A phenology-based vegetation index classification (PVC) algorithm for coastal salt marshes using Landsat 8 images

Zeng, Jing; Sun, Yonghua; Cao, Peirun; Wang, Huiyuan

doi:10.1016/j.jag.2022.102776

Cited by 10 publications

(6 citation statements)

References 53 publications

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“…52,64 Therefore, the accuracy of remote sensing monitoring results can only be assessed indirectly through comparisons of spatial and temporal trends in vegetation phenology. Our comparison results showed that the spatial and temporal trends of vegetation phenology extracted in this study were consistent with those of other scholars, 18,22,28,65 which provides evidence of the reliability of our vegetation phenological parameters extracted using HANTS and the derivative method.…”

Section: Phenological Parameters and Unique Phenology Periodssupporting

confidence: 90%

“…The number of Sentinel-2 images available for the study area per year is limited, and successful extraction of vegetation phenological periods from multi-year remote sensing data has been reported in previous studies. 22 Thus, we extracted NDVI values for four vegetation species by using pixel points from all available Sentinel-2 images between January 1, 2019, and December 31, 2021. To ensure the validity of the NDVI values, we removed pixels affected by Opaque and Cirrus clouds using the QA60 band.…”

Section: Ndvi Time-seriesmentioning

confidence: 99%

“…19 Vegetation phenology refers to the growth features of vegetation during a complete growth cycle, and different vegetation exhibits significant differences in spectral features during specific phenological periods. [20][21][22] Studies have shown that using a multi-temporal remote sensing approach to extract vegetation phenological features can effectively increase spectral separability among vegetation. 23,24 This method has been successfully applied to cropland, 25 paddy rice, 26 mangroves, 27 and S. alterniflora 28 in remote sensing identification of vegetation.…”

Section: Introductionmentioning

confidence: 99%

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Pixel-based unique phenological feature composite method: tackle the challenges of Spartina alterniflora identification and salt marsh classification in mixed vegetations area

Dai

Luo

Chen

et al. 2023

J. Appl. Rem. Sens.

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Coastal salt marshes are valuable wetland ecosystems, and obtaining accurate information on their spatial and temporal distribution is crucial. However, due to the strong spectral similarity among various types of salt marshes, distinguishing them is difficult, especially in areas with mixed salt marsh growth. In this study, we developed a pixel-based unique phenological feature composite method (PUpf-CM). First, we identified a unique phenological period for each type of salt marsh by analyzing the normalized difference vegetation index time-series of Spartina alterniflora (S. alterniflora) and native salt marshes [Suaeda salsa (S. salsa), Phragmites australis (P. australis), and Imperata cylindrica (I. cylindrica)] in Yancheng National Nature Reserve, Jiangsu Province, China. Then, we generated a composite image for each unique phenological period, maximizing the spectral separability between the corresponding salt marsh and background species. Second, we used the composite images obtained at the unique phenological period of S. alterniflora as input to the random forest classifier, achieving high precision identification of S. alterniflora. Compared with the previously developed pixel-based PUpf-CM, the overall accuracy (OA) of PUpf-CM was 98.26% to 99.42%, and the Kappa was 0.940 to 0.975, indicating an improvement of 0.87% to 4.94% and 0.031 to 0.179, respectively. Finally, we tested the possibility of applying PUpf-CM to salt marsh classification by stacking four composite images obtained at different unique phenological periods. We found that the maximum spectral separability was achieved for the combination of four unique phenological periods, and the OA and Kappa of the PUpf-CM-based salt marsh classification reached 97.54% and 0.969, respectively.

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Section: Phenological Parameters and Unique Phenology Periodssupporting

confidence: 90%

Section: Ndvi Time-seriesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pixel-based unique phenological feature composite method: tackle the challenges of Spartina alterniflora identification and salt marsh classification in mixed vegetations area

Dai

Luo

Chen

et al. 2023

J. Appl. Rem. Sens.

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“…Spartina alterniflora has been extensively classified and mapped using satellite remote sensing technology in recent years. Several researchers have utilized freely available satellite images, including Landsat images, for this purpose, as demonstrated in studies conducted by Mao et al [ 40 ], Wang et al [ 41 ], and Zeng et al [ 42 ]. Figure 1 shows a spatial spread of SA in China.…”

Section: Spatiotemporal Distribution Of Spartina Alterniflo...mentioning

confidence: 99%

Impact of Spartina alterniflora Invasion in Coastal Wetlands of China: Boon or Bane?

Zheng,

Javed,

Liu

et al. 2023

Biology

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Invasive plants, like Spartina alterniflora (SA), have a competitive advantage over native flora due to their rapid utilization of vital soil nutrients. This results in the depletion of resources for native plant species, significantly impacting ecosystem diversity and stability. This comprehensive review addresses several key aspects related to SA’s spread and spatial distribution in China’s wetlands. The rapid expansion of Spartina alterniflora is attributed to its high reproductive ability, adaptability to environmental factors like elevated salinity, and ability to disperse its seeds via tides. Spartina alterniflora mainly were found in Zhejiang, Jiangsu, Fujian, and Shanghai provinces, accounting for more than 90% of China’s total Spartina alterniflora area. Spartina alterniflora rapid growth results in displacement of native species and loss of vital microbial, plant, and animal diversity. Some studies reported that Spartina alterniflora increases carbon storage, while others argue that it weakens this function. The impact of Spartina alterniflora on organic and inorganic carbon requires further research for better understanding dynamics of carbon in coastal wetlands. The controlled growth of Spartina alterniflora can be beneficial in many aspects of the coastal wetlands’ ecosystem. In China, various methods have been employed to control the invasion of SA. Physical control, such as removing the plants and converting them into fertilizer or bioenergy, has been commonly used but has limitations like air pollution and the potential for re-invasion. Chemical herbicides like Imazapyr and Haloxyfop-R-methyl have effectively controlled and prevented re-invasion in specific areas, but their potential adverse impacts are still uncertain. Wetland Park construction, aquaculture development, and substituting native or exotic species with mangroves or reed communities have also been successful. It becomes evident that a long-standing and Contextual approach is necessary to effectively manage the advantages and curtail the drawbacks associated with S. alterniflora across China.

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“…Marsh is an important type of wetland ecosystems, which plays a key part in protecting biodiversity, regulating runoff, and changing global climate (Chatterjee et al, 2015 ; Erwin, 2009 ; Hu, Borsje, et al, 2021 ; Junk et al, 2013 ; Lewitus et al, 1998 ; Natuhara, 2013 ; Saderne et al, 2021 ; Sarkar & Borah, 2018 ; Smith & Kirwan, 2021 ). Vegetation is an important component of marsh ecosystem (Marani et al, 2013 ; Shen, Xue, et al, 2019 ; Shen et al, 2021 ; Zeng et al, 2022 ). Marsh vegetation phenology significantly affects energy exchange, ecosystem functions, and carbon cycling (Vázquez‐Lule & Vargas, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal variation in vegetation phenology and its response to climate change in marshes of Sanjiang Plain, China

Liu

Shen

Zhang

et al. 2023

Ecology and Evolution

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A phenology-based vegetation index classification (PVC) algorithm for coastal salt marshes using Landsat 8 images

Cited by 10 publications

References 53 publications

Pixel-based unique phenological feature composite method: tackle the challenges of Spartina alterniflora identification and salt marsh classification in mixed vegetations area

Pixel-based unique phenological feature composite method: tackle the challenges of Spartina alterniflora identification and salt marsh classification in mixed vegetations area

Impact of Spartina alterniflora Invasion in Coastal Wetlands of China: Boon or Bane?

Spatiotemporal variation in vegetation phenology and its response to climate change in marshes of Sanjiang Plain, China

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