Classification of wetland vegetation in the Yellow River Delta based on the fusion of hyperspectral data

Hao Tian; Xintong Qian; Fei Meng

doi:10.1117/12.3032330

3 June 2024 Classification of wetland vegetation in the Yellow River Delta based on the fusion of hyperspectral data

Hao Tian, Xintong Qian, Fei Meng

Proceedings Volume 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024); 131701A (2024) https://doi.org/10.1117/12.3032330
Event: Third International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 2024, Wuhan, China

Abstract

The Yellow River Delta wetlands are rich in vegetation species and the ecosystem is sensitive and fragile, so it is of great practical significance to accurately extract the information of the vegetation in the Yellow River Delta wetlands and analyze its spatial and temporal changes. Based on Sentinel-2A multispectral images and ZY1-02D hyperspectral images, this study addresses the problem of high spectral resolution and low spatial resolution of hyperspectral images, and adopts the Gram-Schmidt fusion method to fuse the two kinds of images, and uses the Random Forest Classification method to complete the classification of the typical vegetation of the Yellow River Delta region, and compares the classification accuracies of the three kinds of images. The study shows that: (1) Gram-Schmidt is more effective for image fusion, and the fusion of fused hyperspectral images based on the NIR band of Sentinel-2A images has the best fusion effect, which maximally retains the original spectral reflectance values, and at the same time improves the spatial resolution. (2) The classification accuracy of the fused hyperspectral images is high, with an overall classification accuracy of 85.62%, which is higher than that of single hyperspectral images and multispectral images.

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

Citation Download Citation

Hao Tian, Xintong Qian, and Fei Meng "Classification of wetland vegetation in the Yellow River Delta based on the fusion of hyperspectral data", Proc. SPIE 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 131701A (3 June 2024); https://doi.org/10.1117/12.3032330

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available