Amit Mushkin

Linear mixing in thermal infrared temperature retrieval

Virtually all remotely sensed thermal infrared (IR) pixels are, to some degree, mixtures of different materials or temperatures: real pixels are rarely thermally homogeneous. As sensors improve and spectral thermal IR remote sensing becomes more quantitative, the concept of homogeneous pixels becomes inadequate. Quantitative thermal IR remote sensors measure radiance. Plancks Law defines a relationship between temperature and radiance that is more complex than linear proportionality and is strongly wavelength‐dependent. As a result, the area‐averaged temperature of a pixel is not the same as the temperature derived from the radiance averaged over the pixel footprint, even for blackbodies. This paper uses simple linear mixing of pixel elements (subpixels) to examine the impacts of pixel mixtures on temperature retrieval and ground leaving radiance. The results show that for a single material with one temperature distribution and with a subpixel temperature standard deviation of 6 K (daytime images), the effects of subpixel temperature variability are small but can exceed 0.5 K in the 3–5 µm band and about a third of that in the 8–12 µm band. For pixels with a 50 : 50 mixture of materials (two temperature distributions with different means) the impact of subpixel radiance variability on temperature retrieval can exceed 6 K in the 3–5 µm band and 2 K in the 8–12 µm band. Sub‐pixel temperatures determined from Gaussian distributions and also from high‐resolution thermal images are used as inputs to our linear mixing model. Model results are compared directly to these broadband thermal images of plowed soil and senesced barley. Finally, a theoretical framework for quantifying the effect of non‐homogeneous temperature distributions for the case of a binary combination of mixed pixels is derived, with results shown to be valid for the range of standard deviations and temperature differences examined herein.

Linking coarse silt production in Asian sand deserts and Quaternary accretion of the Chinese Loess Plateau

The Chinese Loess Plateau (CLP) is a large, spatially well defined and persistent zone of loess accumulation developed near the fluctuating northwest margin of the East Asian monsoon. Many studies have analyzed its loess sediments to provide insights into paleoclimatic conditions. Although spatial and temporal variations in the grain sizes of CLP sediments are fundamental to this effort, controversy over the origin of the dominant coarse quartz silt has limited interpretations. Reexamination of the spatial pattern of grain-size distribution across the CLP and a field-scale experiment conducted in the Gobi Desert revealed a genetic association between the coarse silt fraction of the loess and primary production of coarse silt through eolian abrasion of sand in the proximal Mu-Us, Tengger, and Badain Jaran sandy deserts. Our results demonstrate the effectiveness of eolian abrasion of quartz sand in primary coarse silt production in Central Asia and identify this process as the most consistent with the well-recognized systematic northwest-southeast depositional pattern of the CLP. We suggest that only abraded coarse quartz grains transported short distances by long-term persistent eolian activity can build up thick loess sequences to form a massive and spatially well defined loess plateau. These results decouple the production and transport of coarse silt and finer silt and clay particles, which have a more distant and wider provenance, changing the constraints on previous paleoclimatic reconstructions.

Longwave Thermal Infrared Spectral Variability in Individual Rocks

An hyperspectral imaging spectrometer measuring in the longwave thermal infrared (7.6-11.6 mum), with a spatial resolution less than 5 mm at a range of 10 m, was used in the field to observe the variability of emissivity spectra of individual rock surfaces. The rocks were obtained commercially, were on the order of 20 cm in size, and were selected to have distinct spectral features: they include alabaster (gypsum), soapstone (steatite with talc), obsidian (volcanic glass), norite (plagioclase and orthopyroxene), and ldquojasperrdquo (silica with iron oxides). The advantages of using an imaging spectrometer to characterize these rocks spectrally are apparent. Large spectral variations were observed within individual rocks that may be attributed to roughness, surface geometry, and compositional variation. Nonimaging spectrometers would normally miss these variations as would small samples used in laboratory measurements, spatially averaged spectra can miss the optimum spectra for identification of materials, and spatially localized components of the rock can be obscured.

Measuring the time and scale-dependency of subaerial rock weathering rates over geologic time scales with ground-based lidar

The evolution of roughness as a function of surface age was used to quantify weathering rates on rocky desert surfaces. Surface topography on eight late Quaternary alluvial terraces, which record the weathering of Holocene (5 ± 1 ka) boulder-strewn deposits into mature (87 ± 2 ka) desert pavements in the Negev desert of Israel, was measured with ground-based lidar. Roughness on each terrace was characterized with power spectral density (PSD) analysis, and changes in PSD as a function of length scale (λ ∼ 0.04–1.50 m) and surface age were used to estimate diminution/weathering rates of the surface rocks. We found PSD values that systematically increase as a power-law function of λ (roughness exponent of ∼2.0) and decrease as an inverse power-law function of surface age. This PSD evolution indicates a fragmentation rock weathering process driven by salt shattering throughout the 87 k.y. period examined. PSD analysis of the lidar data also revealed weathering rates that increase with rock size and decrease as an inverse power-law function of time, from initial values >20 mm/k.y. to <1 mm/k.y. within ∼60 k.y.

Planetary science: Are there active glaciers on Mars?

Arising from: J. W. Head et al. 434, 346–351 (2005); Head et al. reply.Head et al. interpret spectacular images from the Mars Express high-resolution stereo camera as evidence of geologically recent rock glaciers in Tharsis and of a piedmont (‘hourglass’) glacier at the base of a 3-km-high massif east of Hellas. They attribute growth of the low-latitude glaciers to snowfall during periods of increased spin-axis obliquity. The age of the hourglass glacier, considered to be inactive and slowly shrinking beneath a debris cover in the absence of modern snowfall, is estimated to be more than 40 Myr. Although we agree that the maximum glacier extent was climatically controlled, we find evidence in the images to support local augmentation of accumulation from snowfall through a mechanism that does not require climate change on Mars.

Estimating subpixel surface roughness using remotely sensed stereoscopic data

Surface roughness at the 10/sup -2/-10/sup 1/ m scale is estimated using the ratio between the reflectances of the surface measured from two view angles. As reflectance is dependant on surface roughness at these scales, this ratio provides us with a proxy for relative surface roughness within a single image that is largely independent of surface composition. Roughness estimates using stereoscopic data with 15-m spatial resolution from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) in Death Valley, California and ground based stereoscopic measurements at the /spl sim/1-m scale were both found to be in good agreement with observed surface roughnesses.

Temperature/emissivity separation of MTI data using the Terra/ASTER TES algorithm

Surface temperatures and emissivities can be estimated using multispectral thermal infrared (TIR) data, from various instruments. In this paper the temperature-emissivity separation algorithm (TES) is modified to recover surface temperatures and emissivities using Multispectral Thermal Imager (MTI) data from two mid infrared (MIR) and three TIR bands. As TES was originally designed for use with the five TIR bands from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) instrument, broadening its application to MIR wavelengths requires careful evaluation of possible atmospheric and reflected daytime solar illumination effects. Numerical simulations show that TES results for MTI data, assuming error-free atmospheric corrections, are statistically similar to TES results for ASTER data, with surface temperature recovery within +/- 1.5K and emissivity recovery within +/- 0.02. However, strong atmospheric absorption (as high as 61%), and expected daytime reflected solar illumination (as high as 50% of measured radiance) in the MIR bands suggest that TES results for MTI data are more sensitive to errors in atmospheric compensation. Furthermore, the relatively steep slope of Plancks radiation curve for typical terrestrial temperatures in the MIR wavelengths, suggests that inverting temperatures from measured MIR radiance using Plancks law will be more sensitive to error. Numerical simulations and preliminary image analysis suggest that the three TIR MTI bands are not sufficient to obtain the desired TES results. However, omitting one of the MIR bands and using a four-band configuration decreases sensitivity to atmospheric effects, while still maintaining acceptable theoretical TES performance.

Subpixel roughness effects in spectral thermal infrared emissivity images

Emissivity spectra recovered from spectral radiance images may have lowered spectral contrast due to irradiance from nearby surface elements (“cavity effect”). For analyses based only on photointerpretation or Reststrahlen band identification, it is not always necessary to account for cavity effects, but for full spectral analyses, including spectral unmixing, it may be desirable. We present a method that is under development for compensating thermal infrared images for cavity radiation based on optical estimates of surface roughness and model inversion for percent cavity contribution. The approach is adaptable for different spectral resolutions, including hyperspectral. It will be tested on tripod-mounted Telops HyperCam hyperspectral thermal-infrared images of natural targets, LiDAR DEMs of similar targets, and optical estimates of shadowing, related to roughness.

Effect of the Qinghai–Tibet Railway on vegetation abundance

Large-scale engineering projects such as mines and dams cause ecological damage that can persist after construction is complete. The Qinghai–Tibet Railway (QTR) from Golmud to Lhasa was constructed entirely during the Landsat era and began operating in 2006. Therefore, it presents an opportunity for determining both the extent of ecological damage and the time required for some level of natural restoration after a major construction project. We have studied the effect of the QTR construction on vegetation abundance measured using multi-endmember spectral mixture analysis (MESMA) of a time series of Landsat TM/ETM+ images (2001, 2007, 2010) covering the 231 km stretch of the railway from south of Kaixinling Station to north of Chumaerhe Station. We found that the effect of QTR construction on vegetation abundance was limited to within 5.0 km of the tracks, the largest decrease, 2.9%, occurring within 0.125 km of the tracks from 2001 to 2007. There was only 0.4% further decrease in vegetation abundance from 2007 to 2010. We attributed the decrease in vegetation abundance within 0.125 km of the tracks mostly to the accumulation of drifting sand resulting from the barrier of the railway and the measures adopted to keep the sand away from the railway under the prevailing west or northwest winds. It appears that in this sensitive cold desert, vegetation damage was limited to the period of railway construction.

Compensation for subpixel roughness effects in thermal infrared images

Emissivity spectra recovered from spectral radiance images may have lowered spectral contrast due to irradiance from nearby surface elements (‘cavity effect’). For analysis based only on photointerpretation or Reststrahlen band identification, it is not always necessary to account for cavity effects, but for full spectral analysis it may be desirable. We present an approach to compensate thermal infrared (TIR) images for cavity radiation. This approach is based on optical estimates of subpixel surface roughness and estimation of cavity contribution for different natural surfaces using a TIR radiosity model. It was tested using tripod-mounted Hyper-Cam (Telops, Inc., Quebec City, Canada) hyperspectral TIR images of natural targets from the Mojave Desert, California, USA, along with centimetre-scale digital elevation models of similar targets measured by ground lidar. For remote subpixel roughness estimation, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) nadir- and aft-looking (27.6°) near-infrared (NIR) brightness ratios, as well as synthetic aperture radar (SAR) images calibrated to roughness root mean square (RMS), were used. The TIR compensation approach is adaptable for different spectral resolutions, including hyperspectral.