Abstract
Most of the methods used to retrieve land surface temperature (LST) from thermal infrared (TIR) satellite data in urban areas do not take into account the complexity of the surface. Cities are characterized by high surface roughness and one of the main constraints to estimate LST over those areas is the difficulty to define an effective emissivity for a given pixel at a given scale. When working with mixed pixels, the emissivity used to estimate the LST is an effective emissivity composed of the emissivities of each basic element constituting the pixel. In urban areas, the surface geometry has a strong impact on this effective emissivity. Its estimation from TIR satellite data must be carried out considering multiple surface reflections and diffusions within the urban canopy in order to retrieve accurate LST values. The objective of this study is then to evaluate the impact of the surface geometry within the pixel on effective emissivity estimation and to propose a method to derive an effective emissivity corrected for those effects. Emissivity can be derived at 90 m of spatial resolution from the TIR data acquired by ASTER. To evaluate the impact of the geometry at the scale of an ASTER pixel, several urban canyon configurations are designed to develop and test the correction method. The basic principle behind the method is to accurately estimate the downwelling TIR radiation received by a pixel integrating contributions from both the atmosphere and the scene inside this pixel and then derive the corrected effective emissivity from ASTER data using the TES (temperature emissivity separation) algorithm. First, the total downwelling TIR radiation is estimated from the geometric characteristics of the scene, using morphological indicators and integrating the non-isothermal behavior of the pixel thanks to 3D thermo-radiative model simulations. The validation of those estimations for each canyon configuration provides a maximum RMSE (Root Mean Square Error) value of 2.2 W·m−2. The validation performed over a district extracted from the 3D numerical model of Strasbourg (France) shows a RMSE of 2.5 W·m−2. Once the method to estimate the total downwelling TIR radiation is validated, LSE and LST maps are retrieved from an ASTER image over three districts of Strasbourg, showing that accounting for the surface geometry highlights thermal behavior differences inside districts, and that the impact of the geometry seems more influenced by building height than street width or building density.
Highlights
The growing trend towards urbanization raises a number of issues such as deteriorating air quality or rising temperatures [1,2]
Most of those models provide broadband estimations, which are difficult to convert to narrowband estimations corresponding to the ASTER spectral bands. For those allowing narrowband simulations, they require complex parameterization datasets. Setting out from these facts, this study proposes a method to estimate the total downwelling thermal infrared (TIR) radiation narrowband based on the geometric characteristics of the surface derived from a digital surface model (DSM) combined with metric spatial resolution land surface temperature (LST) simulated with a simple 3D radiative model parameterization
The effective LSE and the LST are estimated for three districts presenting different urban configurations, the objective being to investigate the impact of the geometric correction and to quantify the errors caused by neglecting the surface geometry
Summary
The growing trend towards urbanization raises a number of issues such as deteriorating air quality or rising temperatures [1,2]. LST and LSE data products are operationally derived at 90 m spatial resolution from ASTER data using the TES (temperature emissivity separation) algorithm [16] This method provides satisfying results in most cases [17,18], it does not take into account the complexity of the surface over urban areas while the surface geometry was identified as one of the factors of error [18]. The impact of the surface geometry is integrated into the estimation of the downwelling TIR radiation for each pixel by taking into account all contributions, namely radiation coming from the atmosphere, radiation emitted by the surrounding elements, and radiation from multiple reflections in the scene inside the pixels This total downwelling TIR radiation can be estimated precisely using 3D thermo-radiative models, such as DART [20], TUF-3D [21], LASER/F [22], SOLENE-Microclimat [23], ENVI-met [24], etc., which simulate the energy transfers at the soil–atmosphere interface for urban environment. This paper proposes a method to derive R↓T,λ for the 5 ASTER TIR bands based on the geometric characteristics of the considered scene and simulated LST
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