Back to Search Start Over

Precise mapping of coastal wetlands using time-series remote sensing images and deep learning model.

Authors :
Lina Ke
Yao Lu
Qin Tan
Yu Zhao
Quanming Wang
Source :
Frontiers in Forests & Global Change; 2024, p1-16, 16p
Publication Year :
2024

Abstract

Mapping coastal wetlands' spatial distribution and spatiotemporal dynamics is crucial for ecological conservation and restoration efforts. However, the high hydrological dynamics and steep environmental gradients pose challenges for precise mapping. This study developed a new method for mapping coastal wetlands using time-series remote sensing images and a deep learning model. Precise mapping and change analysis were conducted in the Liaohe Estuary Reserve in 2017 and 2022. The results demonstrated the superiority of Temporal Optimize Features (TOFs) in feature importance and classification accuracy. Incorporating TOFs into the ResNet model effectively combined temporal and spatial information, enhancing coastal wetland mapping accuracy. Comparative analysis revealed ecological restoration trends, emphasizing artificial restoration's predominant role in salt marsh vegetation rehabilitation. These findings provide essential technical support for coastal wetland ecosystem monitoring and contribute to the study of sustainability under global climate change. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2624893X
Database :
Complementary Index
Journal :
Frontiers in Forests & Global Change
Publication Type :
Academic Journal
Accession number :
178081820
Full Text :
https://doi.org/10.3389/ffgc.2024.1409985