Comparative study on water extraction based on Sentinel image and UAV image

Ruiyan Fan; Yue Ti

doi:10.1117/12.3035842

10 July 2024 Comparative study on water extraction based on Sentinel image and UAV image

Ruiyan Fan, Yue Ti

Proceedings Volume 13223, Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024); 132231T (2024) https://doi.org/10.1117/12.3035842
Event: 2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2024), 2024, Wuhan, China

Abstract

Quickly and accurately obtaining water body information and its distribution is helpful for rational planning and management of water resources, and has important value for national resource management, planning and development, and rapid disaster assessment. With the continuous development of remote sensing technology, its application in water extraction is becoming increasingly widespread and in-depth. However, further comparative research is needed to improve the accuracy and efficiency of applying remote sensing technology to water extraction. In order to seek accurate and fast water extraction methods, the Sentinel-2 satellite remote sensing data and UAV aerial photography data were respectively used to extract water information, and the accuracy evaluation was carried out in combination with Google Earth images. The results show that Sentinel-2 satellite remote sensing data combined with normalized differential water index (NDWI)^[1] and improved normalized differential water index (MNDWI) can extract large water bodies more accurately, but the performance of small water bodies is not good. In contrast, UAV aerial images combined with maximum likelihood classification algorithm show high precision water information extraction ability, especially in the identification of small water bodies.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruiyan Fan and Yue Ti "Comparative study on water extraction based on Sentinel image and UAV image", Proc. SPIE 13223, Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024), 132231T (10 July 2024); https://doi.org/10.1117/12.3035842

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KEYWORDS

Unmanned aerial vehicles

Remote sensing

Satellites

Satellite imaging

Image classification

Buildings

Image resolution

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