Beyond the urban mask

Bechtel, Benjamin; Conrad, Olaf; Tamminga, Matthias; Verdonck, Marie-Leen; Coillie, Frieke Van; Tuia, Devis; Demuzere, Matthias; See, Linda; Lopes, Patricia; Fonte, Cidália C.; Xu, Yong; Ren, Chao; Mills, Gerald; Kaloustian, Noushig; Cassone, Arthur

doi:10.1109/jurse.2017.7924557

Cited by 18 publications

(13 citation statements)

References 17 publications

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“…The quality approaches described in this paper are generally being applied to LCZ maps developed using the WUDAPT production workflow as described in section 2. However, there are many ongoing developments with respect to improving the actual method used to derive the LCZ maps (Bechtel et al, 2017a) and hence improve their overall quality. These include the transferability of TAs, the use of new data sets and features and new approaches to LCZ classification.…”

Section: Improvements In Lcz Mappingmentioning

confidence: 99%

Generating WUDAPT Level 0 data – Current status of production and evaluation

et al. 2019

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The World Urban Database and Access Portal Tools (WUDAPT) project has grown out of the need for better information on the form and function of cities globally. Cities are described using Local Climate Zones (LCZ), which are associated with a range of key urban climate model parameters and thus can serve as inputs to high resolution urban climate models. We refer to this as level 0 data for each city. The LCZ level 0 product is produced using freely available Landsat imagery, crowdsourced training areas from the community, and the open source SAGA software. This paper outlines the protocol by which LCZ maps generated by different members of the community are produced and evaluated. In particular, the quality assessment comprises cross-validation, review, and cross-comparison with other data sets. To date, the results from the different quality assessments show that the LCZ maps are generally of moderate quality, i.e. 50-60% overall

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Section: Improvements In Lcz Mappingmentioning

confidence: 99%

Generating WUDAPT Level 0 data – Current status of production and evaluation

et al. 2019

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“…Sphere of Application [35] Soil sealing, rainwater management [36] Urban land use [37] Informal settlements [38] Landscape metrics, urban land use structures [39] Urban patterns and morphology [40] Local potential of district heat, settlement structures [41] Urban morphology analysis [42] Urban structure types, land use [16] Local Climate Zones, urban structure [43] Local Climate Zones, WUDAPT [44] Local Climate Zones, neighborhood information…”

Section: Referring To the Urban Structure Type (Ust) Concept Without mentioning

confidence: 99%

“…As discussed in Section 2.1 Theoretical Background and 2.3 Specificity of cities vs. generic applicability, the urban structure type approach has been established, enabling holistic descriptions of a city and its interactions [20]. In contrast to USTs, local climate zones (LCZs) are a generic, climate-based typology of urban and natural landscapes [43]. LCZs are defined as "regions of uniform surface cover, structure, material, and human activity that span hundreds of meters to several kilometres in horizontal scale" [43,49] and have a "characteristic screen-height temperature regime".…”

Section: Related and Alternative Conceptsmentioning

confidence: 99%

“…In contrast to USTs, local climate zones (LCZs) are a generic, climate-based typology of urban and natural landscapes [43]. LCZs are defined as "regions of uniform surface cover, structure, material, and human activity that span hundreds of meters to several kilometres in horizontal scale" [43,49] and have a "characteristic screen-height temperature regime". The introduction of the LCZs within the frame of the WUDAPT project highlights the definition of a common standard that is applicable for all urban agglomerations on a global scale.…”

Section: Related and Alternative Conceptsmentioning

confidence: 99%

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A Generic Classification Scheme for Urban Structure Types

Lehner

Blaschke

2019

Remote Sensing

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This paper presents a proposal for a generic urban structure type (UST) scheme. Initially developed in the context of urban ecology, the UST approach is increasingly popular in the remote sensing community. However, there is no consistent and standardized UST framework. Until now, the terms land use and certain USTs are often used and described synonymously, or components of structure and use are intermingled. We suggest a generic nomenclature and a respective UST scheme that can be applied worldwide by stakeholders of different disciplines. Based on the insights of a rigorous literature analysis, we formulate a generic structural- and object-based typology, allowing for the generation of hierarchically and terminologically consistent USTs. The developed terminology exclusively focuses on morphology, urban structures and the general exterior appearance of buildings. It builds on the delimitation of spatial objects at several scales and leaves out all social aspects and land use aspects of an urban area. These underlying objects or urban artefacts and their structure- and object-related features, such as texture, patterns, shape, etc. are the core of the hierarchically structured UST scheme. Finally, the authors present a generic framework for the implementation of a remote sensing-based UST classification along with the requirements regarding sensors, data and data types.

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“…The local climate zone (LCZ) scheme is a novel climate-based classification scheme [1], which skillfully relates the urban climate represented by physical traits with urban morphology depicted through landscape cover. The LCZ scheme has the potential to be accepted as a standard description for worldwide cities [2], since its strong performance in indicating the diversity inside cities is also important for urban study. It has been widely used in various fields, such as a series of studies of the urban heat island (UHI) effect [3,4], which adopted the LCZ scheme rather than the traditional dichotomic urban or rural regions to analyze the effects of urban heat islands, making the study of thermal phenomena more specific.…”

Section: Introductionmentioning

confidence: 99%

Self-Training Classification Framework with Spatial-Contextual Information for Local Climate Zones

Zhao

Zhong

et al. 2019

Remote Sensing

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Local climate zones (LCZ) have become a generic criterion for climate analysis among global cities, as they can describe not only the urban climate but also the morphology inside the city. LCZ mapping based on the remote sensing classification method is a fundamental task, and the protocol proposed by the World Urban Database and Access Portal Tools (WUDAPT) project, which consists of random forest classification and filter-based spatial smoothing, is the most common approach. However, the classification and spatial smoothing lack a unified framework, which causes the appearance of small, isolated areas in the LCZ maps. In this paper, a spatial-contextual information-based self-training classification framework (SCSF) is proposed to solve this LCZ classification problem. In SCSF, conditional random field (CRF) is used to integrate the classification and spatial smoothing processing into one model and a self-training method is adopted, considering that the lack of sufficient expert-labeled training samples is always a big issue, especially for the complex LCZ scheme. Moreover, in the unary potentials of CRF modeling, pseudo-label selection using a self-training process is used to train the classifier, which fuses the regional spatial information through segmentation and the local neighborhood information through moving windows to provide a more reliable probabilistic classification map. In the pairwise potential function, SCSF can effectively improve the classification accuracy by integrating the spatial-contextual information through CRF. The experimental results prove that the proposed framework is efficient when compared to the traditional mapping product of WUDAPT in LCZ classification.

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Beyond the urban mask

Cited by 18 publications

References 17 publications

Generating WUDAPT Level 0 data – Current status of production and evaluation

Generating WUDAPT Level 0 data – Current status of production and evaluation

A Generic Classification Scheme for Urban Structure Types

Self-Training Classification Framework with Spatial-Contextual Information for Local Climate Zones

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