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Remote Sensing Identification and Spatiotemporal Change Analysis of Cladophora with Different Morphologies
- Source :
- Remote Sensing, Vol 16, Iss 3, p 602 (2024)
- Publication Year :
- 2024
- Publisher :
- MDPI AG, 2024.
-
Abstract
- Cladophora qinghaiensis, an endemic species of Cladophora in saltwater lakes, was scientifically named in 2021 (hereafter referred to as Cladophora). Cladophora exists in different morphologies, including attached submerged Cladophora (AC), grown floating Cladophora (GFC), and death floating Cladophora (DFC). Previous satellite remote sensing has mainly focused on identifying floating algae. In this study, Qinghai Lake served as a case study, and a classification decision tree model (CDTM) was proposed. The model employed the chlorophyll spectral index (CSI) and the normalized difference vegetation index (NDVI) to differentiate AC, Floating Cladophora (FC), and water. Additionally, the floating Cladophora index (FCI) was introduced to further distinguish GFC and DFC within FC. The method was applicable to Sentinel-2 images from 2016–2023. Visual interpretation methods were used for Landsat series images from the summer months (July to September) to obtain the AC and FC. The results demonstrate that over the past 30 years, the areas inhabited by AC and FC have increased gradually. The three morphologies of Cladophora also exhibited seasonal variations, with growth observed annually in May–June, reaching peaks in August–September, and gradually declining in October. In addition, by combining factors such as water surface area and climatic factors, we analyzed the driving forces influencing the changes in Cladophora. In this research, AC and FC showed significant correlations with the water surface area, with correlation coefficients (r) of approximately 0.9 and 0.7, respectively. These new findings provide valuable insights regarding the spatiotemporal changes and underlying causes for different morphologies of Cladophora in global saline lakes.
- Subjects :
- filamentous algae
Qinghai Lake
Sentinel-2
driving force
climatic factors
Science
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 16
- Issue :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8565608f71d34951a61d8153ab5f7f9b
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs16030602