66 citations as recorded by crossref.

1. Mapping three decades of urban growth in China: a 30 m annual building height dataset (1990–2019) Y. Zhang et al. https://doi.org/10.5194/essd-18-5329-2026
2. Seeing cities in depth: subsurface urban expansion and the case for volumetric monitoring and accountability A. Gil https://doi.org/10.3389/frsc.2026.1878583
3. Surface Urban Heat Island Variability in Cosenza, Southern Italy: The Roles of Urban Morphology, Extreme-Temperature Conditions, and Local Wind Conditions A. Esposito et al. https://doi.org/10.3390/land15091672
4. Who adopts where and when? Electric vehicle diffusion with building-level localization in Germany M. Raab et al. https://doi.org/10.1016/j.adapen.2026.100313
5. A global view of urban land subsidence and its changing trajectories L. Wang et al. https://doi.org/10.1038/s44284-026-00527-8
6. Development and validation of the CanHS: The Canada housing stock datasets for buildings and postal codes L. Minaker et al. https://doi.org/10.1016/j.ubtr.2026.100048
7. Cooler Taxiways and Shoulders: Potential Improvements in On-the-Ground Aircraft Performance H. Taha https://doi.org/10.3390/cli14080157
8. SSDFNet: A State Space Guided Network for Multimodal Building Extraction and Solar Modeling Y. Tan et al. https://doi.org/10.1109/JSTARS.2026.3689074
9. Global Flood Vulnerability Model: Building-Level Assessment Using Multi-Source Remote Sensing S. Olagunju et al. https://doi.org/10.3390/rs18091425
10. Seismic fragility assessment of historic masonry façades: integrating micro-CT material characterization and large-scale vulnerability modeling J. Calderón-Fuentes et al. https://doi.org/10.1016/j.soildyn.2026.110783
11. Land cover classification of Sentinel-1 images at subpixel level using deep learning U. Habiba et al. https://doi.org/10.1080/2150704X.2026.2661869
12. SCS-Net: A Semantic-Contour Synergy Network for Precise Building Delineation From High-Resolution Remote Sensing Imagery T. Zhang et al. https://doi.org/10.1109/JSTARS.2026.3687175
13. Convolution neural network-based estimation of high-resolution urban canopy parameters for urban climate modelling K. Gupta et al. https://doi.org/10.1016/j.uclim.2026.103098
14. Building Detection Under Forest Canopy Using Physically Interpretable SAR Features and Hybrid Machine Learning Across Multiple Forest Biomes D. Nazyrova et al. https://doi.org/10.3390/info17080759
15. A multi-domain scoring framework for solar accessibility at the neighborhood scale M. Formolli et al. https://doi.org/10.1016/j.buildenv.2026.115300
16. A survival guide for assessing global fire risks to natural and human systems C. Steinmann et al. https://doi.org/10.1016/j.ijdrr.2026.106140
17. Groundwater and geothermal archetypes in Berlin, Germany M. Hajizadeh Javaran et al. https://doi.org/10.1186/s40517-026-00375-8
18. Enhancing Urban and Peri-Urban Zoning Using Spatially Constrained Clustering: Evidence from the Jakarta–Bandung Mega-Urban Region N. Rahma et al. https://doi.org/10.3390/land15040534
19. Urban Oases or Heat Islands? Precipitation, Land Cover, and Soil Texture as Factors Associated with Surface Thermal Contrasts in Brazilian Semiarid Cities A. do Amaral & A. de Andrade https://doi.org/10.1007/s41748-026-01298-x
20. A temporally harmonised gridded building-stock dataset for the Global South, 2016-2023 W. Zhang et al. https://doi.org/10.12688/gatesopenres.16394.1
21. Benchmarking Open-Access Building Footprints: A Multi-Dimensional Assessment with High-Fidelity References T. Zhou et al. https://doi.org/10.3390/rs18172895
22. Tiny-Dataset Scale-Consistent Diffusion Framework for Single SAR Image Building Height Estimation Q. Li et al. https://doi.org/10.1109/TGRS.2026.3693803
23. Road and Building Reconstruction from 3D LiDAR Point Clouds: A Scoping Review N. Krishnakumar et al. https://doi.org/10.1007/s11831-026-10580-0
24. Terrain-Aware Optical-SAR Image Registration Under Severe Geometric Distortions Z. Bai et al. https://doi.org/10.1109/JSTARS.2026.3671068
25. Unlocking the carbon reduction potential of building integrated photovoltaics beyond rooftops in an urban core considering inter building shading X. Liu et al. https://doi.org/10.1016/j.jclepro.2026.149752
26. Evaluation of conditional diffusion for cross-sensor land surface temperature downscaling across African cities J. Lee & S. Shamekh https://doi.org/10.1080/01431161.2026.2747322
27. A transferable and interpretable approach to slum mapping using building morphometrics and optical imagery H. Yang et al. https://doi.org/10.1080/15481603.2026.2649308
28. Refined 3D Urban Building Reconstruction from TomoSAR Point Clouds via Multi-Level Geometric Priors and Shadow Analysis W. Liu et al. https://doi.org/10.3390/s26134028
29. Spatial Patterns of Energy-Related Carbon Emissions from Residential Land: A Hybrid Physics–Machine-Learning Study of Shenzhen L. Yao et al. https://doi.org/10.3390/land15050772
30. Slope-aware assessment of particulate matter reduction, avoided mortality, and economic benefits from rooftop greening in Dhaka M. Islam & M. Biswas https://doi.org/10.1016/j.cacint.2026.100483
31. Towards a Comparison of the Semantic Information of Pan-European Open Building Data L. Gabrielli et al. https://doi.org/10.3390/ijgi15060252
32. Remote sensing of building height estimation: A review of data, products, methods, and prospects J. Li et al. https://doi.org/10.1016/j.pce.2026.104843
33. Giant 3D map shows almost every building in the world M. Basu https://doi.org/10.1038/d41586-025-04036-x
34. Beyond local climate zones: Continuous morphology archetypes for heat mitigation across 66 cities S. Emekci & H. Emekci https://doi.org/10.1016/j.scs.2026.107814
35. GLIDE-SOL: a GPU-accelerated global lightweight infrastructure for diagnostic environmental modeling with SOLWEIG A. Zonato et al. https://doi.org/10.5194/gmd-19-7389-2026
36. High Spatial Resolution Building Characteristics for the Global South: Insights from the Google Open Buildings Temporal Dataset (2016-2023) R. Priyatikanto et al. https://doi.org/10.12688/gatesopenres.16386.1
37. Estimating the causal effects of landscape interventions on urban thermal environments using generalized random forests Q. Wang et al. https://doi.org/10.1016/j.scs.2026.107809
38. Satellite earth observation for recovery from hydrometeorological hazards H. Friedrich et al. https://doi.org/10.1016/j.wasec.2026.100205
39. An Innovative Approach to the Study of Building Stock Through Benchmark BIG Geodata Mining and Automated LiDAR Roof Reconstruction in Urban Areas: A Case Study from Slovakia M. Bindzarova Gergelova & M. Zelenakova https://doi.org/10.3390/land15101806
40. Auto-modelling for rooftop photovoltaic power estimation I. Cheng et al. https://doi.org/10.1016/j.scs.2026.108018
41. Quantifying uncertainty in food waste across an urban area: The role of industrial, commercial, and institutional sectors X. Ni et al. https://doi.org/10.1016/j.wasman.2026.115751
42. Morphology-guided cross-task coupling for joint building height and footprint estimation J. Han et al. https://doi.org/10.1016/j.srs.2026.100474
43. Multi-Scale LiDAR Analysis of Urban Vegetation, Built Morphology, and Population Density in Zagreb L. Rumora et al. https://doi.org/10.3390/rs18111715
44. Toward cooler cities by larger homogeneous functional clusters X. Zhang et al. https://doi.org/10.1073/pnas.2617717123
45. Machine learning for urban wind simulation: A comprehensive review I. Karadag et al. https://doi.org/10.1016/j.scs.2026.107614
46. Filtering GEDI footprints based on combined spatial-spectral characteristics for individual building height mapping in 12 major global cities X. Ma et al. https://doi.org/10.1016/j.jag.2026.105566
47. Technical to deployable potential of rooftop solar photovoltaics M. Shi et al. https://doi.org/10.1038/s44359-026-00179-w
48. A high-resolution framework for urban pluvial flood risk mapping A. Vogelbacher et al. https://doi.org/10.5194/nhess-26-2765-2026
49. How can land development intensity and land use benefit be coordinated in high-speed railway station areas? Evidence from 1570 station areas in China Y. Hao & Z. Shen https://doi.org/10.1016/j.cities.2026.107465
50. When do three-dimensional tree metrics improve pedestrian thermal-environment prediction? Evidence from Shanghai and Singapore S. Jia et al. https://doi.org/10.1016/j.buildenv.2026.115479
51. Large-Scale Polygonal Building Mapping From 3–5 m Medium-Resolution Satellite Imagery F. Zhang & X. Zhu https://doi.org/10.1109/TGRS.2026.3719935
52. Building Footprint Has a Stronger Land Surface Temperature Signal than Building Height across Global Cities J. Hu et al. https://doi.org/10.1021/acs.est.6c09652
53. Munich CO2 emission inventory for sectors public power and commercial and residential combustion for the years 2019–2024 P. Aigner et al. https://doi.org/10.1016/j.aeaoa.2026.100498
54. Modelling spatio-temporal distribution of urban population - A high-resolution model for German cities P. Priesmeier et al. https://doi.org/10.1016/j.compenvurbsys.2026.102419
55. Mapping Brightness Temperature and Urban Heat Islands at a City Scale in Egypt Using 3D Radiative Transfer Modeling and UAV Imagery M. Fahmy et al. https://doi.org/10.3390/su182010344
56. Identifying local climate zones in two U.S. Midwestern cities: a comparison of methods D. Habeeb et al. https://doi.org/10.1007/s43762-026-00261-w
57. Mapping parcel-level Essential Urban Land Use Categories across global cities (EULUC-Globe) B. Chen et al. https://doi.org/10.1016/j.scib.2026.06.053
58. SAR-based individual-building damage identification and large-scale earthquake damage prediction H. Liu et al. https://doi.org/10.1016/j.jag.2026.105260
59. Graph-driven urban structure analysis: Typology inference and performance linkage from VHR imagery Y. Guo et al. https://doi.org/10.1016/j.scs.2026.107527
60. Enabling Circular Reuse of Sandwich Panels Through UAV Inspection, Deep Learning, and BIM-Based Material Passports R. Garcia et al. https://doi.org/10.3390/su18052454
61. LUCIDiT: A Lean Urban Comfort Intelligent Digital Twin for Quick Mean Radiant Temperature Assessment M. Baia et al. https://doi.org/10.3390/atmos17030305
62. Evaluating the suitability of the GlobalBuildingAtlas for digital urban infrastructure analysis in India G. Dandabathula et al. https://doi.org/10.1088/2634-4505/ae7f49
63. A pixel-based integrated multi-hazard coastal vulnerability framework for the Eastern and Southern Coasts of Peninsular Malaysia S. Khurram et al. https://doi.org/10.1016/j.ocecoaman.2026.108329
64. Enhancing Monocular Building Height Estimation via Weak Supervision From Imperfect Labels S. Chen et al. https://doi.org/10.1109/JSTARS.2026.3688751
65. CUBE: An open-source calculator for urban building energy enabling city-scale modeling and batch simulation F. Xu et al. https://doi.org/10.1016/j.enbuild.2026.117969
66. Multihazard Disaster Damage Classification for Buildings in Optical Satellite Images M. Zhang & Z. Chen https://doi.org/10.1061/AOMJAH.AOENG-0077