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	title = {River body extraction from sentinel-{2A}/{B} {MSI} images based on an adaptive multi-scale region growth method},
	journal = {Remote Sensing of Environment},
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	year = {2021},
	month = {mar},
	pages = {112297},
	issn = {00344257},
	doi = {10.1016/j.rse.2021.112297},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0034425721000158},
	author = {Jin, Song and Liu, Yongxue and Fagherazzi, Sergio and Mi, Huan and Qiao, Gang and Xu, Wenxuan and Sun, Chao and Liu, Yongchao and Zhao, Bingxue and Fichot, C{\'e}dric G.}
}
@article {quan_intensity_2020,
	title = {Intensity {Analysis} to communicate land change during three time intervals in two regions of {Quanzhou} {City}, {China}},
	journal = {GIScience \& Remote Sensing},
	volume = {57},
	number = {1},
	year = {2020},
	month = {jan},
	pages = {21{\textendash}36},
	issn = {1548-1603, 1943-7226},
	doi = {10.1080/15481603.2019.1658420},
	url = {https://www.tandfonline.com/doi/full/10.1080/15481603.2019.1658420},
	author = {Quan, Bin and Pontius, Robert Gilmore and Song, Hui}
}
@techreport {PIE469,
	title = {Hurricane Sandy Impacts on Coastal Wetland Resilience},
	year = {2019},
	note = {PI Plum Data},
	pages = {117},
	institution = {USGS},
	keywords = {accretion, LTER-PIE, disturbance, salt marsh, sedimentation, wetlands},
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	doi = {10.3133/ofr20181142},
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	editor = {USGS}
}
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	journal = {GIScience \& Remote Sensing},
	year = {2019},
	note = {PI},
	keywords = {China, GIS, intensity analysis, land change, LTER-PIE, Quanzhou City, regionalization},
	doi = {10.1080/15481603.2019.1658420},
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}
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}
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	keywords = {annual change percentage, China, CLUDD, disturbance, intensity analysis, land change, LTER-PIE, mathematical notation},
	doi = {10.1007/s10980-017-0584-x},
	author = {Pontius, R.G., Jr. and Huang, J. and Jiang, W. and Khallaghi, S. and Lin, Y. and Liu, J. and Quan, B. and Ye, S.}
}
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	note = {PI Plum Data},
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	note = {PI Plum Data},
	pages = {23-38},
	keywords = {carbon, climate change, disturbance, energy, land use, LTER-PIE},
	doi = {10.1525/bio.2012.62.1.7},
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}
