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Coastline Types and Their Spatiotemporal Variations in San Francisco Bay (1980-2020)


SU Qianxin1LI Zhiqiang*1
1 Department of Ocean Technology,School of Electronic and Information Engineering,Guangdong Ocean University,Zhanjiang 524088,China

DOI:10.3974/geodb.2021.04.09.V1

Published:Apr. 2021

Visitors:6290       Data Files Downloaded:55      
Data Downloaded:1265.23 MB      Citations:

Key Words:

San Francisco Bay,USA,coastline change,coastline type,utilization index

Abstract:

The coastline in the San Francisco Bay is the largest bay along the California coast of the United States, located between 121.8°W to 122.5°W and 37.4°N to 38.1°N. The dataset of the coastline types and their spatiotemporal variations in San Francisco Bay (1980-2020) was developed based on Landsat remote sensing images of seven periods from 1979 to 2020, and Google Earth high resolution images. The coastline is defined by the mean high-water line, which is divided into two categories: natural coastline and artificial coastline. The natural coastline is divided into bedrock coastline, gravel coastline and muddy coastline. Artificial coastline is divided into farmland aquaculture coastline, port wharf coastline and other artificial coastline. Furthermore, the intensity of coastline length change, type structure change, and utilization degree index were calculated. The dataset includes the following data from San Francisco Bay from 1980 to 2020: (1) spatial distribution data of coastlines and their types in seven periods (.shp, .kmz); (2) coastline type structure data (.xlsx); (3) coastline length change intensity (.xlsx); (4) coastline utilization index (.xlsx). The dataset is archived in .shp, .kmz and .xlsx data formats, and consists of 64 data files with data size of 49.4 MB (compressed to 23.0 MB in one data file).Browse

Foundation Item:

National Natural Science Foundation of China(41676079); Guangdong Ocean University(Q18307)

Data Citation:

SU Qianxin, LI Zhiqiang*. Coastline Types and Their Spatiotemporal Variations in San Francisco Bay (1980-2020)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2021. https://doi.org/10.3974/geodb.2021.04.09.V1.

SU Qianxin, LI Zhiqiang. Coastline datasets cover the Guangdong-Hong Kong-Macao, Tokyo and San Francisco Bays (1979-2020) [J]. Journal of Global Change Data & Discovery, 2021, 5(2): 148-155. https://doi.org/10.3974/geodp.2021.02.06.

References:

[1] Gao, S. Regional differences in coastal zones and classification of Marine economic potential: a land-sea perspective [J]. Democracy & Science, 2020(1): 29-31.
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     [3] Hou, X. Y., Wu, T., Wang, Y. D., et al. Extraction and accuracy evaluation of multi-temporal coastlines of mainland China since 1940s [J]. Marine Sciences, 2014, 38(11): 66-73. DOI: 10.11759/hykx20131217001.
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     [5] Liu, C., Shi, R. X., Zhang, Y. H., et al. Global multi-scale shoreline dataset of land and sea based on Google Earth remote sensing image(2015) [J/DB/OL]. Digital Journal of Global Change Data Repository, 2019. DOI: 10.3974/geodb.2019.04.13.V1.
     [6] Chen, B. Q., Xiao, X. M., Li, X. P., et al. Spatial distribution data of mangroves in China in 2015 [J/DB/OL]. Digital Journal of Global Change Data Repository, 2017. DOI: 10.3974/geodb.2017.03.06.V1.
     [7] Gao, Z. Q., Liu, X. Y., Ning, J. C., et al. Analysis on changes in coastline and reclamation area and its causes based on 30-year satellite data in China [J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(12): 140-147.
     [8] Liu, X. L., Deng, R. R., Xu, J. H., et al. Spatiotemporal evolution characteristics of coastlines and driving force analysis of the Pearl River estuary in the past 40 years [J]. Journal of Geo-information Science, 2017, 19(10): 1336-1345.
     [9] Xiao, R. Analysis of change and driving force of the coastline of mainland in nearly 35 years [D]. Shanghai: East China Normal University, 2017.
     

Data Product:

ID Data Name Data Size Operation
0Datapaper_SF_Coastline_1980-2020.pdf245.00kbDownLoad
1 SF_Coastline_1980-2020.rar 23556.35KB
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