Contribution of Landsat TM Data for the Detection ofUrban Heat Islands Areas Case of Casablanca
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Abstract
Casablanca, main metropolis of Morocco concentrates more than 46% of the working population. She is considered as the most affected city by the increase of the temperature. We have therefore chosen to base our study on the city of Ca- sablanca. The main objective of this study is to estimate the ground temperature in order to evaluate the impact of the vegetation on cooling the ground temperature. In order to move to the achievement and to identify the formation of is- lands of warmth or coolness which occur in the urban municipalities of Casablanca, we have used the satellites images Landsat 5 TM. Graphical analysis based on studying the correlation was performed to quantify the strength of the link between the coolest urban surfaces and the green spaces. To achieve this, we used “mono-window” algorithm which re- quires knowledge of the atmospheric transmittance, the emissivity of soil and the effective temperature of the air. This study revealed a strong correlation between vegetation cover and cold areas (R2 = 0.911) and allowed us to determine graphically that there is a strong link between the urban ground temperature and the density of buildings.
- Haut-Commissariat au Plan, “Les villes Marocaines Face au Changement Climatique. Le Maroc en Perspective: Regards Croisés,” Les Cahiers de l’IAU ?dF, No. 154, 2010, p. 87.
- J. Zhang and Y. Wang, “Study of the Relationships between the Spatial Extent of Surface Urban Heat Islands and Urban Characteristic Factors Based on Landsat ETM+ Data,” Sensors, Vol. 8, No. 11, 2008, pp. 7453- 7468. doi:10.3390/s8117453
- S. Gadal, “Télédétections Thermiques Infrarouges des Concentrations Urbaines au Maroc,” Cybergeo: European Journal of Geography, Cartographie, Imagerie, SIG, Article 421, 2008.
- A. Asmat, S. Mansor and W.-T. Hong, “Rule Based Classification for Urban Heat Island Mapping,” Proceedings of the 2nd FIG Regional Conference Marrakech, Morocco, 2-5 December 2003.
- V. Dubreuil, C. Delahaye and A. Le Strat, “Dynamiques d'occupation et d’utilisation du sol et leurs impacts climatiques au Mato Grosso, Brésil,” Confins, No. 10, 2010, p. 16.
- Egis Bceom International/IAU-IDF BRGM, “Résumé exécutif Rapport Phase 1 Maroc,” 2005.
- http://www.tutiempo.net/en/Climate/Casablanca/08-01-2011/601550.htm
- Q. Weng, D. Lu and J. Schubring, “Estimation of Land Surface Temperature-Vegetation Abundance Relationship for Urban Heat Island Studies,” Remote Sensing of Environment, Vol. 89, No. 4, 2004, pp. 467-483. doi:10.1016/j.rse.2003.11.005
- W. P. du Plessis, “Linear Regression Relationships between NDVI, Vegetation and Rainfall in Etosha National Park, Namibia,” Journal of Arid Environments, Vol. 42, No. 4, 1999, pp. 235-260. doi:10.1006/jare.1999.0505
- A. Bannari, D.-C. He, D. Morin, et al., “Analyse de l’apport de deux Indices de Vegetation à la Classification dans les Milieux hétéRogènes,” Journal Canadien de Télédétection, Vol. 24, No. 3, 1998, pp. 233-239.
- V. M. Griend, A. A. Owe, H. F. Vugts, G. K. Ramothw and S. W. M. Peters, “Bostswanawater ans Surface Ene- Rgy Balance Research Program. Part 1: Integrated Ap- proach and Field Campaign Results,” BCRS Report N 91-38a, 1992.
- R. R. Irish, “Landsat 7 Science Data User’S Handbook,” National Aeronautics and Space Administration, Report 430-15-01-003-0, 2001.
- Z. Qin and A. Karnieli, “A Mono-Window Algorithm for Retrieving Land Surface Temperature from Landsat TM Data and Its Application to the Israel-Egypt Border Region,” International Journal of Remote Sensing, Vol. 22, No. 18, 2001, pp. 3719-3746. doi:10.1080/01431160010006971