Object-oriented tracking of the dynamic behavior of urban heat islands

Zhu, Rui; Guilbert, Éric; Wong, Man Sing

doi:10.1080/13658816.2016.1211282

Cited by 23 publications

(24 citation statements)

References 35 publications

(35 reference statements)

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“…Several algorithms track cloud entities and cloud microphysical properties with geostationary satellites (Berendes et al, 2008;Bennartz & Schroeder, 2012;Bley et al, 2016;Guilbert & Lin, 2007;Patou et al, 2018;Senf et al, 2015;Senf & Deneke, 2017;Zhu et al, 2017;Zinner et al, 2008). The information on r e could be used to detect mixed-phase clouds.…”

Section: Resultsmentioning

confidence: 99%

Detection of Mixed‐Phase Convective Clouds by a Binary Phase Information From the Passive Geostationary Instrument SEVIRI

2019

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Between −37 and 0 °C, clouds are liquid, ice, or mixed phase. Nearly all retrieval algorithms for passive instruments provide binary phase information—ice or liquid—making it difficult to retrieve mixed‐phase cloud properties. Based on measurements from the geostationary space‐based instrument Spinning Enhanced Visible and InfraRed Imager (SEVIRI), we show that the retrieved ice crystal effective radius is smaller than the liquid droplet effective radius for 48% of 230 analyzed cloud thermodynamic phase transitions—phase transition from liquid to ice of rising convective clouds—while ice crystals are expected to be larger than cloud droplets. We simulate mixed‐phase cloud radiances with the numerical model Santa Barbara DISORT Atmospheric Radiative Transfer for which we compare simulated effective radius retrievals with observations. The phase retrieval algorithm from SEVIRI does not represent well mixed‐phase clouds, and categorizing clouds by only ice and liquid is not enough to accurately represent mixed‐phase cloud optical properties. We conclude that the mixed‐phase nature of clouds explains that retrieved cloud droplet radii are larger than ice crystal radii directly before and after the phase transition. However, from a cloud tracking algorithm perspective, the variation of the effective radius enables the detection of mixed‐phase convective clouds from binary phase information.

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Section: Resultsmentioning

confidence: 99%

Detection of Mixed‐Phase Convective Clouds by a Binary Phase Information From the Passive Geostationary Instrument SEVIRI

2019

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“…According to the above the perception, relationship between zones are essentially determined by topological relationships of cores between different zones. Therefore, at least one core r At a time instant, UHIs alternatively have transformation or areal change (Zhu et al 2016). However, this study suggests that both can happen simultaneously in two specific scenarios, i.e., separation and annexation when the zone still exists.…”

Section: Spatial Behavior Of the Uhimentioning

confidence: 83%

Object-Core Oriented Data Modelling for Tracking of Behaviors of Urban Heat Islands

Zhu

Guilbert

Wong

2018

EasyChair Preprints

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ABSTRACT:Modeling thematic and spatial dynamic behaviors of Urban Heat Islands (UHIs) over time is crucial to understand the evolution of this phenomenon and the city micro-climate. Previous studies conceptualized that a UHI can only have a single life period with spatial behaviors (i.e. areal changes and topological transformations). However, a UHI can also appear and disappear periodically several times expressed by thematic and spatial integrated behaviors, which has not been established yet. Thus, this study conceptualizes each UHI as an object which has thematic and spatial behaviors simultaneously and proposes several graphs to depict periodic life-time transitions triggered by the behaviors. The model was implemented in an object-relational database, and air temperatures collected from a number of weather stations were interpolated as temperature images each hour for six weeks. Results indicated that the model could track the spatial and thematic evolution of UHIs through continuous time effectively, and also revealed the periodical patterns and abnormal cases of UHIs over a city.

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“…A previous study proposed a set of filiations by investigating the relations between zones in two consecutive time instants (Zhu et al 2016). For example, two zones that have significant overlapping in two continuous time instants can be viewed as the same UHI in two statuses.…”

Section: Core-oriented Behavior Modelingmentioning

confidence: 99%

“…Zones of (z i−1 , z i ) that have significant overlapping were perceived as the same UHI, and hence specific filiation can be further identified (Zhu et al 2016). However, thematic cores of both zones may not locate in the overlapping region but are separated in the non-overlapping region of each zone.…”

Section: Spatial Behavior Of the Uhimentioning

confidence: 99%

“…Another study explicitly described these transformations (Del Mondo et al 2013), which presents spatiotemporal relationships in a graph to continuously track changes of objects over time. Other transitions that affect the shape and thematic attribute of a field-object were established in two graphs (Zhu et al 2016). As a consequence, a graph to systematically describe locational movements has not been built yet.…”

Section: Introductionmentioning

confidence: 99%

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Object-Core Oriented Data Modelling for Tracking of Behaviors of Urban Heat Islands

Zhu

Guilbert

Wong

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Modeling thematic and spatial dynamic behaviors of Urban Heat Islands (UHIs) over time is crucial to understand the evolution of this phenomenon and the city micro-climate. Previous studies conceptualized that a UHI can only have a single life period with spatial behaviors (i.e. areal changes and topological transformations). However, a UHI can also appear and disappear periodically several times expressed by thematic and spatial integrated behaviors, which has not been established yet. Thus, this study conceptualizes each UHI as an object which has thematic and spatial behaviors simultaneously and proposes several graphs to depict periodic life-time transitions triggered by the behaviors. The model was implemented in an object-relational database, and air temperatures collected from a number of weather stations were interpolated as temperature images each hour for six weeks. Results indicated that the model could track the spatial and thematic evolution of UHIs through continuous time effectively, and also revealed the periodical patterns and abnormal cases of UHIs over a city.</p>

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Object-oriented tracking of the dynamic behavior of urban heat islands

Cited by 23 publications

References 35 publications

Detection of Mixed‐Phase Convective Clouds by a Binary Phase Information From the Passive Geostationary Instrument SEVIRI

Detection of Mixed‐Phase Convective Clouds by a Binary Phase Information From the Passive Geostationary Instrument SEVIRI

Object-Core Oriented Data Modelling for Tracking of Behaviors of Urban Heat Islands

Object-Core Oriented Data Modelling for Tracking of Behaviors of Urban Heat Islands

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