Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series. Millard, K., Kirby, P., Nandlall, S. D., Behnamian, A., Banks, S. N., & Pacini, F. Remote. Sens., 12(15):2465, 2020.
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Paper bibtex @article{journals/remotesensing/MillardKNBBP20,
added-at = {2020-09-05T00:00:00.000+0200},
author = {Millard, Koreen and Kirby, Patrick and Nandlall, Sacha D. and Behnamian, Amir and Banks, Sarah N. and Pacini, Fabrizio},
biburl = {https://www.bibsonomy.org/bibtex/21f0ca4acfb40c465aceb308ebbf5e56e/dblp},
ee = {https://doi.org/10.3390/rs12152465},
interhash = {2d890e90387d6004335d272d536baa9f},
intrahash = {1f0ca4acfb40c465aceb308ebbf5e56e},
journal = {Remote. Sens.},
keywords = {dblp},
number = 15,
pages = 2465,
timestamp = {2020-09-09T11:49:07.000+0200},
title = {Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series.},
url = {http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing12.html#MillardKNBBP20},
volume = 12,
year = 2020
}
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