scholarly journals Local Climate Zone (LCZ) Map Accuracy Assessments Should Account for Land Cover Physical Characteristics that Affect the Local Thermal Environment

2019 ◽  
Vol 11 (20) ◽  
pp. 2420 ◽  
Author(s):  
Brian Alan Johnson ◽  
Shahab Eddin Jozdani
Keyword(s):  
Land Cover ◽  
Thermal Environment ◽  
Accuracy Assessment ◽  
Remote Sensing Data ◽  
Physical Characteristics ◽  
Anthropogenic Heat ◽  
Climate Zone ◽  
Local Climate ◽  
Local Climate Zone ◽  
Map Accuracy

Local climate zone (LCZ) maps are increasingly being used to help understand and model the urban microclimate, but traditional land use/land cover map (LULC) accuracy assessment approaches do not convey the accuracy at which LCZ maps depict the local thermal environment. 17 types of LCZs exist, each having unique physical characteristics that affect the local microclimate. Many studies have focused on generating LCZ maps using remote sensing data, but nearly all have used traditional LULC map accuracy metrics, which penalize all map classification errors equally, to evaluate the accuracy of these maps. Here, we proposed a new accuracy assessment approach that better explains the accuracy of the physical properties (i.e., surface structure, land cover, and anthropogenic heat emissions) depicted in an LCZ map, which allows for a better understanding of the accuracy at which the map portrays the local thermal environment.

scholarly journals Confusion Matrices Help Prevent Reader Confusion: Reply to Bechtel, B., et al. 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

2020 ◽  
Vol 12 (11) ◽  
pp. 1771
Author(s):  
Brian Alan Johnson ◽  
Shahab Eddin Jozdani
Keyword(s):  
Land Cover ◽  
Thermal Environment ◽  
Confusion Matrix ◽  
Urban Heat Islands ◽  
Estimation Errors ◽  
Climate Zone ◽  
Local Climate ◽  
Accuracy Measure ◽  
Local Climate Zone ◽  
Map Accuracy

Land use/land cover (LULC) maps are now being used across disciplines for many different types of applications, e.g., to analyze urban heat islands or rainfall-runoff dynamics. Traditional map accuracy metrics are limited in this regard, as they only assess LULC map thematic accuracy. In reality, some types of misclassification lead to larger estimation errors for these specific applications. In a previous study, we developed a new map accuracy metric (referred to here as “JJ19”) to assess the accuracy of local climate zone maps for urban microclimate analysis. In the previous work, we also attempted to reproduce another metric (weighted accuracy (WA)) proposed for this purpose, but misinterpreted it due to a lack of methodological information available (principally, the lack of a confusion matrix to demonstrate how WA was derived). We sincerely thank the authors of Bechtel et al. 2019 for providing more information on WA in response to our previous study and are happy to report that we found that the metric is now both reproducible and valid. On the other hand, we found some other aspects of Bechtel et al. 2019’s study to be inaccurate, particularly their claims regarding the suitability of the JJ19 metric. Finally, we made a minor improvement to the JJ19 metric based on Bechtel et al.’s comments.

scholarly journals 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

2020 ◽  
Vol 12 (11) ◽  
pp. 1769 ◽  
Author(s):  
Benjamin Bechtel ◽  
Matthias Demuzere ◽  
Iain D. Stewart
Keyword(s):  
Land Cover ◽  
Thermal Environment ◽  
Land Cover Mapping ◽  
Climate Zone ◽  
Local Climate ◽  
Accuracy Measure ◽  
The Common ◽  
Multi Class Classification ◽  
Accuracy Assessments ◽  
Local Climate Zone

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.

scholarly journals Investigations of Surface Urban Heat Island Effect Based on Local Climate Zone Method: A Case of Xi'an

2019 ◽  
Vol 136 ◽  
pp. 05011
Author(s):  
Kaikai Mu ◽  
Yan Liu ◽  
Moyan Zhang ◽  
Bing Han ◽  
Liu Yang
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Urban Form ◽  
Heat Island ◽  
Zone Method ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Local Climate Zone

Urbanization seriously affects the urban climate and the quality of human settlement. Based on Landsat8 remote sensing and building vector data, local climate zone (LCZ) method is employed to study the influences of urban form on land surface temperature (LST) of Xi'an. The results confirmed that the LST of the built-up LCZ is higher than the land cover LCZ. In built-up LCZ, LST is increasing with the increasing of building density. In land cover LCZ, the LST of bare land is the highest. Surface urban heat island (SUHI) of 14 samples in LCZ also been calculated. Highest SUHI intensity is found in low-rise buildings with high density area. LST intensity of water body and forest are lower than others in land cover LCZ.

How well does the local climate zone scheme discern the thermal environment of Toulouse (France)? An analysis using numerical simulation data

2019 ◽  
Vol 39 (14) ◽  
pp. 5292-5315 ◽  
Author(s):  
Yu Ting Kwok ◽  
Robert Schoetter ◽  
Kevin Ka‐Lun Lau ◽  
Julia Hidalgo ◽  
Chao Ren ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Thermal Environment ◽  
Simulation Data ◽  
Climate Zone ◽  
Local Climate ◽  
Local Climate Zone

scholarly journals Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

2020 ◽  
Vol 12 (7) ◽  
pp. 2752 ◽  
Author(s):  
Yaping Chen ◽  
Bohong Zheng ◽  
Yinze Hu
Keyword(s):  
Numerical Simulation ◽  
Air Temperature ◽  
Thermal Environment ◽  
Green Roofs ◽  
Climate Zone ◽  
Local Climate ◽  
Cooling Effects ◽  
Combined Cooling ◽  
Local Climate Zone

By exploring the cooling potential of tree quantity, ground albedo, green roofs and their combinations in local climate zone (LCZ)-4, LCZ-5, and LCZ-6, this study focuses on the optimum cooling level that can be achieved in open residential regions in Changsha. It designs and models 39 scenarios by integrating in situ measurement and ENVI-met numerical simulation and further compares cooling effects of various combinations of the cooling factors. The results show that (1) an increased number of trees and higher albedo are more effective compared to green roofs in reducing summer potential temperatures at street level (2 m high) in three LCZs. Negative correlations are observed in the pedestrian air temperature with trees and ground albedo; (2) the effects of cooling factors vary among different LCZ classes, with the increased 60% more trees leading to lower outdoor temperatures for LCZ-4 (0.28 °C), LCZ-5 (0.39 °C), and LCZ-6 (0.54 °C), while higher albedo of asphalt surface (increased by 0.4) is more effective in LCZ-4 (reaches to 0.68 °C) 14:00, compare to LCZ-5 (0.49 °C) and LCZ-6 (0.38 °C); (3) applying combined cooling methods can provoke air temperature reduction (up to 0.96 °C), especially when higher levels of tree quantities (increased by 60%) are coupled with cool ground materials (albedo increased by 0.4). The results can contribute useful information for improving thermal environment in existing residential regions and future residential planning.

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