Temperature and Emissivity Separation from Thermal Airborne Hyperspectral Imager (TASI) Data

Yang, Hang; Zhang, Lifu; Yingqian, GAO; Hu, Shunshi; Li, Xueke; Genzhong, Zhang; Tong, Qingxi

doi:10.14358/pers.79.12.1099

Cited by 10 publications

(8 citation statements)

References 27 publications

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“…More specifically, four predominant land covers including construction material (five samples), soil (two samples), vegetation (four samples) and water body (two samples) collected on August 15, 2010 were used to assess the performance of TASI. Results [33] showed a satisfactory agreement with ground data in the same program of Shijiazhuang, with root mean square error value of 0.046 for broad-emissivity and 2.2 °C for temperature. This suggests the airborne based LST can be acceptable and reliable for further analysis.…”

Section: Analysis Of Urban Thermal Patterns At the Microscale Levelmentioning

confidence: 53%

“…The retrieved spectra of welling path radiance and downwelling sky radiance were both integrated to TASI channels on the basis of the corresponding filter function. More detailed information about the data pre-processing can be found in our previous study [33].…”

Section: Image Pre-processingmentioning

confidence: 99%

“…Figure 13b confirms that more detailed information of the surface temperature can be captured by the TASI sensor. The LST from the TASI sensor was assessed in a prior study [33]. An accuracy of 2.2 K was achieved by comparing the TASI LST with the in situ LST measured at the same local time.…”

Section: Comparison Of the Tasi And Landsat Tm Lstmentioning

confidence: 99%

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Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

Liu

Zhang

et al. 2015

Remote Sensing

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Abstract:The urban heat island (UHI) effect resulting from rapid urbanization generally has a negative impact on urban residents. Shijiazhuang, the capital of Hebei Province in China, was selected to assess surface thermal patterns and its correlation with Land Cover Types (LCTs). This study was conducted using Landsat TM images on the mesoscale level and airborne hyperspectral thermal images on the microscale level. Land surface temperature (LST) was retrieved from four scenes of Landsat TM data in the summer days to analyze the thermal spatial patterns and intensity of surface UHI (SUHI). Surface thermal characteristics were further examined by relating LST to percentage of imperious surface area (ISA%) and four remote sensing indices (RSIs), the Normalized Difference Vegetation Index (NDVI), Universal Pattern Decomposition method (VIUPD), Normalized Difference Built-up Index (NDBI) and Biophysical Composition Index (BCI). On the other hand, fives scenes of airborne TASI (Thermal Airborne Spectrographic Imager sensor) images were utilized to describe more detailed urban thermal characteristics of the downtown of Shijiazhuang city. Our results show that an obvious surface heat island effect OPEN ACCESSRemote Sens. 2015, 7 4805 existed in the study area during summer days, with a SUHI intensity of 2-4 °C. The analyses reveal that ISA% can provide an additional metric for the study of SUHI, yet its association with LST is not straightforward and this should a focus in future work. It was also found that two physically based indices, VIUPD and BCI, have the potential to account for the variation in urban LST. The results concerning on TASI indicate that diversity of impervious surfaces (rooftops, concrete, and mixed asphalt) contribute most to the SUHI, among all of the land cover features. Moreover, the effect of impervious surfaces on LST is complicated, and the composition and arrangement of land cover features may play an important role in determining the magnitude and intensity of SUHI. Overall, the analysis of urban thermal signatures at two spatial scales complement each other and the use of airborne imagery data with higher spatial resolution is helpful in revealing more details for understanding urban thermal environments.Keywords: urban heat island (UHI); land cover types (LCTs); impervious surface area (ISA); thermal airborne spectrographic imager (TASI)

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Section: Analysis Of Urban Thermal Patterns At the Microscale Levelmentioning

confidence: 53%

Section: Image Pre-processingmentioning

confidence: 99%

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Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

Liu

Zhang

et al. 2015

Remote Sensing

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“…Thus, an a priori assumption or an empirical relation must be introduced to solve the system [26]. On this basis, several temperature/emissivity separation methods were developed to be used with both multispectral and hyperspectral infrared sensors [21,27]: among the most popular, the reference channel method, the emissivity normalization, the alpha residual, the temperature/emissivity separation (TES) and the day/night method. The last one, adopted for MODIS products, uses two images to increase the number of equations, avoiding the ill-posed problem.…”

Section: Resultsmentioning

confidence: 99%

“…In the present study, a direct measure of the emissivity for bituminous and gravel roofing surfaces was performed during a special survey, by means of a thermal camera and a contact probe thermometer. For the other roofing materials, the emissivity values were set according to data published in the literature [19][20][21][22]. The values used for the present study are summarized in Table 2.…”

Section: Emissivity Mapmentioning

confidence: 99%

Aerial Thermography for Energetic Modelling of Cities

et al. 2015

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Abstract:The rising attention to energy consumption problems is renewing interest in the applications of thermal remote sensing in urban areas. The research presented here aims to test a methodology to retrieve information about roof surface temperature by means of a high resolution orthomosaic of airborne thermal infrared images, based on a case study acquired over Bologna (Italy). The ultimate aim of such work is obtaining datasets useful to support, in a GIS environment, the decision makers in developing adequate strategies to reduce energy consumption and CO2 emission. In the processing proposed, the computing of radiometric quantities related to the atmosphere was performed by the Modtran 5 radiative transfer code, while an object-oriented supervised classification was applied on a WorldView-2 multispectral image, together with a high-resolution digital surface model (DSM), to distinguish among the major roofing material types and to model the effects of the emissivity. The emissivity values were derived from literature data, except for some roofing materials, which were measured during ad hoc surveys, by means of a thermal camera and a contact probe. These preliminary results demonstrate the high sensitivity of the model to the variability of the surface emissivity and of the atmospheric parameters, especially transmittance and upwelling radiance.

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Assessing the effects of urban green landscape on urban thermal environment dynamic in a semiarid city by integrated use of airborne data, satellite imagery and land surface model

Wang

et al. 2022

International Journal of Applied Earth Observation and Geoinfor

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Temperature and Emissivity Separation from Thermal Airborne Hyperspectral Imager (TASI) Data

Cited by 10 publications

References 27 publications

Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

Aerial Thermography for Energetic Modelling of Cities

Assessing the effects of urban green landscape on urban thermal environment dynamic in a semiarid city by integrated use of airborne data, satellite imagery and land surface model

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