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An Emissivity Modulation Method for Spatial Enhancement of Thermal Satellite Images in Urban Heat Island Analysis

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An Emissivity Modulation Method for Spatial Enhancement of Thermal Satellite Images in Urban Heat Island Analysis 547-556_08-003.qxd 4/16/09 10:37 AM Page 547 An Emissivity Modulation Method for Spatial Enhancement of Thermal Satellite Images in Urban Heat Island Analysis Janet Nichol Abstract NASA’s newly announced Hyperspectral Infrared Imager This study examines and validates a technique for spatial (Nichol et al., 2007), means that the highest resolution enhancement of thermal satellite images for urban heat island obtainable available from thermal satellite sensors in the analysis, using a nighttime ASTER satellite image. The tech- foreseeable future is 90 m from ASTER. nique, termed Emissivity Modulation, enhances the spatial This study examines and validates a simple technique resolution while simultaneously correcting the image derived for enhancing the spatial resolution of ASTER thermal images, temperatures for emissivity differences of earth surface while simultaneously correcting the image derived tempera- materials. A classified image derived from a higher resolution tures for emissivity differences of surface materials. The visible wavelength sensor is combined with a lower resolution method combines a classified image derived from a higher thermal image in the emissivity correction equation in a resolution visible wavelength sensor, and a set of externally procedure derived from the Stephan Bolzmann law. This has derived emissivity values with a lower resolution thermal the effect of simultaneously correcting the image-derived image. It effectively ratios the visible and thermal datasets in “Brightness Temperature” (Tb) to the true Kinetic Tempera- the emissivity correction equation in a procedure derived ture (Ts), while enhancing the spatial resolution of the from the Stephan Bolzmann law. This has the effect of thermal data. Although the method has been used for studies simultaneously correcting the image-derived “Brightness of the urban heat island, it has not been validated by com- Temperature” (Tb) to the actual Kinetic Temperature of the parison with “in situ” derived surface or air temperatures, surface (Ts), while enhancing the spatial resolution of the and researchers may be discouraged from its use due to the thermal data. Although the method has been used for fact that it creates sharp boundaries in the image. The studies of urban microclimate due to its apparent ability to emissivity modulated image with 10 m pixel size was found depict detailed temperature patterns, it has not been vali- to be highly correlated with 18 in situ surface and air temper- dated by comparison with in situ derived surface or air ature measurements and a low Mean Absolute Difference of 1 temperatures. The present study uses a nighttime ASTER K was observed between image and in situ surface tempera- image covering both urban and rural areas of Hong Kong, tures. Lower accuracies were obtained for the Ts and Tb and compares the emissivity modulated (EM) image to images at 90 m resolution. The study demonstrates that the eighteen in situ surface temperatures collected at the image emissivity modulation method can increase accuracy in the time to examine the extent of the accuracy improvement, if computation of kinetic temperature, improve the relationship any, in the context of urban heat island analysis. between image values and air temperature, and enable the Due to the difficulty of synchronizing ground measure- observation of microscale temperature patterns. ment with image acquisition, the few studies which have verified satellite-derived surface temperatures with substan- tial in situ contact surface temperatures have been for Introduction sensors with high temporal resolution, but incidentally, low Rising temperatures in tropical and sub-tropical cities mean spatial resolution (Ulivieri et al., 1992; Prata, 1994). Those that planners now need to consider adverse health effects studies examining higher spatial resolution sensors have such as respiratory problems due to increase in ground level measured only near-surface radiance representing Tb, from ozone, and heat stress, and heat-induced mortality in their towers and helicopters (Goetz et al., 1997; Li et al., 2004; planning strategies. Measures include the influence of street Rigo et al., 2006), which tends to be more variable than the layout, building geometry, and surface materials. Due to the actual surface temperature (Prata, 1994; Figure 1). The low resolution of the current thermal satellite sensors, results of both types of studies suggest that the derived accuracies do not vary according to the spatial resolution if Landsat TM (120 m), Landsat ETMϩ (60 m), and ASTER (90 m), there are no spatially detailed climatic data covering the field of view of the image data is comparable to the whole cities. Furthermore, the scan line corrector problem ground area being measured. For example, Prata (1994) obtained very high correlations between AVHRR-derived Ts experienced by Landsat ETMϩ since 2003, the lack of a thermal infrared band in the Landsat Data Continuity Mission and the potentially long development period for Photogrammetric Engineering & Remote Sensing Vol. 75, No. 5, May 2009, pp. 547–556. Department of Land Surveying and Geo-Informatics, 0099-1112/09/7505–0547/$3.00/0 The Hong Kong Polytechnic University, Kowloon, Hong © 2009 American Society for Photogrammetry Kong ([email protected]). and Remote Sensing PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING May 2009 547 547-556_08-003.qxd 4/16/09 10:37 AM Page 548 summed across the four endmember fraction images to give thermal radiance at 15 m. The temperatures so derived require further refinement using multiple thermal bands in a Temperature Emissivity Separation (TES) algorithm (Gillespie et al., 1998), due to the non-linearity referred to above. In general, the outputs from spectral unmixing are computation- ally complex and have not been substantially verified. These constraints would be even greater for night scenes due to the lack of spectral contrast between bands, thus the difficulty of defining meaningful endmembers. Pixel Block Modulation The second group of methods incorporating ancillary data of higher resolution is computationally simpler, and Figure 1. Effect of pixel block membership on fragmented applicable to a single thermal band. Guo and Moore (1998) land cover types in Emissivity Modulation. A tree canopy proposed the Pixel Block Intensity Modulation method, in a dominantly urban pixel block will have the same which uses the higher resolution reflective bands of a high Tb value as urban before emissivity modulation. sensor to identify topographic variations within a lower This erroneously high apparent temperature will not be resolution thermal band pixel block. Using the observed corrected by the EM process, and the temperature of the illumination differences on opposing sunny and shady tree pixel will be further increased, though to a lesser slopes, temperatures within the lower resolution pixel extent than that of urban pixels. blocks of the thermal band are adjusted. The method improves the thermal variation due to topography within the block and is recommended for use in simple land-cover types where temperature variations due to topography are important. However, the method is inapplicable to night- and in situ measurements when contact thermistors were time images, and in flat terrain where any DN variation deployed over an area of approximately 1 km2, correspon- within a thermal block is solely due to the thermal proper- ding to the size of an AVHRR pixel. Li et al. (2004) and Rigo ties of the surface. Most urban areas tend to occupy flatter et al. (2006) support this assertion, and Rigo et al. (2006) ground and thermal variations due to topography may be recommend higher spatial resolution sensors for urban of similar magnitude to those due to mixed land-cover. climatology due to the greater size correspondence between Differential reflectance intensity on opposing 3D building image pixels and urban features. facets may be indistinguishable from low and high albedo urban surfaces, vegetation and shadows, and vertical Spatial Enhancement of Thermal Images surfaces are actually unseen on nadir images. A simple method which is the subject of this paper may Two groups of methods have been proposed to enhance the be termed Emissivity Modulation (EM). It was first used for detail within thermal image pixels. These are (a) a spectral microclimate analysis in Singapore (Nichol, 1994) with unmixing approach which uses several thermal bands to Landsat-5’s 120 m resolution thermal band, and subse- retrieve sub-pixel constituents (Dozier, 1981; Gillespie, 1992; quently by Weng (2001) using Landsat ETMϩ and Lu and Collins et al., 2001), and (b) pixel block modulation (Guo Weng (2006) using ASTER. Thermal pixels of the high- and McMoore, 1998) which incorporates visible wavebands resolution thermal sensors Landsat TM and ASTER correspond of the same sensor or ancillary information at a higher to pixel blocks comprising many visible band pixels (16 for resolution, to enhance a single thermal band. Landsat TM and 36 for ASTER). The differential emissivity of land-cover types within a single larger pixel may be repre- Spectral Unmixing sented by applying known emissivity values to land-cover In spectral unmixing, the objective is to retrieve a set of types classified from the higher resolution visible bands. component fractions and one or more temperatures for The larger pixels of the blackbody temperature (Tb) image each thermal pixel, based on the thermal spectrum of the are combined with the emissivity
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