Abstract
Abstract. Constituents of hydrologic network, River and water canals play a key role in Agriculture for cultivation, Industrial activities and urban planning. Remote sensing images can be effectively used for water canal extraction, which significantly improves the accuracy and reduces the cost involved in mapping using conventional means. Using remote sensing data, the water Index (WI), Normalized Difference Water Index (NDWI) and Modified NDWI (MNDWI) are used in extracting the water bodies. These techniques are aimed at water body detection and need to be complemented with additional information for the extraction of complete water canal networks. The proposed index MNDWI-2 is able to find the water bodies and water canals as well from the Landsat-8 OLI imagery and is based on the SWIR2 band. In this paper, we use Level-1 precision terrain corrected OLI imagery at 30 meter spatial resolution. The proposed MNDWI-2 index is derived using SWIR2 (B7) band and Green (B3) band. The usage of SWIR2 band over SWIR1 results in very low reflectance values for water features, detection of shallow water and delineation of water features with rest of the features in the image. The computed MNDWI-2 index values are threshold by making the values greater than zero as 1 and less than zero as zero. The binarised values of 1 represent the water bodies and 0 represent the non-water body. This normalized index detects the water bodies and canals as well as vegetation which appears in the form of noise. The vegetation from the MNDWI-2 image is removed by using the NDVI index, which is calculated using the Top of Atmosphere (TOA) corrected images. The paper presents the results of water canal extraction in comparison with the major available indexes. The proposed index can be used for water and water canal extraction from L8 OLI imagery, and can be extended for other high resolution sensors.
Highlights
Water is one of the most essential resources for human life and covers about 70 percent of the earth
The proposed method is performed on the L1TP corrected Operational Land Imagery (OLI) data with the 30-meter spatial resolution
The water indices Modified NDWI (MNDWI), AWEInsh and AWEIsh were calculated to evaluate their performances for the extraction of water bodies and water canal
Summary
Water is one of the most essential resources for human life and covers about 70 percent of the earth. Since last 3 decades, water detection from the Remote Sensing images are being widely used to reduce the cost and time. Standard approaches rely heavily on the manual delineation of water bodies from remote sensing images (Schumann et al, 2008). The detection of water & water canals is an involved problem for researchers in remote sensing. For water body detection and change detection, many remote sensing studies use the Landsat imagery because of its temporal coverage. Several indexes were developed for Water body detection and Water Index (WI) (McFeeter's, 1996) (Xu, 2006) using the OLI data. The Landsat-8 Operational Land Imagery (OLI) contains 8 multispectral bands with a spatial resolutions of 30-meter and contain one panchromatic band (B8) with 15-meter with a radiometric resolution of 16-bit as shown in Table-1
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