Temporal monitoring of water level changes in Seyfe Lake using remote sensing

Abstract

Abstract:The Earth's water resources are endangered by inconsiderate use, pollution and lack of conservation measures. Temporal monitoring is necessary for the conservation and usage planning of water resources and to make informed decisions. Seyfe Lake and its environs in Turkey is one of the most important water basins in the world, because it is a node on bird migration paths between Europe, Asia and Africa. For this reason, the International Council of Bird Preservation (ICBP) has registered 27 of the bird species living at Seyfe Lake on the conservation list. In this work, the temporal changes in the water surface area of Seyfe Lake and its environs, which are important for ecological, historical and tourism reasons, are investigated. The change of water surface in the lake is examined over a 26 year period using satellite images taken between 1975 . Landsat images from years 1975 , 1987 are used. The change is tracked from the images using an unsupervised classification method. A decrease of slightly more than 33% was observed in the water surface area this 26 year period. The temporal change indicated by the images was compared with the related meteorological data between 1975 and 2001. Over this time period, climate conditions (rainfall, temperature and evaporation) in the study area have been changed by approximately 21%. These changes could have affected the Lake surface area, but so also could external human interference around the Lake.

Automated mapping of water bodies using Landsat multispectral data

“…Because unsupervised (e.g., K-mean, isodata) classification methods are frequently used in water resources studies to delineate water boundaries and determine changes (Olmanson et al 2008;Castañeda et al 2005;Reis and Yilmaz 2008), we decided to compare the respective classification accuracies (GWEM, Kmean, isodata) resulting directly from the confusion matrix analysis. Each classification scheme was cross-compared with the reference set.…”

“…However, supervised methods require a priori knowledge about the number of classes and the spectral signature attributed to each class in the scene. Unsupervised classification based on "isodata" (Iterative Self-Organizing Data Analysis Technique) or "k-mean" clustering is often used to generate spectral signatures of each class (Olmanson et al 2008;Kloiber et al 2002a;Reis and Yilmaz 2008).…”

Changes in the Coastline and Water Level of the Akşehir and Eber Lakes Between 1975 and 2009

“…In Turkey, most lake monitoring studies that use remote sensing have been conducted to assess the water level because of changes in climate and human activities such as the Salt Lake (Ormeci and Ekercin 2007), Ulubat Lake (Taǧıl 2007), Seyfe Lake (Reis and Yılmaz 2008) and Akşehir and Eber Lakes (Sener et al 2009). …”

Mapping and Monitoring Lakes Intra-Annual Variability in Semi-Arid Regions: A Case of Study in Patagonian Plains (Argentina)

“…All of those features are associated with an unsupervised classification method of satellite digital data. In this context, IsoData [51] is one of the most used clustering algorithms when working with an unsupervised classification of satellite images data [52], and it is frequently used in water resources studies to delineate and determine changes in water boundaries [53][54][55][56]. The information was processed by Envi 4.1 (ESRI) software and a Geographic Information System (GIS) (ArcGIS v10.0, (ESRI, Redlands, CA, USA).…”