Thermal Infrared

This paper compares the normalized difference vegetation index (NDVI) and percent impervious surface as indicators of surface urban heat island effects in Landsat imagery by investigating the relationships between the land surface temperature (LST), percent impervious surface area (%ISA), and the NDVI. Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data were used to estimate the LST from four different seasons for the Twin Cities, Minnesota, metropolitan area. A map of percent impervious surface with a standard error of 7.95% was generated using a normalized spectral mixture analysis of July 2002 Landsat TM imagery. Our analysis indicates there is a strong linear relationship between LST and percent impervious surface for all seasons, whereas the relationship between LST and NDVI is much less strong and varies by season. This result suggests percent impervious surface provides a complementary metric to the traditionally applied NDVI for analyzing LST quantitatively over the seasons for surface urban heat island studies using thermal infrared remote sensing in an urbanized environment.

The emission of light by a material at temperature T has been shown recently to be coherent in the near field. These properties were attributed to the thermal excitation of surface polaritons. We review the origin of this phenomenon. We analyze the influence of the microstructure and temperature on the coherence properties and show how to engineer thermoradiative properties of surfaces. We report the design of a quasi-isotropic source and a very directional source of thermal light. We also report a measurement of the transverse coherence length of a thermal source of light.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution, multispectral imager with alongtrack stereo capabilities scheduled for launch on the first NASA spacecraft of the Earth Observing System (EOS AM-1) in mid-199 . Data will be obtained in 14 spectral bands covering the visible through the < hermal infrared wavelength region. A number of standard data products will be available to requesters through an on-line archival and processing system. Particular, user-specified data acquisitions will be possible through a Data Acquisition Request system. res0000913 06-09-99 2 0 : 5 7 : 4 0 R.-W 1 4 -0 5 r e s 0 0 0 0 9 1 3 0 6 -0 9 -9 9 2 0 : 5 7 : 4 0 R e v 1 4 . 0 5 The Charlesworth Group, Huddersfield 01484 517077

The Thermal Emission Imaging System (THEMIS) on 2001 Mars Odyssey will investigate the surface mineralogy and physical properties of Mars using multi-spectral thermal-infrared images in nine wavelengths centered from 6.8 to 14.9 µm, and visible/near-infrared images in five bands centered from 0.42 to 0.86 µm. THEMIS will map the entire planet in both day and night multi-spectral infrared images at 100-m per pixel resolution, 60% of the planet in one-band visible images at 18-m per pixel, and several percent of the planet in 5-band visible color. Most geologic materials, including carbonates, silicates, sulfates, phosphates, and hydroxides have strong fundamental vibrational absorption bands in the thermal-infrared spectral region that provide diagnostic information on mineral composition. The ability to identify a wide range of minerals allows key aqueous minerals, such as carbonates and hydrothermal silica, to be placed into their proper geologic context. The specific objectives of this investigation are to: (1) determine the mineralogy and petrology of localized deposits associated with hydrothermal or sub-aqueous environments, and to identify future landing sites likely to represent these environments; (2) search for thermal anomalies associated with active sub-surface hydrothermal systems; (3) study small-scale geologic processes and landing site characteristics using morphologic and thermophysical properties; and (4) investigate polar cap processes at all seasons. THEMIS follows the Mars Global Surveyor Thermal Emission Spectrometer (TES) and Mars Orbiter Camera (MOC) experiments, providing substantially higher spatial resolution IR multi-spectral images to complement TES hyperspectral (143-band) global mapping, and regional visible imaging at scales intermediate between the Viking and MOC cameras. The THEMIS uses an uncooled microbolometer detector array for the IR focal plane. The optics consists of all-reflective, three-mirror anastigmat telescope with a 12-cm effective aperture and a speed of f/1.6. The IR and visible cameras share the optics and housing, but have independent power and data interfaces to the spacecraft. The IR focal plane has 320 cross-track pixels and 240 downtrack pixels covered by 10 ∼1-µm-bandwidth strip filters in nine different wavelengths. The visible camera has a 1024 × 1024 pixel array with 5 filters. The instrument weighs 11.2 kg, is 29 cm by 37 cm by 55 cm in size, and consumes an orbital average power of 14 W.

Land Surface Temperature (LST) is operationally retrieved from measurements of several space-borne sensors, e.g. the LST product derived by Land Surface Analysis -Satellite Application Facility (LSA-SAF) for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board Meteosat Second Generation (MSG) and the LST product derived for the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-Terra by the MODIS Land Team. The relative accuracy of an LST product can be assessed by cross-validating between products obtained with different LST retrieval algorithms and / or for different sensors. Alternatively, so-called 'radiance based validation' can be employed, which is not a validation method in a strict sense but a comparison of satellite-retrieved LST with results from radiative transfer models and requires precise knowledge of surface and atmospheric conditions. Ultimately, 'ground truth' measurements are needed for validating satellite LST products. Therefore, the LST product derived by LSA-SAF is validated with independent in-situ measurements ('temperature based validation') at four permanent stations located in different climate regions. However, temperature based validation is largely complicated by the spatial scale mismatch between satellite sensors and ground based sensors: areas observed by ground radiometers usually cover about 10 m 2 , whereas satellite measurements in the thermal infrared typically cover between 1 km 2 and 100 km 2 . The characterization of the surface is particularly critical for all validation approaches, as in-situ measurements revealed that current land surface emissivity (LSE) products over arid regions can be wrong by more than 3%. LSEs of the dominant surface cover types at Gobabeb (Namibia) and at Dahra (Senegal) were obtained from in-situ and laboratory measurements. Both validation sites have quite large fractions of bare ground and are, therefore, particularly prone to be misrepresented in satellite-retrieved LSEs. Accurate estimations of in-situ LSE are essential to validate satellite LST&E products and to limit the uncertainty of ground-based LST observations. The monitoring capability of the validation stations is demonstrated with 5 years of LST derived operationally by LSA-SAF from MSG/SEVIRI data.

This paper presents an evaluation of the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared bands and the status of land surface temperature (LST) version-3 standard products retrieved from Terra MODIS data. The accuracy of daily MODIS LST products has been validated in more than 20 clear-sky cases with in situ measurement data collected in field campaigns in 2000-2002. The MODIS LST accuracy is better than 1 ‡C in the range from 210 to 50 ‡C. Refinements and improvements were made to the new version of MODIS LST product generation executive code. Using both Terra and Aqua MODIS data for LST retrieval improves the quality of the LST product and the diurnal feature in the product due to better temporal, spatial and angular coverage of clear-sky observations.

We present an operational two-source (soil+vegetation) ,ugdel for evaluating the surface energy balance given measurements of the time rate of change in radiometric surface temperature (TRao) during the ~u~rning hours. This model consists of a two-source surface component describing the relation between T~o and sensible heat flux, coupled with a time-integrated component connecting surface sensible heating with planetary boundary layer development. By tying together the time-dependent behavior of surface temperature and the temperature in the boundary layer with the flux of sensible heat from the surface to the atmosphere, the need fi~r ancillary measurements of near-surface air temperature is eliminated. This is a significant benefit when T~ao is acquired remotely. Air temperature can be strongly coupled to local biophysical surface conditions and, if the surface air and brightness temperature measurements" used by a model are not collocated, energy flux estimates can be significantly corrupted. Furthermore, because this model uses only temporal changes in radiometric temperatures rather than absolute temperatures', time-independent biases in T~ao, resulting from atmospheric effects or other sources, do not affect the estimated fluxes; only the timevarying component of corrections need be computed. The algorithm also decomposes the surface radiometric tern-

It Is possible to measure surface radmnt temperature fields of subplxel spatial resolution from satellites which contain more than one channel m the thermal infrared spectral regmn Because of the different response of the Planck hmctmn at different wavelengths, the radmnt temperatures measured m two channels may be expressed m terms of contributions from two temperatttre fields, each occupying a pomon of the plxel, where the portJons are not necessarily contiguous The resulting simultaneous nonhnear equations may be solved for the comphmentary portions of the plxel occupied and one unknown temperature In two adjacent plxels which can be assumed to have the same target temperatures and same background temperatures, both unknown temperatures may be found

Robust satellite-derived moisture stress indices will be beneficial to operational drought monitoring, both in the United States and globally. Using thermal infrared imagery from the Geostationary Operational Environmental Satellites (GOES) and vegetation information from the Moderate Resolution Imaging Spectrometer (MODIS), a fully automated inverse model of Atmosphere-Land Exchange (ALEXI) has been used to model daily evapotranspiration and surface moisture stress over a 10-km resolution grid covering the continental United States. Examining monthly clear-sky composites for April-October 2002-2004, the ALEXI evaporative stress index (ESI) shows good spatial and temporal correlation with the Palmer drought index but at considerably higher spatial resolution. The ESI also compares well to anomalies in monthly precipitation fields, demonstrating that surface moisture has an identifiable thermal signature that can be detected from space, even under dense vegetation cover. Simple empirical thermal drought indices like the vegetation health index do not account for important forcings on surface temperature, such as available energy and atmospheric conditions, and can therefore generate spurious drought detections under certain circumstances. Surface energy balance inherently incorporates these forcings, constraining ESI response in both energy- and water-limited situations. The surface flux modeling techniques described here have demonstrated skill in identifying areas subject to soil moisture stress on the basis of the thermal land surface signature, without requiring information regarding antecedent rainfall. ALEXI therefore may have potential for operational drought monitoring in countries lacking well-established precipitation measurement networks.

This paper discusses the application and adaptation of two existing operational algorithms for land surface emissivity (ε) retrieval from different operational satellite/airborne sensors with bands in the visible and near-infrared (VNIR) and thermal IR (TIR) regions: 1) the temperature and emissivity separation algorithm, which retrieves ε only from TIR data and 2) the normalized-difference vegetation index thresholds method, in which ε is retrieved from VNIR data.

The use of thermal infrared (IR) imaging is a valuable tool for inspecting and performing non-destructive testing of building elements, detecting where and how energy is leaking from a building’s envelope, collecting data for clarifying the operating conditions of hard to reach heating, ventilating and air-conditioning (HVAC) installations, identifying problems with the electrical and mechanical installations under full-load operating conditions. IR inspections involve the detection of IR electromagnetic radiation emitted by the inspected object. The collected information can be used as part of other investigative procedures to identify potential problems, quantify potential energy savings, schedule interventions and set priorities for preventive and predictive maintenance or the need for immediate service to minimise the risk of failure. This paper reviews the main areas for using IR in building diagnostics with an emphasis on how it was implemented to support office building audits following the TOBUS methodology. Representative examples from building envelope, mechanical and electrical inspections in audited Hellenic office buildings are presented to demonstrate common problems and data interpretation.

A consistent nomenclature for thermal infrared remote sensing of natural surfaces is outlined in this paper. Terms such as 'canopy temperature' and 'surface temperature' should be confined to general, qualitative descriptions and terms such as directional radiometric temperature, hemispherical emissivity, aerodynamic temperature, or hemispherical-directional reflectance used for technical precision. Some discussion also is included on the relation between hemispherical-directional thermal reflectance and directional thermal emissivity. A distinction is made between two kinds of emissivity; e-emissivity and r-emissivity. Through use of detailed models of directional thermal emissivity and bidirectional reflectance, we suggest that the influence of temperature gradients in vegetation on directional emissivity usually will cause uncertainties of less than 0.005. In addition, uncertainties that occur in estimating surface temperature, which arise because an ensemble of black bodies each at a different temperature does not have a black body radiance distribution with temperature, will not always be negligible for purposes of remote sensing of natural surfaces. Differences between mean thermodynamic and ensemble radiometric temperatures of 1 K or larger are possible even though differences in ensemble radiometric temperatures for different wavelength bands in the atmospheric window (8-14 p,rn) usually will be less than 0.1 K. 016%1923/95/$09.50 0 1995 Elsevier Science B.V. All rights reserved SSDI 0168-1923(95)02259-7

Thermal imaging using infrared (IR) is now an established technology for the study of stomatal responses and for phenotyping plants for differences in stomatal behaviour. This paper outlines the potential applications of IR sensing in drought phenotyping, with particular emphasis on a description of the problems with extrapolation of the technique from the study of single leaves in controlled environments to the study of plant canopies is field plots, with examples taken from studies on grapevine (Vitis vinifera L.) and rice (Oryza sativa L.). Particular problems include the sensitivity of leaf temperature (and potentially the temperature of reference surfaces) to both temporal and spatial variation in absorbed radiation, with leaf temperature varying by as much as 15 C between full sun and deep shade. Examples of application of the approach to phenotyping in the field and the steps in data analysis are outlined, demonstrating that clear genotypic variation may be detected despite substantial variation in soil moisture status or incident radiation by the use of appropriate normalisation techniques.

A soil-derived dust enfission scheme has been designed in order to provide si•nulation of •nineral dust sources for atmospheric transport •nodels . This physical scheme considers the influence of surthce t•atures to compute the erosion tlu-eshold and the intensity of the dust enfissions. It has been validated by comparison with relevant experimental data. However, it was necessary to extend its applicability m•d to test its capability to reproduce dust enfissions over large arid areas.

In standard near-field scanning optical microscopy (NSOM), a subwavelength probe acts as an optical 'stethoscope' to map the near field produced at the sample surface by external illumination 1 . This technique has been applied using visible 1,2 , infrared 3 , terahertz 4 and gigahertz 5,6 radiation to illuminate the sample, providing a resolution well beyond the diffraction limit. NSOM is well suited to study surface waves such as surface plasmons 7 or surfacephonon polaritons 8 . Using an aperture NSOM with visible laser illumination, a near-field interference pattern around a corral structure has been observed 9 , whose features were similar to the scanning tunnelling microscope image of the electronic waves in a quantum corral 10 . Here we describe an infrared NSOM that operates without any external illumination: it is a near-field analogue of a night-vision camera, making use of the thermal infrared evanescent fields emitted by the surface, and behaves as an optical scanning tunnelling microscope 11,12 . We therefore term this instrument a 'thermal radiation scanning tunnelling microscope' (TRSTM). We show the first TRSTM images of thermally excited surface plasmons, and demonstrate spatial coherence effects in near-field thermal emission.

The Sun and &gt;15per cent of nearby stars are surrounded by dusty disks that must be collisionally replenished by asteroids and comets, as the dust would otherwise be depleted on timescales &lt;107years (ref. 1). Theoretical studies show that the structure of a dusty disk can be modified by the gravitational influence of planets, but the observational evidence is incomplete, at

Multiple satellite sensors are used to analyze physical processes that determine energy fluxes and their interaction at the urban surface. The study is based on summertime microclimate analyses of the Los Angeles and Paris metropolises. The method consists of deriving some parameters governing the surface heat fluxes, constructing statistics of thermal infrared images, and using a GIS to combine them with a landcover classification from SPOT-HRV multispectral images, and with data from intensive in-situ experiments. The average images reveal spatial and temporal variations of land surface temperature (LST), and distinct microclimatic patterns. The combined interpretation of the statistics images and of the landcover classification shows: (i) the effect of surface physical properties, especially in downtown business and industrial districts that display heat-islands larger than 7 jC; (ii) the temperating influence of water; (iii) the negative correlation between afternoon land surface temperature and normalized vegetation index, which confirms the cooling effect of urban parks; (iv) the correlation between variations of surface temperature and ozone concentration at diurnal and longer time scales.

Airborne remote sensing methods are needed to assess spatial patterns of stream temperature at scales relevant to issues in water quality and fisheries management. In this study, we developed an airborne remote sensing method to measure spatially continuous patterns of stream temperature and evaluated the physical factors that influence the accuracy of thermal remote sensing of flowing waters. The airborne thermal infrared (TIR) system incorporated an internally calibrated thermal imager (8 ± 12 mm) aligned with a visible band camera in a vertically mounted, gimbaled pod attached to the underside of a helicopter. High-resolution imagery (0.2 ± 0.4 m) covering the entire channel and adjacent floodplains was recorded digitally and georeferenced in-flight along 50-to 60-km river sections ranging from 2 to 110 m in width. Radiant water temperature corresponded to kinetic water temperature (5 ± 27°C) in a range of stream environments within 0.5°C. Longitudinal profiles of radiant water temperature from downstream to headwater reaches provided a spatial context for assessing large-scale patterns of thermal heterogeneity and fine-scale thermal features such as tributaries and groundwater inputs. Potential sources of error in remote measurements of stream temperature included reflected longwave radiation, thermal boundary layer effects at the water surface, and vertical thermal stratification. After taking into account the radiative properties of the surrounding environment and the physical qualities of the stream, thermal remote sensing proved highly effective for examining spatial patterns of stream temperature at a resolution and extent previously unattainable through conventional methods of stream temperature measurement using in-stream data recorders. D Remote Sensing of Environment 76 (2001) 386 ± 398 0034-4257/01/$ ± see front matter D 2001 Elsevier Science Inc. All rights reserved. PII: S 0 0 3 4 -4 2 5 7 ( 0 1 ) 0 0 1 8 6 -9

With the NEOWISE portion of the Wide-field Infrared Survey Explorer (WISE) project, we have carried out a highly uniform survey of the near-Earth object (NEO) population at thermal infrared wavelengths ranging from 3 to 22 µm, allowing us to refine estimates of their numbers, sizes, and albedos. The NEOWISE survey detected NEOs the same way whether they were previously known or not, subject to the availability of ground-based follow-up observations, resulting in the discovery of more than 130 new NEOs. The survey's uniform sensitivity, observing cadence, and image quality have permitted extrapolation of the 428 near-Earth asteroids (NEAs) detected by NEOWISE during the fully cryogenic portion of the WISE mission to the larger population. We find that there are 981±19 NEAs larger than 1 km and 20,500±3000 NEAs larger than 100 m. We show that the Spaceguard goal of detecting 90% of all 1 km NEAs has been met, and that the cumulative size distribution is best represented by a broken power law with a slope of 1.32±0.14 below 1.5 km. This power law slope produces ∼ 13, 200±1,900 NEAs with D >140 m. Although previous studies predict another break in the cumulative size distribution below D ∼50-100 m, resulting in an increase in the number of NEOs in this size range and smaller, we did not detect enough objects to comment on this increase. The overall number for the NEA population between 100-1000 m is lower than previous estimates. The numbers of near-Earth comets and potentially hazardous NEOs will be the subject of future work.

Satellite images in the thermal infrared can be used for assessing the thermal urban environment as well as for defining heat islands in urban areas. In this study, the thermal environment of major cities in Greece (Athens, Thessaloniki, Patra, Volos and Heraklion) is examined using satellite images provided by the Landsat Enhanced Thematic Mapper (ETM+) sensor on board Landsat 7 satellite corresponding to the daytime and warm period when the surface urban heat island (SUHI) phenomenon is best observed. The spatial structure of the thermal urban environment is analyzed in each case study and the ''hottest'' surfaces within the urban settings are identified and related to the urban surface characteristics and land use. For the needs of the study, the Corine land cover (CLC) database for Greece is also used, in an effort to define more effectively the link between surface emissivities, land surface temperatures and urban surface characteristics.

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (soil moisture, advection, air temperature) are affecting plant stress. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5-10 km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI), spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions of 30 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe and, Africa and other continents with geostationary satellite coverage.

We report the first near infrared (NIR) imaging of a circumstellar annular disk around the young (∼8 Myr), Vega-like star, HR 4796A. NICMOS coronagraph observations at 1.1 and 1.6 µm reveal a ring-like symmetrical structure peaking in reflected intensity 1.05 ′′ ± 0.02 ′′ (∼70 AU) from the central A0V star. The ring geometry, with an inclination of 73.1 • ± 1.2 • and a major axis PA of 26.8 • ± 0.6 • is in good agreement with recent 12.5 and 20.8 µm observations of a truncated disk ). The ring is resolved with a characteristic width of less than 0.26 ′′ (17 AU) and appears abruptly truncated at both the inner and outer edges. The region of the disk-plane inward of ∼60 AU appears to be relatively free of scattering material. The integrated flux density of the part of the disk that is visible (greater than 0.65 ′′ from the star) is found to be 7.5 ± 0.5 mJy and 7.4 ± 1.2 mJy at 1.1 and 1.6 µm, respectively.

The MODIS/ASTER Airborne Simulator was developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) projects. ASTER and MODIS are both spaceborne imaging instruments on the Terra platform launched in the fall of 1999. Currently MASTER is flown on the Department of Energy (DOE) King Air Beachcraft B200 aircraft and the NASA DC-8. In order to validate the in-flight performance of the instrument, the Jet Propulsion Laboratory and the University of Arizona conducted a joint experiment in December 1998. The experiment involved overflights of the MASTER instrument at two sites at three elevations (2000, 4000, and 6000 m). The two sites: Ivanpah Playa, California, and Lake Mead, Nevada, were selected to validate the visible ± shortwave infrared and thermal infrared (TIR) channels, respectively. At Ivanpah Playa, a spectrometer was used to determine the surface reflectance and a sun photometer used to obtain the optical depth. At Lake Mead contact and radiometric surface lake temperatures were measured by buoy-mounted thermistors and self-calibrating radiometers, respectively. Atmospheric profiles of temperature, pressure, and relative humidity were obtained by launching an atmospheric sounding balloon. The measured surface radiances were then propagated to the at-sensor radiance using radiative transfer models driven by the local atmospheric data. There was excellent agreement between the predicted radiance at sensor and the measured radiance at sensor at all three altitudes. The percent difference between the channels not strongly affected by the atmosphere in the visible ± shortwave infrared was typically 1 ± 5% and the percent difference between the TIR channels not strongly affected by the atmosphere was typically less than 0.5%. These results indicate the MASTER instrument should provide a well-calibrated instrument for Earth Science Studies. It should prove particularly valuable for those studies that leverage information across the electromagnetic spectrum from the visible to the TIR. D (S.J. Hook). www.elsevier.com/locate/rse Remote Sensing of Environment 76 (2001) 93 ± 102 0034-4257/00/$ ± see front matter D 2001 Elsevier Science Inc. All rights reserved. PII: S 0 0 3 4 -4 2 5 7 ( 0 0 ) 0 0 1 9 5 -4

The current dominant approaches to face recognition rely on facial characteristics that are on or over the skin. Some of these characteristics have low permanency can be altered, and their phenomenology varies significantly with environmental factors (e.g., lighting). Many methodologies have been developed to address these problems to various degrees. However, the current framework of face recognition research has a potential weakness due to its very nature. We present a novel framework for face recognition based on physiological information. The motivation behind this effort is to capitalize on the permanency of innate characteristics that are under the skin. To establish feasibility, we propose a specific methodology to capture facial physiological patterns using the bioheat information contained in thermal imagery. First, the algorithm delineates the human face from the background using the Bayesian framework. Then, it localizes the superficial blood vessel network using image morphology. The extracted vascular network produces contour shapes that are characteristic to each individual. The branching points of the skeletonized vascular network are referred to as Thermal Minutia Points (TMPs) and constitute the feature database. To render the method robust to facial pose variations, we collect for each subject to be stored in the database five different pose images (center, midleft profile, left profile, midright profile, and right profile). During the classification stage, the algorithm first estimates the pose of the test image. Then, it matches the local and global TMP structures extracted from the test image with those of the corresponding pose images in the database. We have conducted experiments on a multipose database of thermal facial images collected in our laboratory, as well as on the time-gap database of the University of Notre Dame. The good experimental results show that the proposed methodology has merit, especially with respect to the problem of low permanence over time. More importantly, the results demonstrate the feasibility of the physiological framework in face recognition and open the way for further methodological and experimental research in the area.

Remote sensing of snowpack temperatures from satellites requires knowledge of the spectral emissivity of snow. A model for spectral emissivity is combined with the Planck function to calculate bffghtness temperature of snow in thermal infrared wavelengths for a range of grain sizes and viewing angles. Emissivity variations caused by density, grain shape, liquid water, and grain size are apparently unimportant, but emissivity varies with viewing angle to produce differences between thermodynamic temperature and brightness temperature as large as 3 K at Wavelengths 12 to 14/am, within the major atmospheric infrared window. This difference is also verified by experimental measurements. An equation to convert b.rightness temperatures to thermodynamic temperatures is presented, and this is also combined with a dual-wavelength atmospheric correction method. The spe.ctra.1 emissivity model is also used to calculate an 'all-wave' emissivity of snow: 0.985-0.990 for all grain sizes. emissivity (also;called emittance) can be calculated if the directional-hemispherical reflectance (the term defined by Nicodemus et al. [1977] for total hemispherical reflectance of d. irect irradiance) is known: es(},,/Xv) = 1 -Rs(},,

To simulate the formation of impact glasses on Mars, an analogue of martian bright soil (altered volcanic soil JSC Mars-1) was melted at relevant oxygen fugacities using a pulsed laser and a resistance furnace. Reduction of Fe 3+ to Fe 2+ and in some cases formation of nanophase Fe 0 in the glasses were documented by Mössbauer spectroscopy and TEM studies. Reflectance spectra for several size fractions of the JSC Mars-1 sample and the glasses were acquired between 0.3 and 25 μm. The glasses produced from the JSC Mars-1 soil show significant spectral variability depending on the method of production and the cooling rate. In general, they are dark and less red in the visible compared to the original JSC Mars-1 soil. Their spectra do not have absorption bands due to bound water and structural OH, have positive spectral slopes in the near-infrared range, and show two broad bands centered near 1.05 and 1.9 μm, typical of glasses rich in ferrous iron. The latter bands and low albedo partly mimic the spectral properties of martian dark regions, and may easily be confused with mafic materials containing olivine and low-Ca pyroxene. Due to their disordered structures and vesicular textures, the glasses show relatively weak absorption features from the visible to the thermal infrared. These weak absorption bands may be masked by the stronger bands of mafic minerals. Positive near-infrared spectral slopes typical of fresh iron-bearing impact or volcanic glasses may be masked either by oxide/dust coatings or by aerosols in the Mars' atmosphere. As a result, impact glasses may be present on the surface of Mars in significant quantities that have been either misidentified as other phases or masked by phases with stronger infrared features. Spectrometers with sufficient spatial resolution and wavelength coverage may detect impact glasses at certain locations, e.g., in the vicinity of fresh impact craters. Such dark materials are usually interpreted as accumulations of mafic volcanic sand, but the possibility of an impact melt origin of such materials also should be considered. In addition, our data suggest that high contents of feldspars or zeolites are not necessary to produce the transparency feature at 12.1 μm typical of martian dust spectra.

An investigation of the detection of water stress in non-homogeneous crop canopies such as orchards using high-spatial resolution remote sensing thermal imagery is presented. An airborne campaign was conducted with the Airborne Hyperspectral Scanner (AHS) acquiring imagery in 38 spectral bands in the 0.43-12.5 mm spectral range at 2.5 m spatial resolution. The AHS sensor was flown at 7:30, 9:30 and 12:30 GMT in 25 July 2004 over an olive orchard with three different water-deficit irrigation treatments to study the spatial and diurnal variability of temperature as a function of water stress. A total of 10 AHS bands located within the thermal-infrared region were assessed for the retrieval of the land surface temperature using the split-window algorithm, separating pure crowns from shadows and sunlit soil pixels using the reflectance bands. Ground truth validation was conducted with infrared thermal sensors placed on top of the trees for continuous thermal data acquisition. Crown temperature (T c ), crown minus air temperature (T c À T a ), and relative temperature difference to well-irrigated trees (T c À T R , where T R is the mean temperature of the well-irrigated trees) were calculated from the ground sensors and from the AHS imagery at the crown spatial resolution. Correlation coefficients for T c À T R between ground IRT sensors and airborne image-based AHS estimations were R 2 = 0.50 (7:30 GMT), R 2 = 0.45 (9:30 GMT) and R 2 = 0.57 (12:30 GMT). Relationships between leaf water potential and crown T c À T a measured with the airborne sensor obtained determination coefficients of R 2 = 0.62 (7:30 GMT), R 2 = 0.35 (9:30 GMT) and R 2 = 0.25 (12:30 GMT). Images of T c À T a and T c À T R for the entire field were obtained at the three times during the day of the overflight, showing the spatial and temporal distribution of the thermal variability as a function of the water deficit irrigation schemes. #

We infer CO 2 surface fluxes using satellite observations of mid-tropospheric CO 2 from the Tropospheric Emission Spectrometer (TES) and measurements of CO 2 from surface flasks in a time-independent inversion analysis based on the GEOS-Chem model. Using TES CO 2 observations over oceans, spanning 40 • S-40 • N, we find that the hor-5 izontal and vertical coverage of the TES and flask data are complementary. This complementarity is demonstrated by combining the datasets in a joint inversion, which provides better constraints than from either dataset alone, when a posteriori CO 2 distributions are evaluated against independent ship and aircraft CO 2 data. In particular, the joint inversion offers improved constraints in the tropics where surface measure-10 ments are sparse, such as the tropical forests of South America, which the joint inversion suggests was a weak sink of −0.17 ± 0.20 Pg C in 2006. Aggregating the annual surface-to-atmosphere fluxes from the joint inversion yields −1.13 ± 0.21 Pg C for the global ocean, −2.77 ± 0.20 Pg C for the global land biosphere and −3.90 ± 0.29 Pg C for the total global natural flux (defined as the sum of all biospheric, oceanic, and 15 biomass burning contributions but excluding CO 2 emissions from fossil fuel combustion). These global ocean, global land and total global fluxes are shown to be in the range of other inversion results for 2006. To achieve these results, a latitude dependent bias in TES CO 2 in the Southern Hemisphere was assessed and corrected using aircraft flask data, and we demonstrate that our results have low sensitivity to variations 20 in the bias correction approach. Overall, this analysis suggests that future carbon data assimilation systems can benefit by integrating in situ and satellite observations of CO 2 and that the vertical information provided by satellite observations of mid-tropospheric CO 2 combined with measurements of surface CO 2 , provides an important additional constraint for flux inversions. Chevallier et al., 2010a) using in situ observations from instruments at surface stations, towers, ships and aircraft and/or flask samples collected from these platforms, then later analyzed in a laboratory (Conway et al., 1994). Measurement 25 coverage has increased over the years, and forward and inverse modeling techniques have also improved, but a major limitation in achieving further reductions in CO 2 flux uncertainties is the sparse data coverage that remains throughout the tropics, extra-4266

Thermal infrared (IR) imagery offers a promising alternative to visible imagery for face recognition due to its relative insensitive to variations in face appearance caused by illumination changes. Despite its advantages, however, thermal IR has several limitations including that it is opaque to glass. The focus of this study is on the sensitivity of thermal IR imagery to facial occlusions caused by eyeglasses. Specifically, our experimental results illustrate that recognition performance in the IR spectrum degrades seriously when eyeglasses are present in the probe image but not in the gallery image and vice versa. To address this serious limitation of IR, we propose fusing IR with visible imagery. Since IR and visible imagery capture intrinsically different characteristics of the observed faces, intuitively, a better face description could be found by utilizing the complimentary information present in the two spectra. Two different fusion schemes have been investigated in this study. The first one is pixelbased and operates in the wavelet domain, while the second one is feature-based and operates in the eigenspace domain. In both cases, we employ a simple and general framework based on Genetic Algorithms (GAs) to find an optimum fusion strategy. We have evaluated our approaches through extensive experiments using the Equinox face database and the eigenface recognition methodology. Our results illustrate significant performance improvements in recognition, suggesting that IR and visible fusion is a viable approach that deserves further consideration. q

The optical and radiative properties of dust particles in solar and thermal infrared regions are investigated. Dust particles are assumed to be spheres and spheroids for a comparison aimed at understanding the nonsphericity effect of these particles on the radiation at the top of a dusty atmosphere. The classical Lorenz–Mie theory is employed to compute the optical properties of spherical dust particles. To compute the single-scattering properties of spheroidal dust particles, a combination of the T-matrix method and an approximate method is used in the present study. In the approximate method, applicable to large particles, the geometric optics method is applied to the computation of the scattering phase matrix. A combination of the solution from the geometric optics method and the contribution of the so-called edge effect is used to compute the extinction efficiency of a spheroidal particle whose absorption efficiency is computed by adding the so-called above- and below-edge effect (a term from the well-known complex angular momentum theory) to the geometric optics result. Numerical results show that the results from the T-matrix method and the present approximate approach converge at a size parameter of 50 for computing the integrated scattering properties (i.e., the extinction efficiency, single-scattering albedo, and asymmetry factor). Additionally, the phase functions computed from the two methods are quite similar for size parameters larger than 40 although some considerable differences may still be noticed for other phase matrix elements. Furthermore, the effect of surface roughness on the single-scattering properties of spheroidal particles is discussed. The present radiative transfer simulations illustrate the nonsphericity effect of dust particles is significant at short wavelengths, however, not at the thermal infrared wavelengths.

Data from three thermal sensors with different spatial resolution were assessed for urban surface temperature retrieval over the Yokohama City, Japan. The sensors are Thermal Airborne Broadband Imager (TABI), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and MODerate resolution Imaging Spectroradiometer (MODIS). Two algorithms were developed for land surface temperature (LST) retrieval from TABI image and ASTER thermal infrared (TIR) channels 13 and 14. In addition, ASTER LST and MODIS LST products were also collected. All the LST images were assessed by analyzing the relationship between LST and normalized difference vegetation index (NDVI) and by spatial distributions of LST profiles, derived from typical transects over the LST images. In this study, a strong negative relationship between LST and NDVI has been demonstrated although the degree of correlation between NDVI and LST varies slightly among the different LST images. Cross-validation among the LST images retrieved from the three thermal sensors of different spatial resolutions indicates that the LST images retrieved from the 2 channel ASTER data and a single band TABI thermal image using our developed algorithms are reliable. The LST images retrieved from the three sensors should have different potential to urban environmental studies. The MODIS thermal sensor can be used for the synoptic overview of an urban area and for studying urban thermal environment. The ASTER, with its TIR subsystem of 90-m resolution, allows for a more accurate determination of thermal patterns and properties of urban land use/land cover types, and hence, a more accurate determination of the LST. In consideration of the high heterogeneity of urban environment, the TABI thermal image, with a high spatial resolution of 2 m, can be used for rendering and assessing complex urban thermal patterns and detailed distribution of LST at the individual house level more accurately.

The volcanological community has a powerful new tool in the spaceborne moderate resolution imaging spectroradiometer (MODIS), which, from its synoptic perspective, provides satellite imagery of every volcano on Earth every 2 days. MODIS has the spectral characteristics to be able to utilise previously developed retrievals that quantify volcanic ash, ice, sulfates and sulfur dioxide using their thermal infrared (8 -12 Am) transmission signature. In this paper, we present a detailed description of the methodologies, based within the thermal infrared region, that are being applied to MODIS data. MODIS data for two eruptions, Hekla, Iceland and Cleveland, Alaska are presented to show results from the ice, ash and SO 2 retrieval schemes. We look at current problems with the retrievals used to quantify volcanic emissions, detail recent developments within the field that can be applied to MODIS data, and suggest areas where improvements need to be made in the future. Published by Elsevier B.V.

In 1992 Thermal Infrared Multispectral Scanner (TIMS) ferent lines on the same day. However, there are differdata were acquired from the NASA C-130 aircraft over ences when the same area is seen on the two days espethe Sahelian region of West Africa as part of the Hydrocially for the low emissivity values. Some of these logical and Atmospheric Pilot Experiment in the Sahel differences may be due to soil moisture differences of 2-(HAPEX). TIMS measures the radiation from the surface 3%, which were observed for the two days. The observed modified by the atmosphere in six channels located besurface temperatures were in good agreement with other tween 8 mm and 12.5 lm in the thermal infrared. By measures, for example, vegetation temperatures agreed using a variety of techniques it is possible to extract both well with the measured air temperatures. Published by the surface temperature and surface emissivity from the Elsevier Science Inc. 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 face temperature, T a is the air temperature at some ref-@hydrolab.arsusda.gov Received . erence height, and r ah is the resistance to heat transfer. REMOTE SENS. ENVIRON. 65:121-131 (1998) Published by Elsevier Science Inc.

1] The Moderate Resolution Imaging Spectroradiometer (MODIS) global land surface temperature (LST)/emissivity products supply daily, 8-day, and monthly global temperature and narrowband emissivity data. This article uses these products to calculate the surface long wave radiation of natural objects such as sand, soil, vegetation, etc., based on the Planck function and the Stefan-Boltzmann law. The results show that using the narrowband emissivity of a single band instead of the broadband emissivity results in large errors of up to 100 W m À2 of the calculated long wave radiation. A method to calculate broadband emissivity in the entire TIR spectral region from the narrowband emissivities of the MODIS bands (29, 31, and 32) in the thermal infrared region is proposed. Using the broadband emissivity, the surface long wave radiation could be calculated to an accuracy better than 6 W m À2 in the temperature region of 240-330 K, with a standard deviation of 1.22 W m À2 , and a maximum error of 6.05 W m À2 (not considering the uncertainty associated with the MODIS LST/emissivity products themselves). The satellite estimated broadband emissivity was compared with 3-year (January 2001 to December 2003) ground-based measurements of emissivity at Gaize (32.30°N, 84.06°E, 4420 m) on the western Tibetan Plateau. The results show that the broadband emissivity calculated from MODIS narrowband emissivities by this method matches well the ground measurements, with a standard deviation of 0.0085 and a bias of 0.0015. (2005), Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature/ emissivity products,

We report the discovery of a very cool, isolated brown dwarf, UGPS 0722-05, with the UKIDSS Galactic Plane Survey. The near-infrared spectrum displays deeper H 2 O and CH 4 troughs than the coolest known T dwarfs and an unidentified absorption feature at 1.275 µm. We provisionally classify the object as a T10 dwarf but note that it may in future come to be regarded as the first example of a new spectral type. The distance is measured by trigonometric parallax as d=4.1 +0.6 −0.5 pc, making it the closest known isolated brown dwarf. With the aid of Spitzer/IRAC we measure H-[4.5] = 4.71. It is the coolest brown dwarf presently known -the only known T dwarf that is redder in H-[4.5] is the peculiar T7.5 dwarf SDSS J1416+13B, which is thought to be warmer and more luminous than UGPS 0722-05. Our measurement of the luminosity, aided by Gemini/T-ReCS N band photometry, is L=9.2±3.1×10 −7 L ⊙ . Using a comparison with well studied T8.5 and T9 dwarfs we deduce T ef f =520±40 K. This is supported by predictions of the Saumon & Marley models. With apparent magnitude J = 16.52, UGPS 0722-05 is the brightest brown dwarf discovered by UKIDSS so far. It offers opportunities for future study via high resolution near-infrared spectroscopy and spectroscopy in the thermal infrared.

Cloud cover usually denies the generation of land surface temperature (LST) time series over large areas from thermal infrared (TIR) data sensed by satellites. If cloud cover is brief ( < 4 h) and only partial on the scale of a METEOSAT pixel, the discontinuous time series of cloud-free measurements still approximates a cloud-free diurnal temperature cycle (DTC). In order to interpolate the missing values and to describe the thermal behaviour of the land surface as a whole, advantage is taken of METEOSAT's high temporal resolution of 30 min. A Levenberg ± Marquardt minimisation scheme is utilised to automatically fit a model of the DTC to the time series of cloud-screened brightness temperatures (BT). Out of physical considerations and in order to stabilise the fits, a priori knowledge from solar geometry is utilised and the model function is required to be smooth and continuous. A robust estimator of the error, which is based on the median rather than the arithmetic mean, is used to lessen the impact of outliers on the fits. The thermal behaviour of the land surface is then described by the determined model parameters, and the 48 METEOSAT BTs per pixel per day are reduced to five parameters per pixel per day. Monthly maximum and median composites of cloud-screened METEOSAT BTs yield synthetic DTCs, which are less influenced by synoptic effects. Fitting the model to monthly composites reduces the 17 520 METEOSAT BTs per pixel per year to 60 parameters per pixel per year. This data reduction is advantageous to climatological studies, which require the processing of long time series. The model parameters are shown to be related to physical properties of the land surface, particularly to the normalised difference vegetation index (NDVI) and thermal inertia. D

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. D

Land surface temperature (LST) is estimated from thermal infrared data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), using a generalized split-window (GSW) algorithm. The uncertainty of the LST retrievals is highly dependent on the input accuracy and retrieval conditions, particularly the sensor view angle and the atmospheric water vapor content. This paper presents a quantification of the uncertainty of LST estimations, taking into account error statistics of the GSW under a globally representative collection of atmospheric profiles, and a careful characterization of the uncertainty of input data, particularly the surface emissivity and forecasts of the total water vapor content. Such analysis is the basis for LST uncertainty estimation, also distributed to users, in the form of error bars, along with the LST retrievals. Moreover, the spatial coverage of SEVIRI LST is essentially determined by the LST expected uncertainty, instead of being restricted to view zenith angles below a given threshold (e.g., 60 • ). Within the MSG disk, the atmosphere is often dry for clear-sky conditions where angles are large (e.g., Northern and Eastern Europe and Saudi Arabia). By considering several factors that contribute to LST inaccuracies, it is possible to increase the spatial coverage to regions such as those mentioned earlier. Retrieved values are also compared with in situ observations collected in Namibia, covering a seasonal cycle. The two data sets are in good agreement with root-mean-square differences ranging between 1 • C and 2 • C, which is well below the average error estimated for the satellite retrievals.

Multiangle algorithms for estimating sea and land surface temperature with Along-Track Scanning Radiometer data require a precise knowledge of the angular variation of surface emissivity in the thermal infrared. Currently, few measurements of this variation exist. Here an experimental investigation of the angular variation of the infrared emissivity in the thermal infrared ͑8 -14-m͒ band of some representative samples was made at angles of 0°-65°͑at 5°increments͒ to the surface normal. The results show a decrease of the emissivity with increasing viewing angle, with water showing the highest angular dependence ͑ϳ7% from 0°to 65°views͒. Clay, sand, slime, and gravel show variations of approximately 1-3% for the same range of views, whereas a homogeneous grass cover does not show angular dependence. Finally, we include an evaluation of the impact that these data can produce on the algorithms for determining land and sea surface temperature from double-angle views.

We have found that image data acquired with NASA's airborne Thermal Infrared Multispectral Scanner (TIMS) can be used to make estimates of the SO2 content of volcanic plumes. TIMS image data are most applicable to the study of partially transparent SO2 plumes, such as those released during quiescent periods or nonexplosive eruptions. The estimation procedure is based on the LOWTRAN 7 radiative transfer code, which we use to model the radiance perceived by TIMS as it views the ground through an SO2 plume. The input to the procedure includes the altitudes of the aircraft and ground, the altitude and thickness of the SO2 plume, the emissivity of the ground, and altitude profiles of the atmospheric pressure, temperature, and relative humidity. We use the TIMS data to estimate both ground temperatures beneath a plume and SO2 concentrations within a plume. Applying our procedure to TIMS data acquired over Mount Etna, Sicily, on July 29, 1986, we estimate that the SO2 flux from the volcano was approximately 6700 t d -• . The use of TIMS to study SO2 plumes represents a bridge between highly localized methods, such as correlation spectroscopy or direct sampling, and small-scale mapping techniques involving satellite instruments such as the Total Ozone Mapping Spectrometer or Microwave Limb Sounder. We require further airborne experiments to refine our estimation procedure. This refinement is a necessary preparation for the scheduled 1998 launch of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer, which will allow large-scale multispectral thermal infrared image data to be collected over virtually any volcano on Earth at least once every 16 days.

Laser-induced infrared photocarrier radiometry ͑PCR͒ is introduced theoretically and experimentally through deep subsurface scanning imaging and signal frequency dependencies from Si wafers. A roomtemperature InGaAs detector (0.8-1.8 m) with integrated amplification electronics is used instead of the liquid-nitrogen-cooled HgCdTe photodetector (2 -12 m) of conventional photothermal radiometry. PCR measures purely electronic carrier-wave ͑CW͒ recombination. The InGaAs detector completely obliterates the thermal-infrared emission band (8 -12 m), unlike the known photothermal signal types, which invariably contain combinations of carrier-wave and thermal-wave infrared emissions due to the concurrent lattice absorption of the incident beam and nonradiative heating. The PCR theory is presented as infrared depth integrals of CW density profiles. Experimental aspects of this methodology are given, including the determination of photocarrier transport parameters through modulation frequency scans, as well as CW scanning imaging. The PCR coordinate scans at the front surface of 500Ϫm-thick Si wafers with slight back-surface mechanical defects can easily ''see'' and create clear images of the defects at modulation frequencies up to 100 kHz, at laser-beam optical penetration depth ϳ1 m below the surface ͑at 514 nm͒. The physics of the contrast mechanism for the nonthermal nature of the PCR signal is described: it involves self-reabsorption of CWrecombination-generated IR photons emitted by the photoexcited carrier-wave distribution depth profile throughout the wafer bulk. The distribution is modified by enhanced recombination at localized or extended defects, even as remote as the back surface of the material. The high-frequency, deep-defect PCR images thus obtained prove that very-near-surface ͑where optoelectronic device fabrication takes place͒ photocarrier generation can be detrimentally affected not only by local electronic defects as is commonly assumed, but also by defects in remote wafer regions much deeper than the extent of the electronically active thin surface layer.

The influence of soil water content in thermal infrared emissivity is a known fact but has been poorly studied in the past. A laboratory study for quantifying the dependence of emissivity on soil moisture was carried out. Six samples of surface horizons of different soil types were selected for the experiment. The gravimetric method was chosen for determining the soil moisture, whereas the emissivity was measured at different soil water contents using the two-lid variant of the box method. As a result, the study showed that emissivity increases from 1.7% to 16% when water content becomes higher, especially in sandy soils in the 8.2-9.2 mm range. Accordingly, a set of equations was derived to obtain emissivity from soil moisture at different spectral bands for the analyzed mineral soils. Moreover, results showed that the spectral ratio decreases with increasing soil water content. Finally, the study showed that systematic errors from 0.1 to 2 K can be caused by soil moisture influence on emissivity.