English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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.

remote sensing

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