Mapping Europe into local climate zones

Abstract

Cities are major drivers of environmental change at all scales and are especially at risk from the ensuing effects, which include poor air quality, flooding and heat waves. Typically, these issues are studied on a city-by-city basis owing to the spatial complexity of built landscapes, local topography and emission patterns. However, to ensure knowledge sharing and to integrate local-scale processes with regional and global scale modelling initiatives, there is a pressing need for a world-wide database on cities that is suited for environmental studies. In this paper we present a European database that has a particular focus on characterising urbanised landscapes. It has been derived using tools and techniques developed as part of the World Urban Database and Access Portal Tools (WUDAPT) project, which has the goal of acquiring and disseminating climate-relevant information on cities worldwide. The European map is the first major step toward creating a global database on cities that can be integrated with existing topographic and natural land-cover databases to support modelling initiatives.

The Human Influence Experiment (Part 2): Guidelines for Improved Mapping of Local Climate Zones Using a Supervised Classification

“…Second, due to the fact that less then 10% of the participants lived in Berlin or were familiar with the city, it was not possible to investigate the influence of local knowledge on the classification results. Even though, currently research is done investigating the potential of continental-scale LCZ maps [26][27][28], the question on local knowledge remains important. In this respect, it might be better to include more cities.…”

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

“…The significance is that the weighted accuracy values cannot be lower than their unweighted counterparts, because the multiplier for misclassification is always assumed to be 1 in the traditional error matrix. Thus, our error matrix weighting approach is somewhat akin to the process of merging of LCZs into fewer, more general LULC categories (e.g., either "built-up" or "natural" [9,18]) for accuracy assessment, but our approach is more of a partial merging (unless D ij = 0).…”

“…The most common approach involves performing supervised classification of Landsat satellite imagery using the random forest classification algorithm [8], and this approach has been termed the "world urban database and access portals tools" (WUDAPT) protocol [7]. The WUDAPT protocol has been applied successfully in many LCZ mapping studies in different geographic regions [4][5][6]9,10]. To build on the WUDAPT approach, some studies have proposed the use of additional remote sensing datasets, e.g., nighttime optical imagery [11], nighttime thermal infrared imagery [12], synthetic aperture radar data [9], or LiDAR data [13].…”

“…The WUDAPT protocol has been applied successfully in many LCZ mapping studies in different geographic regions [4][5][6]9,10]. To build on the WUDAPT approach, some studies have proposed the use of additional remote sensing datasets, e.g., nighttime optical imagery [11], nighttime thermal infrared imagery [12], synthetic aperture radar data [9], or LiDAR data [13]. Other studies have proposed incorporating ancillary GIS datasets in the image classification workflow, e.g., OpenStreetMap data [11,14], and/or the use of alternative classification algorithms (e.g., convolutional neural networks [11]).…”

A Study of Local Climate Zones in Abu Dhabi with Urban Weather Stations and Numerical Simulations

“…However, there are several studies done in European cities through the WUDAPT methodology. An open data source that can be used from researches around the world to map cities according to the climate zones [1][2][3]. Microclimate variations in urban environments have been studied for 50 years.…”