Sentinel-1 And Sentinel-2 Data For The Characterisation Of The States Of Continental Surface Over A Semi-Arid Region En Tunisia-Reference-Cited by-同舟云学术

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Sentinel-1 And Sentinel-2 Data For The Characterisation Of The States Of Continental Surface Over A Semi-Arid Region En Tunisia

Published:2020-03 Issue: Volume: Page:
ISSN:
Container-title:2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS)
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Author:

Bousbih Safa,Zribi Mehrez,Lili-Chabaane Zohra,Mougenot Bernard,Pelletier Charlotte,Hajj Mohammad El,Baghdadi Nicolas

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9102710/9105127/09105158.pdf?arnumber=9105158

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Use of Machine Learning and Remote Sensing Data for Land Cover and Moisture Classification;2023 IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI);2023-12-13

2. Sentinel Data and Machine Learning Algorithms for Soil Moisture Land Classification;The 3rd International Electronic Conference on Agronomy;2023-11-13

3. Soil Moisture Inversion in Grassland Ecosystem Using Remote Sensing Considering Different Grazing Intensities and Growing Seasons;Sustainability;2023-04-12

4. Soil Moisture Retrieval From Sentinel-1 and Sentinel-2 Data Using Ensemble Learning Over Vegetated Fields;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023

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