Monitoring of water clarity, and submerged and emergent plant coverages in shallow lake wetlands using remote sensing techniques


Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey

Approval Date: 2007

Student: ÖZGE KARABULUT DOĞAN

Co-Supervisor: MERYEM BEKLİOĞLU, SEVDA ZUHAL AKYÜREK

Abstract:

Shallow lake wetlands, for which aquatic plants (macrophytes) and water clarity are the key indicators of ecological status, provide valuable services to wildlife and humanity. Conservation of these ecosystems requires development of rapid and large scale monitoring strategies, where remote sensing and Geographic Information Systems (GIS) can be advantageous. In this study, high spatial resolution Quickbird and IKONOS and medium spatial resolution Landsat and Aster images were used for monitoring the aquatic plants and water clarity in Lakes Mogan and Eymir. Classification of emergent plants with high spatial resolution data yielded overall accuracies greater than 90% for both lakes, while overall accuracies obtained from the medium spatial resolution data ranged between 80% and 93% for Lake Mogan and between 70% and 78% for Lake Eymir. It was found that there was 23ha reed bed loss in Lake Mogan between 2002 and 2005 and an additional 14ha was lost between 2005 and 2006. In Lake Eymir, no significant change in reed bed area was detected from high spatial resolution images; however medium spatial resolution images revealed 8ha of change which was attributed to the presence of mixed pixels due to low resolution. The overall accuracies for submerged plant coverage classification from Quickbird images in Lake Mogan were 83% (2005) and 79% (2006) and for classification of submerged plants species were 72% (2005) and 69% (2006). Moreover, it was found that blue band together with the ratio of red band to blue band, were the best predictors of Secchi disc depth.