Research on Water Extraction from Remote Sensing Images based on Ada Boost Algorithm

Dan Wu; Shenglan Ye

doi:10.54097/fcis.v4i1.9478

Authors

Dan Wu
Shenglan Ye

DOI:

https://doi.org/10.54097/fcis.v4i1.9478

Keywords:

Remote Sensing Image, Ada Boost Algorithm, Water Extraction

Abstract

The extraction of water in remote sensing image is a key step in the application of remote sensing image. Aiming at the existing problems in remote sensing image water extraction, a water extraction method based on Ada Boost algorithm is proposed. In this method, multiple thresholds are set for image segmentation, and the results are voted, and finally the water extraction results are obtained. Using the threshold value of 7 algorithms to synthesize, using the Ada Boost algorithm, the advantages and disadvantages of each algorithm are analyzed and compared. The experimental results show that the water body extracted by a single method and a combination of 7 methods is not ideal, but the water body extracted by a combination of two, three, four and five methods is relatively good, among which the best effect is the water body extracted by a combination of three methods.

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References

Rishikeshan, C. A., and H. Ramesh. "An automated mathematical morphology driven algorithm for water body extraction from remotely sensed images." ISPRS Journal of Photogrammetry and Remote Sensing (2018).

Jiang, Wei, et al. "An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery." Water (2021).

Yue, H., et al. "A new accuracy evaluation method for water body extraction." International Journal of Remote Sensing (2020).

Zhuang, Yin, et al. "Harbor Water Area Extraction From Pan-Sharpened Remotely Sensed Images Based on the Definition Circle Model." IEEE Geoscience and Remote Sensing Letters (2017).

Xu X. Research on automatic water extraction scheme of remote sensing image based on image features [J]. Anhui building, 2019, 26 (9): 50-51. DOI: 10.16330 / j. carol carroll nki. 1007-7359.2019.09.020.

Zhao Chenxi, Hu Jingfang, Song Yu et al. Research on water body identification and extraction of image review [J]. Journal of sensor world, 2022, 28 (08): 1-9.

Wang Xin, Xu Mingjun, Li Ke et al. An effective method for water extraction from high-resolution remote sensing images [J]. Computer Engineering and Applications, 2019,55(20):145-151+207. (In Chinese)

Pan, F., X. Xi, and Cheng Wang. "A Comparative Study of Water Indices and Image Classification Algorithms for Mapping Inland Surface Water Bodies Using Landsat Imagery." Remote. Sens. (2020).

Hu, Shunshi, et al. "Automatic Extraction of Water Inundation Areas Using Sentinel-1 Data for Large Plain Areas." Remote. Sens. (2020).

Zhai, K., et al. "Comparison of surface water extraction performances of different classic water indices using OLI and TM imageries in different situations." Geo-spatial Information Science (2015).

Song Yingqiang, Yang Lian 'an, Xu Jingting, Wei Anlei. Water body information extraction based on Landsat-8 OLI remote sensing image and AdaBoost algorithm [J]. Surveying, Mapping and Geographic Information,2017,42(03):44-47.