Using local climate zones to compare remotely sensed surface temperatures in temperate cities and hot desert cities
Author:
Fricke Cathy1, Pongrácz Rita2, Gál Tamás1, Savić Stevan3, Unger János1
Affiliation:
1. Department of Climatology and Landscape Ecology , University of Szeged , Szeged , Hungary 2. Department of Meteorology , Eötvös Loránd University , Budapest , Hungary 3. Climatology and Hydrology Research Centre , Faculty of Sciences , University of Novi Sad , Novi Sad , Serbia
Abstract
Abstract
Urban and rural thermal properties mainly depend on surface cover features as well as vegetation cover. Surface classification using the local climate zone (LCZ) system provides an appropriate approach for distinguishing urban and rural areas, as well as comparing the surface urban heat island (SUHI) of climatically different regions. Our goal is to compare the SUHI effects of two Central European cities (Szeged, Hungary and Novi Sad, Serbia) with a temperate climate (Köppen-Geiger’s Cfa), and a city (Beer Sheva, Israel) with a hot desert (BWh) climate. LCZ classification is completed using WUDAPT (World Urban Database and Access Portal Tools) methodology and the thermal differences are analysed on the basis of the land surface temperature data of the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor, derived on clear days over a four-year period. This intra-climate region comparison shows the difference between the SUHI effects of Szeged and Novi Sad in spring and autumn. As the pattern of NDVI (Normalised Difference Vegetation Index) indicates, the vegetation coverage of the surrounding rural areas is an important modifying factor of the diurnal SUHI effect, and can change the sign of the urban-rural thermal difference. According to the inter-climate comparison, the urban-rural thermal contrast is the strongest during daytime in summer with an opposite sign in each season.
Publisher
Walter de Gruyter GmbH
Reference60 articles.
1. BARTESHAGI KOC, C., OSMOND, P., PETERS, A., IRGER, M. (2018): Understanding land surface temperature differences of Local Climate Zones based on airborne remote sensing data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11: 2724–2730. 2. BECHTEL, B., ALEXANDER, P. J., BÖHNER, J., CHING, J., CONRAD, O., FEDDEMA, F., MILLS, G., SEE, L., STEWART, I. (2015): Mapping Local Climate Zones for a worldwide database of the form and function of cities. ISPRS International Journal of Geo-Information, 4: 199–219. 3. BECHTEL, B., DANEKE, C. (2012): Classification of Local Climate Zones based on Multiple Earth observation data. IEEE Journal Selected Topics in Applied Earth Observation and Remote Sensing, 99: 1–5. 4. BECHTEL, B., ALEXANDER, P., BECK, C., BÖHNER, J., BROUSSE, O., CHING, J., DEMUZERE, M., FONTE, C., GÁL, T., HIDALGO, J., HOFFMANN, P., MIDDEL, A., MILLS, G., REN, C., SEE, L., SISMANIDIS, P., VERDONCK, M. L., XU, G., XU, Y. (2019): Generating WUDAPT Level 0 data – Current status of production and evaluation. Urban Climate, 27: 24–45. 5. BECK, H. E., ZIMMERMANN, N. E., MCVICAR, T. R., VERGOPOLAN, N., BERG, A., WOOD E. F. (2018): Present and future Köppen-Geiger climate classification maps at 1-km resolution. Scientific Data, 5: 180–214.
Cited by
18 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|