Papers and Presentations


The fundamental idea behind WUDAPT and the state of the project are discussed here:

  • Ching, J., Mills, G., Bechtel, B., See, L., Feddema, J., Wang, X., Ren, C., Brousse, O., Martilli, A., Neophytou, M., Mouzourides, P., Stewart, I., Hanna, A., Ng, E., Foley, M., Alexander, P., Aliaga, D., Niyogi, D., Shreevastava, A., Bhalachandran, P., Masson, V., Hidalgo, J., Fung, J., Andrade, M., Baklanov, A., Dai, W., Milcinski, G., Demuzere, M., Brunsell, N., Pesaresi, M., Miao, S., Mu, Q., Chen, F., Theeuwes, N., 2018. WUDAPT: An Urban Weather, Climate, and Environmental Modeling Infrastructure for the Anthropocene. Bull. Amer. Meteor. Soc. 99, 1907–1924.
  • We have compiled a briefing document on WUDAPT that you can download from here.
  • We have also written a small piece in Nature, which is accompanied by an IIASA blog on WUDAPT.
  • The need for WUDAPT for weather, climate and air quality applications is outlined here:
  • Ching, J., Mills, G., Fedema, J., Oleson, K., See, L., Stewart, I., Bechtel, B., Chen, F., Neophytou, M. and Hanna, A. 2014. Facilitating advanced urban canopy modeling for weather, climate and air quality applications. American Meteorological Society Symposium on Urban Environment, 2-7 February 2014, Atlanta Georgia.
  • Jason Ching gave a presentation on WUDAPT at the American Meteorological Society meeting (10-14 January 2016) in New Orleans entitled ‘The World Urban Database and Access Portal Tools, WUDAPT, an international collaborative project for climate relevant physical geography data for the world’s cities’.  The extended abstract can be accessed here.

LCZ mapping (level 0)

The LCZ workflow is presented in this open access paper:

  • Bechtel, B., Alexander, P., Böhner, J., Ching, J., Conrad, O., Feddema, J., Mills, G., See, L. and Stewart, I. 2015. Mapping local climate zones for a worldwide database of form and function of cities. International Journal of Geographic Information, 4(1), 199-219. doi:10.3390/ijgi4010199.

The standard quality assessment and the state of the database are discussed here:

  • Bechtel, B., Alexander, P.J., Beck, C., Böhner, J., Brousse, O., Ching, J., Demuzere, M., Fonte, C., Gál, T., Hidalgo, J., Hoffmann, P., Middel, A., Mills, G., Ren, C., See, L., Sismanidis, P., Verdonck, M.-L., Xu, G., Xu, Y., 2019. Generating WUDAPT Level 0 data – Current status of production and evaluation. Urban Climate 27, 24–45.

Further studies applied the LCZ mapping methodology in different environments and presented alterantive methods:

  • Bechtel, B., See, L., Mills, G., & Foley, M. (2016). Classification of Local Climate Zones Using SAR and Multispectral Data in an Arid Environment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP(99), 1–9.
  • Bechtel, B., Demuzere, M., Sismanidis, P., Fenner, D., Brousse, O., Beck, C.,Van Coillie, F., Conrad, O., Keramitsoglou, I., Middel, A., Mills, G., Niyogi, D., Otto, M., See, L., Verdonck, M.-L., 2017. Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX). Urban Science, 1(2).  
  • Danylo, O., See, L., Bechtel, B., Schepaschenko, D., & Fritz, S. (2016). Contributing to WUDAPT: A Local Climate Zone Classification of Two Cities in Ukraine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP(99), 1–13.
  • Mitraka, Z., Del Frate, F., Chrysoulakis, N., & Gastellu-Etchegorry, J.-P. (2015). Exploiting Earth Observation data products for mapping Local Climate Zones. In Urban Remote Sensing Event (JURSE), 2015 Joint (pp. 1–4). IEEE. Retrieved from
  • Geletič, J., & Lehnert, M. (2016). GIS-based delineation of local climate zones: The case of medium-sized Central European cities. Moravian Geographical Reports, 24(3), 2–12.
  • Kaloustian, N., & Bechtel, B. (2016). Local Climatic Zoning and Urban Heat Island in Beirut. Procedia Engineering, 169, 216–223.
  • Perera, N. G. R., & Emmanuel, R. (2016). A “Local Climate Zone” based approach to urban planning in Colombo, Sri Lanka. Urban Climate. Retrieved from
  • Qiu, C., Schmitt, M., Mou, L., Ghamisi, P., Zhu, X., Qiu, C., Schmitt, M., Mou, L., Ghamisi, P. & Zhu, X.X. (2018). Feature Importance Analysis for Local Climate Zone Classification Using a Residual Convolutional Neural Network with Multi-Source Datasets. Remote Sensing, 10, 1572, 10.3390/rs10101572.
  • REN, C., WANG, R., CAI, M., XU, Y., Zheng, Y., & Ng, E. (2016). The Accuracy of LCZ maps Generated by the World Urban Database and Access Portal Tools (WUDAPT) Method: A Case Study of Hong Kong. Retrieved from [RG]
  • Verdonck, M.-L., Okujeni, A., Van Der Linden, S., Demuzere, M., De Wulf, R. & Van Coillie, F. 2017. Influence of Neighbourhood Information on ‘ Local Climate Zone ’ Mapping in Heterogeneous Cities. Int J Appl Earth Obs Geoinformation 62, 102–13. doi:10.1016/j.jag.2017.05.017
  • Xu, Y., Ren, C., Cai, M., Edward, N. Y. Y., & Wu, T. (2017). Classification of Local Climate Zones Using ASTER and Landsat Data for High-Density Cities. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
  • Yokoya, N., Ghamisi, P., Xia, J., Sukhanov, S., Heremans, R., Tankoyeu, I., Bechtel, B., Saux, B.L., Moser, G. & Tuia, D. (2018). Open Data for Global Multimodal Land Use Classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 1363–1377, 10.1109/JSTARS.2018.2799698.
  • Zhongli, L., & Hanqiu, X. (2016). A study of Urban heat island intensity based on “local climate zones”: A case study in Fuzhou, China. In Earth Observation and Remote Sensing Applications (EORSA), 2016 4th International Workshop on (pp. 250–254). IEEE. Retrieved from

Model applications

Several studies have applied WUDAPT data in different models:

  • Alexander, P. J., Bechtel, B., Chow, W. T. L., Fealy, R., & Mills, G. (2016). Linking urban climate classification with an urban energy and water budget model: Multi-site and multi-seasonal evaluation. Urban Climate, 17, 196–215.
  • Alexander, P. J., Mills, G., & Fealy, R. (2015). Using LCZ data to run an urban energy balance model. Urban Climate, 13, 14–37.
  • Brousse, O., Martilli, A., Foley, M., Mills, G., & Bechtel, B. (2016). WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid. Urban Climate, 17, 116–134.
  • Geletič, J., Lehnert, M., Dobrovolný, P., Žuvela-Aloise, M., (2019). Spatial modelling of summer climate indices based on local climate zones: expected changes in the future climate of Brno, Czech Republic. Climatic Change.
  • Hammerberg, K., Brousse, O., Martilli, A. and Mahdav, A. (2018). Implications of employing detailed urban canopy parameters for mesoscale climate modelling: a comparison between WUDAPT and GIS databases over Vienna, Austria. International Journal of Climatology. doi: 10.1002/joc.5447
  • Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., … van Lipzig, N. P. M. (2016). The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geosci. Model Dev., 9(9), 3027–3054.

Level 1 and 2 data

Methodologies to derive more detailed information on urban morphology:

  • Ching, J., Aliaga, D., Mills, G., Masson, V., See, L., Neophytou, M., et al. (2019). Pathway using WUDAPT’s Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling. Urban Climate, 28, 100459.
  • Xu, Y., Ren, C., Ma, P., Ho, J., Wang, W., et al. (2017). Urban morphology detection and computation for urban climate research. Landscape and Urban Planning, 167, 212-224.


At ICUC9 in Toulouse, we held a session on WUDAPT. Below you will find links to the papers:

  1. Mills, G., Ching, J., See, L., Bechtel, B., Feddema, J., Masson, V., Stewart, I., Neophytou, M., O’Connor, M., Chen, F., Martilli, A., Grimmond, S., Alexander, P., Foley, M., Gal, T., Wang, X., Mitra, C., Pereira, N., Steeneveld, G.-J.  Introduction to the WUDAPT Project [pdf]
  2. Bechtel, B., Foley, M., Mills, G., Ching, J., See, L., Alexander, P., O’Connor, M., Albuquerque, T., de Fatima Andrade, M., Brovelli, M., Das, D., Fonte, C., Petit, G., Hanif, U., Jimenez, J., Lackner, S., Liu, W., Pereira, N., Rosni, N.A., Theeuwes, N., Gal, T. CENSUS of Cities: LCZ Classification of Cities (Level 0): Workflow and Initial Results from Various Cities [pdf]
  3. See, L., Ching, J., Masson, V., Feddema, J., Mills, G., Neophytou, M., Foley, M., O’Connor, M., Perger, C., Duerauer, M., Fritz, S., Bechtel, B. Generating WUDAPT’s Specific Scale-dependent Urban Modeling and Activity Parameters: Collection of Level 1 and Level 2 Data [paper] [presentation]
  4. Feddema, J., Mills, G. and Ching, J. Demonstrating the Added Value of WUDAPT for Urban Climate Modelling [pdf]
  5. Ching, J., Mills, G., See, L., Bechtel, B., Feddema, J., Hanna, A., Milcinski, G., Masson, V., Neophytou, M., Mitra, C., O’Connor, M., Pereira, N., Steeneveld, G.-J., Stewart, I., Wang, X., Alexander, P., Foley, M., Gál, T. The Portal Component, Strategic Perspectives and  Review of Tactical plans for Full Implementation of WUDAPT [paper] [presentation]
  6. Gál, T., Bechtel, B. and Unger, J. Comparison of two different Local Climate Zone mapping methods [paper] [presentation]