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|Title:||Monitoring landcover changes on the coastal zone of north Lebanon using object-based image analysis of multi-temporal landsat images||Authors:||Mitri, George
Van Der Molen, Irna
Lovett, Jon C.
|Affiliations:||Institute of Environment
Institute of Environment
|Issue Date:||2012||Conference:||EARSEL Workshop on temporal analysis of satellite images (1st : 24-25 May 2012 : Mykonos, Greece)||Abstract:||
Monitoring landcover changes in Lebanon using multi-temporal satellite images is considered an important step towards investigating environmental change over large areas with the severe lack of environmental measurements and records. Automated change detection presents a valuable tool for monitoring large areas. Until present, Lebanon lacks an operational mechanism for monitoring changes in landcover/landuse at the National level. Simultaneously, there is continuous demand for techniques such as Object-Based Image Analysis (OBIA) that allow the integration in the analysis of more than one image (possibly of different spatial resolution) and produce GIS-ready results. This work aimed to characterize landcover changes during the last four decades on the coastal zone of North-Lebanon using an OBIA approach. This was an initial step towards conducting a more advanced investigation for assessing the effect of repetitive armed conflicts on the Northern coastal environment. A total of five Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) images covering the same geographical area of North-Lebanon were employed. The methodology of work included 1) satellite data pre-processing, 2) image segmentation and classification, and 3) post-classification comparison of the results. Pre-processing of data included geometric calibration and masking of images. OBIA comprised segmentation of images at different levels and classification incorporating spectral and contextual information. Overall, OBIA proved to be successful in monitoring landcover change with the use of multi-temporal satellite images. Field visits combined with visual interpretation of the results derived from landcover classification of multi-temporal very high spatial resolution SPOT imagery showed that recorded changes in landcover came in the form of: deforestation, land reclamation from the sea, indiscriminate construction, new road networks, and quarrying, among others. Future work will include 1) the .
|Appears in Collections:||Institute of Environment|
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