Remote Sensing Based Building Extraction II

Dear Colleagues,

Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. The rapid development of image processing techniques and easily available very-high-resolution multispectral, hyperspectral, LiDAR, and SAR remote sensing images have further boosted the research on building-extraction-related topics. Especially, in recent years, many research institutes and associations have provided open source datasets and annotated training data to meet the demand of advanced artificial intelligence models, which brings new opportunities to develop advanced approaches for building extraction and monitoring.

Hence, there are higher expectations on the efficiency, accuracy, and robustness of building extraction approaches. They should also meet the demand of processing large datasets at city, national, and global scale. Moreover, challenges remain on transform learning and dealing with imperfect training data, as well as unexpected objects in urban scenes such as trees, cloud, and shadows. Along with the building masks, more research arises to generate LoD2/3 building models from remote sensing data automatically.

The previous Special Issue ‘Remote Sensing based Building Extraction’ was a great success. This Special Issue aims to investigate the cutting-edge methodology and applications related to one or more of the following topics,

• Advanced AI models for building detection and extraction;
• Semantic remote sensing image segmentation;
• 2D/3D change detection;
• Disaster monitoring;
• Rooftop modelling from remotely sensed data;
• 3D point cloud segmentation;
• Building boundary extraction and vectorization;
• Large scale urban growth monitoring;
• Weakly supervised urban classification;
• Time-series remote sensing data analysis;
• Roof-top modelling;
• Urban object (vehicle, road, etc.) detection;
• Multi-sensor, multi-resolution, and multi-modality data fusion;
• Climate adaptation of smart cities;
• Sustainable development.

Dr. Jiaojiao Tian
Prof. Dr. Qin Yan
Dr. Mohammad Awrangjeb
Dr. Beril Kallfelz-Sirmacek
Dr. Nusret Demir
Guest Editors

Manuscript Submission Information

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