In this study we use ALOS PALSAR satellite data to classify land cover using a decision tree algorithm. We apply polarimetric decomposition methods to coherence and covariance matrices obtained from the data and then

In this letter, we apply the multifractal formalism to land cover change detection on very high spatial resolution data. Specifically, multifractal spectra are determined and, with modifications, are used as an initial general indicator

The spatial resolution of remote sensing instruments installed onboard satellites is one of the key factors for accurate estimations of cloud amount. In general terms, the larger the instantaneous field of view (IFOV), the

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

We cordially invite you to participate in the 2017 SPIE Remote Sensing symposium.  Over the past 23 years SPIE Remote Sensing has become the largest and most prestigious annual international meeting on this subject

On 14th December 2016 seminary of the Remote Sensing Section, which is part of the Space and Satellite Research Committee, took place. The main subject of the 4th seminar was “Transformation and acquisition of

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