Abstract
Abstract. Water is one of the most important resources that essential need for human life. Due to population growth and increasing need of human to water, proper management of water resources will be one of the serious challenges of next decades. Remote sensing data is the best way to the management of water resources due time and cost effectiveness over a greater range of temporal and spatial scales. Between many kinds of satellite data, from SAR to optic or from high resolution to low resolution, Landsat imagery is more interesting data for water detection and management of earth surface water. Landsat8 OLI/TIRS is the newest version of Landsat satellite series. In this paper, we investigated the full spectral potential of Landsat8 for water detection. It is developed many kinds of methods for this purpose that index based methods have some advantages than other methods. Pervious indices just use a limited number of spectral band. In this paper, Modified Optimization Water Index (MOWI) defined by consideration of a linear combination of bands that each coefficient of bands calculated by particle swarm algorithm. The result shows that modified optimization water index (MOWI) has a proper performance on different condition like cloud, cloud shadow and mountain shadow.
Highlights
Water is one of most important earth resources that about 71 percent of the Earth's surface is covered by water (Williams 2014)
Results of four subsets show that Modified normalized difference water index (MNDWI) and WRI have the problem by cloud and its shadow, and AEWI has a little problem for narrow water detection
Between many kinds of satellite data, Landsat imagery is the more interesting data for water detection especially Landsat8 Operational Land Imager (OLI)/TIRS that is the newest version of Landsat satellite series
Summary
Water is one of most important earth resources that about 71 percent of the Earth's surface is covered by water (Williams 2014). If images consist of complex topologies such as mountain shadows, roads, and urban areas, high false classification rate may be achieved in water body detection process (Ko, Kim et al 2015). Index-based methods can detect water body more accurately, quickly and than classification methods and does not need any prior knowledge (Li, Du et al 2013), especially on low-resolution images and single-class (water) study. Automated water extraction index (AWEI) introduced for better result achieving in an area by shadow and dark surface on Landsat TM. A modified optimization water index (MOWI) is proposed to use the full spectral potential of landsat-8 OLI/TIRS as the newest generation of Landsat series of satellites in water detection and reduce shadow effects, cloud effects and other disturbing factors. The proposed method can be considered as classification method or index-base method that we have an index-based view in this paper
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