Extraction of long time series wetland information based on Google Earth Engine and random forest algorithm for a plateau lake basin – A case study of Dianchi Lake, Yunnan Province, China

Zhao, Fang; Feng, Siwen; Xie, Fei; Zhu, Sijin; Zhang, Sujin

doi:10.1016/j.ecolind.2022.109813

Cited by 24 publications

(15 citation statements)

References 57 publications

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“…As one of the important wetlands in the Ramsar Convention, the Yellow River Delta Wetland is also the most complete, extensive, and youngest coastal wetland in China [1] . It plays an important role in protecting biodiversity, conserving water sources, improving water quality, regulating climate, promoting land reclamation, and providing tourism resources [2] . In recent years, under the multiple pressures of climate warming, species invasion, and human activities, the Yellow River Delta wetland has faced huge threats and challenges.…”

Section: Introductionmentioning

confidence: 99%

Study of wetland sample discrimination using a long time series of SAR data

Huo,

Zhao,

Zhao

2024

Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023)

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The wetland is one of the most important ecosystems in the world, and monitoring its evolution is of great significance to protect wetland biodiversity and maintain ecosystem stability. This study aims to address the problem of low accuracy in salt marsh vegetation monitoring due to the difficulty of obtaining measured data in complex wetland areas. The Yellow River Delta serves as the test area in this study. The method for discriminating samples of dual-polarization time-series datasets is constructed by combining the time-weighted dynamic temporal warping algorithm and the DBSCAN clustering algorithm, using the intensity information provided by time-series Sentinel-1A images. On this basis, the support vector machine classifier is used to classify different polarized temporal datasets. Research shows that the sample discrimination method based on this article can extract wetland feature information. Among the classification results, the VV+VH polarization dataset exhibits the highest accuracy, with overall accuracy and Kappa coefficient of 88.734% and 0.857, respectively. These values are 2.43% and 0.025 higher than the classification accuracy of the VH polarization time series dataset relying only on visual discrimination samples. The research results in this paper provide a basis for decision-making on the restoration and protection of wetlands in the Yellow River Delta.

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Section: Introductionmentioning

confidence: 99%

Study of wetland sample discrimination using a long time series of SAR data

Huo,

Zhao,

Zhao

2024

Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023)

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“…The nine major plateau lakes (>30km 2 ) in Yunnan Province are significant ecological and environmental functional areas in southwest China, playing a crucial role in the regional economic and social development of Yunnan Province (Zhao et al, 2023; Ma et al, 2022). Yangzong Lake, as one of the nine major plateau lakes, is an important component of the upstream Pearl River and plays a critical role in biodiversity conservation in Yunnan Province and the establishment of an ecological security barrier in southwest China (Zhang et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

The structure and diversity of the bacterial community in the overlying water of the Yangzong Lake in Yunnan

Huang,

Li,

et al. 2024

Preprint

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Bacteria are critical components of lake ecosystems, and understanding the characteristics of bacterial community structure and diversity indices is of significant importance for the analysis and management of lake ecology. In this study, overlying water samples were collected from Yangzong Lake in May, June, and July 2021. High-throughput sequencing and statistical analysis were employed to investigate the relationships between physicochemical factors, bacterial community structure, and diversity in the overlying water of Yangzong Lake. The results showed significant differences in oxidation-reduction potential among the sampling points. The order of oxidation-reduction potential was as follows: Yangzong DAHE > Yangzong Lake South > Yangzong Lake Middle > Yangzong Lake North, while other physicochemical factors exhibited minor differences. The number of OTUs and bacterial alpha diversity index in the overlying water of Yangzong Lake Middle were higher than those in Yangzong Lake North, Yangzong Lake South, and Yangzong DAHE. The dominant bacterial phyla in the overlying water were Actinobacteriota, Bacteroidota, and Proteobacteria. Actinobacteriota had the highest relative abundance of 34.63% in Yangzong Lake North, while Bacteroidota had the highest relative abundance of 33.79% in Yangzong Lake South, and Proteobacteria had the highest relative abundance of 27.29% in Yangzong Lake Middle. The dominant genera were hgcI_clade, CL500-29_marine_group, and Flavobacterium. Among them, hgcI_clade had the highest relative abundance of 37.56% in Yangzong Lake North, CL500-29_marine_group had the highest relative abundance of 35.22% in Yangzong Lake South, and Flavobacterium had the highest relative abundance of 42.02% in Yangzong Lake Middle. Correlation analysis revealed significant correlations between Campilobacterota at the phylum level and dissolved oxygen (DO) and total phosphorus (TP). At the genus level, Flavobacterium, Limnohabitans, and Pseudarcicella showed significant correlations with DO and TP.

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“…In the long-time-series and large-scale remote sensing exploration of the earth, the GEE platform provides a large number of high-resolution Landsat TM/ETM+/OLI remote sensing images through dedicated cloud storage, which can access, process, and extract wetland water body information online, thus greatly improved the efficiency of remote sensing scholars [10]. In practice, the GEE has proven to be a powerful tool that can be used to extract wetland information [11,12].…”

Section: Introductionmentioning

confidence: 99%

Effects of Temporal and Spatial Changes in Wetlands on Regional Carbon Storage in the Naoli River Basin, Sanjiang Plain, China

Dai

Wang

et al. 2023

Land

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The Naoli River (NLR) Basin is a crucial distribution area for wetlands in China. Investigating the link between land use changes and carbon storage in this basin is of significant importance for protecting regional ecosystems and promoting the sustainable development of the social economy. This paper uses long-term Landsat satellite images provided on the GEE (Google Earth Engine) platform and the random forest classification algorithm to create spatial distribution maps of land use in the NLR Basin from 1993 to 2022. The study analyzes the dynamic changes in wetlands in the basin over the past 30 years and employs the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model to explore the temporal and spatial evolution characteristics of carbon storage. The results reveal that the wetland area of the NLR Basin showed a downward trend from 1993 to 2022, with a total decrease of 1507.18 hm2 over 30 years. During this period, the carbon storage in the NLR Basin decreased, with a cumulative loss of 1.98 × 107 t, mainly due to the continuous reductions in wetland and forest land. Additionally, the change in carbon storage in the basin has a strong spatial and temporal relationship with the changes in land use/cover area. The total carbon storage is positively associated with the areas of wetland, forest land, and water bodies. The conversion of wetlands into any other land type results in the reduction in carbon storage. These findings can improve our understanding of the spatial and temporal dynamics of wetlands in the NLR Basin over the past 30 years and enable us to analyze the relationship between land use changes and regional carbon storage. The results of this study have great significance for protecting the wetland ecology and regional carbon balance in the NLR Basin.

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Extraction of long time series wetland information based on Google Earth Engine and random forest algorithm for a plateau lake basin – A case study of Dianchi Lake, Yunnan Province, China

Cited by 24 publications

References 57 publications

Study of wetland sample discrimination using a long time series of SAR data

Study of wetland sample discrimination using a long time series of SAR data

The structure and diversity of the bacterial community in the overlying water of the Yangzong Lake in Yunnan

Effects of Temporal and Spatial Changes in Wetlands on Regional Carbon Storage in the Naoli River Basin, Sanjiang Plain, China

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