The construction and verification of a water index in the complex environment based on GF-2 images

WANG Chunxia; ZHANG Jun; LI Yixu; PHOUMILAY

doi:10.6046/zrzyyg.2021227

2022 Vol. 34, No. 3

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Article navigation > Remote Sensing for Natural Resources > 2022 > 34(3): 50-58

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WANG Chunxia, ZHANG Jun, LI Yixu, PHOUMILAY. 2022. The construction and verification of a water index in the complex environment based on GF-2 images. Remote Sensing for Natural Resources, 34(3): 50-58. doi: 10.6046/zrzyyg.2021227

Citation:

WANG Chunxia, ZHANG Jun, LI Yixu, PHOUMILAY. 2022. The construction and verification of a water index in the complex environment based on GF-2 images. Remote Sensing for Natural Resources, 34(3): 50-58. doi: 10.6046/zrzyyg.2021227

The construction and verification of a water index in the complex environment based on GF-2 images

1. College of Mining, Guizhou University, Guiyang 550000, China；
2. College of Agriculture, Guizhou University, Guiyang 550000, China

Received Date: 28 July 2021

Revised Date: 15 September 2022

Publish Date: 21 September 2022

Abstract

Abstract

The high spatial resolution of GF-2 images helps to obtain more accurate water distribution information. This study constructed a water index based on GF-2 images and verified it, aiming to solve the problem that the salt and pepper noise is prone to occur when the existing water indices are used to extract information on water bodies in complex environments from high-resolution remote sensing images. Firstly, this study established a comprehensive water index (CWI) by analyzing the spectral information of surface coverings and verified its precision. Secondly, information on water bodies was extracted through image segmentation combined with the CWI, and the extraction precision was verified. Then, to fully utilize the spectral information and the advantages of a classifier, the spectral information on the segmented homogeneous objects and the CWI were combined as the input data of the classifier to extract information on water bodies and verify the extraction precision. Finally, this study verified the applicability of the CWI in both WorldView-2 and GF-1 images. The results are as follows. ① The newly constructed CWI can effectively suppress the impacts of surface coverings, such as shadow, buildings, roads, vegetation, and bare soil, thus significantly improving the extraction precision. ② Extracting information on water bodies through image segmentation combined with the CWI can effectively inhibit the occurrence of the pepper and salt noise. ③ A classifier combined with a water index can effectively improve the information extraction precision of water bodies. ④ The CWI is applicable to both WorldView-2 and GF-1 images. In sum, the CWI can be used to effectively extract information on water bodies and applies to the information extraction and renewal of rivers and lakes and the surveys of the cultivation area of pounds and thereby is a high-precision method for extraction information of water bodies.
- information extraction of water bodies /
- comprehensive water index /
- GF-2 /
- support vector machine /
- random forest

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References

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