Terms of Service
All data are distributed under the
CC BY-SA 4.0 license. In particular, permission is hereby granted, free
of charge, to any person obtaining a copy of this data and associated
documentation files, to copy and redistribute the material in any medium or
format, and to remix, transform, and build upon the material for any purpose,
even commercially, all subject to the following:
Understand that these data are created by crowdsourcing and machine learning
and will - by design - contain errors. It comes as is without any warranty.
We do not guarantee the quality and reliability of this dataset and assume
no responsibility whatsoever for any direct or indirect damage and loss
caused by use of this dataset or damages for users due to changing, deleting
or terminating the provision of this dataset.
The provided copyright and permission notice shall be included in all copies
or substantial portions of the data. If you remix, transform, or build upon
the material, you must distribute your contributions under the same license
as the original.
You must give appropriate credit, provide a link to the license, and indicate
if changes were made. You may do so in any reasonable manner, but not in any
way that suggests the licensor endorses you or your use.
The authors are acknowledged appropriately and changes must be indicated.
The persons referred to as authors developed the original training dataset.
Please use the following citation when using the LCZ Generator:
In case you use training area data of one or more cities, we suggest to add the following statement to the acknowledgements:
We acknowledge all WUDAPT contributors for providing the training areas for our city/cities of interest.
Alternatively, you can also explicitly cite this training data by using the following reference:
All required Local Climate Zone context and in-depth methodological
information is provided in the following papers. Please cite where
Stewart, I. D., & Oke, T. R. (2012). Local Climate Zones for Urban
Temperature Studies. Bulletin of the American Meteorological Society,
Bechtel, B., & Daneke, C. (2012). Classification of local climate zones
based on multiple earth observation data. IEEE Journal of Selected Topics in
Applied Earth Observations and Remote Sensing, 5(4), 1191–1202.
Bechtel, B., Alexander, P., Böhner, J., Ching, J., Conrad, O., Feddema, J.,
… Stewart, I. (2015). Mapping Local Climate Zones for a Worldwide Database
of the Form and Function of Cities. ISPRS International Journal of
Geo-Information, 4(1), 199–219.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore,
R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for
everyone. Remote sensing of Environment, 202, 18-27.
Bechtel, B., Demuzere, M., Sismanidis, P., Fenner, D., Brousse, O., Beck,
C., … Verdonck, M.-L. (2017). Quality of Crowdsourced Data on Urban
Morphology—The Human Influence Experiment (HUMINEX). Urban Science, 1(2),
Ching, J., Mills, G., Bechtel, B., See, L., Feddema, J., Wang, X., …
Theeuwes, N. (2018). WUDAPT: An Urban Weather, Climate, and Environmental
Modeling Infrastructure for the Anthropocene. Bulletin of the American
Meteorological Society, 99(9), 1907–1924.
Bechtel, B., Alexander, P. J., Beck, C., Böhner, J., Brousse, O., Ching, J.,
… Xu, Y. (2019). Generating WUDAPT Level 0 data – Current status of
production and evaluation. Urban Climate, 27, 24–45.
Demuzere, M., Bechtel, B., & Mills, G. (2019). Global transferability of
local climate zone models. Urban Climate, 27, 46–63.
Demuzere, M., Bechtel, B., Middel, A., & Mills, G. (2019). Mapping Europe
into local climate zones. PLOS ONE, 14(4), e0214474.
Bechtel, B., Demuzere, M., & Stewart, I. D. (2020). A Weighted Accuracy
Measure for Land Cover Mapping: Comment on Johnson et al. Local Climate Zone
(LCZ) Map Accuracy Assessments Should Account for Land Cover Physical
Characteristics that Affect the Local Thermal Environment. Remote Sens.
2019, 11, 2420. Remote Sensing, 12(11), 1769.
Demuzere, M., Hankey, S., Mills, G., Zhang, W., Lu, T., & Bechtel, B.
(2020). Combining expert and crowd-sourced training data to map urban form
and functions for the continental US. Nature Scientific Data.