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.

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.; and Pacini, F. Remote. Sens., 12(15):2465, 2020.

Link

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
}

Downloads: 0