Building type classification using spatial and landscape attributes derived from LiDAR remote sensing data
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
LiDAR data are often used to retrieve heights or classify buildings at city scale, but its collection is expensive.
“To generate 3D models, LiDAR data are often used to retrieve heights or classify buildings at city scale [339,496], but its collection is expensive.”
From Tackling climate change with machine learning (2023) · cites this paper as [496]
Remote sensing is key to inferring infrastructure data, as satellite data are globally available and largely consistent.
“Remote sensing is key to inferring infrastructure data [79,224,339,496,535,868] as satellite data 19 present a source of information that is globally available and largely consistent worldwide.”
From Tackling climate change with machine learning (2023) · cites this paper as [496]
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538 · see citing works
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421 · see citing works
Cortes, C., & Vapnik, V. N. (1995) · Machine Learning · doi:10.1023/a:1022627411411 · Cited by 34,565 · see citing works
A Practical Guide to Support Vector Classication
Hsu, C., Chang, C.-C., & Lin, C. (2008) · Cited by 5,070 · see citing works
Introductory digital image processing: A remote sensing perspective
Jensen, J. R., & Lulla, K. (1987) · Geocarto International · doi:10.1080/10106048709354084 · Cited by 5,015 · see citing works
Support vector machines in remote sensing: a review
Mountrakis, G., Im, J., & Ogole, C. (2011) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2010.11.001 · Cited by 3,473 · see citing works
Self-citationAssessing the Accuracy of Remotely Sensed Data
Congalton, R. G., & Green, K. (1998) · Mapping sciences series/Mapping science · doi:10.1201/9781420048568 · Cited by 3,434 · see citing works
Assessing the Accuracy of Remotely Sensed Data: Principles and Practices
Foody, G. M. (2010) · The Photogrammetric Record · doi:10.1111/j.1477-9730.2010.00574_2.x · Cited by 2,836 · see citing works
Introductory digital image processing: a remote sensing perspective
Tailor, A. (1986) · Image and Vision Computing · doi:10.1016/0262-8856(86)90052-1 · Cited by 1,967 · see citing works
Foody, G. M. (2004) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.70.5.627 · Cited by 1,065 · see citing works
Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles
Fauvel, M., Benediktsson, J. A., Chanussot, J., & Sveinsson, J. R. (2008) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2008.922034 · Cited by 1,009 · see citing works
Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles
Fauvel, M., Chanussot, J., Benediktsson, J. A., & Sveinsson, J. R. (2007) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2007.4423943 · Cited by 910 · see citing works
Machine Learning Benchmarks and Random Forest Regression
Segal, M. R. (2004) · eScholarship (California Digital Library) · Cited by 684 · see citing works
Classes of kernels for machine learning: a statistics perspective
Genton, M. G. (2002) · doi:10.5555/944790.944815 · Cited by 628 · see citing works
Kong, F., Yin, H., & Nakagoshi, N. (2006) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2006.02.013 · Cited by 545 · see citing works
Constructing support vector machine ensemble
Kim, H., Pang, S., Je, H.-M., Kim, D., & Bang, S. Y. (2003) · Pattern Recognition · doi:10.1016/s0031-3203(03)00175-4 · Cited by 480 · see citing works
Guo, L., Chehata, N., Mallet, C., & Boukir, S. (2010) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2010.08.007 · Cited by 471 · see citing works
Spatial Metrics and Image Texture for Mapping Urban Land Use
Herold, M., Liu, X., & Clarke, K. (2003) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.69.9.991 · Cited by 450 · see citing works
Brandtberg, T. (2003) · Remote Sensing of Environment · doi:10.1016/s0034-4257(03)00008-7 · Cited by 433 · see citing works
Object‐based change detection using correlation image analysis and image segmentation
Im, J., Jensen, J. R., & Tullis, J. A. (2007) · International Journal of Remote Sensing · doi:10.1080/01431160601075582 · Cited by 413 · see citing works
Self-citationAn object‐oriented approach for analysing and characterizing urban landscape at the parcel level
Zhou, W., & Troy, A. R. (2008) · International Journal of Remote Sensing · doi:10.1080/01431160701469065 · Cited by 333 · see citing works
Property values, parks, and crime: A hedonic analysis in Baltimore, MD
Troy, A. R., & Grove, J. M. (2008) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2008.06.005 · Cited by 313 · see citing works
Im, J., & JENSEN, J. (2005) · Remote Sensing of Environment · doi:10.1016/j.rse.2005.09.008 · Cited by 311 · see citing works
Self-citationAutomatic Construction of Building Footprints From Airborne LIDAR Data
Zhang, K., Yan, J., & Chen, S.-C. (2006) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2006.874137 · Cited by 285 · see citing works
Automatic detection of residential buildings using LIDAR data and multispectral imagery
Awrangjeb, M., Ravanbakhsh, M., & Fraser, C. S. (2010) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2010.06.001 · Cited by 276 · see citing works
Building Boundary Tracing and Regularization from Airborne Lidar Point Clouds
Sampath, A., & Shan, J. (2007) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.73.7.805 · Cited by 273 · see citing works
Inglada, J. (2007) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2007.05.011 · Cited by 262 · see citing works
Classification using ASTER data and SVM algorithms;
Zhu, G., & Blumberg, D. G. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(01)00305-4 · Cited by 237 · see citing works
Bouziani, M., Goı̈ta, K., & He, D.-C. (2009) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2009.10.002 · Cited by 225 · see citing works
Exploring full-waveform LiDAR parameters for tree species classification
Heinzel, J., & Koch, B. (2010) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2010.09.010 · Cited by 215 · see citing works
Data Mining Tools See5 and C5.0
Quinlan, J. R. (2004) · Medical Entomology and Zoology · Cited by 204 · see citing works
Dalponte, M., Bruzzone, L., Vescovo, L., et al. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2009.06.013 · Cited by 201 · see citing works
Subpixel Urban Land Cover Estimation
Walton, J. T. (2008) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.74.10.1213 · Cited by 181 · see citing works
Synergistic Use of Lidar and Color Aerial Photography for Mapping Urban Parcel Imperviousness
Hodgson, M. E., Jensen, J. R., Tullis, J. A., et al. (2003) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.69.9.973 · Cited by 179 · see citing works
Self-citationHuang, X., & Zhang, L.-P. (2009) · International Journal of Remote Sensing · doi:10.1080/01431160802546837 · Cited by 154 · see citing works
Li, M., Im, J., & Beier, C. M. (2013) · GIScience & Remote Sensing · doi:10.1080/15481603.2013.819161 · Cited by 143 · see citing works
Self-citationEmpirical analysis of support vector machine ensemble classifiers
Wang, S., Mathew, A., Chen, Y., Xi, L., Ma, L., & Lee, J. (2008) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.07.041 · Cited by 142 · see citing works
Genetic Algorithms for Support Vector Machine Model Selection
Lessmann, S., Stahlbock, R., & Crone, S. F. (2006) · 2022 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2006.247266 · Cited by 122 · see citing works
A Review of Remote Sensing of Forest Biomass and Biofuel: Options for Small-Area Applications
Gleason, C. J., & Im, J. (2011) · GIScience & Remote Sensing · doi:10.2747/1548-1603.48.2.141 · Cited by 117 · see citing works
Self-citationYoo, S., Im, J., & Wagner, J. E. (2012) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2012.06.009 · Cited by 117 · see citing works
Self-citationGuide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data
Berthold, M. R., Borgelt, C., Hppner, F., et al. (2010) · Texts in computer science · doi:10.1007/978-1-84882-260-3 · Cited by 111 · see citing works
Morphology-based Building Detection from Airborne Lidar Data
Meng, X., Wang, L., & Currit, N. (2009) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.75.4.437 · Cited by 107 · see citing works
Im, J., Lu, Z., Rhee, J., et al. (2011) · Remote Sensing of Environment · doi:10.1016/j.rse.2011.06.024 · Cited by 99 · see citing works
Self-citationObject-Based Land Cover Classification Using High-Posting-Density LiDAR Data
Im, J., Jensen, J. R., & Hodgson, M. E. (2008) · GIScience & Remote Sensing · doi:10.2747/1548-1603.45.2.209 · Cited by 98 · see citing works
Self-citationFusion of Lidar and Imagery for Reliable Building Extraction
Lee, D. H., Lee, K. M., & Lee, S. U. (2008) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.74.2.215 · Cited by 94 · see citing works
Alexander, C., Smith‐Voysey, S., Jarvis, C., et al. (2009) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2009.01.009 · Cited by 93 · see citing works
Instability of decision tree classification algorithms
Li, R.-H., & Belford, G. G. (2002) · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/775047.775131 · Cited by 90 · see citing works
Wu, S.-S., Qiu, X., Usery, E. L., et al. (2008) · Annals of the Association of American Geographers · doi:10.1080/00045600802459028 · Cited by 81 · see citing works
The value of water-related amenities in an arid city: The case of the Phoenix metropolitan area
Larson, E. K., & Perrings, C. A. (2012) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2012.10.008 · Cited by 78 · see citing works
Assessing contextual descriptive features for plot-based classification of urban areas
Hermosilla, T., Ruiz, L. Á., Recio, J. A., et al. (2012) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2012.02.008 · Cited by 76 · see citing works
An efficient stochastic approach for building footprint extraction from digital elevation models
Tournaire, O., Brédif, M., Boldo, D., et al. (2010) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2010.02.002 · Cited by 68 · see citing works
Wu, S.-S., Wang, L., & Qiu, X. (2008) · The Professional Geographer · doi:10.1080/00330120701724251 · Cited by 68 · see citing works
Population estimation based on multi-sensor data fusion
Lu, Z., Im, J., Quackenbush, L. J., et al. (2010) · International Journal of Remote Sensing · doi:10.1080/01431161.2010.496801 · Cited by 62 · see citing works
Self-citationAn artificial immune network approach to multi-sensor land use/land cover classification
Gong, B., Im, J., & Mountrakis, G. (2010) · Remote Sensing of Environment · doi:10.1016/j.rse.2010.10.005 · Cited by 62 · see citing works
Self-citationDelineation of climate regions using in-situ and remotely-sensed data for the Carolinas
Rhee, J., Im, J., Carbone, G. J., & Jensen, J. R. (2008) · Remote Sensing of Environment · doi:10.1016/j.rse.2008.03.001 · Cited by 53 · see citing works
Self-citationAn automated binary change detection model using a calibration approach
Im, J., Rhee, J., Jensen, J. R., et al. (2006) · Remote Sensing of Environment · doi:10.1016/j.rse.2006.07.019 · Cited by 52 · see citing works
Self-citationA Volumetric Approach to Population Estimation Using Lidar Remote Sensing
Lu, Z., Im, J., & Quackenbush, L. J. (2011) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.77.11.1145 · Cited by 47 · see citing works
Self-citationÜnsalan, C., & Boyer, K. L. (2004) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2004.835224 · Cited by 45 · see citing works
Urban Land-use Classification Using Variogram-based Analysis with an Aerial Photograph
Wu, S.-S., Xu, B., & Wang, L. (2006) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.72.7.813 · Cited by 35 · see citing works
Güneralp, İ., Filippi, A. M., & Hales, B. U. (2013) · GIScience & Remote Sensing · doi:10.1080/15481603.2013.778560 · Cited by 33 · see citing works
A Fusion Approach for Tree Crown Delineation from Lidar Data
Gleason, C. J., & Im, J. (2012) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.78.7.679 · Cited by 26 · see citing works
Self-citationRule Extraction from Ensemble Methods Using Aggregated Decision Trees
Iqbal, M. R. A. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-34481-7_73 · Cited by 11 · see citing works
Arun, P. V., & Katiyar, S. K. (2013) · GIScience & Remote Sensing · doi:10.1080/15481603.2013.802870 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Rhee, J., & Im, J. (2017) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2017.02.011 · Cited by 245 · see citing works
Self-citationTackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
- Authors
- Lu, Z., Im, J., Rhee, J., & Hodgson, M.
- Affiliations
- SUNY College of Environmental Science and Forestry (US)
- APEC Climate Center (KR)
- University of South Carolina (US)
- Corresponding author
- Im, Jungho
- Venue
- Landscape and Urban Planning
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 130
- Pages
- 134-148
- ISSN
- 0169-2046 (ISSN-L)
- OpenAlex
- W2137825465
- Cited by
- 121
- References
- 64
- Citations by year
- 2026: 9 · 2025: 12 · 2024: 14 · 2023: 9 · 2022: 10 · 2021: 12 · 2020: 10 · 2019: 12 · 2018: 7 · 2017: 14 · 2016: 7 · 2015: 3 · 2014: 2
- FWCI
- 11.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Landscape and Urban Planning (publishedVersion)
- Scholarworks@UNIST (Ulsan National Institute of Science and Technology) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Ocean Engineering › Automated Road and Building Extraction
- Physical Sciences › Engineering › Building and Construction › 3D Modeling in Geospatial Applications
- Physical Sciences › Environmental Science › Environmental Engineering › Remote Sensing and LiDAR Applications
- Keywords
- building type classification, LiDAR, spatial characteristics, landscape attributes, single-family house, non-residential buildings, building geometry, footprint area, urban planning, Denver
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review