Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/4483
Title: | Monitoring Urban Land Cover Using Satellite Remote Sensing Techniques and Field Spectroradiometric Measurements: Case Study of “Yialias” Catchment Area in Cyprus | Authors: | Alexakis, Dimitrios Agapiou, Athos Themistocleous, Kyriacos Retalis, Adrianos Hadjimitsis, Diofantos G. |
Major Field of Science: | Engineering and Technology | Field Category: | Civil Engineering | Keywords: | Land cover;Texture;Satellite imagery;Landscape metrics;Classification;Object based | Issue Date: | 7-Nov-2012 | Source: | Journal of Applied Remote Sensing, 2012, vol. 6, no. 1 | Volume: | 6 | Issue: | 1 | Link: | http://remotesensing.spiedigitallibrary.org/article.aspx?articleid=1390078 | Journal: | Journal of Applied Remote Sensing | Series/Report no.: | Journal of Applied Remote Sensing, 2012, Volume 6, Issue 1 | Abstract: | This study highlights the need for digital mapping of urban sprawl phenomenon in catchment areas with the use of both satellite and ground remote-sensing techniques. The Yialias River, located in the central part of Cyprus, was selected as a case study area. In this catchment,devastating flash flood events took place in both 2003 and 2009, with catastrophic results. Initially, ground spectroradiometric measurements were applied to nvestigate the spectral similarity of different classes such as those of “urban fabric” and “marl/chalk origin formations” within the watershed. Temporal land cover changes were analyzed by using multitemporal satellite imagery (ASTER) and by incorporating both pixel- and object-oriented classification techniques. To create effective land use and land cover maps, a classification model was proposed based on spectral, texture, and shape characteristics. The pixel-based classification results were compared and evaluated with the object-based classification products. The optimum classification products were imported to geographical information systems and FRAGSTATS software and were used to visually and statistically detect landscape identifying trends based on spatial landscape metrics. The final results indicated considerable urban expansion within the study area during the last 10 years. | URI: | https://hdl.handle.net/20.500.14279/4483 | ISSN: | 19313195 | DOI: | 10.1117/1.JRS.6.063603 | Rights: | © SPIE.Digital Library | Type: | Article | Affiliation : | National Observatory of Athens Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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