A framework base on deep neural network (DNN) for land use land cover (LULC) and rice crop classification without using survey data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Atmospheric Science
Link
https://link.springer.com/content/pdf/10.1007/s00382-023-06874-9.pdf
Reference155 articles.
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3. Agovino M, Casaccia M, Ciommi M et al (2019) Agriculture, climate change and sustainability: the case of EU-28. Ecol Indic 105:525–543. https://doi.org/10.1016/J.ECOLIND.2018.04.064
4. Amani M, Kakooei M, Moghimi A et al (2020) Application of Google Earth Engine cloud computing platform, Sentinel imagery, and neural networks for crop mapping in Canada. Remote Sens 12:3561. https://doi.org/10.3390/RS12213561
5. Anwar MR, Liu DL, Macadam I (2012) Kelly G (2012) Adapting agriculture to climate change: a review. Theor Appl Climatol 1131(113):225–245. https://doi.org/10.1007/S00704-012-0780-1
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