Remote Sensing and Deep Learning Techniques for Impact Assessment of Shaheen Cyclone on Vegetation Cover at Al Batinah Governorate of Oman

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Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings of Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV Conference, Berlin, Germany
Publication status	Published - 2022

Cite this

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

@inproceedings{977802f4203d41f3b60e3412c35a4a52,

title = "Remote Sensing and Deep Learning Techniques for Impact Assessment of Shaheen Cyclone on Vegetation Cover at Al Batinah Governorate of Oman",

author = "Yaseen Al-Mulla and K. Parimi and {M. Bait-Suwailam}, Mohammed",

year = "2022",

language = "English",

booktitle = "Proceedings of Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV Conference, Berlin, Germany",

}

TY - GEN

T1 - Remote Sensing and Deep Learning Techniques for Impact Assessment of Shaheen Cyclone on Vegetation Cover at Al Batinah Governorate of Oman

AU - Al-Mulla, Yaseen

AU - Parimi, K.

AU - M. Bait-Suwailam, Mohammed

PY - 2022

Y1 - 2022

M3 - Conference contribution

BT - Proceedings of Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV Conference, Berlin, Germany

ER -