LCZ-Generator Training Areas

This dataset contains all training areas (TA) submitted to the LCZ Generator (Demuzere et al. 2021) since 2021-04-14. The LCZ Generator follows a crowdsourcing approach, making fast and easy LCZ-mapping available to the public, while collecting LCZ maps and TAs in a centralized, easy to access, location. The crowdsoucing approach overcomes the limitations of previous approaches where a manual review was mandatory before publication. While this improved the quality of individual LCZ-maps, the number of cities mapped during this period remained low. The LCZ Generator removed the manual review process, allowing for faster collection of LCZ maps and TAs, however, sacrificing some quality since any person can submit to the LCZ Generator without prior training or review.This dataset is based on crowdsourcing, hence LCZs may be mislabelled, polygon shapes may not be perfect etc. also city names may not be correct. Some contributors chose to name their city e.g. "..", "....amsa" etc. also some author names may not be correct. The automated quality control (see table below and section 2.3 in Demuzere et al. 2021) may help filter out some of the incorrect TAs. We intentionally included all available TAs to allow for (the development of) custom filtering.The data was extracted from the LCZ-Generator database taking into account:Whether or not the submitting author agreed to show their name (if not, it is also left blank in this dataset)The license the TA was submitted under (a license change happened with version 2.0.0 of the LCZ Generator)Duplicate geometries were dropped, since multiple (re-)submission may have the same geometries. Only the first submitted version is kept and attributed to the submission_id of the first submission.The data, up to December 2021, was used during creation of the global LCZ Map (Demuzere et al. 2022).Additional TAs were extracted from the WUDAPT Portal and processed using the LCZ-Generator.Note: The data is updated periodically, but not on a fixed schedule.Data DescriptionThe data is provided as GeoPackage (.gkpg) which can be used with most GIS.Column NameDescriptiongeometryThe polygon geometry of the training area (TA) in EPSG:4326submission_idThe ID of the corresponding submission in the LCZ Generatorsubmission_dateThe date and time in UTC the TA was submitted to the LCZ GeneratorcityThe city the TAs are for. Note: This is sometimes incorrect due to users entering incorrect information and the LCZ Generator following a crowdsourcing approach.referenceThe submitting author may have provided (additional) references via this field. This can be a scientific paper or a citation of the original creator of this TAremarksGeneral information: e.g. co-authors, information about the study/framework the TAs were generated forrepresentative_dateThe date the TAs are representative for (i.e. the date the aerial image was taken)firstnameFirst name of the submitting author (if the author did not agree to publish their name, this is left blank and the submission is treated anonymously)lastnameLast name of the submitting author (if the author did not agree to publish their name, this is left blank and the submission is treated anonymously)licenseThe license this specific polygon is licensed under. With version 2.0.0 of the LCZ Generator the license was changed from CC BY-SA to CC BY-NC-SA 4.0cite_asA suggestion how to cite the TA (-set) based on the name, year, and city information. If the author submitted anonymously, this is left blankversionThe version of the LCZ Generator the polygon was submitted to. Detailed information can be found in the ChangelogclassThe LCZ Class the TA-polygon has been labelled (1 - 17)areaThe area of the TA-polygon in km2perimeterThe perimeter of the TA-polygon kmshapeThe shape of the TA-polygon calculated as: (perimeter2) / (4 π · area)verticesThe number of vertices of the TA-polygonqc_step1Whether the TA-polygon passed the automated quality control (QC) step 1: Surface area below 0.04 km2 (too small) or a shape ratio 3 (too complex shape) are flagged. More information about the QC can be found in the FAQ and the corresponding paper Demuzere et al. 2021qc_step2Whether the TA-polygon passed the automated quality control (QC) step 2: Average spectral value of a polygon of LCZ class is considered as an outlier compared to the average spectral values of all other polygons of that class. Note that this is done on a per-submission basis More information about the QC can be found in the FAQ and the corresponding paper Demuzere et al. 2021qc_step3Whether the TA-polygon passed the automated quality control (QC) step 3: Considers all individual pixel values of all polygons in each LCZ class compared to the polygon average approach from QC Step 2. More information about the QC can be found in the FAQ and the corresponding paper Demuzere et al. 2021oaThe overall accuracy of the submission based on Demuzere et al. 2020oauThe overall accuracy for the urban LCZ classes only of the submission based on Demuzere et al. 2020oabuThe overall accuracy of the built versus natural LCZ classes only of the submission based on Demuzere et al. 2020oawA weighted accuracy taking the similarities of LCZs into account based on Demuzere et al. 2020f1_1Class-wise metric F1 for LCZ class 1f1_2Class-wise metric F1 for LCZ class 2f1_3Class-wise metric F1 for LCZ class 3f1_4Class-wise metric F1 for LCZ class 4f1_5Class-wise metric F1 for LCZ class 5f1_6Class-wise metric F1 for LCZ class 6f1_7Class-wise metric F1 for LCZ class 7f1_8Class-wise metric F1 for LCZ class 8f1_9Class-wise metric F1 for LCZ class 9f1_10Class-wise metric F1 for LCZ class 10f1_11Class-wise metric F1 for LCZ class 11f1_12Class-wise metric F1 for LCZ class 12f1_13Class-wise metric F1 for LCZ class 13f1_14Class-wise metric F1 for LCZ class 14f1_15Class-wise metric F1 for LCZ class 15f1_16Class-wise metric F1 for LCZ class 16f1_17Class-wise metric F1 for LCZ class 17AcknowledgementsWe acknowledge all WUDAPT contributors and community members for providing the training areas via the LCZ Generator.