# Automated Road and Building Extraction

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/automated-road-and-building-extraction/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the automatic extraction of road networks from remote sensing images, utilizing techniques such as deep learning, high-resolution imagery, and GPS traces. The research covers areas such as GIS update, aerial images, urban road networks, and map inference, with a particular emphasis on the application of these methods to road extraction. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | t13282 |
| Works | 24 |

## Topic papers all

Showing 15 of 24.

- [Distributed solar photovoltaic array location and extent dataset for remote sensing object identification](https://scholariq.org/papers/distributed-solar-photovoltaic-array-location-and-extent-dataset-for-remote/)
- [MCANet: A joint semantic segmentation framework of optical and SAR images for land use classification](https://scholariq.org/papers/mcanet-a-joint-semantic-segmentation-framework-of-optical-and-sar-images-for/)
- [Geospatial data to images: A deep-learning framework for traffic forecasting](https://scholariq.org/papers/geospatial-data-to-images-a-deep-learning-framework-for-traffic-forecasting/)
- [Automatic Extraction of Power Lines From Aerial Images](https://scholariq.org/papers/automatic-extraction-of-power-lines-from-aerial-images/)
- [Building Extraction from High-Resolution Aerial Imagery Using a Generative Adversarial Network with Spatial and Channel Attention Mechanisms](https://scholariq.org/papers/building-extraction-from-high-resolution-aerial-imagery-using-a-generative/)
- [Data fusion for ITS: A systematic literature review](https://scholariq.org/papers/data-fusion-for-its-a-systematic-literature-review/)
- [Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview](https://scholariq.org/papers/image-processing-techniques-for-analysis-of-satellite-images-for-historical-maps/)
- [Efficient Evaluation of All-Nearest-Neighbor Queries](https://scholariq.org/papers/efficient-evaluation-of-all-nearest-neighbor-queries/)
- [Full Convolutional Neural Network Based on Multi-Scale Feature Fusion for the Class Imbalance Remote Sensing Image Classification](https://scholariq.org/papers/full-convolutional-neural-network-based-on-multi-scale-feature-fusion-for-the/)
- [Segmenting human trajectory data by movement states while addressing signal loss and signal noise](https://scholariq.org/papers/segmenting-human-trajectory-data-by-movement-states-while-addressing-signal-loss/)
- [State-of-the-Art Deep Learning Methods for Objects Detection in Remote Sensing Satellite Images](https://scholariq.org/papers/state-of-the-art-deep-learning-methods-for-objects-detection-in-remote-sensing/)
- [Semiautomatic Road Extraction Framework Based on Shape Features and LS-SVM from High-Resolution Images](https://scholariq.org/papers/semiautomatic-road-extraction-framework-based-on-shape-features-and-ls-svm-from/)
- [An Integrated Object and Machine Learning Approach for Tree Canopy Extraction from UAV Datasets](https://scholariq.org/papers/an-integrated-object-and-machine-learning-approach-for-tree-canopy-extraction/)
- [A Comprehensive Review on Segmentation Techniques for Satellite Images](https://scholariq.org/papers/a-comprehensive-review-on-segmentation-techniques-for-satellite-images/)
- [Unsupervised feature extraction of aerial images for clustering and understanding hazardous road segments](https://scholariq.org/papers/unsupervised-feature-extraction-of-aerial-images-for-clustering-and/)

## Topic primary papers

- [Semiautomatic Road Extraction Framework Based on Shape Features and LS-SVM from High-Resolution Images](https://scholariq.org/papers/semiautomatic-road-extraction-framework-based-on-shape-features-and-ls-svm-from/)
- [Road Extraction from High-Resolution Remotely Sensed Image Based on Improved Ant Colony Optimization Method](https://scholariq.org/papers/road-extraction-from-high-resolution-remotely-sensed-image-based-on-improved-ant/)
- [Target Detection Based on Cascade Network and Densely Connected Network in Remote Sensing Image](https://scholariq.org/papers/target-detection-based-on-cascade-network-and-densely-connected-network-in/)

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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.