Characteristics of Vegetation Carbon, Nitrogen, and C/N Ratio in a Tamarix chinensis Coastal Wetland of China

2019 ◽  
Vol 47 (9) ◽  
pp. 1800452 ◽  
Author(s):  
Linping Xie ◽  
Baodong Wang ◽  
Ming Xin ◽  
Min Wang ◽  
Xiuping He ◽  
...  
Keyword(s):  
Coastal Wetland ◽  
Tamarix Chinensis ◽  
Vegetation Carbon

Leaf carbon, nitrogen and phosphorus stoichiometry of Tamarix chinensis Lour. in the Laizhou Bay coastal wetland, China

2015 ◽  
Vol 76 ◽  
pp. 57-65 ◽  
Author(s):  
Qiangqiang Rong ◽  
Jingtao Liu ◽  
Yanpeng Cai ◽  
Zhaohua Lu ◽  
Zhenzhen Zhao ◽  
...  
Keyword(s):  
Coastal Wetland ◽  
Laizhou Bay ◽  
Nitrogen And Phosphorus ◽  
Tamarix Chinensis

“Fertile island” effects of Tamarix chinensis Lour. on soil N and P stoichiometry in the coastal wetland of Laizhou Bay, China

2015 ◽  
Vol 16 (3) ◽  
pp. 864-877 ◽  
Author(s):  
Qiangqiang Rong ◽  
Jingtao Liu ◽  
Yanpeng Cai ◽  
Zhaohua Lu ◽  
Zhenzhen Zhao ◽  
...  
Keyword(s):  
Coastal Wetland ◽  
Laizhou Bay ◽  
Soil N ◽  
Tamarix Chinensis ◽  
Fertile Island

DISTRIBUTION AND ACCUMULATION OF ARSENIC，CADMIUM AND MERCURY IN COASTAL WETLAND SEDIMENT OF NORTHERN BEIBU GULF

2013 ◽  
Vol 33 (3) ◽  
pp. 15 ◽  
Author(s):  
Huayang GAN ◽  
Kai LIANG ◽  
Jinqing LIN ◽  
Zhichang ZHENG ◽  
Zhangcun YAN
Keyword(s):  
Coastal Wetland ◽  
Beibu Gulf ◽  
Wetland Sediment

scholarly journals Consistent Long-Term Monthly Coastal Wetland Vegetation Monitoring Using a Virtual Satellite Constellation

2021 ◽  
Vol 13 (3) ◽  
pp. 438
Author(s):  
Subrina Tahsin ◽  
Stephen C. Medeiros ◽  
Arvind Singh
Keyword(s):  
Vegetation Index ◽  
Coastal Wetland ◽  
Thermal Emission ◽  
Mean Squared Error ◽  
Wetland Vegetation ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Vegetation Monitoring ◽  
Time Space

Long-term monthly coastal wetland vegetation monitoring is the key to quantifying the effects of natural and anthropogenic events, such as severe storms, as well as assessing restoration efforts. Remote sensing data products such as Normalized Difference Vegetation Index (NDVI), alongside emerging data analysis techniques, have enabled broader investigations into their dynamics at monthly to decadal time scales. However, NDVI data suffer from cloud contamination making periods within the time series sparse and often unusable during meteorologically active seasons. This paper proposes a virtual constellation for NDVI consisting of the red and near-infrared bands of Landsat 8 Operational Land Imager, Sentinel-2A Multi-Spectral Instrument, and Advanced Spaceborne Thermal Emission and Reflection Radiometer. The virtual constellation uses time-space-spectrum relationships from 2014 to 2018 and a random forest to produce synthetic NDVI imagery rectified to Landsat 8 format. Over the sample coverage area near Apalachicola, Florida, USA, the synthetic NDVI showed good visual coherence with observed Landsat 8 NDVI. Comparisons between the synthetic and observed NDVI showed Root Mean Squared Error and Coefficient of Determination (R2) values of 0.0020 sr−1 and 0.88, respectively. The results suggest that the virtual constellation was able to mitigate NDVI data loss due to clouds and may have the potential to do the same for other data. The ability to participate in a virtual constellation for a useful end product such as NDVI adds value to existing satellite missions and provides economic justification for future projects.

Protecting People and Property While Restoring Coastal Wetland Habitats

2021 ◽  
Author(s):  
Michael P. Weinstein ◽  
Qizhong Guo ◽  
Colette Santasieri
Keyword(s):  
Coastal Wetland ◽  
Wetland Habitats

scholarly journals Research on the Evolution of Island Coastal Wetland Landscape Pattern

2021 ◽  
Vol 787 (1) ◽  
pp. 012053
Author(s):  
D G Wang ◽  
Y J Dou ◽  
A Q Shi ◽  
J Cheng ◽  
D A Lv
Keyword(s):  
Landscape Pattern ◽  
Coastal Wetland ◽  
Wetland Landscape
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