Cartographie des températures à Tunis par modélisation statistique et télédétection

Tunis, with a population of 2.7 million, is located south of the Mediterranean Sea. Its topography and shape impacts its urban thermal field. Meteorological records given by network stations and mobile surveys have highlighted a multitude of parameters that explain the spatial variability of air tem...

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Main Authors: Sami Charfi, Salem Dahech
Format: Article
Language:Spanish
Published: OpenEdition 2018-02-01
Series:M@ppemonde
Subjects:
Online Access:https://journals.openedition.org/mappemonde/442
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author Sami Charfi
Salem Dahech
author_facet Sami Charfi
Salem Dahech
author_sort Sami Charfi
collection DOAJ
description Tunis, with a population of 2.7 million, is located south of the Mediterranean Sea. Its topography and shape impacts its urban thermal field. Meteorological records given by network stations and mobile surveys have highlighted a multitude of parameters that explain the spatial variability of air temperature. In addition, modelling and satellite images were used to estimate the values in areas without observations. Night-time situations were simulated and validated by brightness temperatures given by satellite image. The determination coefficient of the statistical model reaches 0.9 at night.
format Article
id doaj-art-0bc44cb1c7ff464d87771312fa7bcfd0
institution OA Journals
issn 0764-3470
1769-7298
language Spanish
publishDate 2018-02-01
publisher OpenEdition
record_format Article
series M@ppemonde
spelling doaj-art-0bc44cb1c7ff464d87771312fa7bcfd02025-08-20T02:21:20ZspaOpenEditionM@ppemonde0764-34701769-72982018-02-0112310.4000/mappemonde.442Cartographie des températures à Tunis par modélisation statistique et télédétectionSami CharfiSalem DahechTunis, with a population of 2.7 million, is located south of the Mediterranean Sea. Its topography and shape impacts its urban thermal field. Meteorological records given by network stations and mobile surveys have highlighted a multitude of parameters that explain the spatial variability of air temperature. In addition, modelling and satellite images were used to estimate the values in areas without observations. Night-time situations were simulated and validated by brightness temperatures given by satellite image. The determination coefficient of the statistical model reaches 0.9 at night.https://journals.openedition.org/mappemonde/442modellingremote sensingtemperatureTunis
spellingShingle Sami Charfi
Salem Dahech
Cartographie des températures à Tunis par modélisation statistique et télédétection
M@ppemonde
modelling
remote sensing
temperature
Tunis
title Cartographie des températures à Tunis par modélisation statistique et télédétection
title_full Cartographie des températures à Tunis par modélisation statistique et télédétection
title_fullStr Cartographie des températures à Tunis par modélisation statistique et télédétection
title_full_unstemmed Cartographie des températures à Tunis par modélisation statistique et télédétection
title_short Cartographie des températures à Tunis par modélisation statistique et télédétection
title_sort cartographie des temperatures a tunis par modelisation statistique et teledetection
topic modelling
remote sensing
temperature
Tunis
url https://journals.openedition.org/mappemonde/442
work_keys_str_mv AT samicharfi cartographiedestemperaturesatunisparmodelisationstatistiqueetteledetection
AT salemdahech cartographiedestemperaturesatunisparmodelisationstatistiqueetteledetection