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Statistical analyses of Land Surface Temperature in Local Climate Zones: Case study of Brno and Prague (Czech Republic)

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F17%3A00096376" target="_blank" >RIV/00216224:14310/17:00096376 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/86652079:_____/17:00485079

  • Výsledek na webu

    <a href="http://dx.doi.org/10.1109/JURSE.2017.7924530" target="_blank" >http://dx.doi.org/10.1109/JURSE.2017.7924530</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/JURSE.2017.7924530" target="_blank" >10.1109/JURSE.2017.7924530</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Statistical analyses of Land Surface Temperature in Local Climate Zones: Case study of Brno and Prague (Czech Republic)

  • Popis výsledku v původním jazyce

    The classification of “local climate zones” (LCZs) emerged in urban climatology to standardize description of urban climate research sites. One of the goals of classification was to get beyond urban-rural dichotomy which enabled to study urban air temperature field in more detail. Based on empirical and modelling work LCZ have proven effective in examining intra-urban air temperature differences, however a robust examination of intra-urban land surface temperatures using the LCZ framework remains elusive. In this study a GIS-based method is used for LCZ delimitation in Prague and Brno (Czech Republic), while land surface temperatures (LSTs) derived from LANDSAT and ASTER satellite data are employed for exploring the extent to which LCZ classes discriminate with respect to LSTs. Results indicate that LCZs demonstrate the features typical of LST variability, and thus typical surface temperatures differ significantly among most LCZs. ANOVA and subsequent multiple comparison tests demonstrated that significant temperature differences between the various LCZs prevail in both cities (89.3% and 91.6% significant LST differences for Brno and Prague respectively). In general, LCZ 8 (large low-rise buildings), LCZ 10 (heavy industry) and LCZ D (low plants) are well-distinguishable, while LCZ 2 (compact midrise), LCZ 4 (open high-rise), and LCZ 9 (sparsely built-up) are less distinguishable in terms of their LST. In most of the scenes LCZ 10 (heavy industry), LCZ 2 (mid-rise buildings) and LCZ 3 (low-rise building) are the warmest and LCZ G (water bodies) and LCZ A (dense forest) are the coolest zones in term of their LST. Further studies are needed to account for observational errors (such as seasons differences or thermal anisotropy) on LCZ LST patterns.

  • Název v anglickém jazyce

    Statistical analyses of Land Surface Temperature in Local Climate Zones: Case study of Brno and Prague (Czech Republic)

  • Popis výsledku anglicky

    The classification of “local climate zones” (LCZs) emerged in urban climatology to standardize description of urban climate research sites. One of the goals of classification was to get beyond urban-rural dichotomy which enabled to study urban air temperature field in more detail. Based on empirical and modelling work LCZ have proven effective in examining intra-urban air temperature differences, however a robust examination of intra-urban land surface temperatures using the LCZ framework remains elusive. In this study a GIS-based method is used for LCZ delimitation in Prague and Brno (Czech Republic), while land surface temperatures (LSTs) derived from LANDSAT and ASTER satellite data are employed for exploring the extent to which LCZ classes discriminate with respect to LSTs. Results indicate that LCZs demonstrate the features typical of LST variability, and thus typical surface temperatures differ significantly among most LCZs. ANOVA and subsequent multiple comparison tests demonstrated that significant temperature differences between the various LCZs prevail in both cities (89.3% and 91.6% significant LST differences for Brno and Prague respectively). In general, LCZ 8 (large low-rise buildings), LCZ 10 (heavy industry) and LCZ D (low plants) are well-distinguishable, while LCZ 2 (compact midrise), LCZ 4 (open high-rise), and LCZ 9 (sparsely built-up) are less distinguishable in terms of their LST. In most of the scenes LCZ 10 (heavy industry), LCZ 2 (mid-rise buildings) and LCZ 3 (low-rise building) are the warmest and LCZ G (water bodies) and LCZ A (dense forest) are the coolest zones in term of their LST. Further studies are needed to account for observational errors (such as seasons differences or thermal anisotropy) on LCZ LST patterns.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    10500 - Earth and related environmental sciences

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/LO1415" target="_blank" >LO1415: CzechGlobe 2020 - Rozvoj Centra pro studium dopadů globální změny klimatu</a><br>

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    Joint Urban Remote Sensing Event 2017

  • ISBN

    9781509058082

  • ISSN

  • e-ISSN

  • Počet stran výsledku

    4

  • Strana od-do

  • Název nakladatele

    IEEE

  • Místo vydání

    Dubai

  • Místo konání akce

    Dubai, United Arab Emirates

  • Datum konání akce

    6. 3. 2017

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000406006100002