Surface-based and satellite-based observations remain the fundamental source of cloud amount data for climatologists. However, both data sets show inconsistency related to the interpretation of instantaneous cloud detection, whether measured using the okta scale
Although natural values are crucial for most of outdoor activities, they are rarely included into tourism accounts. Balmford et al.1 estimate the global value of tourism in natural protected areas as USD 600 billion
In this work we analyse fractal and multifractal characteristics for description and extraction of information from VHR satellite images. We propose the degree of multifractality as a global descriptor of satellite image content and
After decades of mining and industrialization in Qatar, it is important to estimate their impact on soil pollution with toxic metals. The study utilized 300 topsoil (0–30 cm) samples, multi-spectral images (Landsat 8), spectral
Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques
Every year thousands of people are displaced by conflicts or natural disasters and often gather in large camps. Knowing how many people have been gathered is crucial for an efficient relief operation. However, it
Most satellite cloud climatologies come in the form of global, low-resolution datasets: so- called ‘gridded’ Level 3 products, resulting from the reprojection and spatio-temporal aggregation of swath (Level 2) data. Their coarse resolution means
In the frame of this work six satellite images (at six spectral bands) from Landsat 5, Landsat 7 and Landsat 8 have been analysed. For this purpose 30 meter resolution images showing the regions
In order to describe relations between tourism and landscape, it is important to operate within two scopes. The first is landscape potential and the second – the way it is used by tourists. In
Boosting is a classification method which has been proven useful in non-satellite image processing while it is still new to satellite remote sensing. It is a meta-algorithm, which builds a strong classifier from many