# MCANet: A joint semantic segmentation framework of optical and SAR images for land use classification

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/mcanet-a-joint-semantic-segmentation-framework-of-optical-and-sar-images-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Xue Li,Guo Zhang,Hao Cui,Shasha Hou,Shunyao Wang,Xin Li,Yujia Chen,Zhijiang Li,Li Zhang |
| Citations | 267 |
| DOI | 10.1016/j.jag.2021.102638 |
| Fields | Earth and Planetary Sciences,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1016/j.jag.2021.102638 |
| OpenAlex ID | https://openalex.org/W4200556575 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Xue Li](https://scholariq.org/researchers/xue-li/)

## Paper primary topic

- [Remote-Sensing Image Classification](https://scholariq.org/topics/remote-sensing-image-classification/)

## Paper topics

- [Remote-Sensing Image Classification](https://scholariq.org/topics/remote-sensing-image-classification/)
- [Remote Sensing and Land Use](https://scholariq.org/topics/remote-sensing-and-land-use/)
- [Automated Road and Building Extraction](https://scholariq.org/topics/automated-road-and-building-extraction/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.