Improving an index for urban surface water detection

다국어 초록 (Multilingual Abstract)

Identifying waterbody from remote sensing images, namely water detection, helps understand continuous redistribution of terrestrial water storage and accompanying hydrological processes. It also allows us to estimate available surface water resources and help effective water management. For this problem, NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) are widely used. Although remote sensing indexes can highlight remote sensing image in the water, the noise and the spatial information of the remote sensing image are difficult to be considered, so the accuracy is difficult to be compared with the visual interpretation (the most accurate method, but it requires a lot of labor, which makes it difficult to apply). In this study, we attempt to improve existing NDWI and MNDWI to better water detection.

목차 (Table of Contents)

• 1 Introduction 1
• 2 Remote sensing index 5
• 3 Topography Normalized Difference Water Index 12
• 3.1 Problems of traditional water index 12
• 3.2 The relationship between water body and topographic factors 15
• 4 Data and study area 19
• 4.1 Study area 19
• 4.2 Satellite Data 20
• 4.3 Digital Elevation Model 22
• 4.4 Water body map 24
• 5 Result 27
• 5.1 Enhancement 27
• 5.2 Histogram bimodal method 31
• 5.3 Classification 36
• 5.4 Evaluation of classification results 41
• 6 Conclusion 45
• 7 Future work 46
• 7.1 Snow,frozen water,water body 46
• 7.2 Threshold calculation 47