Assessing different remote sensing techniques to detect land use/cover changes in the eastern Mediterranean

A new approach for land cover classification and change analysis: Integrating backdating and an object-based method

“…In addition to its wide applications in forest ecosystems, such method has also been applied to quantify changes of impervious surfaces in urban environments (Powell, Cohen, Yang, Pierce, & Alberti, 2008;Schneider, 2012), coral reef health (Palandro et al, 2008) and fire events (Röder, Hill, Duguy, Alloza, & Vallejo, 2008). Pre-classification change detection techniques, whether using dense time series image data or not, generally only generates "change" vs. "no-change" maps, but do not specify the type of change (Berberoglu & Akin, 2009;Lu et al, 2004;Singh, 1989).…”

Coastal changes and movements in the wider vlora (Albania) area

“…These differences can mask real changes or make similar land covers appear to have changed (Berberoglu and Akin, 2009). To overcome this problem, we applied atmospheric correction using ATCOR software.…”

“…Based on the results of research done by (Berberoglu and Akin, 2009) change vector analysis is the most appropriate model for handling the variability present in the Mediterranean land use/cover. We have used this method to obtain changes of erosion and urbanisation on the Albanian southern coast.…”

“…Many Mediterranean land covers exhibit similar spectral characteristics making the separation in feature space by simple per-pixels classifiers difficult, leading to inaccurate classification (Berberoglu and Akin, 2009). We used objectbased approach to conduct the classification separately on the two Landsat images, from 2010 and 2015 respectively.…”

“…Several scholars (Allen and Kupfer, 2000;Baker et al, 2007;Lorena et al, 2002;Xiaolu and Bo, 2011) have conducted studies of change detection using change vector analysis from Landsat data. Authors (Berberoglu and Akin, 2009) undertook a comparison of different change detection techniques in the Mediterranean environment and although different change detection algorithms have their own merits and advantages, change vector analysis resulted in the largest overall accuracy. We first applied change vector analysis on the multi-temporal remote sensing data, where we detected two major types of coastal changes seen in this area: coastal erosion and coastal urbanisation.…”