Monitoring wetland evolution in the Yellow River delta from 1990 to 2020 based on long time series landsat data

Xiaotong Liu; Zhiyong Wang; Huiyang Zhang

doi:10.1117/12.3007339

30 August 2023 Monitoring wetland evolution in the Yellow River delta from 1990 to 2020 based on long time series landsat data

Xiaotong Liu, Zhiyong Wang, Huiyang Zhang

Author Affiliations +

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127972R (2023) https://doi.org/10.1117/12.3007339
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

In recent years, the stability of ecosystems in the Yellow River Delta has been damaged by the influence of invasive alien species such as Spartina alterniflora, so monitoring and protecting the wetland environment is of great significance. In this study, based on the Google Earth Engine platform, multiple features of Landsat optical satellite remote sensing data were assembled: vegetation index, water index, texture features, and land surface temperature features. The feature dataset was optimized, and finally, the wetland information was extracted from the optimized feature variables using the Support Vector Machine classification method. In this paper, the estuary of the Yellow River Delta is taken as the study area, and the wetland classification results at the estuary of the Yellow River Delta from 1990 to 2020 were obtained. The results show that (1) the surface temperature feature is of great significance for the classification of wetlands in the Yellow River Delta, and it ranks fourth in the order of importance. (2) The number of composite images has less influence on the final results. In 1990, four images were used to synthesize, and the overall accuracy and Kappa coefficient of classification results reached 89.15% and 0.832. In 2002, 12 images were used to synthesize, and the overall accuracy and Kappa coefficient of classification results reached 87.95% and 0.822. The research results in this paper can provide a basis for decision-making on the restoration and protection of wetlands in the Yellow River Delta.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Xiaotong Liu, Zhiyong Wang, and Huiyang Zhang "Monitoring wetland evolution in the Yellow River delta from 1990 to 2020 based on long time series landsat data", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127972R (30 August 2023); https://doi.org/10.1117/12.3007339

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KEYWORDS

Landsat

Image classification

Vegetation

Earth observing sensors

Environmental monitoring

Remote sensing

Feature extraction

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