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Climate change, combined with rapid urbanization, can face many challenges in achieving urban ecological sustainability, especially in developing countries. Due to the lack of valuable data, measuring the negative impact of this urban environmental damage, particularly in African cities, is however difficult to investigate. In this context, this research proposes an efficient index, including environmental, societal, and topographic indicators, extracted from remote sensing data, to evaluate the spatial ecological vulnerability of Tangier city in Morocco. This composite index, called the Urban Ecological Quality Index (UEQI), was developed for 2002, 2013, and 2023 in the spring season, using the Principal Component Analysis (PCA) as a multivariate statistical technique. Furthermore, the spatial autocorrelation analysis of the UEQI was performed to study the correlation between the index values and its surroundings, using Global Moran’s I and Local Moran’s I test statistics. The results show that on the one hand, zones located in the center of the city kept poor ecological quality in the three studied years, where the lack of green spaces and the high population density are the main reasons for this bad state. On the other hand, climate variability, such as precipitation change, directly affects the ecological quality of Tangier city. In fact, from 2002 to 2013, due to Morocco’s increased precipitation during this decade, the UEQI improved in 36%, unchanged in 50%, and degraded in 14% of the study area. However, from 2013 to 2023, with more than 52% degraded UEQI, the ecological quality of the city was affected by drought periods, which have been more frequent and intense in this decade, especially in green areas and agricultural land.
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Tom
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204--217
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Bibliogr. 46 poz., rys., tab.
Twórcy
autor
- Laboratory of Geosciences, Water and Environment, Department of Earth Sciences, Faculty of Sciences, Mohammed V University in Rabat, Morocco
autor
- School of Architecture, Planning and Design, Mohammed VI Polytechnic University, Benguerir, Morocco
autor
- Laboratory of Geosciences, Water and Environment, Department of Earth Sciences, Faculty of Sciences, Mohammed V University in Rabat, Morocco
autor
- School of Architecture, Planning and Design, Mohammed VI Polytechnic University, Benguerir, Morocco
autor
- School of Architecture, Planning and Design, Mohammed VI Polytechnic University, Benguerir, Morocco
autor
- Laboratory of Geosciences, Water and Environment, Department of Earth Sciences, Faculty of Sciences, Mohammed V University in Rabat, Morocco
autor
- Laboratory of Geosciences, Water and Environment, Department of Earth Sciences, Faculty of Sciences, Mohammed V University in Rabat, Morocco
Bibliografia
- 1. Anselin, L. 1995. Local Indicators of Spatial Association – LISA. Geographical Analysis. 27, 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
- 2. Artis, D.A., Carnahan, W.H. 1982. Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12(4), 313–329. https://doi.org/10.1016/0034-4257(82)90043-8
- 3. Assaye, R., Suryabhagavan, K.V., Balakrishnan, M., Hameed, S. 2017. Geo-Spatial Approach for Urban Green Space and Environmental Quality Assessment: A Case Study in Addis Ababa City. Journal of Geographic Information System, 9, 191–206. https://doi.org/10.4236/jgis.2017.92012
- 4. Azyat, A., Raissouni, N., Achhab, N.B., Chahboun, A., Lahraoua, M., Elmaghnougi, I., Sebbah, B., Ismaili, I.A. 2018. Urban Parks Spatial Distribution Analysis and Assessment Using GIS and Citizen Survey in Tangier City, Morocco (2015 Situation). Advances in Intelligent Systems and Computing. Vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-11928-7_55
- 5. Bahi, H. ; Rhinane, H.; Bensalmia, A.; Fehrenbach, U.; Scherer, D. 2016. Effects of Urbanization and Seasonal Cycle on the Surface Urban Heat Island Patterns in the Coastal Growing Cities : A Case Study of Casablanca, Morocco. Remote Sensing. 8(10), Article 10. https://doi.org/10.3390/rs8100829
- 6. Bouramtane, T., Kacimi, I., Bouramtane, K., Aziz, M., Abraham, S., Omari, K., Valles, V., Leblanc, M., Kassou, N., El Beqqali, O., Bahaj, T., Morarech, M., Yameogo, S., Barbiero, L. 2021. Multivariate Analysis and Machine Learning Approach for Mapping the Variability and Vulnerability of Urban Flooding : The Case of Tangier City, Morocco. Hydrology, 8(4), Article 4. https://doi.org/10.3390/hydrology8040182
- 7. Chai, N. Mao, C. 2022. Population management in an urban center using the dynamic integrated solution for an adequate atmospheric environmental quality. Environmental Research. 205, 112482. https://doi.org/10.1016/j.envres.2021.112482
- 8. Farr, T.G., Kobrick, M. 2000. Shuttle Radar Topography Mission Produces a Wealth of Data. Eos, Transactions American Geophysical Union., 81, 583–585. https://doi.org/10.1029/EO081i048p00583
- 9. Feola, G., Suzunaga, J., Soler, J., Wilson, A.D. 2020. Peri-urban agriculture as quiet sustainability: Challenging the urban development discourse in Sogamoso, Colombia. Journal of Rural Studies, 80, 1–12. https://doi.org/10.1016/j.jrurstud.2020.04.032
- 10. Gao, B.-C. 1996. NDWI – A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58(3), 257–266. https://doi.org/10.1016/S0034-4257(96)00067-3
- 11. He, C., Shi, P., Xie, D., Zhao, Y. 2010. Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach. Remote Sensing Letters, 1(4), 213–221. https://doi.org/10.1080/01431161.2010.481681
- 12. High Commissioner for Planning. 2014. General Census of Population and Housing 2014. Regional series of the Tangier-Tetouan-Al Hoceima region.
- 13. High Commissioner for Planning. 2018. Projections of the population of regions and provinces 2014–2030. https://www.hcp.ma/region-tanger/Projections-de-la-population-des-provinces-et-prefectures-de-la-region-TTA_a322.html
- 14. Huete, A.R. 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment. 25(3), 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
- 15. Iwaniak, A., Hrynkiewicz, M., Bucholska, J., Darewicz, M., Minkiewicz, P. 2018. Structural characteristics of food protein-originating di- and tripeptides using principal component analysis. European Food Research and Technology. 244(10), 1751–1758. https://doi.org/10.1007/s00217-018-3087-3
- 16.Joseph, M., Wang, F., Wang, L. 2014. GIS-based assessment of urban environmental quality in Port-au-Prince, Haiti. Habitat International. 41, 33–40. https://doi.org/10.1016/j.habitatint.2013.06.009
- 17. Kaiser, H.F. 1960. The Application of Electronic Computers to Factor Analysis. Educational and Psychological Measurement. 20(1), 141–151. https://doi.org/10.1177/001316446002000116
- 18. Kamp, I., Leidelmeijer, K., Marsman, G., Hollander, A.E. 2003. Urban environmental quality and human well-being Towards a conceptual framework and demarcation of concepts; a literature study. Landscape and Urban Planning. 65, 5–18. https://doi.org/10.1016/S0169-2046(02)00232-3
- 19. Kazemzadeh-Zow, A., Boloorani, A.D., Samany, N.N., Toomanian, A., Pourahmad, A. 2018. Spatiotemporal modelling of urban quality of life (UQoL) using satellite images and GIS. Int. J. Remote Sens. 39, 6095–6116. https://doi.org/10.1080/01431161.2018.1447160
- 20. Li, G. 2007. Measuring the Quality of Life in City of Indianapolis by Integration of Remote Sensing and Census Data. International Journal of Remote Sensing - INT J REMOTE SENS. 28. https://doi.org/10.1080/01431160600735624
- 21. Liang, S., Shuey, C.J., Russ, A.L., Fang, H., Chen, M., Walthall, C.L., Daughtry, C.S., Hunt, B.R. 2003. Narrowband to broadband conversions of land surface albedo: II. Validation. Remote Sensing of Environment. Volume 84, Issue 1, Pages 25–41. https://doi.org/10.1016/S0034-4257(02)00068-8
- 22. Liu, H., Cui, W., Zhang, M. 2022. Exploring the causal relationship between urbanization and air pollution : Evidence from China. Sustainable Cities and Society. 80, 103783. https://doi.org/10.1016/j.scs.2022.103783
- 23. Lo, C.P. 1997. Application of LandSat TM data for quality of life assessment in an urban environment. Computers, Environment and Urban Systems. 21(3), 259–276. https://doi.org/10.1016/S0198-9715(97)01002-8
- 24. López, E.; Bocco, G.; Mendoza, M.; Duhau, E. 2001. Predicting land-cover and land-use change in the urban fringe : A case in Morelia city, Mexico. Landscape and Urban Planning. 55(4), 271–285. https://doi.org/10.1016/S0169-2046(01)00160-8
- 25. Malah, A., Bahi, H. 2022. Integrated multivariate data analysis for Urban Sustainability Assessment, a case study of Casablanca city. Sustainable Cities and Society. 86, 104100. https://doi.org/10.1016/j.scs.2022.104100
- 26. Malah, A., Bahi, H., Radoine, H., Maanan, M., Mastouri, H. 2022. Assessment of Urban Environmental Quality: A Case Study of Casablanca, Morocco. ISPRS – International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, XLVI-4/W3-2021, 205–210. https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-205-2022
- 27. Martin, D., 1996. An assessment of surface and zonal models of population. Int. J. Geograph. Informat. Syst. 10, 973–989.
- 28. Merschdorf, H., Hodgson, M.E. Blaschke, T. 2020. Modeling Quality of Urban Life Using a Geospatial Approach. Urban Science, 4, 5. https://doi.org/10.3390/urbansci4010005
- 29. Musse, M.A., Barona, D.A., Rodríguez, L.M. 2018. Urban environmental quality assessment using remote sensing and census data. Int. J. Appl. Earth Obs. Geoinformation.71, 95–108.https://doi.org/10.1016/j.jag.2018.05.010
- 30. Nardo, M., Saisana, M., Saltelli, A., Tarantola, S. 2005. Tools for Composite Indicators Building. EUR 21682 EN. 2005. JRC31473. https://publications.jrc.ec.europa.eu/repository/handle/JRC31473
- 31. Pacione, M. 2003. Urban environmental quality and human wellbeing—a social geographical perspective. Landscape and Urban Planning, 65, 19–30.
- 32. Paweł, P., Marek, P., Elżbieta, D. 2019. Evaluation of the location of cities in terms of land cover on the example of Poland. Urban Ecosystems, 22, 619–630. https://doi.org/10.1007/s11252-019-00848-8
- 33. Pesaresi, M., Politis, P. 2022a. GHS-BUILT-S R2022A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030). European Commission, Joint Research Centre (JRC). https://doi.org/10.2905/D07D81B4-7680-4D28-B896-583745C27085
- 34. Pesaresi, M., Politis, P. 2022b. GHS-BUILT-H R2022A - GHS building height, derived from AW3D30, SRTM30, and Sentinel2 composite (2018). European Commission, Joint Research Centre (JRC). https://doi.org/10.2905/CE7C0310-9D5E-4AEB-B99E-4755F6062557
- 35. Pramanik, S., Areendran, G., Punia, M., Sahoo, S.K. 2021. Spatio-temporal pattern of urban eco-environmental quality of Indian megacities using geo-spatial techniques. Geocarto International. 37, 5067–5090. https://doi.org/10.1080/10106049.2021.1903578
- 36.Roy, S., Bose, A., Majumadar, S., Roy Chowdhury, I., Abdo, H.G., Almohamad, H., Abdullah Al Dughairi, A. 2022. Evaluating urban environment quality (UEQ) for Class-I Indian city: An integrated RS-GIS based exploratory spatial analysis. Geocarto International. https://doi.org/10.1080/10106049.2022.2153932
- 37. Schiavina, M., Freire, S., MacManus, K. 2022. GHS-POP R2022A - GHS population grid multitemporal (1975–2030). European Commission, Joint Research Centre (JRC). https://doi.org/10.2905/D6D86A90-4351-4508-99C1-CB074B022C4A
- 38. Sousa, J.A., Sales, J.C., Silva, D.C., Silva, R.C., Lourenço, R.W. 2021. Developing Of An Urban Environmental Quality Indicator. Geography, Environment, Sustainability, Vol.14, No 2, p. 30–41. https://doi.org/10.24057/2071-9388-2020-210
- 39. Sun, Z., Wang, C., Guo, H., Shang, R. 2017. A Modified Normalized Difference Impervious Surface Index (MNDISI) for Automatic Urban Mapping from Landsat Imagery. Remote. Sens., 9, 942. https://doi.org/10.3390/rs9090942
- 40. Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150. https://doi.org/10.1016/0034-4257(79)90013-0
- 41. UN. 2007. State of World Population 2007. United Nations Population Fund. https://www.unfpa.org/publications/state-world-population-2007
- 42. UN. 2010. State of African Cities 2010 , Governance, Inequalities and Urban Land Markets | UN-Habitat. https://unhabitat.org/state-of-african-cities-2010-governance-inequalities-and-urban-land-markets-2
- 43. UN. 2022. World Population Prospects – Population Division, United Nations. https://population.un.org/wpp/
- 44. Weng, Q. 2012. Remote sensing of impervious surfaces in the urban areas : Requirements, methods, and trends. Remote Sensing of Environment. 117, 34–49. https://doi.org/10.1016/j.rse.2011.02.030
- 45. World Bank. 2021. Morocco | Data. https://data.worldbank.org/country/MA
- 46. Xu, H. 2006. Modification of Normalized Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery. International Journal of Remote Sensing, 27, 3025–3033. https://doi.org/10.1080/01431160600589179
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-201107ee-80cb-401c-9dc5-615915a2e746