World Urban Database And Access Portal Tools Research Articles

WUDAPT: An Urban Weather, Climate, and Environmental Modeling Infrastructure for the Anthropocene

AbstractThe World Urban Database and Access Portal Tools (WUDAPT) is an international community-based initiative to acquire and disseminate climate relevant data on the physical geographies of cities for modeling and analysis purposes. The current lacuna of globally consistent information on cities is a major impediment to urban climate science toward informing and developing climate mitigation and adaptation strategies at urban scales. WUDAPT consists of a database and a portal system; its database is structured into a hierarchy representing different levels of detail, and the data are acquired using innovative protocols that utilize crowdsourcing approaches, Geowiki tools, freely accessible data, and building typology archetypes. The base level of information (L0) consists of local climate zone (LCZ) maps of cities; each LCZ category is associated with a range of values for model-relevant surface descriptors (roughness, impervious surface cover, roof area, building heights, etc.). Levels 1 (L1) and 2 (L2) will provide specific intra-urban values for other relevant descriptors at greater precision, such as data morphological forms, material composition data, and energy usage. This article describes the status of the WUDAPT project and demonstrates its potential value using observations and models. As a community-based project, other researchers are encouraged to participate to help create a global urban database of value to urban climate scientists.

Assessing local climate zones in arid cities: The case of Phoenix, Arizona and Las Vegas, Nevada

The local climate zone (LCZ) classification scheme is a standardization framework to describe the form and function of cities for urban heat island (UHI) studies. This study classifies and evaluates LCZs for two arid desert cities in the Southwestern United States – Phoenix and Las Vegas – following the World Urban Database and Access Portal Tools (WUDAPT) method. Both cities are classified into seven built type LCZs and seven land-cover type LCZs at 100-m resolution using Google Earth, Saga GIS, and Landsat 8 scenes. Average surface cover properties (building fraction, impervious fraction, pervious fraction) and sky view factors of classified LCZs are then evaluated and compared to pre-defined LCZ representative ranges from the literature, and their implications on the surface UHI (SUHI) effect are explained. Results suggest that observed LCZ properties in arid desert environments do not always match the proposed value ranges from the literature, especially with regard to sky view factor (SVF) upper boundaries. Although the LCZ classification scheme was originally designed to describe local climates with respect to air temperature, our analysis shows that much can be learned from investigating land surface temperature (LST) in these zones. This study serves as a substantial new resource laying a foundation for assessing the SUHI in cities using the LCZ scheme, which could inform climate simulations at local and regional scales.

Mapping the local climate zones of urban areas by GIS-based and WUDAPT methods: A case study of Hong Kong

Local Climate Zone (LCZ) developed by Stewart and Oke has become an international standard to analyse urban morphology and the corresponding urban heat island phenomenon. Primary methods for LCZ mapping include in-situ measurements, geographic information system (GIS)-based and remote-sensing-image-based calculations. However, there are few studies discussing their accuracy and suitability. This study focuses on examining and discussing the GIS-based method and the World Urban Database and Access Portal Tools (WUDAPT) Level 0 method. Hong Kong is selected as the study area due to its complex urban morphology and high-density context. The results show, at a city level, both methods can detect LCZ classifications that match with the actual spatial distribution of land use in Hong Kong. Thus WUDAPT level 0 data can be used as input data for mesoscale weather and climate modelling, when lacking precise urban morphology data. Meanwhile, at a district level, the GIS-based method detects more details than the WUDAPT method. However, WUDAPT method classifies land cover types more accurately. These findings provide an in-depth understanding of different LCZ mapping methods and their advantages and limitations. It can also help climatologists, modellers and planners select an appropriate LCZ mapping method for their studies of urban climatic applications.

Urban morphology detection and computation for urban climate research

Urban morphology information is an important indicator in urban planning, information management, and urban climatic applications. However, the problem of urban morphological data harmonization, quality, and availability are well-known, especially in developing countries. In this study, a novel satellite-based approach was proposed to extract 3D urban morphology information, and then retrieve and validate typical urban morphological parameters for urban climatic applications. Some most widely used urban morphological parameters—building coverage ratio (BCR), building height (BH), building volume density (BVD), frontal area index (FAI), sky view factor (SVF), and roughness length (RL)—were calculated and validated. Experiments conducted throughout the entire urban environment of Kowloon Peninsula, the most complex and high-density urban area in Hong Kong, demonstrated that all of the retrieved parameters had a high prediction accuracy, compared with the actual data at spatial resolutions of hundreds of meters. In particular, the prediction accuracy of BCR, BH, BVD, and RL was 70–80% while the accuracy of SVF and FAI was 80–90%. This set of urban morphological data is employed to generate a Hong Kong Urban Climatic Map. As an extension of the World Urban Database and Access Portal Tools (WUDAPT) method to provide 2D urban form data for cities worldwide, this newly developed method can quickly and efficiently produce highly accurate 3D urban morphology data for cities where actual urban morphology data are not accessible. This study also expands spatial understanding of urban climatic conditions in a fast and efficient way, enabling urban climatic application in urban planning for sustainable urban living.

Classification of Local Climate Zones Using ASTER and Landsat Data for High-Density Cities

The local climate zone (LCZ) scheme provides a standard method to conduct urban heat island studies, in which urban landscapes are classified into different LCZs according to urban structures, land cover, and construction materials. Based on the LCZ classification scheme, the World Urban Database and Access Portal Tools (WUDAPT) is a new initiative to generate LCZ maps of cities worldwide with the use of freely available Landsat data. This paper aims to evaluate the performance of the original WUDAPT method in LCZ mapping for high-density cities. To further improve LCZ mapping accuracy for high-density cities, we investigate the usage of both freely available Landsat and advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite data to generate better LCZ mapping results. Experiments on two high-density Chinese cities, Guangzhou and Wuhan, showed that combining Landsat and ASTER data can improve the overall performance of LCZ mapping results, especially for urban areas. This finding indicates that further applications of the WUDAPT method for high-density cities can include both ASTER and Landsat data.

Influence of neighbourhood information on ‘Local Climate Zone’ mapping in heterogeneous cities

Local climate zone (LCZ) mapping is an emerging field in urban climate research. LCZs potentially provide an objective framework to assess urban form and function worldwide. The scheme is currently being used to globally map LCZs as a part of the World Urban Database and Access Portal Tools (WUDAPT) initiative. So far, most of the LCZ maps lack proper quantitative assessment, challenging the generic character of the WUDAPT workflow. Using the standard method introduced by the WUDAPT community difficulties arose concerning the built zones due to high levels of heterogeneity. To overcome this problem a contextual classifier is adopted in the mapping process. This paper quantitatively assesses the influence of neighbourhood information on the LCZ mapping result of three cities in Belgium: Antwerp, Brussels and Ghent. Overall accuracies for the maps were respectively 85.7±0.5, 79.6±0.9, 90.2±0.4%. The approach presented here results in overall accuracies of 93.6±0.2, 92.6±0.3 and 95.6±0.3% for Antwerp, Brussels and Ghent. The results thus indicate a positive influence of neighbourhood information for all study areas with an increase in overall accuracies of 7.9, 13.0 and 5.4%. This paper reaches two main conclusions. Firstly, evidence was introduced on the relevance of a quantitative accuracy assessment in LCZ mapping, showing that the accuracies reported in previous papers are not easily achieved. Secondly, the method presented in this paper proves to be highly effective in Belgian cities, and given its open character shows promise for application in other heterogeneous cities worldwide.

Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX)

The World Urban Database and Access Portal Tools (WUDAPT) is a community initiative to collect worldwide data on urban form (i.e., morphology, materials) and function (i.e., use and metabolism). This is achieved through crowdsourcing, which we define here as the collection of data by a bounded crowd, composed of students. In this process, training data for the classification of urban structures into Local Climate Zones (LCZ) are obtained, which are, like most volunteered geographic information initiatives, of unknown quality. In this study, we investigated the quality of 94 crowdsourced training datasets for ten cities, generated by 119 students from six universities. The results showed large discrepancies and the resulting LCZ maps were mostly of poor to moderate quality. This was due to general difficulties in the human interpretation of the (urban) landscape and in the understanding of the LCZ scheme. However, the quality of the LCZ maps improved with the number of training data revisions. As evidence for the wisdom of the crowd, improvements of up to 20% in overall accuracy were found when multiple training datasets were used together to create a single LCZ map. This improvement was greatest for small training datasets, saturating at about ten to fifteen sets.

2017 IEEE GRSS Data Fusion Contest: Open Data for Global Multimodal Land Use Classification [Technical Committees

The 2017 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), aims at providing a challenging image analysis opportunity, including multiresolution and multimodal fusion. The 2017 contest focuses on the classification of local climate zones (LCZs) [1] in various urban environments. LCZs are a generic, climate-based typology of urban and natural landscapes that deliver information on basic physical properties of an area that can be used by land-use planners or climate modelers [2]. They are used as first-order discretization of urban areas by the World Urban Database and Access Portal Tools (WUDAPT) initiative, which aims to collect, store, and disseminate data on the form and function of cities around the world [3].

WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid

Nowadays, the absence of suitable data that describes the urban landscape in climate relevant terms for climatic models is a significant impediment to progress, even if the physics that underpins these models is universal. To address this data gap the World Urban Database and Access Portal Tools (WUDAPT) project focuses on creating a global database on cities suited for urban climate studies. The first phase of WUDAPT has established a protocol using the Local Climate Zones classification system to partition the urban landscape of cities into neighbourhood types that can inform parameter selection in model applications. In this paper, we explore the potential of these data for use in the application of the Weather Research Forecasting (WRF) model, which incorporates Building Effect Parameterization and Building Energy Model (BEP-BEM) schemes. The test is conducted for Madrid (Spain) during winter and summer and the results of using LCZ derived data are compared with those using CORINE land-cover data. The results are indicative but show that the LCZ scheme improves model performance. The paper emphasizes the need for further work to extend the value of these models for decisions on urban planning. However, such work will need useful urban data to make progress.

Classification of Local Climate Zones Using SAR and Multispectral Data in an Arid Environment

There is an urgent need for more detailed spatial information on cities globally that has been acquired using a standard method to facilitate comparison and the transfer of scientific and practical knowledge between places. As part of the world urban database and access portal tools (WUDAPT) initiative, a simple workflow has been developed to perform this task. Using freely available satellite imagery (Landsat) and software (SAGA), WUDAPT characterizes settlements using the local climate zone (LCZ) scheme, which decomposes the city into distinctive neighborhoods ( ${ > } \text{1} \hbox{km}^2$ ) based on typical properties (e.g., green proportion and built fraction). In this paper, the methodology is extended to examine the effect of adding synthetic aperture radar (SAR) data, which is now freely available from Sentinel 1, for generating LCZs. Using the city of Khartoum as a case study, the results show that combining multispectral and SAR data improves the overall performance of several classifiers, with random forest (RF) performing the best overall.

Local Climate Zone Study for Sustainable Megacities Development by Using Improved WUDAPT Methodology – A Case Study in Guangzhou

High density urban development in the past has not only changed natural landscape into artificial constructions and pavements, but also brought along many environmental problems like air pollution, urban heat island (UHI) and dust haze, which can affect the public health condition. There are limited applied urban climatic studies in urban planning and development. One of key reasons is there is a missing link between urban development and its corresponding impact on local climatic conditions. The concept of Local Climate Zone scheme has been developed to fit into this gap1. It introduces a standardized scientific way to describe the land cover and its thermal performance on the UHI. Since 2012, The World Urban Database and Access Portal Tools (WUDAPT) have been developed to call for international efforts and collaborations on world-wide LCZ studies. Its level 0 method can quickly collect urban morphology information and create LCZ maps2. However, it's time consuming to use WUDAPT to classify cities globally as WUDAPT is designed at city scale. This paper aims to improve the current methodology to classify more cities in a shorter time and also achieve a more accurate result. In this paper, Guangzhou is selected as case study since it has complex urban morphology and can represent as typical megacity in China. The study firstly reviews the concept of LCZ and WUDAPT. Secondly, the level 0 method of WUDAPT is used to initially classify LCZs of Guangzhou. For enhancing the efficiency of the existing WUDAPT, an improved methodology is developed to use WUDAPT to classify a region and extract the cities inside the region. Thirdly, the relevant quality checking work of the two methodologies is also conducted to detect the accuracy of the two methodologies. The improved outputs can be applied to numerical modellings and local planning implementation3. Because the future trend of urbanization in China is towards megacity development, the lessons learnt from the study can be applied to other megacities and regions for better climatic-spatial planning in future.

Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities

Progress in urban climate science is severely restricted by the lack of useful information that describes aspects of the form and function of cities at a detailed spatial resolution. To overcome this shortcoming we are initiating an international effort to develop the World Urban Database and Access Portal Tools (WUDAPT) to gather and disseminate this information in a consistent manner for urban areas worldwide. The first step in developing WUDAPT is a description of cities based on the Local Climate Zone (LCZ) scheme, which classifies natural and urban landscapes into categories based on climate-relevant surface properties. This methodology provides a culturally-neutral framework for collecting information about the internal physical structure of cities. Moreover, studies have shown that remote sensing data can be used for supervised LCZ mapping. Mapping of LCZs is complicated because similar LCZs in different regions have dissimilar spectral properties due to differences in vegetation, building materials and other variations in cultural and physical environmental factors. The WUDAPT protocol developed here provides an easy to understand workflow; uses freely available data and software; and can be applied by someone without specialist knowledge in spatial analysis or urban climate science. The paper also provides an example use of the WUDAPT project results.