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  • Qiu Y, Wu M, Huang Q and Kang Y. (2025). Do You Know Your Neighborhood? Integrating Street View Images and Multi-task Learning for Fine-Grained Multi-Class Neighborhood Wealthiness Perception Prediction. Cities. 10.1016/j.cities.2025.105703. 158. (105703). Online publication date: 1-Mar-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0264275125000034

  • Saeed N, Shafi I, Pervez S, Thompson E, Castilla A, Samad M and Ashraf I. (2025). Intelligent Decision Making for Commodities Price Prediction: Opportunities, Challenges and Future Avenues. Computational Economics. 10.1007/s10614-024-10837-5.

    https://link.springer.com/10.1007/s10614-024-10837-5

  • Zhong C, Zeng S and Zhu H. (2025). Adaptive Multimodal Fusion with Cross-Attention for Robust Scene Segmentation and Urban Economic Analysis. Applied Sciences. 10.3390/app15010438. 15:1. (438).

    https://www.mdpi.com/2076-3417/15/1/438

  • Dey U, Rabbi M, Hamim M and Habib M. (2025). Tailored House Price Prediction Insights for Dhaka and Chittagong City. Innovations in Electrical and Electronics Engineering. 10.1007/978-981-97-9112-5_14. (229-250).

    https://link.springer.com/10.1007/978-981-97-9112-5_14

  • Yao S, Ghorbany S, Sisk M, Hu M and Wang C. (2025). Leveraging Zero-Shot Learning on Street-View Imagery for Built Environment Variable Analysis. Advances in Visual Computing. 10.1007/978-3-031-77389-1_19. (243-254).

    https://link.springer.com/10.1007/978-3-031-77389-1_19

  • Hoang V, Nguyen K, Nguyen M and Blake A. (2024). Unlocking visual data to enhance the accuracy of AI-enabled mass valuation of urban houses: An Australian city case study. Expert Systems with Applications. 10.1016/j.eswa.2024.124784. 255. (124784). Online publication date: 1-Dec-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417424016518

  • Bardhan M, Li F, Browning M, Dong J, Zhang K, Yuan S, İnan H, McAnirlin O, Dagan D, Maynard A, Thurson K, Zhang F, Wang R and Helbich M. (2024). From space to street: A systematic review of the associations between visible greenery and bluespace in street view imagery and mental health. Environmental Research. 10.1016/j.envres.2024.120213. 263. (120213). Online publication date: 1-Dec-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0013935124021200

  • Geerts M, vanden Broucke S and De Weerdt J. (2024). Graph neural networks for house price prediction: do or don’t?. International Journal of Data Science and Analytics. 10.1007/s41060-024-00682-y.

    https://link.springer.com/10.1007/s41060-024-00682-y

  • Adziima A, Wara S, Pratama A and Nasrudin M. (2024). Optimizing Urban Farming Potential Using Google Street View and Machine Learning 2024 IEEE 10th Information Technology International Seminar (ITIS). 10.1109/ITIS64716.2024.10845695. 979-8-3315-2129-5. (68-72).

    https://ieeexplore.ieee.org/document/10845695/

  • Zhu Y, Su F, Han X, Fu Q and Liu J. (2024). Uncovering the drivers of gender inequality in perceptions of safety: An interdisciplinary approach combining street view imagery, socio-economic data and spatial statistical modelling. International Journal of Applied Earth Observation and Geoinformation. 10.1016/j.jag.2024.104230. 134. (104230). Online publication date: 1-Nov-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S1569843224005867

  • Kim J, Kim D and David-John B. (2024). The role of privacy concerns, perceived benefits, and trust in citizens' acceptance of street-view image collection by local planning agencies. Cities. 10.1016/j.cities.2024.105339. 154. (105339). Online publication date: 1-Nov-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0264275124005535

  • Hou C, Zhang F, Kang Y, Gao S, Li Y, Duarte F and Li S. (2024). Transferred Bias Uncovers the Balance Between the Development of Physical and Socioeconomic Environments of Cities. Annals of the American Association of Geographers. 10.1080/24694452.2024.2412173. (1-19).

    https://www.tandfonline.com/doi/full/10.1080/24694452.2024.2412173

  • Cui Y, He Y and Zhu F. (2024). A Edge-Guided Satellite Image Semantic Segmentation Method for Real Estate Appraisal 2024 3rd International Conference on Artificial Intelligence, Internet of Things and Cloud Computing Technology (AIoTC). 10.1109/AIoTC63215.2024.10748329. 979-8-3315-3028-0. (303-308).

    https://ieeexplore.ieee.org/document/10748329/

  • Sun H, Caluyo F, De Ocampo A, Hernandez R and Sarmiento J. (2024). Urban energy management system based on intelligent linker. Salud, Ciencia y Tecnología. 10.56294/saludcyt2024.915. 4.

    https://sct.ageditor.ar/index.php/sct/article/view/915

  • Wang R, Wang Y and Zhang Y. (2024). Optimizing housing price estimation through image segmentation and geographically weighted regression: an empirical study in Nanjing, China. Journal of Housing and the Built Environment. 10.1007/s10901-024-10133-6. 39:3. (1491-1507). Online publication date: 1-Sep-2024.

    https://link.springer.com/10.1007/s10901-024-10133-6

  • Karamanou A, Brimos P, Kalampokis E and Tarabanis K. (2024). Explainable Graph Neural Networks: An Application to Open Statistics Knowledge Graphs for Estimating House Prices. Technologies. 10.3390/technologies12080128. 12:8. (128).

    https://www.mdpi.com/2227-7080/12/8/128

  • San Martin Saldias D, McGlade J, Guzman Aguayo L, Reinke K and Wallace L. (2024). Evaluation and interpretation of landscapes from satellite imagery. GeoJournal. 10.1007/s10708-024-11183-7. 89:4.

    https://link.springer.com/10.1007/s10708-024-11183-7

  • Kucklick J. (2023). HIEF: a holistic interpretability and explainability framework. Journal of Decision Systems. 10.1080/12460125.2023.2207268. 33:3. (335-375). Online publication date: 2-Jul-2024.

    https://www.tandfonline.com/doi/full/10.1080/12460125.2023.2207268

  • Pohl H and Hornbæk K. Integrated Calculators: Moving Calculation into the World. Proceedings of the 2024 ACM Designing Interactive Systems Conference. (343-355).

    https://doi.org/10.1145/3643834.3661523

  • Maya M, Simi H and Pearsall H. (2024). Machine learning to model gentrification: A synthesis of emerging forms. Computers, Environment and Urban Systems. 10.1016/j.compenvurbsys.2024.102119. 111. (102119). Online publication date: 1-Jul-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0198971524000486

  • Liu L and Sevtsuk A. (2024). Clarity or confusion: A review of computer vision street attributes in urban studies and planning. Cities. 10.1016/j.cities.2024.105022. 150. (105022). Online publication date: 1-Jul-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0264275124002361

  • Roychowdhury S, Mazumdar S, Thakker D, Checco A, Lanfranchi V and Goodchild B. (2024). Integrating Virtual Walkthroughs for Subjective Urban Evaluations: A Case Study of Neighbourhoods in Sheffield, England. Land. 10.3390/land13060831. 13:6. (831).

    https://www.mdpi.com/2073-445X/13/6/831

  • Alpherts T, Ghebreab S, Hsu Y and Van Noord N. Perceptive Visual Urban Analytics is Not (Yet) Suitable for Municipalities. Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency. (1341-1354).

    https://doi.org/10.1145/3630106.3658976

  • Despotovic M, Koch D, Thaler S, Stumpe E, Brunauer W and Zeppelzauer M. (2024). Linking repeated subjective judgments and ConvNets for multimodal assessment of the immediate living environment. MethodsX. 10.1016/j.mex.2024.102556. 12. (102556). Online publication date: 1-Jun-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S2215016124000116

  • Guo W, Xu C and Jin S. (2024). Fusion of satellite and street view data for urban traffic accident hotspot identification. International Journal of Applied Earth Observation and Geoinformation. 10.1016/j.jag.2024.103853. 130. (103853). Online publication date: 1-Jun-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S1569843224002073

  • Droj G, Kwartnik-Pruc A and Droj L. (2024). A Comprehensive Overview Regarding the Impact of GIS on Property Valuation. ISPRS International Journal of Geo-Information. 10.3390/ijgi13060175. 13:6. (175).

    https://www.mdpi.com/2220-9964/13/6/175

  • Yan Y, Wen H, Zhong S, Chen W, Chen H, Wen Q, Zimmermann R and Liang Y. UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web. Proceedings of the ACM Web Conference 2024. (4006-4017).

    https://doi.org/10.1145/3589334.3645378

  • Cao Q and Choe Y. (2023). Posthurricane damage assessment using satellite imagery and geolocation features. Risk Analysis. 10.1111/risa.14244. 44:5. (1103-1113). Online publication date: 1-May-2024.

    https://onlinelibrary.wiley.com/doi/10.1111/risa.14244

  • Gosling-Goldsmith J, Antos S, Triveno L, Benjamin A and Wang C. (2024). Aerial-terrestrial data fusion for fine-grained detection of urban clues. Environment and Planning B: Urban Analytics and City Science. 10.1177/23998083241247870.

    https://journals.sagepub.com/doi/10.1177/23998083241247870

  • Kenyon G, Arribas-Bel D and Robinson C. (2024). Extracting Features from Satellite Imagery to Understand the Size and Scale of Housing Sub-Markets in Madrid. Land. 10.3390/land13050575. 13:5. (575).

    https://www.mdpi.com/2073-445X/13/5/575

  • Lee C. (2023). Measuring land lot shapes for property valuation. Data Technologies and Applications. 10.1108/DTA-12-2022-0461. 58:2. (267-279). Online publication date: 15-Apr-2024.

    https://www.emerald.com/insight/content/doi/10.1108/DTA-12-2022-0461/full/html

  • Zhang F, Salazar-Miranda A, Duarte F, Vale L, Hack G, Chen M, Liu Y, Batty M and Ratti C. (2024). Urban Visual Intelligence: Studying Cities with Artificial Intelligence and Street-Level Imagery. Annals of the American Association of Geographers. 10.1080/24694452.2024.2313515. (1-22).

    https://www.tandfonline.com/doi/full/10.1080/24694452.2024.2313515

  • Osunsanmi T, Olawumi T, Smith A, Jaradat S, Aigbavboa C, Aliu J, Oke A, Ajayi O and Oyeyipo O. (2023). Modelling the drivers of data science techniques for real estate professionals in the fourth industrial revolution era. Property Management. 10.1108/PM-05-2022-0034. 42:2. (310-331). Online publication date: 22-Mar-2024.

    https://www.emerald.com/insight/content/doi/10.1108/PM-05-2022-0034/full/html

  • Guerrero O and Law S. (2024). The spatial structure of housing affordability and the impact of public infrastructure. Journal of Simulation. 10.1080/17477778.2024.2325428. (1-15).

    https://www.tandfonline.com/doi/full/10.1080/17477778.2024.2325428

  • Wang G. (2024). Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences. Social Science Computer Review. 42:1. (326-351). Online publication date: 1-Feb-2024.

    https://doi.org/10.1177/08944393231178604

  • Woo A, Han J, Shin H and Lee S. (2024). Economic benefits of urban streetscapes: Analyzing the interrelationships between visual street environments and single-family property values in Seoul, Korea. Applied Geography. 10.1016/j.apgeog.2023.103182. 163. (103182). Online publication date: 1-Feb-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0143622823003132

  • Lee H, Han H, Pettit C, Gao Q and Shi V. (2023). Machine learning approach to residential valuation: a convolutional neural network model for geographic variation. The Annals of Regional Science. 10.1007/s00168-023-01212-7. 72:2. (579-599). Online publication date: 1-Feb-2024.

    https://link.springer.com/10.1007/s00168-023-01212-7

  • Deng H, Zhang W, Yang Y and Nejad E. (2024). Enhancing Residential Real Estate Search with Classification Strategies Using Diffusion and CLIP 2024 IEEE International Conference on Consumer Electronics (ICCE). 10.1109/ICCE59016.2024.10444335. 979-8-3503-2413-6. (1-6).

    https://ieeexplore.ieee.org/document/10444335/

  • Ni Y, Zou M, Dong F and Zhang J. (2024). Paint Price Prediction Using a Triplet Network-Multimodal Network-LSTM Combined Deep Learning Approach. Computer Applications. 10.1007/978-981-99-8761-0_3. (20-32).

    https://link.springer.com/10.1007/978-981-99-8761-0_3

  • Li C, Wang W, Du W and Peng W. (2024). Look Around! A Neighbor Relation Graph Learning Framework for Real Estate Appraisal. Advances in Knowledge Discovery and Data Mining. 10.1007/978-981-97-2238-9_1. (3-16).

    https://link.springer.com/10.1007/978-981-97-2238-9_1

  • Ateig N, Milad A, Almezhghwi K and Benlamma S. (2024). Real Estate Price Prediction Using Machine Learning. International Conference on Smart Environment and Green Technologies – ICSEGT2024. 10.1007/978-3-031-81564-5_25. (201-207).

    https://link.springer.com/10.1007/978-3-031-81564-5_25

  • Charpentier A. (2024). Some Examples of Discrimination. Insurance, Biases, Discrimination and Fairness. 10.1007/978-3-031-49783-4_6. (217-273).

    https://link.springer.com/10.1007/978-3-031-49783-4_6

  • Starzyńska-Grześ M, Roussel R, Jacoby S and Asadipour A. (2023). Computer Vision-based Analysis of Buildings and Built Environments: A Systematic Review of Current Approaches. ACM Computing Surveys. 55:13s. (1-25). Online publication date: 31-Dec-2024.

    https://doi.org/10.1145/3578552

  • Swietek A and Zumwald M. (2023). Visual Capital: Evaluating building-level visual landscape quality at scale. Landscape and Urban Planning. 10.1016/j.landurbplan.2023.104880. 240. (104880). Online publication date: 1-Dec-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0169204623001998

  • Zhan C, Liu Y, Wu Z, Zhao M and Chow T. (2023). A hybrid machine learning framework for forecasting house price. Expert Systems with Applications. 10.1016/j.eswa.2023.120981. 233. (120981). Online publication date: 1-Dec-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417423014835

  • Zhang Y, Wang L, Dong R, Deng H, Fu X, Huang B, Niu Z and Chen F. (2023). Understanding the effects of urban perceptions on housing rent using big data and machine learning. International Journal of Sustainable Development & World Ecology. 10.1080/13504509.2023.2234332. 30:8. (964-980). Online publication date: 17-Nov-2023.

    https://www.tandfonline.com/doi/full/10.1080/13504509.2023.2234332

  • Lee H, Jeong H, Lee B, Lee K and Choo J. ST-RAP: A Spatio-Temporal Framework for Real Estate Appraisal. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. (4053-4058).

    https://doi.org/10.1145/3583780.3615168

  • Zhou Z, Zhong T, Liu M and Ye Y. (2022). Evaluating building color harmoniousness in a historic district intelligently: An algorithm-driven approach using street-view images. Environment and Planning B: Urban Analytics and City Science. 10.1177/23998083221146539. 50:7. (1838-1857). Online publication date: 1-Sep-2023.

    http://journals.sagepub.com/doi/10.1177/23998083221146539

  • Li T, Xi Y, Wang H, Li Y, Tarkoma S and Hui P. (2023). Learning Representations of Satellite Imagery by Leveraging Point-of-Interests. ACM Transactions on Intelligent Systems and Technology. 14:4. (1-32). Online publication date: 31-Aug-2023.

    https://doi.org/10.1145/3589344

  • Hwang J and Naik N. (2023). Systematic Social Observation at Scale: Using Crowdsourcing and Computer Vision to Measure Visible Neighborhood Conditions. Sociological Methodology. 10.1177/00811750231160781. 53:2. (183-216). Online publication date: 1-Aug-2023.

    http://journals.sagepub.com/doi/10.1177/00811750231160781

  • Nukavarapu N, Yang J and Jankowska M. (2023). Unsupervised Deep Learning Approach to Analyze Spatio-Temporal Change in Satellite Imagery IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. 10.1109/IGARSS52108.2023.10282519. 979-8-3503-2010-7. (2496-2499).

    https://ieeexplore.ieee.org/document/10282519/

  • Fang F, Zhang J, Li S, Zheng D, Zeng L and Wan B. (2023). Spatial Extent-Aware Multimodal Fusion Method for Measuring Urban Socioeconomic Status IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. 10.1109/IGARSS52108.2023.10282332. 979-8-3503-2010-7. (6839-6842).

    https://ieeexplore.ieee.org/document/10282332/

  • Suel E, Muller E, Bennett J, Blakely T, Doyle Y, Lynch J, Mackenbach J, Middel A, Mizdrak A, Nathvani R, Brauer M and Ezzati M. (2023). Do poverty and wealth look the same the world over? A comparative study of 12 cities from five high-income countries using street images. EPJ Data Science. 10.1140/epjds/s13688-023-00394-6. 12:1.

    https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-023-00394-6

  • Makkonen J, Latikka R, Kaukonen L, Laine M and Väänänen K. (2022). Advancing residents’ use of shared spaces in Nordic superblocks with intelligent technologies. AI & Society. 38:3. (1167-1184). Online publication date: 1-Jun-2023.

    https://doi.org/10.1007/s00146-022-01604-x

  • Doozandeh P, Cui L and Yu R. (2022). Street surface condition of wealthy and poor neighborhoods: the case of Los Angeles. AI & Society. 38:3. (1185-1192). Online publication date: 1-Jun-2023.

    https://doi.org/10.1007/s00146-022-01603-y

  • Iapaolo F. (2023). The system of autono‑mobility: computer vision and urban complexity—reflections on artificial intelligence at urban scale. AI & Society. 38:3. (1111-1122). Online publication date: 1-Jun-2023.

    https://doi.org/10.1007/s00146-022-01590-0

  • Lehtiö A, Hartikainen M, Ala-Luopa S, Olsson T and Väänänen K. (2022). Understanding citizen perceptions of AI in the smart city. AI & Society. 38:3. (1123-1134). Online publication date: 1-Jun-2023.

    https://doi.org/10.1007/s00146-022-01589-7

  • Suzuki M, Mori J, Maeda T and Ikeda J. (2022). The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images. Journal of Asian Architecture and Building Engineering. 10.1080/13467581.2022.2070492. 22:3. (1110-1125). Online publication date: 4-May-2023.

    https://www.tandfonline.com/doi/full/10.1080/13467581.2022.2070492

  • Wan W and Lindenthal T. (2022). Testing machine learning systems in real estate. Real Estate Economics. 10.1111/1540-6229.12416. 51:3. (754-778). Online publication date: 1-May-2023.

    https://onlinelibrary.wiley.com/doi/10.1111/1540-6229.12416

  • Zhang G, Yi J, Yuan J, Li Y and Jin D. (2023). DAS: Efficient Street View Image Sampling for Urban Prediction. ACM Transactions on Intelligent Systems and Technology. 14:2. (1-20). Online publication date: 30-Apr-2023.

    https://doi.org/10.1145/3576902

  • Liu Y, Zhang X, Ding J, Xi Y and Li Y. Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction. Proceedings of the ACM Web Conference 2023. (4150-4160).

    https://doi.org/10.1145/3543507.3583876

  • Fathalla A, Salah A and Ali A. (2023). A Novel Price Prediction Service for E-Commerce Categorical Data. Mathematics. 10.3390/math11081938. 11:8. (1938).

    https://www.mdpi.com/2227-7390/11/8/1938

  • Kucklick J and Müller O. (2023). Tackling the Accuracy-Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal. ACM Transactions on Management Information Systems. 14:1. (1-24). Online publication date: 31-Mar-2023.

    https://doi.org/10.1145/3567430

  • Yin C, Peng N, Li Y, Shi Y, Yang S and Jia P. (2023). A review on street view observations in support of the sustainable development goals. International Journal of Applied Earth Observation and Geoinformation. 10.1016/j.jag.2023.103205. 117. (103205). Online publication date: 1-Mar-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S1569843223000274

  • Wang G. (2022). The effect of environment on housing prices: Evidence from the Google Street View. Journal of Forecasting. 10.1002/for.2907. 42:2. (288-311). Online publication date: 1-Mar-2023.

    https://onlinelibrary.wiley.com/doi/10.1002/for.2907

  • Karamanou A, Kalampokis E and Tarabanis K. (2023). Integrated statistical indicators from Scottish linked open government data. Data in Brief. 10.1016/j.dib.2022.108779. 46. (108779). Online publication date: 1-Feb-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S2352340922009829

  • Narahara T and Yamasaki T. Subjective Functionality and Comfort Prediction for Apartment Floor Plans and Its Application to Intuitive Online Property Search. IEEE Transactions on Multimedia. 10.1109/TMM.2022.3214072. 25. (6729-6742).

    https://ieeexplore.ieee.org/document/9931648/

  • Liao C, Cao R, Gao Q, Cao J and Luo N. Exploring How Street-Level Images Help Enhance Remote-Sensing-Based Local Climate Zone Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 10.1109/JSTARS.2023.3301792. 16. (7662-7674).

    https://ieeexplore.ieee.org/document/10207711/

  • Martinez J and Mahajan S. Smart Cities and Access to Nature: A Framework for Evaluating Green Recreation Space Accessibility. IEEE Access. 10.1109/ACCESS.2023.3303571. 11. (102014-102024).

    https://ieeexplore.ieee.org/document/10214011/

  • Kitabayashi R, Narahara T and Yamasaki T. Graph Neural Network Based Living Comfort Prediction Using Real Estate Floor Plan Images. Proceedings of the 4th ACM International Conference on Multimedia in Asia. (1-5).

    https://doi.org/10.1145/3551626.3564970

  • Gao Q, Shi V, Pettit C and Han H. (2022). Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia. Land Use Policy. 10.1016/j.landusepol.2022.106409. 123. (106409). Online publication date: 1-Dec-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0264837722004367

  • Hou Y and Biljecki F. (2022). A comprehensive framework for evaluating the quality of street view imagery. International Journal of Applied Earth Observation and Geoinformation. 10.1016/j.jag.2022.103094. 115. (103094). Online publication date: 1-Dec-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S1569843222002825

  • Chen Y, Chau K, Zhang M and Yang L. (2022). Institutional innovations from state-dominated to market-oriented: Price premium differentials of urban redevelopment projects in Shenzhen, China. Cities. 10.1016/j.cities.2022.103993. 131. (103993). Online publication date: 1-Dec-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0264275122004322

  • Liu Y and Liu Y. (2022). Detecting the city-scale spatial pattern of the urban informal sector by using the street view images: A street vendor massive investigation case. Cities. 10.1016/j.cities.2022.103959. 131. (103959). Online publication date: 1-Dec-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0264275122003985

  • Karamanou A, Kalampokis E and Tarabanis K. (2022). Linked Open Government Data to Predict and Explain House Prices. Big Data Research. 30:C. Online publication date: 28-Nov-2022.

    https://doi.org/10.1016/j.bdr.2022.100355

  • Bittencourt L, Parraga O, Ruiz D, Manssour I, Musse S and Barros R. Leveraging Textual Descriptions for House Price Valuation. Intelligent Systems. (355-369).

    https://doi.org/10.1007/978-3-031-21686-2_25

  • Li T, Xin S, Xi Y, Tarkoma S, Hui P and Li Y. Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. (3282-3291).

    https://doi.org/10.1145/3511808.3557153

  • Chen M, Liu Y, Arribas-Bel D and Singleton A. (2022). Assessing the value of user-generated images of urban surroundings for house price estimation. Landscape and Urban Planning. 10.1016/j.landurbplan.2022.104486. 226. (104486). Online publication date: 1-Oct-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0169204622001359

  • Azizi I and Rudnytskyi I. (2022). Improving Real Estate Rental Estimations with Visual Data. Big Data and Cognitive Computing. 10.3390/bdcc6030096. 6:3. (96).

    https://www.mdpi.com/2504-2289/6/3/96

  • Zou S and Wang L. (2022). Mapping individual abandoned houses across cities by integrating VHR remote sensing and street view imagery. International Journal of Applied Earth Observation and Geoinformation. 10.1016/j.jag.2022.103018. 113. (103018). Online publication date: 1-Sep-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S1569843222002060

  • Zhang Y, Zhang F and Chen N. (2022). Migratable urban street scene sensing method based on vision language pre-trained model. International Journal of Applied Earth Observation and Geoinformation. 10.1016/j.jag.2022.102989. 113. (102989). Online publication date: 1-Sep-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S1569843222001807

  • Atiqi R, Dimyati M, Gamal A and Pramayuda R. (2022). Appraisal of Building Price in Urban Area Using Light Detection and Ranging (LiDAR) Data in Depok City. Land. 10.3390/land11081320. 11:8. (1320).

    https://www.mdpi.com/2073-445X/11/8/1320

  • Li Y, Peng L, Wu C and Zhang J. (2022). Street View Imagery (SVI) in the Built Environment: A Theoretical and Systematic Review. Buildings. 10.3390/buildings12081167. 12:8. (1167).

    https://www.mdpi.com/2075-5309/12/8/1167

  • Chen L, Lu Y, Ye Y, Xiao Y and Yang L. (2022). Examining the association between the built environment and pedestrian volume using street view images. Cities. 10.1016/j.cities.2022.103734. 127. (103734). Online publication date: 1-Aug-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0264275122001731

  • Li W and Hsu C. (2022). GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography. ISPRS International Journal of Geo-Information. 10.3390/ijgi11070385. 11:7. (385).

    https://www.mdpi.com/2220-9964/11/7/385

  • Jia J, Zhang X, Huang C and Luan H. (2022). Multiscale analysis of human social sensing of urban appearance and its effects on house price appreciation in Wuhan, China. Sustainable Cities and Society. 10.1016/j.scs.2022.103844. 81. (103844). Online publication date: 1-Jun-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S2210670722001718

  • Wang Z, Yang W, Xiang L, Wang X, Zhao Y, Xiao Y, Liu P, Liu Y, Banu M, Zikanov O and Chen L. (2022). Multi-input convolutional network for ultrafast simulation of field evolvement. Patterns. 10.1016/j.patter.2022.100494. 3:6. (100494). Online publication date: 1-Jun-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S2666389922000794

  • Potrawa T and Tetereva A. (2022). How much is the view from the window worth? Machine learning-driven hedonic pricing model of the real estate market. Journal of Business Research. 10.1016/j.jbusres.2022.01.027. 144. (50-65). Online publication date: 1-May-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S014829632200039X

  • Stevenson M, Mues C and Bravo C. (2022). Deep residential representations: Using unsupervised learning to unlock elevation data for geo-demographic prediction. ISPRS Journal of Photogrammetry and Remote Sensing. 10.1016/j.isprsjprs.2022.03.015. 187. (378-392). Online publication date: 1-May-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0924271622000880

  • Gao G, Bao Z, Cao J, Qin A and Sellis T. (2022). Location-Centered House Price Prediction: A Multi-Task Learning Approach. ACM Transactions on Intelligent Systems and Technology. 13:2. (1-25). Online publication date: 30-Apr-2022.

    https://doi.org/10.1145/3501806

  • Lee C. (2022). FORECASTING SPATIALLY CORRELATED TARGETS: SIMULTANEOUS PREDICTION OF HOUSING MARKET ACTIVITY ACROSS MULTIPLE AREAS. International Journal of Strategic Property Management. 10.3846/ijspm.2022.16786. 26:2. (119-126). Online publication date: 11-Apr-2022.

    https://journals.vilniustech.lt/index.php/IJSPM/article/view/16786

  • Wei C, Fu M, Wang L, Yang H, Tang F and Xiong Y. (2022). The Research Development of Hedonic Price Model-Based Real Estate Appraisal in the Era of Big Data. Land. 10.3390/land11030334. 11:3. (334).

    https://www.mdpi.com/2073-445X/11/3/334

  • Kalfarisi R, Hmosze M and Wu Z. (2022). Detecting and Geolocating City-Scale Soft-Story Buildings by Deep Machine Learning for Urban Seismic Resilience. Natural Hazards Review. 10.1061/(ASCE)NH.1527-6996.0000541. 23:1. Online publication date: 1-Feb-2022.

    https://ascelibrary.org/doi/10.1061/%28ASCE%29NH.1527-6996.0000541

  • Yang Z, Hong Z, Zhou R and Ai H. Graph Convolutional Network-Based Model for Megacity Real Estate Valuation. IEEE Access. 10.1109/ACCESS.2022.3210281. 10. (104811-104828).

    https://ieeexplore.ieee.org/document/9904611/

  • Geerts M, Shaikh K, De Weerdt J and Broucke S. (2022). Predicting the State of a House Using Google Street View. Research Challenges in Information Science. 10.1007/978-3-031-05760-1_46. (703-710).

    https://link.springer.com/10.1007/978-3-031-05760-1_46

  • Roche N and Moore A. (2022). Oracles and Internet of Things in the Internet of Value. Enabling the Internet of Value. 10.1007/978-3-030-78184-2_14. (157-174).

    https://link.springer.com/10.1007/978-3-030-78184-2_14

  • Liao X, Deng M and Huang H. (2021). Analyzing Multiscale Spatial Relationships between the House Price and Visual Environment Factors. Applied Sciences. 10.3390/app12010213. 12:1. (213).

    https://www.mdpi.com/2076-3417/12/1/213

  • Lin R, Ou C, Tseng K, Bowen D, Yung K and Ip W. (2021). The Spatial neural network model with disruptive technology for property appraisal in real estate industry. Technological Forecasting and Social Change. 10.1016/j.techfore.2021.121067. 173. (121067). Online publication date: 1-Dec-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0040162521004996

  • Kagan D, Fuhrmann Alpert G and Fire M. (2021). Automatic large scale detection of red palm weevil infestation using street view images. ISPRS Journal of Photogrammetry and Remote Sensing. 10.1016/j.isprsjprs.2021.10.004. 182. (122-133). Online publication date: 1-Dec-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0924271621002665

  • Biljecki F and Ito K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning. 10.1016/j.landurbplan.2021.104217. 215. (104217). Online publication date: 1-Nov-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0169204621001808

  • Jia J and Zhang X. (2021). A human-scale investigation into economic benefits of urban green and blue infrastructure based on big data and machine learning: A case study of Wuhan. Journal of Cleaner Production. 10.1016/j.jclepro.2021.128321. 316. (128321). Online publication date: 1-Sep-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0959652621025361

  • Zhang C, Wu T, Zhang Y, Zhao B, Wang T, Cui C and Yin Y. (2021). Deep semantic-aware network for zero-shot visual urban perception. International Journal of Machine Learning and Cybernetics. 10.1007/s13042-021-01401-w.

    https://link.springer.com/10.1007/s13042-021-01401-w

  • Zhang W, Liu H, Zha L, Zhu H, Liu J, Dou D and Xiong H. MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. (3937-3947).

    https://doi.org/10.1145/3447548.3467187

  • Suel E, Bhatt S, Brauer M, Flaxman S and Ezzati M. (2021). Multimodal deep learning from satellite and street-level imagery for measuring income, overcrowding, and environmental deprivation in urban areas. Remote Sensing of Environment. 10.1016/j.rse.2021.112339. 257. (112339). Online publication date: 1-May-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0034425721000572

  • Zou S and Wang L. (2021). Detecting individual abandoned houses from google street view: A hierarchical deep learning approach. ISPRS Journal of Photogrammetry and Remote Sensing. 10.1016/j.isprsjprs.2021.03.020. 175. (298-310). Online publication date: 1-May-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0924271621000915

  • Scepanovic S, Joglekar S, Law S and Quercia D. (2021). Jane Jacobs in the Sky. Proceedings of the ACM on Human-Computer Interaction. 5:CSCW1. (1-25). Online publication date: 13-Apr-2021.

    https://doi.org/10.1145/3449257

  • Yao Y, Zhang J, Qian C, Wang Y, Ren S, Yuan Z and Guan Q. (2021). Delineating urban job-housing patterns at a parcel scale with street view imagery. International Journal of Geographical Information Science. 10.1080/13658816.2021.1895170. (1-24).

    https://www.tandfonline.com/doi/full/10.1080/13658816.2021.1895170

  • Kou J, Du J, Fu X, Zhang G, Wang H and Zhang Y. The Effect of Regional Economic Clusters on Housing Price. Databases Theory and Applications. (180-191).

    https://doi.org/10.1007/978-3-030-69377-0_15

  • Fu A, Patil K and Iiyama M. Region Proposal and Regression Network for Fishing Spots Detection From Sea Environment. IEEE Access. 10.1109/ACCESS.2021.3077514. 9. (68366-68375).

    https://ieeexplore.ieee.org/document/9422702/

  • Wang P, Chen C, Su J, Wang T and Huang S. Deep Learning Model for House Price Prediction Using Heterogeneous Data Analysis Along With Joint Self-Attention Mechanism. IEEE Access. 10.1109/ACCESS.2021.3071306. 9. (55244-55259).

    https://ieeexplore.ieee.org/document/9395585/

  • Tozzi J and Guarino F. (2021). Potential Sales Estimates of a New Store. Optimization and Data Science: Trends and Applications. 10.1007/978-3-030-86286-2_2. (15-24).

    https://link.springer.com/10.1007/978-3-030-86286-2_2

  • Naser N, Serte S and Al-Turjman F. (2021). From Traditional House Price Appraisal to Computer Vision-Based: A Survey. Forthcoming Networks and Sustainability in the IoT Era. 10.1007/978-3-030-69431-9_1. (1-10).

    http://link.springer.com/10.1007/978-3-030-69431-9_1

  • Hattori R, Okamoto K and Shibata A. (2020). Visualizing the Importance of Floor-Plan Image Features in Rent-Prediction Models 2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS). 10.1109/SCISISIS50064.2020.9322769. 978-1-7281-9732-6. (1-3).

    https://ieeexplore.ieee.org/document/9322769/

  • Lee C and Park K. (2020). Using photographs and metadata to estimate house prices in South Korea. Data Technologies and Applications. 10.1108/DTA-05-2020-0111. ahead-of-print:ahead-of-print. Online publication date: 24-Nov-2020.

    https://www.emerald.com/insight/content/doi/10.1108/DTA-05-2020-0111/full/html

  • Soares Silva J and de Almeida Filho A. (2020). Performing hierarchical Bayesian regression to assess the best districts for building new residential real estate developments 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 10.1109/SMC42975.2020.9282906. 978-1-7281-8526-2. (2411-2416).

    https://ieeexplore.ieee.org/document/9282906/

  • Ahsan M, E. Alam T, Trafalis T and Huebner P. (2020). Deep MLP-CNN Model Using Mixed-Data to Distinguish between COVID-19 and Non-COVID-19 Patients. Symmetry. 10.3390/sym12091526. 12:9. (1526).

    https://www.mdpi.com/2073-8994/12/9/1526

  • Kim Y, Choi S and Yi M. (2020). Applying Comparable Sales Method to the Automated Estimation of Real Estate Prices. Sustainability. 10.3390/su12145679. 12:14. (5679).

    https://www.mdpi.com/2071-1050/12/14/5679

  • Zech M and Ranalli J. (2020). Predicting PV Areas in Aerial Images with Deep Learning 2020 IEEE 47th Photovoltaic Specialists Conference (PVSC). 10.1109/PVSC45281.2020.9300636. 978-1-7281-6115-0. (0767-0774).

    https://ieeexplore.ieee.org/document/9300636/

  • Saull A, Baum A and Braesemann F. (2020). Can digital technologies speed up real estate transactions?. Journal of Property Investment & Finance. 10.1108/JPIF-09-2019-0131. ahead-of-print:ahead-of-print. Online publication date: 21-May-2020.

    https://www.emerald.com/insight/content/doi/10.1108/JPIF-09-2019-0131/full/html

  • Bai R, Lam J and Li V. Siamese-Like Convolutional Neural Network for Fine-Grained Income Estimation of Developed Economies. IEEE Access. 10.1109/ACCESS.2020.3019239. 8. (162533-162547).

    https://ieeexplore.ieee.org/document/9178284/

  • Takizawa A and Kinugawa H. (2020). Deep learning model to reconstruct 3D cityscapes by generating depth maps from omnidirectional images and its application to visual preference prediction. Design Science. 10.1017/dsj.2020.27. 6.

    https://www.cambridge.org/core/product/identifier/S205347012000027X/type/journal_article

  • Cellmer R and Trojanek R. (2019). Towards Increasing Residential Market Transparency: Mapping Local Housing Prices and Dynamics. ISPRS International Journal of Geo-Information. 10.3390/ijgi9010002. 9:1. (2).

    https://www.mdpi.com/2220-9964/9/1/2

  • Zhang F, Wu L, Zhu D and Liu Y. (2019). Social sensing from street-level imagery: A case study in learning spatio-temporal urban mobility patterns. ISPRS Journal of Photogrammetry and Remote Sensing. 10.1016/j.isprsjprs.2019.04.017. 153. (48-58). Online publication date: 1-Jul-2019.

    https://linkinghub.elsevier.com/retrieve/pii/S0924271619301133

  • Xu Y, Yang Q, Cui C, Shi C, Song G, Han X and Yin Y. (2019). Visual Urban Perception with Deep Semantic-Aware Network. MultiMedia Modeling. 10.1007/978-3-030-05716-9_3. (28-40).

    http://link.springer.com/10.1007/978-3-030-05716-9_3

  • AHMED K, Mohammadi F, Matus M, Shenavarmasouleh F, Pereira L, Zisis I and Amini M. Towards Real-Time House Detection in Aerial Images Using Faster Region-Based Convolutional Neural Network. SSRN Electronic Journal. 10.2139/ssrn.3994191.

    https://www.ssrn.com/abstract=3994191

  • Wan W and Lindenthal T. Towards Accountability in Machine Learning Applications: A System-testing Approach. SSRN Electronic Journal. 10.2139/ssrn.3758451.

    https://www.ssrn.com/abstract=3758451