Abstract-The standard data fusion methods may not be satisfactory to merge a high-resolution panchromatic image and a low-resolution multispectral image because they can distort the spectral characteristics of the multispectral data. In this paper, we developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of such images. The method presented here consists of adding the wavelet coefficients of the high-resolution image to the multispectral (lowresolution) data. We have studied several possibilities concluding that the method which produces the best results consists in adding the high order coefficients of the wavelet transform of the panchromatic image to the intensity component (defined as L = R+G+B 3 ) of the multispectral image. The method is, thus, an improvement on standard intensity-hue-saturation (IHS or LHS) mergers. We used the "à trous" algorithm which allows to use a dyadic wavelet to merge nondyadic data in a simple and efficient scheme. We used the method to merge SPOT and LANDSAT (TM) images. The technique presented is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.

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Airborne hyperspectral cameras provide the basic information to estimate the energy wasted skywards by outdoor lighting systems, as well as to locate and identify their sources. However, a complete characterization of the urban light pollution levels also requires evaluating these effects from the city dwellers standpoint, e.g. the energy waste associated to the excessive illuminance on walls and pavements, light trespass, or the luminance distributions causing potential glare, to mention but a few. On the other hand, the spectral irradiance at the entrance of the human eye is the primary input to evaluate the possible health effects associated with the exposure to artificial This is an author-created, accepted version of the paper "Ground-based hyperspectral analysis of the urban nightscape" by R. We also present the preliminary results from a field campaign carried out in the downtown of Barcelona.

Abstract-Spatial resolution is a key parameter of all remote sensing satellites and platforms. The nominal spatial resolution of satellites is a well-known characteristic because it is directly related to the area in ground that represents a pixel in the detector. Nevertheless, in practice, the actual resolution of a specific image obtained from a satellite is difficult to know precisely because it depends on many other factors such as atmospheric conditions. However, if one has two or more images of the same region, it is possible to compare their relative resolutions. In this paper, a wavelet-decomposition-based method for the determination of the relative resolution between two remotely sensed images of the same area is proposed. The method can be applied to panchromatic, multispectral, and mixed (one panchromatic and one multispectral) images. As an example, the method was applied to compute the relative resolution between SPOT-3, Landsat-5, and Landsat-7 panchromatic and multispectral images taken under similar as well as under very different conditions. On the other hand, if the true absolute resolution of one of the images of the pair is known, the resolution of the other can be computed. Thus, in the last part of this paper, a spatial calibrator that is designed and constructed to help compute the absolute resolution of a single remotely sensed image is described, and an example of its use is presented.

The Institut Cartogràfic de Catalunya (ICC) operates a Digital Metric Camera (DMC), manufactured by Z/Imaging. It supports the simultaneous capture of panchromatic, RGB colour and near-infrared images. One of the most important ICC products is the Catalonia orthophotomap series. This product is intended to depict the territory as realistically as possible. With this aim, ICC is developing a project to obtain genuine colours in the photographic products produced with the DMC camera and this paper contains some preliminary results. Since an absolute radiometric calibration of the DMC is not available yet, this is accomplished through simultaneous images acquired with both DMC and a Compact Airborne Spectral Imager (CASI) also operated by ICC. These images are used to locate common areas imaged in similar geometrical conditions, and then a linear relationship between Digital Numbers (DN) from DMC and radiance values of a CASI image emulating DMC bands is calculated. To improve the colour of the DMC products, a colorimetric calibration based on polynomial transformations has been developed. This transformation allows changing from DMC-RGB space to a sRGB space that is based on CIE-XYZ colour space. Airborne ICC-CASI images acquired with a Cessna Caravan B20 over Banyoles (Spain) in 2005 were used to test the methodology. The comparison between the training colours and the ones obtained after colorimetric calibration yield differences in 8bit DN that range from 4 to 36 DN with a mean value of 12 DN. The effect was also visually analyzed on different subsets of images that include agriculture areas, urban landscape and a natural water layer. Finally, it was found that the application of both calibrations to the DMC images results in a consistent colour combinations for all the analyzed subsets.