowlers Gap using thermal infrared, radar and airborne geophysical remote sensing techniques.

This study summarises the application of several remote sensing techniques to investigate various components of a land surface in the semi-arid environment of Fowlers Gap. These remote sensing techniques included NASA's Thermal Infrared Multispectral Scanner (TIMS) and CSIRO's Mid-Infrared Airborne CO, Laser Spectrometer (MIRACO,LAS), NASA's AIRSAR radar and geophysical airborne radiometrics. Linear spectral unmixing of extracted emissivities from the TIMS data produced four endmembers: quartz, clay minerals, dry vegetation (cellulose) in fine soils, and green vegetation/moisture. MIRAC0,LAS data identified spectral signatures similar to the spectra of endmembers derived from TIMS data. The sensitivity of both thermal infrared remote sensing techniques to the quartzklay contents and textures of the soils and sediments was confirmed by detailed laboratory spectral measurements. Surface roughness information from AIRSAR's band C radar backscatter assisted the discrimination of alluvial and colluvial quartz and clay-rich deposits from the outcropping geological units. In particular the C band AIRSAR radar discriminated the coarse grained sandstone and quartzite scree within the colluvial pediments, from the finer grained quartz-rich 'radar smooth' alluvium in the scalds. Airborne radiometrics were also found useful for further discriminating potassium and thorium- bearing phyllosilicate/clay minerals, within shales and ghyllites, from the kaolinite and montmorillonite- rich alluvium. This study found that TIMS data could identify some of the geomorphological features at Fowlers Gap, such as colluvial pediments, depositional scalds and gilgai landforms, that characterise some of the land systems in the Lowlands and Plains relief class of the Fowlers Gap land system classification. Thermal infrared remote sensing techniques also proved capable of discriminating areas of cellulose-rich dry vegetation and fine grained soils within the Plains relief class. The sensitivity of AIRSAR radar for topographic relief and surface roughness suggests that it is useful for distinguishing land systems in the Ranges relief class. Radiometrics appeared useful for land system definition when outcropping argillaceous units and alluvium assisted their classification. Key words: remote sensing, Fowlers Gap, thermal infrared, land system, spectral unmixing

Estimating surface fluxes over the SGP site with remotely sensed data

The estimation of surface energy fluxes using remotely sensed data requires the combination of data from several sources, including land use, vegetation cover and surface temperature. Land use and vegetation cover were obtained from visible and near infrared (VNIR) data, while the state variable, surface temperature, was obtained from thermal infrared (TIR) data. An approach to combine these data with an energy balance model was studied as part of the 1997 Southern Great Plains Experiment (SGP97). Toward this end, VNIR and TIR images for 2 July 1997 were analyzed over the El Reno, Oklahoma (OK) site using data from the Thermal Infrared Multispectral Scanner (TIMS) and Thematic Mapper Simulator (TMS) airborne instruments. Intensive ground measurements constrained leaf area indices, canopy height and surface meteorological inputs required by the model. The observed brightness temperatures, when corrected for atmospheric effects using MODTRAN, nearby radiosoundings and the temperature-emissivity separation (TES) algorithm, were mostly within VC of ground based temperatures. The resulting surface temperatures were used in a two-source model that considers the heat flux and temperature contributions from the soil and vegetation. The heat flux predictions on average agree within 50 W m−2 of tower-based observations.

Evaluation of Six Methods for Extracting Relative Emissivity Spectra from Thermal Infrared Images

The performance of six published methods for extracting relative spectral emissivity information from thermal infrared multispectral data has been evaluated. In the first part of this article, we recall those six methods and show mathematically that they are almost equivalent to each other. Then, using simulated data for the TIMS (Thermal Infrared Multispectral Scanner) instrument, we analyze the sensitivity of those methods to different sources of error which may occur in real data such as errors due to 1) method simplification, 2) instrumental noise and systematic calibration error, 3) uncertainties on the estimation of downwelling atmospheric radiance, and 4) uncertainties of atmospheric parameters in atmospheric corrections. In terms of resulting errors in relative emissivity, the results show that: a) all methods are very sensitive to the uncertainties of atmosphere. An error of 20% of water vapor in midlatitude summer atmosphere (2.9 cm) may lead to an error of 0.03 (rms) for Channel 1 (worst case) of TIMS. b) The effect of the atmospheric reflection term is very important. If this term is neglected in method development, this may lead to an error of 0.03 (rms) for Channel 1 and midlatitude summer atmosphere. This is the case for the alpha method. c) Instrumental noise commonly expressed by noise equivalent difference temperature (NEΔ T) from 0.1 K to 0.3 K results in an error on relative emissivity ranging from 0.002 to 0.005 for all methods. d) Error on relative emissivity due to the instrumental calibration error (systematic error) is negligible. The study also shows that the relative emissivity derived with deviate atmosphere is linearly related to its actual value derived with correct atmospheric parameters. Based on this property, we propose three methods to correct for the errors caused by atmospheric corrections under horizontally invariant atmospheric conditions. A practical analysis with the real TIMS data acquired for Hapex-Sahel experiment in 1992 supports the results of this simulation.

Evaluation of Different Methods for Extracting Relative Spectral Emissivity Information from Simulated Thermal Infrared Multispectral Scanner Data

The performance of five published methods for extracting relative spectral emissivity information from thermal infrared multispectral data has been evaluated. In the first part of this article, we have recalled those five methods and shown mathematically that they are almost equivalent to each other. Then, using simulated data built up with the TIMS (Thermal Infrared Multispectral Scanner) instrument, we have analyzed the sensitivity of those methods to different sources of error which may occur in real data such as errors due to 1) method simplification, 2) instrumental noise and systematic calibration error, 3) uncertainties on the estimation of downwelling atmospheric radiance, and 4) uncertainties of atmospheric parameters in atmospheric corrections. In terms of resulting errors in relative emissivity, the results show that: a) All methods are very sensitive to the uncertainties of atmosphere. An error of 20% of water vapor in midlatitude summer atmosphere (2.9 cm) may lead to an error of 0.03 (rms) for Channel 1 of TIMS. b) The effect of the atmospheric reflection term is very important. If this term is neglected in method development, this may lead to an error of 0.03 (rms) for Channel 1 and midlatitude summer atmosphere. This is the case for the alpha method. c) Instrumental noise commonly expressed by noise equivalent difference temperature (NEΔT) from 0.1 K to 0.3 K results in an error of relative emissivity ranging from 0.002 to 0.005 for all methods. d) Error in relative emissivity due to the instrument calibration error (systematic error) is negligible. The study also shows that the relative emissivity derived with an incorrect atmosphere is linearly related to its actual value derived with correct atmospheric parameters. Based on this property, we propose three methods to correct for the errors caused by atmospheric corrections under horizontally invariant atmospheric conditions. A practical analysis with the real TIMS data acquired for Hapex-Sahel experiment in 1992 supports the results of this simulation.

Identification of sand sources and transport pathways at the Kelso Dunes, California, using thermal infrared remote sensing

The Kelso dune field is located in the eastern Mojave Desert, California, at the terminus of a sand-transport pathway, which has its primary source at the Mojave River Wash 50 km to the west. Initial examination of 1984 airborne thermal infrared multispectral scanner (TIMS) data showed significant spectral variations that indicate potential mineralogic heterogeneities within the active dunes. This result prompted the collection of a suite of 48 sand samples in 1990, and the acquiring of new TIMS data in 1995. This new data set was used to test a newly developed linear spectral retrieval algorithm in conjunction with a spectral library of end-member minerals. Results of this analysis produced images of end-member minerals that showed marked variations within the dunes. In addition, standard petrographic techniques revealed that the dunes contain mineralogic variations and were much less quartz rich (∼42%) than previously reported (∼70%–90%). Point-count results agreed with the spectral data to within an average of 5.3% for TIMS-derived and 3.1% for laboratory-derived mineralogic abundances. High concentrations of several of the end-member minerals on the surrounding alluvial fans indicate a potential nearby source for these minerals. Most evident is the presence of potassium feldspar from the fan that emanates from the Providence Mountains east of the dunes. This previously unidentified potential sand input is not visible with other remote sensing techniques and was confirmed with additional field sampling. Much of the quartz and some plagioclase feldspar, however, appear to have been transported from the Mojave River Wash source as previously reported. This study also validates the potential of using thermal remote sensing from future satellite-based instruments to globally monitor desert fringe areas susceptible to the changing conditions of sand encroachment.

Analysis of simulated advanced spaceborne thermal emission and reflection (ASTER) radiometer data of the Iron Hill, Colorado, study area for mapping lithologies

The advanced spaceborne thermal emission and reflection (ASTER) radiometer was designed to record reflected energy in nine channels with 15 or 30 m resolution, including stereoscopic images, and emitted energy in five channels with 90 m resolution from the NASA Earth Observing System AMI platform. A simulated ASTER data set was produced for the Iron Hill, Colorado, study area by resampling calibrated, registered airborne visible/infrared imaging spectrometer (AVIRIS) data, and thermal infrared multispectral scanner (TIMS) data to the appropriate spatial and spectral parameters. A digital elevation model was obtained to simulate ASTER‐derived topographic data. The main lithologic units in the area are granitic rocks and felsite into which a carbonatite stock and associated alkalic igneous rocks were intruded; these rocks are locally covered by Jurassic sandstone, Tertiary rhyolitic tuff, and colluvial deposits. Several methods were evaluated for mapping the main lithologic units, including the unsupervised classification and spectral curve‐matching techniques. In the five thermalinfrared (TIR) channels, comparison of the results of linear spectral unmixing and unsupervised classification with published geologic maps showed that the main lithologic units were mapped, but large areas with moderate to dense tree cover were not mapped in the TIR data. Compared to TIMS data, simulated ASTER data permitted slightly less discrimination in the mafic alkalic rock series, and carbonatite was not mapped in the TIMS nor in the simulated ASTER TIR data. In the nine visible and near‐infrared channels, unsupervised classification did not yield useful results, but both the spectral linear unmixing and the matched filter techniques produced useful results, including mapping calcitic and dolomitic carbonatite exposures, travertine in hot spring deposits, kaolinite in argillized sandstone and tuff, and muscovite in sericitized granite and felsite, as well as commonly occurring illite/muscovite. However, the distinction made in AVIRIS data between calcite and dolomite was not consistently feasible in the simulated ASTER data. Comparison of the lithologie information produced by spectral analysis of the simulated ASTER data to a photogeologic interpretation of a simulated ASTER color image illustrates the high potential of spectral analysis of ASTER data to geologic interpretation.

Synergy of active and passive airborne thermal infrared systems for surface compositional mapping

NASA thermal infrared multispectral scanner (TIMS) and Commonwealth Scientific Industrial Research Organisation mid‐infrared airborne CO2 laser spectrometer (MIRACO2LAS) data were acquired over the Mount Fitton area, South Australia, in order to evaluate their combined use for geological mapping and mineral exploration. TIMS is a passive, imaging system with six spectral bands in the thermal infrared wavelength region (8–12 μm), whereas MIRACO2LAS is an active, profiling system with ∼100 spectral bands in the 9–11 μm spectral range. The TIMS and CO2 laser data (emissivity variations for TIMS and apparent reflectance for MIRACO2LAS) were processed to enhance spectral information related to the surface composition. This spectral information was compared with existing geological maps and field emissivity spectra. Known geological units were well discriminated in the TIMS imagery, including a range of quartz‐rich and carbonate‐rich sedimentary units, as well as several previously unmapped areas of alteration in the carbonate rocks. However, the broadband spectral resolution of TIMS did not allow identification of discrete mineral constituents. In contrast, the high spectral resolution MIRACO2LAS data provided diagnostic spectral information about a range of minerals present including quartz, dolomite, talc, and tremolite, albeit, along discrete profiles. The widths of some of these diagnostic spectral features were less than 0.2 μm wide, which is half the resolution of the TIMS band passes (0.4 μm). The MIRACO2LAS spectra closely matched the shape, location, and depth of spectra of field samples measured by both a field emission spectrometer and a laboratory laser spectrometer. Pure mineral spectra measured by the (bidirectional) laboratory laser spectrometer also closely matched those measured by a conventional laboratory spectrometer measuring directional hemispherical reflectance. These results indicate that future remote thermal infrared systems designed for improved geological mapping and mineral exploration should incorporate both an imager for mapping lithological units and a high spectral resolution profiler for identifying dominant mineral constituents. Recently, a hyperspectral imaging thermal infrared instrument has been developed termed Spatially Enhanced Broadband Array Spectrograph System (SEBASS) [Hackwell and Warren, 1997]. This instrument should allow spectral identification of an entire scene [Gillespie et al., 1997], although the swath width is currently limited to 128 pixels as opposed to the 752 pixels of TIMS after panoramic correction.

Recovering Surface Temperature and Emissivity from Thermal Infrared Multispectral Data

In 1992 Thermal Infrared Multispectral Scanner (TIMS) data were acquired from the NASA C-130 aircraft over the Sahelian region of West Africa as part of the Hydrological and Atmospheric Pilot Experiment in the Sahel (HAPEX). TIMS measures the radiation from the surface modified by the atmosphere in six channels located between 8 mm and 12.5 μm in the thermal infrared. By using a variety of techniques it is possible to extract both the surface temperature and surface emissivity from the areas over which TIMS data were acquired. One such technique was tested with the data acquired during this experiment. Several TIMS images of both the east and west central sites on 2 and 4 September were processed, and the spectral behaviors of different land cover types were determined. These included tiger bush, millet, and fallow grassland sites. There was a 5–10 K difference in the brightness temperature over the six channels when significant bare soil was visible. Channels 1–3 (8.2–9.4 μm) were cooler than the longer wavelength channels (9.6–12.5 μm), which is characteristic of soils rich in quartz. These differences in brightness were converted to emissivity differences using the max–min difference (MMD) method. This method relies on an empirical relationship observed between the range of emissivities and the minimum value for the six TIMS channels. The MMD method was applied iteratively to several entire scenes for the east central site on the two days with the interesting results that Channel 5 showed very little spatial variation in emissivity and the short wavelength channels observed substantial regions with emissivities of about 0.8 or less. There is excellent reproducibility when the same area is seen in different lines on the same day. However, there are differences when the same area is seen on the two days especially for the low emissivity values. Some of these differences may be due to soil moisture differences of 2–3%, which were observed for the two days. The observed surface temperatures were in good agreement with other measures, for example, vegetation temperatures agreed well with the measured air temperatures. Published by Elsevier Science Inc.

Thermal infrared spectra and TIMS imagery features of sedimentary rocks in the Kalpin Uplift, Tarim Basin, China

Airborne Thermal Infrared Multispectral Scanner (TIMS) data and laboratory thermal infrared emission spectra were colleted for sedimentary rocks from the Kalpin Uplift, the northwestern margin of Tarim Basin. Sandstone, siltstone and argillite have low emissivity bands between 8 and 10 μm, which results from interatomic stretching vibrations of silicon and oxygen bound in the crystal lattice, and the position of band center has been shown to migrate towards longer wavelength with decreasing of quartz content and the variation of silicon‐oxygen structure. Carbonate rocks exhibit a low emissivity band near 11. 3 μm due to C‐0 bending modes, the position of band center moves to shorter wavelength as of Mg2+ content increases. Based on the analysis of thermal infrared spectral features of sedimentary rocks, integrated with results of the chemical analysis, X‐ray diffraction and thin‐section identification of sedimentary rocks, a colour composite of three of the seven channels of TIMS data was processed with a decorrelation stretch. The sandstones, siltstones, argillites, carbonate rocks and the transitional type rocks among them could be distinguished.

Analysis of vegetation within a semi-arid urban environment using high spatial resolution airborne thermal infrared remote sensing data

High spatial resolution (5 m) remote sensing data obtained using the airborne Thermal Infrared Multispectral Scanner (TIMS) sensor for daytime and nighttime have been used to measure thermal energy responses for 2 broad classes and 10 subclasses of vegetation typical of the Salt Lake City, Utah urban landscape. Polygons representing discrete areas corresponding to the 10 subclasses of vegetation types have been delineated from the remote sensing data and are used for analysis of upwelling thermal energy for day, night, and the change in response between day and night or flux, as measured by the TIMS. These data have been used to produce three-dimensional graphs of energy responses in W m −2 for day, night, and flux, for each urban vegetation land cover as measured by each of the six channels of the TIMS sensor. Analysis of these graphs provides a unique perspective for both viewing and understanding thermal responses, as recorded by the TIMS, for selected vegetation types common to Salt Lake City. A descriptive interpretation is given for each of the day, night, and flux graphs along with an analysis of what the patterns mean in reference to the thermal properties of the vegetation types surveyed in this study. From analyses of these graphs, it is apparent that thermal responses for vegetation can be highly varied as a function of the biophysical properties of the vegetation itself, as well as other factors. Moreover, it is also seen where vegetation, particularly trees, has a significant influence on damping or mitigating the amount of thermal radiation upwelling into the atmosphere across the Salt Lake City urban landscape.

Scale in remote sensing and GIS

Introduction: Scale, Multiscaling, Remote Sensing, and GIS, M.F. Goodchild and D.A. Quattrochi Multiscale Nature of Spatial Data in Scaling Up Environmental Models, L. Bian Scale Dependence of NDVI and its Relationship to Mountainous Terrain, S.J. Walsh, A. Moody, T.R. Allen, and D.G. Brown Understanding the Scale and Resolution Effects in Remote Sensing and GIS, C.-Y. Cao and N. S.-N. Lam Multiresolution Covariation among Landsat and AVHRR Vegetation Indices, L. De Cola Multiscaling Analysis in Distributed Modeling and Remote Sensing: An Application Using Soil Moisture, R. Dubayah, E.F. Wood, and D. Lavallee Examining the Effects of Sensor Resolution and Sub-Pixel Heterogeneity on Spectral Vegetation Indices: Implications for Biophysical Modeling, M.A. Friedl Multiscale Vegetation Data for the Mountains of Southern California: Spatial and Categorical Resolution, J. Franklin and C.E. Woodcock The Use of Remotely Sensed Surface Temperatures from an Aircraft-Based Thermal Infrared Multispectral Scanner (TIMS) to Estimate the Spatial and Temporal Variability of Latent Heat Fluxes and Thermal Response Numbers from a White Pine (Pinus strobus L.) Plantation, J.C. Luvall Scaling Predicted Pine Forest Hydrology and Productivity across the Southern United States, S.G. McNulty, J.M. Vose, and W.T. Swank Modeling Effects of Spatial Pattern, Drought, and Grazing on Rates of Rangeland Degradation: A Combined Markov and Cellular Automaton Approach, H. Li and J.F. Reynolds Scaling Land Cover Heterogeneity for Global Atmosphere-Biosphere Models, R.S. DeFries, J.R. Townshend, and S.O. Los Quadtrees: Hierarchical Multiresolution Data Structures for Analysis of Digital Images, F. Csillag Statistical Models for Multiple Scaled Analysis, D.E. Myers Image Characterization and Modeling System (ICAMS): A Geographic Information System for the Characterization and Modeling of Multiscale Remote Sensing Data, D.A. Quattrochi, N. S.-N. Lam, H.-L. Qiu, and W. Zhao Approaches to Scaling of Geo-Spatial Data, Z.-G. Xia and K.C. Clarke Multifractals and Remotely Sensed Data: Generalized Scale Invariance, Geographical Information Systems and Resolution Dependence, S. Pecknold, S. Lovejoy, D. Schertzer, and C. Hooge Index