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https://github.com/Lihy256/MSCDUnet


https://github.com/Lihy256/MSCDUnet

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# MSCDUnet: https://ieeexplore.ieee.org/document/9791854

We labeled the first change detection datasets containing VHR, multispectral (Sentinel-2) and SAR (Sentinel-1) all.

The download link is here:

Baidulink:https://pan.baidu.com/s/1-f6U8g0i0x8Tmw00Cvguzw
code:xls8

Google dirve link: https://drive.google.com/file/d/1iFp3jMFYwbk0iP4rN3hCIUwmnNxmDewz/view?usp=sharing

MSBC:

![image](https://user-images.githubusercontent.com/93966845/172432466-46d7be4b-321e-439b-8391-5815b08eb0c5.png)

MSOSCD:

![image](https://user-images.githubusercontent.com/93966845/172000053-c7b7d9a2-bdc5-4f77-8963-1dee9cee40a9.png)

**The structure of SAR and OPT our data are as follows:

SAR has 4 bands in all. The first 2 bands are VV, VH of time 1, and the later 2 bands are VV, VH of time 2.

OPT has 14 bands in all. The first 7 bands are B2,B3,B4,B8,B8A,B11,B12 of time 1, and the later 7 bands are B2,B3,B4,B8,B8A,B11,B12 of time 2.

**We will soon open our code and datasets with selected features

Paper citing: H. Li, F. Zhu, X. Zheng, M. Liu and G. Chen, "MSCDUNet: A Deep Learning Framework for Built-Up Area Change Detection Integrating Multispectral, SAR, and VHR Data," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 5163-5176, 2022, doi: 10.1109/JSTARS.2022.3181155.