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International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 11, Issue 6, June 2020, pp. 143-155, Article ID: IJARET_11_06_013

Available online athttp://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=11&IType=6

ISSN Print: 0976-6480 and ISSN Online: 0976-6499

DOI: 10.34218/IJARET.11.6.2020.013

© IAEME Publication Scopus Indexed

URBANIZATION AND ITS IMPACT ON LAND

SURFACE TEMPERATURE CHANGES USING

LANDSAT IMAGE IN DAKHLA CITY,

MOROCCO

S. Hafoud*

Laboratory of the Engineering and Applied Technologies, Higher School of Technology,

Sultan Moulay Slimane University, Beni Mellal - Morocco

K. Boutoial



A. Oussama

Spectro-Chemometrics and Environment laboratory; Faculty of Science and Technology.

Sultan Moulay Slimane University, Beni Mellal - Morocco.

FZ. Mahjoubi



F. Kzaiber



*Correspondence Author Email: [email protected]

ABSTRACT

This work is part of a national strategy for sustainable urban development to offer

more rational information for urban planning and help regional planners in

appropriate land use planning and sustainable development policies.

This paper investigates the effects of urbanization on land surface temperature

LST variation of Dakhla city (Morocco), using two sensors (Thematic Mapper (TM)

and Operational Land Imager (OLI)). Images are also used to analyse the urban

landscape and their impact on the thermal environment using the processing of

Landsat satellite images over the 1984–2018 periods.

The results show that the urban landscape grew by almost 85.79% which may be

explained by the increase of urban population and economic development respectably.

Urbanization and its Impact on Land Surface Temperature Changes Using Landsat Image in

Dakhla City, Morocco


Moreover, these results indicate that the higher land surface temperature (LST) is

observed in the urban areas, whereas the lowest in vegetal areas in this period of

study. This study reveals a positive correlation between the urban land expansion and

LST, which affirms that LST is affected positively by the urban land expansion.

Key words: Urban lands cover, Dakhla city, LST

Cite this Article: S. Hafoud, K. Boutoial, A. Oussama, FZ. Mahjoubi, F. Kzaiber,

Urbanization and its Impact on Land Surface Temperature Changes Using Landsat

Image in Dakhla City, Morocco, International Journal of Advanced Research in

Engineering and Technology, 11(6), 2020, pp. 143-155.

http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=11&IType=6

1. INTRODUCTION

Nowadays, more than 65% of the Moroccan population live in urban areas, the growth of

urbanization has a significant impact on land use by replacing areas of vegetation with

residential and commercial areas and their related infrastructure led to changes in LST ([1]

;[2]).

Several studies have examined the effect of land use/land cover and urbanization index on

LST. These studies have highlighted, a significant relationship patterns between the

urbanization index and the LST variation increases ([1]; [3]; [4]; [5];[6]) and a positive

correlation between urban density and a noteworthy increase in LST in urban areas ([7]; [8]).

The LST can change due to reduction of vegetative cover according to Khandelwal et al.,

2010 [9], which clearly indicates that urbanization leads to a reduction of vegetative cover and

consequent increase in LST. Other researches indicated that land surface temperature (LST)

can be used as an indicator of the environment changes and represent an important factor to

study the terrestrial ecosystems and their relationship with the physical, chemical, and

biological earth's surface.

Although numerous methods have been proposed to collect land use data, remote satellite

technologies have approved their ability to offer accurate and appropriate information on land

use distribution. Supported by Geographic Information Systems (GIS), satellite images allow

for the estimation and analysis of changes and trends.

LST has been calculated from different satellite data such as Landsat Thematic Mapper

(TM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and

Thermal Infrared (TIR). While Faqe et al., 2017 [1] and Vorovencii et al., 2013 [10] propose

the use of Landsat TM thermal images to estimate LST on smaller surfaces.

It is evident today that the urban development of tomorrow cannot be through the

continuation of the practices of the past. It can no longer rely on the single principle of

economic growth and territorial expansion, without taking into account the effects on the

quality of life, social development, or the balance between ecosystems. For these reasons and

to help planners and regional urban to integrate a sustainable urbanization policies, this study

seeks to investigates the effects of urbanization on land surface temperature variation in

Dakhla city (Morocco), using two sensors (Thematic Mapper (TM) and Operational Land

Imager (OLI)). Images were also used to analyse the urban landscape and their impact on the

thermal environment using the processing of Landsat satellite images over the 1984–2018

period.

S. Hafoud, K. Boutoial, A. Oussama, FZ. Mahjoubi, F. Kzaiber


2. MATERIALS AND DATA

2.1. Study Area

Dakhla city is located in the extreme south of Morocco slightly north of the tropic of Cancer

(23 ° 43 North latitude and 15 ° 56 West longitude), 530 as the crow flies (637.5 km by road

or 9 hours) south of Laâyoune, 1500 Km from the capital Rabat. The city grows on a narrow

peninsula, the Rio de Oro peninsula, which extends for about 40 km and wide parallel to the

Atlantic coast, direction north-east south-west. This exceptional site delimits a bay of about

400Km2 (Figure1) [11].

The climate in study area is characterized by an arid temperate climate under the effects of

the cold sea current of the Canary Islands and by high thermal amplitudes between day and

night. The temperatures in this band are generally average and stable during the year are

moderate with a maximum temperature of 40° C in summer and an average temperature of

20° C. The Dakhla peninsula is an exception, the average annual temperature is 25°C.

Precipitation is low with an annual average of 30 mm, however the rains are irregular and

there may be peaks at 100 mm annual, is marked essentially by high humidity giving rise to a

dew at night [12].

Figure 1 Geographical location of the region of Dakhla Oued Eddahab

2.2. Data

In the present study, the data sets were timely collected using two sensors (Thematic Mapper

(TM) and Operational Land Imager (OLI)), received from Landsat satellite images taken on

July 25, 2018. According to their availabilities and the dates adequate to the objectives of the

work (between October and January of the years 1984, 1995, 2006, 2010 and 2018): the

atmosphere is relatively clear which makes pre-processing and processing of satellite images

easy as well as the comparison of the land surface for different months makes no sense (the

coldest months will mark ground temperatures less than those of the warm months). The

processing of downloaded satellite images was based on the image correction technique. The

latter has been used for many years in remote sensing to effectively display the colors of the

land surface temperatures. It also provides a tool for estimating the urban area. Table 1,

summarizes some characteristics of the satellite images used in this work.

The software used to conduct image processing included Environment for Visualizing

Images (ENVI), ArcGIS version 10.3.




Table 1 Information about Landsat images used in this study.

Characteristics

Dates of the

images

Sensor Band Date

Spatial

Resolution

(m)

Radiometric

performance

UTM

zoned

1984

1995

2006

2010

Landsat

4-5 TM

7

1984-06-20

1995-01-08

2006-11-22

2010-01-17

30 8 bits 28

2018 Landsat

8 OLI

9 2018-01-18

30

(Band 8 : 15m) 16 bits 28

3. METHODS

3.1. Urban Land Classification

Fonseka et al., 2019 [8], have used a supervised classification of urban land cover, we

developed land cover maps with Figures which permitted us to appreciate the evolution of the

different classes in our study area.

The supervised classification process begins with the selection the radial basis function for

mapping the data onto a binary separable hyperplane and cross-validating the settings of two

key parameters: Gramma in the RBF, and the penalty (C); then, using the one-against-the-rest

strategy to identify one land cover class. Afterward, the images were classified into: urban,

vegetation, water and Bare Land.

3.2. Land Surface Temperature Calculation

Fonseka et al., 2019 [8] and Zhang et al., 2017 [13], used the radiative transfer equation to

calculate land surface temperature from the Landsat data. This method consists of three steps.

Step 1: The pixels of the images were converted into spectral radiation at the sensor (Lλ)

using Eq:

[( )

( )] ( ) (1)

Where: Lλis the Top-of-Atmosphere (TAO ) radiance image of the thermal band, Lmax and

Lmin are the radiometric calibration parameters, Qcal is the pixel digital number for thermal

band.

Lλ=MLQcal+AL (2)

Where: ML is the band-specific multiplicative rescaling factor,ALis the band-specific

additive rescaling factor. Lλ and Qcal in (2) are the same as those in (1).

Step 2: Is to convert TOA radiance of the thermal band. The surface-leaving radiance LT is

calculated as follows:

LT = (Lλ− Lμ− τ (1 − ε)Ld)/τε (3)

Where:

Lμ: the upwelling radiance,τ : atmospheric transmission , Ld:downwelling radiance, ε is

the emissivity of the surface related to the target type. Therefore, ε is the emissivity map of

the surface with 30 m resolution.

Step 3: The radiance is converted to LST using the Landsat-specific estimate of the Planck

curve as follows.



(

)

(4)

Where K1 and K2 are calibration constants

3.3. The Effect of Urban Land Expansion on LST

To investigate the relationship between annual LST and urban area, a correlation analysis was

used to study this relationship. The analyses are deduced from the linear regression relation.

The correlation coefficient is also calculated to verify the nature and magnitudes of the trends

and significance.

4. RESULTS

4.1. Cartography of Urbanization in Dakhla City

4.1.1. The Urban Land Cover changes in Dakhla

The satellite images disclose an urban expansion in Dakhla in the last 34 years (Figure 2), the

areas of different land covers, and their changes were calculated, and are shown in Figure 3.

The results show an increase in urban areas on the period of study and a decrease in Bare

Lands areas, while the vegetation cover remains reduced, which explains the fact that bare

lands have been replaced by other surfaces urban.

Figure 2 The urban land cover classification results in Dakhla city from 1984 to 2018




Figure 3 Urban land cover change in Dakhla city from 1984 to 2018

(Source: Calculate from satellite images)

4.1.2. Demographics and Urbanization Evolution

The urban area and demographic evolution are summarized in Figure 4, a significant increase

in the urban areas and demographic evolution since 1982 to 2018. It has shown an important

population growth, which increased 12 times between in the same period of study ([12];[14] )

.

Figure 4 Presentation of the urban area in relation to the demographic evolution in Dakhla city [2].

4.1.3. Cartography of the Land Surface Temperature (LST) of Dakhla City

The analysis of Landsat images of the land surface temperature (LST) of the Dakhla city are

presented in Figure 5. It shows a clear increase in LST from 1984 to 2018, the annual

temperature values of LST for each class is calculated and detailed in Figure 6.

The study reveals that the higher temperature has been marked in the urban areas, whereas

the lowest temperature values were observed in vegetal areas. This is consistent with the

results of ([7]; [8]; [15]; [16]; [17]). The LST of the vegetal, Bare Land and urban area were

increased from 23.60 to 35.90 °C, 26.97°C to 40.50°C and 27.40°C to 44.06°C respectively

from 1984 to 2018.

0

10

20

30

40

50

60

1984 1995 2006 2010 2018

Are

a (

km2)

Urban

Vegetation and algue

Bare lands

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

0

5

10

15

20

25

30

35

40

45

50

1980 1985 1990 1995 2000 2005 2010 2015 2020

De

mo

graph

ic evo

lutio

n (in

hab

itant)

urb

aniz

ed

are

a (k

m2

)

Years

urbanized area

Demographic evolution

Groissance of the

populatipon 12 times more

1982/2018

Low population density

(<1 inhabitant/ Km²)

( Source monographie

Highest rate of

demographic change at the

national level (10.5%)

( Source monographie

Highest urbanization rate

at the national level of

around 85,79%








Figure 5 Maps of annual Land Surface Temperature in Dakhla city from 1984 to 2018

Figure 6 Annual variation of Land Surface Temperature in different classes in Dakhla city from 1984

to 2018, calculated from satellite images

5. DISCUSSION

5.1. Urban Evolution in Dakhla City

The urban evolution from 1984 to 2018 detected by satellite images indicated that the urban

landscape grew by almost 85.79%, which may be explained by the conversion of large areas

of bare land to an urban area, due to the increase in urban population and economic

0

5

10

15

20

25

30

35

40

45

50

1984 1995 2006 2010 2018

LS

T (◦C

)

Year

vegetal area

Bare Land area

urban area




development. According to the Moroccan Census of Population and Housing (RGPH), the

population of Dakhla city has grown from 17 309 in 1982 to 129 375 inhabitants in 2018,

with an annual rate of 6% between 1982 and 2018. The urbanized areas have increased from

the 13.73 to 42.9 km2 in the same period. Indeed, the value of the urbanization rate of the last

year studied (85.79%) is higher compared with the national urbanization rate of 60.3% ([2];

[12]).

In this context, to reply to these changes in population and urbanization in the city of

Dakhla, the State and its associates have launched several emergency programs to fill the

housing deficit and create a shelter for the city.

The analysis achieved in Figure 3 revealed the poverty of Dakhla city in vegetation land

cover. Despite the efforts made by planners and elected officials who make a notable effort,

but the indicators of green space per capita are still low. According to Ajbilou, 2005 [18] the

vegetation land cover in the urban desert environment has a particular meaning due to the

difficult conditions of the desert environment, while Dakhla city suffers from water stress,

high evaporation, high salinity levels (1-10 g/l), and arid climate, ([12])

5.2. LST in Land Cover changes of Dakhla City

The study of the effect of urbanization on land-surface temperature (LST) in Dakhla city in

the last 34 years, showed a variation value of 16.66°C in the urban areas from 1984 to 2018,

12.30°C in the vegetal area and 13.53 °C in the bare land area in the same period of study.

These results indicate that the temperature of urban areas is higher than the LST in the vegetal

area ones. These obtained results are confirmed by other studies in different cities of the

world ([1] ;[8] ; [10] ; [15]; [19] ). Although these differences in LST can be explained by the

fact that the vegetation has the capability of evaporating, this helps to accelerate the

progression of heat transfer between land surface and atmosphere. Furthermore, this is

explained by the fact that construction materials absorb and hold heat and evaporate less,

which causes an increase in LST in urban areas ([4] ; [9] ;[10] ;[13] ; [15] ;[20] ).

5.3. The Effect of Urban Land Expansion on LST of Dakhla City

The results obtained in Figure 7, indicate that the expansion of urban land cover is directly

proportional to the LST increase. The results are consistent with a previous study [5]. The

correlation is applied to explain the relationship between the land surface temperature and the

urbanization of Dakhla from 1984 to 2018.

The linear regression analysis for annual LST and urban land cover change could be

addressed as y = 0.495x + 18.862 (R2 = 0.831), where y is LST and x is the urbanization area

in km2.

The analysis of the linear regression result indicates that there is a significant linear

heating, with 5.7°C heating of LST produced by an increase in the urban evolution by 10 km2.

The correlation coefficient calculated is 91%, which indicates that the LST is or has been

affected positively by the urban land expansion. The results are consistent with a previous

study ([1] ; [3] ; [4] ; [5] ; [6] ;[9] ; [13];[21]).



Figure 7 The cover of land and Annual LST in Dakhla city from 1984 to 2018

Figure 8 The relationship between annual LST and the urban area in Dakhla city from 1984 to 2018

6. CONCLUSION

According to the obtained results, the following conclusions can be deduced from this study:

First, Dakhla city has experienced rapid urbanization in the 34 last years. The satellite

images indicated that the urban landscape grew by almost 85.79% which may be explained by

the increase in both urban population and economic development. Moreover, the city suffers

from poverty in vegetation land cover.

Second, this study demonstrates that the variation value of LST in Dakhla city from 1984

to 2018, of the urban area, reached 16.66 °C while in the vegetal area this value reached

12.30°C.

Third, the results obtained show that LST is affected positively by the urban land

expansion and the correlation coefficient calculated is 91%. The outcome is a significant

0

5

10

15

20

25

30

35

40

45

50

0

5

10

15

20

25

30

35

40

45

50

1980 1990 2000 2010 2020

LS

T U

rbain

(◦C)

urb

an a

rea

(km

2)

Years

urban area (km2) LST Urbain (◦C)

y = 0.495x + 18.862

R² = 0.8315

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25 30 35 40 45 50

LS

T U

rbai

n (

◦C)

Urban Area en Km2

LST Urbain (◦C) Linear (LST Urbain (◦C))




linear warming, with 5.7°C heating of LST produced by an increase in the urban evolution by

10 km2.

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URBANIZATION AND ITS IMPACT ON LAND SURFACE … › MasterAdmin › uploadfolder › IJARET_11... · 2 days ago · urbanization has a significant impact on land use by replacing