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A deep learning-based framework for extracting spatial patterns of farmland shelterbelts in the three-north region of China using Sentinel-2 data.

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Title: A deep learning-based framework for extracting spatial patterns of farmland shelterbelts in the three-north region of China using Sentinel-2 data.
Authors: Ma, Hui1,2, Wu, Bingfang1,3, wubf@aircas.ac.cn, Tian, Fuyou1, tianfy@aircas.ac.cn, Zhao, Hang1,2, Li, Yifan1,4, Li, Mengxiao1,2, Zhang, Miao1,2, Wu, Hantian5, Zeng, Hongwei1,2, Zhu, Liang1
Source: Remote Sensing of Environment; Jan2026, Vol. 332, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 189183570
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing+of+Environment%22">Remote Sensing of Environment</searchLink>; Jan2026, Vol. 332, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=189183570
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      – Type: doi
        Value: 10.1016/j.rse.2025.115095
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        Text: English
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      – TitleFull: A deep learning-based framework for extracting spatial patterns of farmland shelterbelts in the three-north region of China using Sentinel-2 data.
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              Text: Jan2026
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              Y: 2026
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              Value: 332
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            – TitleFull: Remote Sensing of Environment
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