Abstract
In this paper, the potential of using free-of-charge Sentinel-1 Synthetic Aperture Radar (SAR) imagery for land cover mapping in urban areas is investigated. To this aim, we use dual-pol (VV+VH) Interferometric Wide swath mode (IW) data collected on September 16th 2015 along descending orbit over Istanbul megacity, Turkey. Data have been calibrated, terrain corrected, and filtered by a 5x5 kernel using gamma map approach. During terrain correction by using a 25m resolution SRTM DEM, SAR data has been resampled resulting into a pixel spacing of 20m. Support Vector Machines (SVM) method has been implemented as a supervised pixel based image classification to classify the dataset. During the classification, different scenarios have been applied to find out the performance of Sentinel-1 data. The training and test data have been collected from high resolution image of Google Earth. Different combinations of VV and VH polarizations have been analysed and the resulting classified images have been assessed using overall classification accuracy and Kappa coefficient. Results demonstrate that, combining opportunely dual polarization data, the overall accuracy increases up to 93.28% against 73.85% and 70.74% of using individual polarization VV and VH, respectively. Our preliminary analysis points out that dual polarimetric Sentinel-1SAR data can be effectively exploited for producing accurate land cover maps, with relevant advantages for urban planning and management of large cities.
Highlights
Land cover maps are essential as a source of practical information for many purposes such as natural environment (Ullmann et al, 2014), biodiversity (Falcucci et al, 2007), urbanization (Geymen and Baz 2008, Liu and Wang 2013), agriculture (Bargiel and Herrmann 2011) and hazard assessment (van der Sande et al 2003).Developments in Remote Sensing technology provides a large number of Earth observation satellites by which enabling of monitoring the Earth surface dynamics
The digital numbers values (DN) of Synthetic Aperture Radar (SAR) data is converted into backscattering values in decibel scale
Sentinel-1 toolbox (S1TBX) in the Sentinel Application Platform provided by European Space Agency (ESA)
Summary
Developments in Remote Sensing technology provides a large number of Earth observation satellites by which enabling of monitoring the Earth surface dynamics. Many studies investigated the efficient utilize of remote sensing data for both local and global scale thematic characterization for land cover analyses (Friedl et al 2010). Remotely sensed images can be utilized monitoring of land cover consistently and continuously to identify spatial distribution land cover changes over the large areas (Congalton et al 2014). SAR satellites can provide cloud-free images (Balzter et al 2015). SAR data has been investigated in several studies and proven that it is effective for land cover monitoring (Longepe et al, 2011, Niu and Ban 2013, Balzter et al, 2015)
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