🌟A collection of papers, datasets, benchmarks, code, and pre-trained weights for Urban Region Representation Learning Models.
- 2024.9.08: Initiate project.
Other names: Urban Region Profiling / Urban Region Embedding / Urban Indicator Prediction
Abbreviation | Title | Publication | Paper | Modality (Coverage) | Methodology | Downstram Tasks | Code & Weights |
---|---|---|---|---|---|---|---|
HDGE | Region Representation Learning via Mobility Flow | CIKM2017 | Mobility | ||||
ZE-Mob | Representing Urban Functions through Zone Embedding with Human Mobility Patterns | IJCAI2018 | Paper | ||||
CDAE | Learning Urban Community Structures: A Collective Embedding Perspective with Periodic Spatial-temporal Mobility Graphs | ACM TITS2018 | |||||
RegionEncoder | Unsupervised Representation Learning of Spatial Data via Multimodal Embedding | CIKM2019 | Paper | ||||
Beyond Geo-First Law: Learning Spatial Representations via Integrated Autocorrelations and Complementarity | ICDM2019 | ||||||
Tile2Vec | Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data | AAAI2019 | Paper | Satellite img | |||
MV-PN | Efficient Region Embedding with Multi-View Spatial Networks: A Perspective of Locality-Constrained Spatial Autocorrelations | AAAI2019 | Paper | POI + Mobility | |||
Learning to Interpret Satellite Images in Global Scale Using Wikipedia | IJCAI2019 | Paper | |||||
CGAL | Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning | KDD2019 | Paper | ||||
Predicting Economic Development using Geolocated Wikipedia Articles | KDD2019 | Satellite img (nighttime) + Wikipedia articles | |||||
Predicting Economic Growth by Region Embedding:A Multigraph Convolutional Network Approach | CIKM2020 | ||||||
Urban2Vec | Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding | AAAI2020 | Paper | Street-view img + POI (with rating & comments) | |||
GMEL | Learning Geo-Contextual Embeddings for Commuting Flow Prediction | AAAI2020 | Paper | ||||
READ | Lightweight and Robust Representation of Economic Scales from Satellite Imagery | AAAI2020 | Paper | Satellite img | |||
Predicting Economic Growth by Region Embedding: A Multigraph Convolutional Network Approach | CIKM2020 | Paper | |||||
Learning to Score Economic Development from Satellite Imagery | KDD2020 | Paper | |||||
MVURE | Multi-View Joint Graph Representation Learning for Urban Region Embedding | IJCAI2020 | Paper | POI + Mobility + Check-in | |||
Using publicly available satellite imagery and deep learning to understand economic well-being in Africa | Nature Communications 2020 | Satellite img (daytime+nighttime) | |||||
SceneParse | Predicting Livelihood Indicators from Community-Generated Street-Level Imagery | AAAI2021 | Paper | Street-view img | |||
M3G | Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond | AAAI2021 | Paper | ||||
HUGAT | Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network (HUGAT) | arxiv2022 | |||||
CcFTL | A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling | arxiv2022 | |||||
PG-SimCLR | Beyond the First Law of Geography: Learning Representations of Satellite Imagery by Leveraging Point-of-Interests | WWW2022 | Paper | Satellite img + POI | |||
Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery | CIKM2022 | Paper | Satellite img + Street-view img (+ Road Network) | ||||
Region2Vec | Urban Region Profiling via Multi-Graph Representation Learning | CIKM2022 | Paper | POI + Mobility | |||
MGFN | Multi-Graph Fusion Networks for Urban Region Embedding | IJCAI2022 | Paper | Mobility | |||
URGENT | Urban Region Profiling With Spatio-Temporal Graph Neural Networks | IEEE TCSS 2022 | Paper | POI + Mobility | |||
ReMVC | Region Embedding with Intra and Inter-View Contrastive Learning | TKDE2022 | Paper | POI + Mobility | |||
Multi-modal Based Region Representation Learning Considering Mobility Data in Seoul | PCS2023 | ||||||
KnowCL | Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction | WWW2023 | Paper | Satellite img + Knowledge Graph | |||
Geo-Tile2Vec | Geo-Tile2Vec: A Multi-Modal and Multi-Stage Embedding Framework for Urban Analytics | ACM TSAS 2023 | Paper | ||||
Point-to-Region Co-learning for Poverty Mapping at High Resolution Using Satellite Imagery | AAAI2023 | ||||||
HREP | Heterogeneous Region Embedding with Prompt Learning | AAAI2023 | Paper | POI + Mobility | |||
RegionDCL | Urban Region Representation Learning with OpenStreetMap Building Footprints | KDD2023 | Paper | OpenStreetMap (Building Footprint + POI) | |||
Learning Region Similarities via Graph-Based Deep Metric Learning | TKDE2023 | ||||||
Urban visual intelligence: Uncovering hidden city profiles with street view images | PNAS2023 | Paper | Street-view img + POI | ||||
HGI | Learning urban region representations with POIs and hierarchical graph infomax | JPRS2023 | Paper | POI | |||
MMGR | Geographic mapping with unsupervised multi-modal representation learning from VHR images and POIs | JPRS2023 | Paper | Satellite img + POI | |||
ROMER | Region-Wise Attentive Multi-View Representation Learning for Urban Region Embeddings | CIKM2023 | Paper | POI + Mobility + Check-in | |||
HAFusion | Urban Region Representation Learning with Attentive Fusion | ICDE2024 | Paper | POI + Mobility + Land use | |||
ReCP | Urban Region Embedding via Multi-View Contrastive Prediction | AAAI2024 | Paper | POI + Mobility | |||
MuseCL | MuseCL: Predicting Urban Socioeconomic Indicators via Multi-Semantic Contrastive Learning | IJCAI2024 | Paper | Satellite img + Street-view img + POI + Mobility | |||
CGAP | CGAP: Urban Region Representation Learning with Coarsened Graph Attention Pooling | IJCAI2024 | Paper | POI + Mobility | |||
UrbanCLIP | UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web | WWW2024 | Paper | Satellite img + Text (generated) | 1. Carbon 2. GDP 3. Population | ||
UrbanVLP | UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Region Profiling | arxiv2024 | Paper | Satellite img + Street-view img + Text (generated) | |||
CityFM | City Foundation Models for Learning General Purpose Representations from OpenStreetMap | CIKM2024 | Paper | OSM data (Node,Way,Relation)(tags as textual annotations) | |||
MTE | Urban region representation learning with human trajectories: a multi-view approach incorporating transition, spatial, and temporal perspectives | GISR2024 | Trajectory | ||||
ReFound | ReFound: Crafting a Foundation Model for Urban Region Understanding upon Language and Visual Foundations | KDD2024 | Paper | Satellite img + POI | 1. Urban Village Detection 2.Commercial Activeness Prediction 3.Population Prediction | ||
USPM | Profiling Urban Streets: A Semi-Supervised Prediction Model Based on Street View Imagery and Spatial Topology | KDD2024 | Paper | Street-view img + Text (generated) | |||
Multi-level urban street representation with street-view imagery and hybrid semantic graph | JATM2024 | Street-view img + (Social media) Check-in (+ Road Network) | |||||
GeoHG | Learning Geospatial Region Embedding with Heterogeneous Graph | arxiv2024 | |||||
Enhanced Urban Region Profiling with Adversarial Contrastive Learning | arxiv2024 | ||||||
Explainable Hierarchical Urban Representation Learning for Commuting Flow Prediction | arxiv2024 | ||||||
Demo2Vec: Learning Region Embedding with Demographic Information | arxiv2024 |