Validation of Landsat-7/ETM+ Thermal-Band Calibration and Atmospheric Correction With Ground-Based Measurements

Coll, César; Galve, Joan M.; Sánchez, Juan Manuel; Caselles, Vicente

doi:10.1109/tgrs.2009.2024934

Cited by 217 publications

(141 citation statements)

References 20 publications

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“…2) according to NASA (2011). It was atmospherically corrected using the methods described by Coll et al (2010). The required meteorological data for the MODTRAN 4 model used by Coll et al (2010) was taken from Pyramid Station.…”

Section: Remotely Sensed Datamentioning

confidence: 99%

“…The required meteorological data for the MODTRAN 4 model used by Coll et al (2010) was taken from Pyramid Station. The image-to-image coregistration for Landsat7 is 7.3 m, and the uncertainty of the derived surface temperature data is estimated to be ± 1.0 K (Barsi et al, 2003;Coll et al, 2010Coll et al, , 2012. The panchromatic band has a horizontal resolution of 15 m and was used to coregister the images.…”

Section: Remotely Sensed Datamentioning

confidence: 99%

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Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model

2014

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Abstract. Debris thickness is an important characteristic of debris-covered glaciers in the Everest region of the Himalayas. The debris thickness controls the melt rates of the glaciers, which has large implications for hydrologic models, the glaciers' response to climate change, and the development of glacial lakes. Despite its importance, there is little knowledge of how the debris thickness varies over these glaciers. This paper uses an energy balance model in conjunction with Landsat7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery to derive thermal resistances, which are the debris thickness divided by the thermal conductivity. Model results are reported in terms of debris thickness using an effective thermal conductivity derived from field data. The developed model accounts for the nonlinear temperature gradient in the debris cover to derive reasonable debris thicknesses. Fieldwork performed on ImjaLhotse Shar Glacier in September 2013 was used to compare to the modeled debris thicknesses. Results indicate that accounting for the nonlinear temperature gradient is crucial. Furthermore, correcting the incoming shortwave radiation term for the effects of topography and resampling to the resolution of the thermal band's pixel is imperative to deriving reasonable debris thicknesses. Since the topographic correction is important, the model will improve with the quality of the digital elevation model (DEM). The main limitation of this work is the poor resolution (60 m) of the satellite's thermal band. The derived debris thicknesses are reasonable at this resolution, but trends related to slope and aspect are unable to be modeled on a finer scale. Nonetheless, the study finds this model derives reasonable debris thicknesses on this scale and was applied to other debris-covered glaciers in the Everest region.

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Section: Remotely Sensed Datamentioning

confidence: 99%

Section: Remotely Sensed Datamentioning

confidence: 99%

Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model

2014

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“…More accurate emissivity values for the selected surface cover classes in this study are suggested to be 0.91 for street, 0.90 for building rooftops (urban), 0.91 for open land and 0.98 for greenery (Nichol 1996, Voogt and Oke 2003, Weng, Lu et al 2004, Coll, Galve et al 2010). …”

Section: Urban Surface Covers Classificationmentioning

confidence: 84%

“…In the final step, the surface temperature in degree Kelvin were calculated from the corrected radiances using this formula (Li, Jackson et al 2004, Coll, Galve et al 2010):…”

Section: Post-print Version 440mentioning

confidence: 99%

Landsat Surface Temperature Data Analysis for Urban Heat Resilience: Case Study of Adelaide

Ehsan¹,

Karuppannan²,

Boland³

2017

Lecture Notes in Geoinformation and Cartography

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This chapter demonstrates the application of Landsat 7 ETM+ and Landsat 8 surface cover-temperature data to support planning for urban heat resilience. Satellite data is used to analyse the correlation of the urban surface covers on surface heat island effect in Adelaide. Methods to identify best-fit satellite images, surface cover classification, surface temperature calculation and their crossmapping are detailed. Results indicate that tree canopy and surface water covers had the least surface temperature variations in micro and mesoscale. Average minimum surface temperature of tree canopy cover was 2.79°C lower than asphalt and 4.74°C lower than paved areas. It is argued that freely available satellite urban surface temperature data analysis can assists urban planning authorities in planning heat resilient urban spaces in the context of climate change.

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“…This energy is further scattered and absorbed by the atmosphere before reaching the sensor (Lee et al, 2015). proposed by Coll et al (2010), was additionally used for TIR images. In terms of atmospheric correction in TIR band images, the DN (Digital Number) is converted into radiance.…”

Section: Atmospheric Correctionmentioning

confidence: 99%

Effectiveness of Using the TIR Band in Landsat 8 Image Classification

Lee¹,

Lee²,

Kim³

et al. 2015

Journal of the Korean Society of Surveying, Geodesy, Photogramm

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This paper discusses the effectiveness of using Landsat 8 TIR (Thermal Infrared) band images to improve the accuracy of landuse/landcover classification of urban areas. According to classification results for the study area using diverse band combinations, the classification accuracy using an image fusion process in which the TIR band is added to the visible and near infrared band was improved by 4.0%, compared to that using a band combination that does not consider the TIR band. For urban area landuse/landcover classification in particular, the producer's accuracy and user's accuracy values were improved by 10.2% and 3.8%, respectively. When MLC (Maximum Likelihood Classification), which is commonly applied to remote sensing images, was used, the TIR band images helped obtain a higher discriminant analysis in landuse/landcover classification. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Validation of Landsat-7/ETM+ Thermal-Band Calibration and Atmospheric Correction With Ground-Based Measurements

Cited by 217 publications

References 20 publications

Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model

Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model

Landsat Surface Temperature Data Analysis for Urban Heat Resilience: Case Study of Adelaide

Effectiveness of Using the TIR Band in Landsat 8 Image Classification

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