Abstract

After the 2000s, the launch of very high-resolution satellites provided great water and irrigation network management personnel opportunities. Now, the water management staff have the opportunity to study and monitor water supply systems and exploitation conditions of irrigation systems remotely via satellite imagery. By using those satellite images, specialists can search for water bodies, detect defected place of irrigation systems, and monitor their technical condition. Another advantage of satellite imagery is that they capture large areas of the Earth, keeping water systems under control in large areas. Therefore, the use of very high-resolution images has greatly developed in the water branch since the 2000s. The creation of different water extraction methods, models, indexes, and using different layers in the analysis for different regions using different satellites with very high resolution is developed. These indexes and layers are so numerous that they are now over 100. The user has difficulty getting any of them in the analyzes. Therefore, in this article, we have studied more than 50 water extraction methods, which gave positive and accurate results in an arid region. From those 50 methods, separated 10 the most effective methods and tested with WorldView-2 image analysis in the arid region and the water-rich region of Syrdarya region. According to the results of the analysis recommend the highest accuracy method for arid areas. Results show that water extraction using NIR2 layer of the WorldView-2 satellite images is the most accurate method than other methods. The accuracy of the results was 94 %. The analysis found the irrigation systems filled with sand and vegetation.

Highlights

  • Remote Sensing (RS) investigated many methods for extraction water objects

  • NDWI is the index for calculating water objects, which was first described in McFeeters' scientific work in 1996

  • For VW images, the following calculating indices of NDWI have been created: According to the results of the analysis of the literature, we found the following NDWI formulas using WV-2 images

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Summary

Introduction

Remote Sensing (RS) investigated many methods for extraction water objects. Most of them gave accurate results in different fields and different satellites. He created the following NDWI formula for calculating in Landsat images [15]: These changes in formula gave better results than determining NDWI for Landsat images as suggested by McFeeters [22]. The NDWI layer was created by using Landsat and WV-2 images to determine water objects.

Results
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