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Special Issue "Thermal Remote Sensing Applications: Present Status and Future Possibilities"

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (15 September 2012)

Special Issue Editors

Guest Editor
Prof. Dr. Dale A. Quattrochi

Earth Science Office, ZP11, Marshall Space Flight Center, NASA, Huntsville, AL 35812, USA
E-Mail
Phone: +1-256-961-7887
Fax: +1-256-961-7788
Interests: thermal remote sensing; urban heat island analysis; geospatial techniques and remote sensing; land use/land cover change
Guest Editor
Prof. Dr. Soe Myint

School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA
Website | E-Mail
Phone: 480-965-6514
Fax: +49-480-965-8313
Interests: remote sensing; GIS; geospatial statistics; land use land cover change and prediction; assessment and monitoring of drought, land degradation, and desertification; landscape fragmentation; urban environmental modeling including urban water use and climate analysis; forest characterization including coastal environments; disaster assessment, recovery, and monitoring; agriculture water use, evapotranspiration, and surface energy analysis; spatial modeling; and classification algorithm development
Guest Editor
Prof. Dr. Janet Nichol

Department of Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon Hong Kong
Website | E-Mail
Interests: remote sensing of urban areas (including urban heat islands, aerosol retrieval and urban enviromental quality); ecological and habitat mapping, biomass and carbon storage estimation of forests; land cover monitoring, satellite sensors (small satellites, visible and thermal infrared sensors); integration of remote sensing and GIS; data visualisation

Special Issue Information

Dear Colleagues,

This special issue of Remote Sensing focuses on examining the current status and trends in thermal infrared remote sensing (i.e., TIR or thermal IR) and a look forward to what the future prospects are for this technology. Remote sensing in the thermal infrared portion of the electromagnetic spectrum has had wide application to many aspects of the Earth’s environment, including oceans, hydrology, geology, biology, and the land surface. TIR remote sensing as applied to Earth Science research has a rich history that has elucidated the virtues of using these data to measure and model Earth surface processes. We wish to publish manuscripts that relate to any aspect of TIR applications and the use of these data in measuring and modeling the Earth’s energy balances or surface-atmosphere interactions. This includes the integration of TIR data in GIS applications. Papers discussing new and innovative TIR data processing or computational methods and modeling techniques for retrieving important factors, such as surface temperature, emissivity, and thermal properties, especially of human-made materials, will be considered. Of particular interest are papers that provide information to support the development of multispectral TIR instruments, as well as manuscripts that offer insight on spatial, spectral, and temporal scaling issues as related to TIR remote sensing. Additionally, TIR remote sensing is now at somewhat of a crossroads wherein older satellite systems that have TIR bandwidths such as the Landsat ETM+, are transitioning into newer but modified TIR sensors such as the Landsat Data Continuity Mission (LDCM) which will have a single TIR spectral channel with 100m spatial resolution. This special issue, therefore, seeks to include manuscripts that offer insight on the potential of new thermal IR satellite and aircraft sensing systems to build upon the foundation established by past sensors. Results from aircraft and field campaigns to collect data from prototype TIR sensors to validate and calibrate surface temperatures or demonstrate instrument capabilities will also be considered.

Prof. Dr. Dale A. Quattrochi
Prof. Dr. Soe Myint
Prof. Dr. Janet Nichol
Guest Editors

Keywords

  • thermal remote sensing
  • TIR
  • multispectral thermal infrared
  • Earth surface thermal energy fluxes
  • surface-atmosphere interactions
  • modeling
  • sensor validation
  • sensor calibration
  • Earth environment

Published Papers (11 papers)

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Research

Open AccessArticle Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data
Remote Sens. 2013, 5(1), 342-366; doi:10.3390/rs5010342
Received: 1 November 2012 / Revised: 8 January 2013 / Accepted: 10 January 2013 / Published: 17 January 2013
Cited by 6 | PDF Full-text (5915 KB) | HTML Full-text | XML Full-text
Abstract
Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation
[...] Read more.
Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM) Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS) with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5) in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature observations valuable, which can lead to improved forecasting and more advanced global climate models. Full article
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Open AccessArticle A Hyperspectral Thermal Infrared Imaging Instrument for Natural Resources Applications
Remote Sens. 2012, 4(12), 3995-4009; doi:10.3390/rs4123995
Received: 15 September 2012 / Revised: 3 December 2012 / Accepted: 4 December 2012 / Published: 14 December 2012
Cited by 10 | PDF Full-text (769 KB) | HTML Full-text | XML Full-text
Abstract
A new instrument has been setup at the Centre de Recherche Public-Gabriel Lippmann to measure spectral emissivity values of typical earth surface samples in the 8 to 12 μm range at a spectral resolution of up to 0.25 cm−1. The instrument
[...] Read more.
A new instrument has been setup at the Centre de Recherche Public-Gabriel Lippmann to measure spectral emissivity values of typical earth surface samples in the 8 to 12 μm range at a spectral resolution of up to 0.25 cm−1. The instrument is based on a Hyper-Cam-LW built by Telops with a modified fore-optic for vertical measurements at ground level and a platform for airborne acquisitions. A processing chain has been developed to convert calibrated radiances into emissivity spectra. Repeat measurements taken on samples of sandstone show a high repeatability of the system with a wavelength dependent standard deviation of less than 0.01 (1.25% of the mean emissivity). Evaluation of retrieved emissivity spectra indicates good agreement with reference measurements. The new instrument facilitates the assessment of the spatial variability of emissivity spectra of material surfaces—at present still largely unknown—at various scales from ground and airborne platforms and thus will provide new opportunities in environmental remote sensing. Full article
Open AccessArticle Pan-Arctic Land Surface Temperature from MODIS and AATSR: Product Development and Intercomparison
Remote Sens. 2012, 4(12), 3833-3856; doi:10.3390/rs4123833
Received: 12 October 2012 / Revised: 26 November 2012 / Accepted: 27 November 2012 / Published: 5 December 2012
Cited by 13 | PDF Full-text (2964 KB) | HTML Full-text | XML Full-text
Abstract
Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and
[...] Read more.
Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and annual LST means over the pan-Arctic region at various grid resolutions (1–25 km) for the past decade (2000–2010). In this paper, we provide: (1) a review of previous validation of MODIS/AATSR L2; (2) a description of the processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max: −1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions. Full article
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Open AccessArticle A Quantitative Approach for Analyzing the Relationship between Urban Heat Islands and Land Cover
Remote Sens. 2012, 4(11), 3596-3618; doi:10.3390/rs4113596
Received: 30 September 2012 / Revised: 12 November 2012 / Accepted: 12 November 2012 / Published: 20 November 2012
Cited by 15 | PDF Full-text (1719 KB) | HTML Full-text | XML Full-text
Abstract
With more than 80% of Brazilians living in cities, urbanization has had an important impact on climatic variations. São José dos Campos is located in a region experiencing rapid urbanization, which has produced a remarkable Urban Heat Island (UHI) effect. This effect influences
[...] Read more.
With more than 80% of Brazilians living in cities, urbanization has had an important impact on climatic variations. São José dos Campos is located in a region experiencing rapid urbanization, which has produced a remarkable Urban Heat Island (UHI) effect. This effect influences the climate, environment and socio-economic development on a regional scale. In this study, the brightness temperatures and land cover types from Landsat TM images of São José dos Campos from 1986, 2001 and 2010 were analyzed for the spatial distribution of changes in temperature and land cover. A quantitative approach was used to explore the relationships among temperature, land cover areas and several indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-up Index (NDBI). The results showed that urban and bare areas correlated positively with high temperatures. Conversely, areas covered in vegetation and water correlated positively with low temperatures. The indices showed that correlations between the NDVI and NDWI and temperature were low (<0.5); however, a moderate correlation was found between the NDBI and temperature. Full article
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Open AccessArticle A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land
Remote Sens. 2012, 4(11), 3287-3319; doi:10.3390/rs4113287
Received: 29 August 2012 / Revised: 22 October 2012 / Accepted: 22 October 2012 / Published: 26 October 2012
Cited by 26 | PDF Full-text (4774 KB) | HTML Full-text | XML Full-text
Abstract
Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes
[...] Read more.
Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes that are at significantly finer spatial scales. Consequently, thermal sharpening techniques have been developed to sharpen TIR imagery to shortwave band pixel resolutions, which are often fine enough for field-scale applications. A classic thermal sharpening technique, TsHARP, uses a relationship between land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) developed empirically at the TIR pixel resolution and applied at the NDVI pixel resolution. However, recent studies show that unique relationships between temperature and NDVI may only exist for a limited class of landscapes, with mostly green vegetation and homogeneous air and soil conditions. To extend application of thermal sharpening to more complex conditions, a new data mining sharpener (DMS) technique is developed. The DMS approach builds regression trees between TIR band brightness temperatures and shortwave spectral reflectances based on intrinsic sample characteristics. A comparison of sharpening techniques applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska indicates that the DMS outperformed TsHARP in all cases. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water bodies, thin clouds or terrain. While the DMS technique can provide fine resolution TIR imagery, there are limits to the sharpening ratios that can be reasonably implemented. Consequently, sharpening techniques cannot replace actual thermal band imagery at fine resolutions or missions that provide high quality thermal band imagery at high temporal and spatial resolution critical for many agricultural, land use and water resource management applications. Full article
Open AccessArticle Applicability of the Thermal Infrared Spectral Region for the Prediction of Soil Properties Across Semi-Arid Agricultural Landscapes
Remote Sens. 2012, 4(11), 3265-3286; doi:10.3390/rs4113265
Received: 14 August 2012 / Revised: 29 September 2012 / Accepted: 16 October 2012 / Published: 24 October 2012
Cited by 18 | PDF Full-text (4077 KB) | HTML Full-text | XML Full-text
Abstract
In this study we tested the feasibility of the thermal infrared (TIR) wavelength region (within the atmospheric window between 8 and 11.5 μm) together with the traditional solar reflective wavelengths for quantifying soil properties for coarse-textured soils from the Australian wheat belt region.
[...] Read more.
In this study we tested the feasibility of the thermal infrared (TIR) wavelength region (within the atmospheric window between 8 and 11.5 μm) together with the traditional solar reflective wavelengths for quantifying soil properties for coarse-textured soils from the Australian wheat belt region. These soils have very narrow ranges of texture and organic carbon contents. Soil surface spectral signatures were acquired in the laboratory, using a directional emissivity spectrometer (μFTIR) in the TIR, as well as a bidirectional reflectance spectrometer (ASD FieldSpec) for the solar reflective wavelengths (0.4–2.5 μm). Soil properties were predicted using multivariate analysis techniques (partial least square regression). The spectra were resampled to operational imaging spectroscopy sensor characteristics (HyMAP and TASI-600). To assess the relevance of specific wavelength regions in the prediction, the drivers of the PLS models were interpreted with respect to the spectral characteristics of the soils’ chemical and physical composition. The study revealed the potential of the TIR (for clay: R2 = 0.93, RMSEP = 0.66% and for sand: R2 = 0.93, RMSEP = 0.82%) and its combination with the solar reflective region (for organic carbon: R2 = 0.95, RMSEP = 0.04%) for retrieving soil properties in typical soils of semi-arid regions. The models’ drivers confirmed the opto-physical base of most of the soils’ constituents (clay minerals, silicates, iron oxides), and emphasizes the TIR’s advantage for soils with compositions dominated by quartz and kaolinite. Full article
Open AccessArticle Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany
Remote Sens. 2012, 4(10), 3184-3200; doi:10.3390/rs4103184
Received: 2 August 2012 / Revised: 10 October 2012 / Accepted: 12 October 2012 / Published: 19 October 2012
Cited by 38 | PDF Full-text (1755 KB) | HTML Full-text | XML Full-text
Abstract
Monitoring of (surface) urban heat islands (UHI) is possible through satellite remote sensing of the land surface temperature (LST). Previous UHI studies are based on medium and high spatial resolution images, which are in the best-case scenario available about four times per day.
[...] Read more.
Monitoring of (surface) urban heat islands (UHI) is possible through satellite remote sensing of the land surface temperature (LST). Previous UHI studies are based on medium and high spatial resolution images, which are in the best-case scenario available about four times per day. This is not adequate for monitoring diurnal UHI development. High temporal resolution LST data (a few measurements per hour) over a whole city can be acquired by instruments onboard geostationary satellites. In northern Germany, geostationary LST data are available in pixels sized 3,300 by 6,700 m. For UHI monitoring, this resolution is too coarse, it should be comparable instead to the width of a building block: usually not more than 100 m. Thus, an LST downscaling is proposed that enhances the spatial resolution by a factor of about 2,000, which is much higher than in any previous study. The case study presented here (Hamburg, Germany) yields promising results. The latter, available every 15 min in 100 m spatial resolution, showed a high explained variance (R2: 0.71) and a relatively low root mean square error (RMSE: 2.2 K). For lower resolutions the downscaling scheme performs even better (R2: 0.80, RMSE: 1.8 K for 500 m; R2: 0.82, RMSE: 1.6 K for 1,000 m). Full article
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Open AccessArticle Estimating Coastal Lagoon Tidal Flooding and Repletion with Multidate ASTER Thermal Imagery
Remote Sens. 2012, 4(10), 3110-3126; doi:10.3390/rs4103110
Received: 19 August 2012 / Revised: 10 October 2012 / Accepted: 12 October 2012 / Published: 18 October 2012
Cited by 1 | PDF Full-text (1479 KB) | HTML Full-text | XML Full-text
Abstract
Coastal lagoons mix inflowing freshwater and tidal marine waters in complex spatial patterns. This project sought to detect and measure temperature and spatial variability of flood tides for a constricted coastal lagoon using multitemporal remote sensing. Advanced Spaceborne Thermal Emission Radiometer (ASTER) thermal
[...] Read more.
Coastal lagoons mix inflowing freshwater and tidal marine waters in complex spatial patterns. This project sought to detect and measure temperature and spatial variability of flood tides for a constricted coastal lagoon using multitemporal remote sensing. Advanced Spaceborne Thermal Emission Radiometer (ASTER) thermal infrared data provided estimates of surface temperature for delineation of repletion zones in portions of Chincoteague Bay, Virginia. ASTER high spatial resolution sea-surface temperature imagery in conjunction with in situ observations and tidal predictions helped determine the optimal seasonal data for analyses. The selected time series ASTER satellite data sets were analyzed at different tidal phases and seasons in 2004–2006. Skin surface temperatures of ocean and estuarine waters were differentiated by flood tidal penetration and ebb flows. Spatially variable tidal flood penetration was evaluated using discrete seed-pixel area analysis and time series Principal Components Analysis. Results from these techniques provide spatial extent and variability dynamics of tidal repletion, flushing, and mixing, important factors in eutrophication assessment, water quality and resource monitoring, and application of hydrodynamic modeling for coastal estuary science and management. Full article
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Open AccessArticle Simulations of Infrared Radiances over a Deep Convective Cloud System Observed during TC4: Potential for Enhancing Nocturnal Ice Cloud Retrievals
Remote Sens. 2012, 4(10), 3022-3054; doi:10.3390/rs4103022
Received: 20 August 2012 / Revised: 29 September 2012 / Accepted: 6 October 2012 / Published: 11 October 2012
Cited by 8 | PDF Full-text (6861 KB) | HTML Full-text | XML Full-text
Abstract
Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 mm can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses t De to optically thick clouds. Measurements from an imager,
[...] Read more.
Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 mm can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses t < ~6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of t and ice particle size De to optically thick clouds. Measurements from an imager, an interferometer, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval potential of infrared radiances over optically thick ice clouds. Simulations based on coincident in situ measurements and combined cloud t from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to t up to ~20 and that for ice clouds having t > 20, the 3.7–10.8 µm and 3.7–6.7 µm BTDs are the most sensitive to De. Satellite imagery appears to be consistent with these results suggesting that t and De could be retrieved for greater optical thicknesses than previously assumed. But, because of sensitivity of the BTDs to uncertainties in the atmospheric profiles of temperature, humidity, and ice water content, and sensor noise, exploiting the small BTD signals in retrieval algorithms will be very challenging. Full article
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Open AccessArticle Flux Measurements in Cairo. Part 2: On the Determination of the Spatial Radiation and Energy Balance Using ASTER Satellite Data
Remote Sens. 2012, 4(9), 2635-2660; doi:10.3390/rs4092635
Received: 18 June 2012 / Revised: 3 September 2012 / Accepted: 5 September 2012 / Published: 13 September 2012
Cited by 9 | PDF Full-text (1774 KB) | HTML Full-text | XML Full-text
Abstract
This study highlights the possibilities and constraints of determining instantaneous spatial surface radiation and land heat fluxes from satellite images in a heterogeneous urban area and its agricultural and natural surroundings. Net radiation was determined using ASTER satellite data and MODTRAN radiative transfer
[...] Read more.
This study highlights the possibilities and constraints of determining instantaneous spatial surface radiation and land heat fluxes from satellite images in a heterogeneous urban area and its agricultural and natural surroundings. Net radiation was determined using ASTER satellite data and MODTRAN radiative transfer calculations. The soil heat flux was estimated with two empirical methods using radiative terms and vegetation indices. The turbulent heat fluxes finally were determined with the LUMPS (Local-Scale Urban Meteorological Parameterization Scheme) and the ARM (Aerodynamic Resistance Method) method. Results were compared to in situ measured ground data. The performance of the atmospheric correction was found to be crucial for the estimation of the radiation balance and thereafter the heat fluxes. The soil heat flux could be modeled satisfactorily by both of the applied approaches. The LUMPS method, for the turbulent fluxes, appeals by its simplicity. However, a correct spatial estimation of associated parameters could not always be achieved. The ARM method showed the better spatial results for the turbulent heat fluxes. In comparison with the in situ measurements however, the LUMPS approach rendered the better results than the ARM method. Full article
Open AccessArticle Simulation of Image Performance Characteristics of the Landsat Data Continuity Mission (LDCM) Thermal Infrared Sensor (TIRS)
Remote Sens. 2012, 4(8), 2477-2491; doi:10.3390/rs4082477
Received: 6 July 2012 / Revised: 15 August 2012 / Accepted: 16 August 2012 / Published: 22 August 2012
Cited by 9 | PDF Full-text (910 KB) | HTML Full-text | XML Full-text
Abstract
The next Landsat satellite, which is scheduled for launch in early 2013, will carry two instruments: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). Significant design changes over previous Landsat instruments have been made to these sensors to potentially enhance
[...] Read more.
The next Landsat satellite, which is scheduled for launch in early 2013, will carry two instruments: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). Significant design changes over previous Landsat instruments have been made to these sensors to potentially enhance the quality of Landsat image data. TIRS, which is the focus of this study, is a dual-band instrument that uses a push-broom style architecture to collect data. To help understand the impact of design trades during instrument build, an effort was initiated to model TIRS imagery. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool was used to produce synthetic “on-orbit” TIRS data with detailed radiometric, geometric, and digital image characteristics. This work presents several studies that used DIRSIG simulated TIRS data to test the impact of engineering performance data on image quality in an effort to determine if the image data meet specifications or, in the event that they do not, to determine if the resulting image data are still acceptable. Full article

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