English(EN) Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset

新框架融合SAR和光学数据，实现抗云土地覆盖制图

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-16 09:25

研究人员开发了CloudLULC-Net，一个新颖的土地利用和土地覆盖制图框架，该框架有效融合了合成孔径雷达（SAR）和光学遥感数据。该方法旨在克服光学影像常被云层和阴影遮挡的局限性。该框架采用了抑制不可靠光学信号并自适应聚合SAR和光学信息的技术，为LULC预测创建统一表示。为支持这项工作，创建了一个名为CloudLULC-Set的新基准数据集，其中包含超过40,000个SAR-光学-标签三元组。 AI

影响这项研究为在多云易受影响的地区进行土地覆盖制图提供了一种更稳健的方法，有望改善环境监测和资源管理。

排序理由该集群描述了在arXiv上发表的一个新颖框架和基准数据集，属于研究类别。

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报道来源 [2]

arXiv cs.CV TIER_1 English(EN) · Jiangong Xu, Weibao Xue, Xiaoyu Yu, Jun Pan, Xinlian Lianga, Mi Wang · 2026-06-17 04:00

Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset

arXiv:2606.17713v1 Announce Type: new Abstract: Optical remote sensing imagery is frequently degraded by cloud and cloud-shadow contamination, which limits its reliability for near-real-time land use and land cover (LULC) mapping. Although synthetic aperture radar (SAR) can provi…
arXiv cs.CV TIER_1 English(EN) · Mi Wang · 2026-06-16 09:25

Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset

Optical remote sensing imagery is frequently degraded by cloud and cloud-shadow contamination, which limits its reliability for near-real-time land use and land cover (LULC) mapping. Although synthetic aperture radar (SAR) can provide cloud-penetrating structural information, exi…

报道来源 [2]

Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset

Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset

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