{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T09:35:46Z","timestamp":1768728946951,"version":"3.49.0"},"reference-count":8,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,5,31]],"date-time":"2020-05-31T00:00:00Z","timestamp":1590883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In multi-class classification tasks such as land cover mapping, the achieved accuracies inherently depend on the complexity of the class typology. More specifically, the more complex the typology of (land cover) classes, the lower the resulting accuracies, since the common measures only consider whether a sample was correctly classified or not. To overcome this, a weighted accuracy measure was introduced in 2017 for the case of Local Climate Zone (LCZ) mapping. This method was recently criticized by Johnson and Jozdani and an alternative method was proposed. In this comment, we explain the weighted accuracy measure in more detail and reject the criticism. We show that the proposed method of Johnson and Jozdani is based on weakly supported assumptions. In addition, it is argued that the weighted accuracy is potentially a useful complementary measure beyond the LCZ classification case.<\/jats:p>","DOI":"10.3390\/rs12111769","type":"journal-article","created":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T09:19:27Z","timestamp":1591089567000},"page":"1769","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["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"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8802-7934","authenticated-orcid":false,"given":"Benjamin","family":"Bechtel","sequence":"first","affiliation":[{"name":"Department of Geography, Ruhr-University Bochum, 44801 Bochum, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3237-4077","authenticated-orcid":false,"given":"Matthias","family":"Demuzere","sequence":"additional","affiliation":[{"name":"Department of Geography, Ruhr-University Bochum, 44801 Bochum, Germany"}]},{"given":"Iain D.","family":"Stewart","sequence":"additional","affiliation":[{"name":"Global Cities Institute, University of Toronto, Suite 1308, Toronto, ON M5P 0P6, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","article-title":"A systematic analysis of performance measures for classification tasks","volume":"45","author":"Sokolova","year":"2009","journal-title":"Inf. Process. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Johnson, B.A., and Jozdani, S.E. (2019). Local Climate Zone (LCZ) Map Accuracy Assessments Should Account for Land Cover Physical Characteristics that Affect the Local Thermal Environment. Remote Sens., 11.","DOI":"10.3390\/rs11202420"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bechtel, B., Demuzere, M., Sismanidis, P., Fenner, D., Brousse, O., Beck, C., Van Coillie, F., Conrad, O., Keramitsoglou, I., and Middel, A. (2017). Quality of Crowdsourced Data on Urban Morphology\u2014The Human Influence Experiment (HUMINEX). Urban Sci., 1.","DOI":"10.3390\/urbansci1020015"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1175\/BAMS-D-11-00019.1","article-title":"Local Climate Zones for Urban Temperature Studies","volume":"93","author":"Stewart","year":"2012","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_6","unstructured":"Stewart, I.D. LCZ metric. Personal communication."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1175\/BAMS-D-16-0236.1","article-title":"WUDAPT: An Urban Weather, Climate, and Environmental Modeling Infrastructure for the Anthropocene","volume":"99","author":"Ching","year":"2018","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_8","unstructured":"Stewart, I.D. (2018, January 6\u201310). Developing a field guide to identify \u2018local climate zones\u2019 in cities. Preprints. Proceedings of the10th International Conference on Urban Climate, New York, NY, USA."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/11\/1769\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:34:17Z","timestamp":1760175257000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/11\/1769"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,31]]},"references-count":8,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["rs12111769"],"URL":"https:\/\/doi.org\/10.3390\/rs12111769","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,31]]}}}