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Nighttime light imagery of the earth are a useful way to study the urbanization process. Satellite nocturnal images have been used to identify metropolitan areas as well as urban growth. However, the study of the extent and internal structure of urban systems by nighttime lights has had a fundamental limitation to date: the low spatial resolution of satellite sensors. DMSP Operational Linescan System (OLS), with its 2.7 km/pixel footprint, and Suomi National Polar Partnership (SNPP) satellite, with the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on board, with a spatial resolution of 742 m/pixel, still have considerable limitations for the in-depth study of the internal structure of urban systems. The launch of Luojia 1-01 in June 2018 has increased expectations. Its high-resolution nocturnal images (130 metres/pixel) allows a better in-depth study of the landscape impacted by the urbanization. Nevertheless, the areas resulting from urban sprawl process are characterized by weak night lighting, which makes identification extremely difficult. Breaking the rigid boundary that historically distinguished the urban from the rural, the topological inversion of the landscape produced by urban sprawl, makes difficult to identify the territories impacted by dispersed, fragmented and low density urbanization processes. The identification of the sprawled zones and their segmentation of the agricultural covers as well as the rest of the open spaces is especially complex, given the spatial resolution of Luojia 1-01. In this sense, the consideration of the NDVI, altitude, orientation, slope as well as the information provided by the thermal bands of Landsat8 can help to carry out a finer identification of the different urban landscapes, and specifically of the Urban Sprawl. The aim of this paper is to analyse the capacity of Luojia 1-01 to identify different types of urban landscapes, especially the results of the urban dispersion process known as Urban Sprawl. The case study is Barcelona Metropolitan Area (636 km² and 3.2 million inhabitants).
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