MSCDUNet: A Deep Learning Framework for Built-Up Area Change Detection Integrating Multispectral, SAR, and VHR Data
Built-up area change detection (CD) plays an important role in city management, which always uses very high spatial resolution (VHR) remote sensing data to extract refined spatial information. Recently, many CD models based on deep learning with VHR data have been proposed. However, due to the compl...
Main Authors: | Haoyang Li, Fangjie Zhu, Xiaoyu Zheng, Mengxi Liu, Guangzhao Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9791854/ |
Similar Items
-
Integrating bi-temporal VHR optical and long-term SAR images for built-up area change detection
by: Haoyang Li, et al.
Published: (2024-12-01) -
Fine-Grained Abandoned Cropland Mapping in Southern China Using Pixel Attention Contrastive Learning
by: Haoyang Li, et al.
Published: (2024-01-01) -
A Hybrid Approach for Extracting Large-Scale and Accurate Built-Up Areas Using SAR and Multispectral Data
by: Rida Azmi, et al.
Published: (2023-01-01) -
A robust and adaptive spatial-spectral fusion model for PlanetScope and Sentinel-2 imagery
by: Yongquan Zhao, et al.
Published: (2022-12-01) -
Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models
by: Ana-Maria Loghin, et al.
Published: (2022-05-01)