December 09, 2020 article Open access Learning from urban form to predict building heights PLoS ONE DOI: 10.1371/journal.pone.0242010 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 5 stored of 93 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Leveraging machine learning to generate a unified and complete building height dataset for Germany 2024 Energy and AI article Engineering 3D Modeling in Geospatial Applications Open access 9 citations Planetary impact shifts from fossil fuels to material extraction 2024 preprint Environmental Science Environmental Impact and Sustainability 1 citations Demand-side strategies key for mitigating material impacts of energy transitions 2024 Nature Climate Change article Environmental Science Sustainability and Ecological Systems Analysis Open access 101 citations Leveraging Machine Learning to Generate a Unified and Complete Building Height Dataset for Germany 2024 SSRN Electronic Journal preprint Engineering 3D Modeling in Geospatial Applications Open access 2 citations Leveraging Machine Learning to Generate a Unified and Complete Building Height Dataset for Germany 2023 SSRN Electronic Journal preprint Engineering 3D Modeling in Geospatial Applications Open access 1 citations 5 results References 0