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Urban Ecological Quality Assessment Based on Remote Sensing Data in African Context – A Case Study of Tangier City (Morocco, NW Africa)

Tahiri Mounia, Bahi Hicham, Bouramtane Tarik, Malah Anass, Sabri Anas, Mohsine Ismail, Kacimi Ilias

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 9

204--217

EN

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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Multivariate statistical characterization of groundwater quality in Fesdis, East of Algeria

Khelif S., Boudoukha A.

Journal of Water and Land Development

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2018

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no. 37

65--74

EN

This study is a contribution to the knowledge of hydrochemical properties of the groundwater in Fesdis Plain, Algeria, using multivariate statistical techniques including principal component analysis (PCA) and cluster analysis. 28 samples were taken during February and July 2015 (14 samples for each month). The principal component analysis (PCA) applied to the data sets has resulted in four significant factors which explain 75.19%, of the total variance. PCA method has enabled to highlight two big phenomena in acquisition of the mineralization of waters. The main phenomenon of production of ions in water is the contact water-rock. The second phenomenon reflects the signatures of the anthropogenic activities. The hierarchical cluster analysis (CA) in R mode grouped the 10 variables into four clusters and in Q mode, 14 sampling points are grouped into three clusters of similar water quality characteristics.

PL

Przedstawione w niniejszej pracy badania stanowią przyczynek do poznania właściwości hydrochemicznych wód gruntowych na równinie Fesdis w Algierii uzyskany z wykorzystaniem wieloczynnikowej analizy statystycznej, w tym analizy głównych składowych (PCA) i analizy skupień. Dwadzieścia osiem próbek wody pobrano w lutym i w lipcu 2015 r. (po 14 próbek w każdym miesiącu). Na podstawie analizy składowych głównych zastosowanej do zbioru danych stwierdzono cztery istotne czynniki, które objaśniały 75,19% całkowitej wariancji. Metoda PCA umożliwiła wyodrębnienie dwóch zjawisk odpowiedzialnych za mineralizację wody. Głównym czynnikiem tworzenia jonów w wodzie jest kontakt wody ze skałą (czas retencji mineralizacji). Drugi czynnik jest odzwierciedleniem aktywności człowieka. W hierarchicznej analizie skupień (CA) zgrupowano 10 zmiennych w cztery skupienia w trybie R, a w trybie Q zgrupowano 14 stanowisk pobierania próbek w trzy skupienia o podobnych cechach jakości wody.

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Evaluation of spatial and temporal variations of surface water quality in the Nile River Damietta branch

El-Tohamy W. S., Abdel-Baki S. N., Abdel-Aziz N. E., Khidr A. A.

Ecological Chemistry and Engineering. S

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2018

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Vol. 25, nr 4

569--580

EN

The objective of this study is to reveal the spatial and temporal variations of surface water quality in this part of the River Nile with respect to heavy metals pioneerution. Seventeen parameters in total were monitored at seven sites on a monthly basis from October 2013 to September 2014. The dataset was treated using the tools of univariate and multivariate statistical analyses. Cluster analysis showed three different groups of similarity between the sampling sites reflecting the variability in physicochemical characteristics and pollution levels of the study area. Six PCs factors were identified as responsible for the data structure explaining 91 % of the total variance. These were eutrophication factor (23.2 %), physicochemical factor (20.6 %), nutrients (16.3 %) and three additional factors, affected by alkalinity and heavy metals, recorded variance less than 15 % each. Also, the heavy metals pollution index (HPI) revealed that most of the calculated values were below the critical index limit of 100. However, two higher values (124.89 and 133.11) were calculated at sites V and VI during summer due to the temperature and increased run-off in the river system.

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Ocena zawartości metali ciężkich w osadach dennych wstępnej części zbiornika retencyjnego Stare Miasto na rzece Powie

Sojka M., Siepak M., Gnojska E.

Rocznik Ochrona Środowiska

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2013

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Tom 15, cz. 2

1916--1928

EN

The aim of this study was the assessment of spatial variability of heavy metals concentration in the Stare Miasto pre-dam reservoir on the Powa river. Sediment samples from 16 locations were collected and analyzed for the trace metal contents (Cr, Ni, Cu, Zn, Cd and Pb), organic carbon and grain size. The variability of heavy metal concentration in bottom sediments was assessed by multivariate statistical methods like cluster analysis (CA), factor analysis (FA) and principal components analysis (PCA). They made it possible to observe similarities and differences in trace metal content in samples taken from specific locations, to identify indicators suitable for characterizing its spatial variability and to uncover hidden factors accounting for the structure of the data. Data of the grain size indicated that sandy sediments dominated in the initial part of the pre-dam reservoir were the Powa river inflow. The mean concentrations of Zn 3.38 – 21.3 mg.kg-1 was the highest followed by Pb and Ni, 0.47 – 4.96 mg.kg-1 and 0.96 – 5.25 mg.kg-1 respectively, relative to other metals. The concentrations of Cu was 1.03 – 2.88 mg.kg-1 while Cd and Cr were the least 0.02 – 0.80 mg.kg-1 and 0.06 do 0.74 mg.kg-1 respectively. Cluster analysis CA of heavy metals content in bottom sediments of the reservoir showed that 16 samples of sediments can be divided into two groups characterized by different content of heavy metals. The analysis showed that the content of Cd, Pb, Ni, Cr and Zn were associated with content of clay and organic matter, depth of sampling and the sampling distance from the inflow point of the river. The concentration of the copper was associated with sampling distance from inflow and out flow point and the content of the silt.