MONITORING LANDUSE/LAND COVER CHANGE AND ITS …geoenv.du.ac.bd/wp-content/uploads/2019/04/04_Kaniz_Maksud_Landuse... · min is the minimum DN (0). L max and L min are the top of

MONITORING LANDUSE/LAND COVER CHANGE AND ITS SUBSEQUENT 51

51

Oriental Geographer

Vol. 59, No. 1 & 2, 2017

Printed in September 2018

MONITORING LANDUSE/LAND COVER CHANGE AND ITS

SUBSEQUENT EFFECTS ON URBAN THERMAL

ENVIRONMENTIN CHITTAGONG METROPOLITAN AREA: A

REMOTE SENSING AND GIS BASED ANALYSIS

Kaniz Farzana*1

M. MaksudurRahman**2

Abstract : The research is carried out to assess the relationship between the changes of

land use/land cover change and land surface temperature change and resulting urban heat

island effect. For the analysis of land use/land cover (LULC) change and to identify its

impact on the land surface temperature in Chittagong Metropolitan Area (CMA), one of

the major urban areas in Bangladesh, temporal Land sat (7ETM+ and 8OLI) imagery of

three time periods (1990, 2002 and 2015) has been used. The widely used Hybrid image

classification method was used to extract LULC categories. In addition, an image based

approach was used to extract land surface temperature of the respective years. As the

urban surface ambient temperature greatly varies from the surrounding area, resulting

urban heat island (UHI) was also estimated. To calculate the statistics of measurement

this research selected 300 random pixels (50 per each category) from each year’s LULC

maps. Contemporary ground truth data collected from different sources were used in

respect of the selected random pixels and finally obtained the results in the form of

accuracy assessment. Overall classification accuracy obtained for CMAwere 79.08 %

with Kappa 0.81. The statistics reveals a dynamic characteristic of LULC in the areas

where maximum fluctuation was observed in built-up area, vegetation and exposed land

category. Built-up areas show a continuous increasing trend in the city. Resulting land

surface temperature also shows fluctuation in each LULC category for different years.

Maximum increase of the mean surface temperature was observed in the built-up and

exposed land areas. Between 1990 to 2015 study periods the UHI area has been increased

by 160.9 ha/yr in CMP area which is a big concern. Maximum magnitude of UHI has

been found 7.09(◦C) which is very high. The findings of this research could provide

assistance in the efficient development of sustainable urban environment and policy

making in the effective use of the natural resources of the study area.

Keywords: Chittagong Metropolitan Area, Landuse/Land cover (LULC), Urban Heat

Island (UHI), Hybrid Image Classification, Remote Sensing, GIS, Landsat, Land Surface

Temperature (LST)

* Kaniz Farzana, PhD Student, Department of Plant and Soil Science, Collage of Agricultural Sciences and

Natural Resources, Texas Tech University, 2500 Broadway, Lubbock, TX 79409, USA

** M. Maksudur Rahman, PhD, Professor, Department Geography and Environment, University of Dhaka,

Dhaka 1000, Bangladesh

52 ORIENTAL GEOGRAPHER

INTRODUCTION

Urban Heat Island (UHI) refers to the phenomenon of higher atmospheric and surface

temperature occurring in urban areas comparing to the surrounding rural areas (Voogt

and Oke,2003). It is the results of major anthropogenic modification of earth surface

(Zhou et al.,2015). Landuse/Land cover change in an urban area is such kind of

modification which has direct impact on urban thermal environment.The variation in

landuse/land cover (LULC) has caused a substantial change in the spatiotemporal

patterns of the UHI in cities and towns due to the loss of waters bodies and vegetated

areas (Zhang et al., 2013, Ramachandra et al.,2015). At the same time a substantial

growth of built-up areas is transforming increasingly the landscape from natural cover

types to impervious surface and building up Urban Heat Island (Roy, 2012).The resulting

urban heat island is present in every town and city and it is the most obvious climatic

manifestation of urbanization (Landsberg, 1981).Precise monitoring of urbanization and

its impact on the environment has become indispensable for a wide array of applications :

Urban Planning, water and Land resource management, disaster management and climate

change research ( Weng, 2001;Roth, 2002;Zhou et al., 2004;Tang et al. 2005;Huang Wei

et al., 2014). As a result, there has been increasing interest in mapping and monitoring

urban land use/land cover change using different remote sensing techniques (Yeh and Li

1996; Mesev 1997; Carlson and Traci Arthur 2000; Ward et al., 2000; Herold et al.,

2003; Maktav et al., 2005; Yang, 2005; Wong and Yan 2008; El-Ashmawy et al., 2011).

Like any largest cities of the world, Chittagong City which is the second largest city of

Bangladesh has also witnessed severe landuse/land cover change and subsequent

temperature increase in the urban area over a long period of time.

In this paper, a precursory study of landuse/land cover change and urban heat island

change has been conducted.

STUDY AREA

Chittagongis the second largest city of Bangladesh famous for sea port(Khan and

Salehuddin, 1967). The Area is quite different from other cities and it’s unique natural

beauty characterized by hills, rivers, sea, forests and valleys (Rahman et al., 2001). The

Chittagong Metropolitan Area (CMA) is the heart of all commercial and business

activities.CMA, is situated within 22° 14′ and 22° 24′ 30″ north latitude and between 91°

46′ and 91° 53′ east longitude (Figure 1) and the total area of CMA is approximately 775

km2 (using Bangladesh Transverse Mercator projection). The city has an estimated

population of more than 4 million (BBS, 2011).

Chittagong is very different in terms of topography. The highest ground level within the

city area is about 60m above MSL (Mahmood and Khan, 2008). This coast city has very

distinctive topography and a wide range of landuse types. The city lands are under

continuous pressure due to rapid development measures and various types of activity

changes, which lead the city environment more susceptible to increasing population

pressure (Islam, 2003). The city has a humid sub-tropical monsoon climate with mean

annual rainfall nearly 2100 mm in the north and east and 2540 mm to 3800 mm in the

south and west (JAICA, 2000), more than 80% of which falls during the monsoon season


53

from June to September. The dry and cool season is from November to March; pre-

monsoon season is April-May and the monsoon season is from June to October.

Figure 1: Location of Study Area

Due to accommodate increasing population and haphazard development of economy and

life style of urban people during the last four decades, the city rapidly expanded mostly in

an unplanned way. The landuse pattern of Chittagong city is therefore irregular,

unclassified, and heterogeneous in character. Due to lack of enough land based data,

particularly the functional characterizes of urban lands it is difficult to classify the city

into specific landuse type. Despite all these limitations and methodological constrains, it

has been attempted to classify the city into different landuse zones.

MATERIALS AND METHODS

Land sat Image and Its Characteristics

The Land sat program offers the longest continuous global record of the Earth's surface.

It continues to deliver visually stunning and scientifically valuable images of our planet.

This research has used Land sat imagery of three different times for each study sites.

Land sat TM/ETM+ images over Chittagong city from 1990 to 2015 has been used. Six


clouds free and geometrically corrected images of both ETM and OLI sensors dated 16

January 1990 (TM), 27 December 2002 (ETM), 5 November 2015 for Chittagong

Metropolitan area were obtained as L1T format from the Earth Resources Observation

and Science (EROS) center through the USGS Global Visualization Viewer.

Table 1: Detail Information of collected land Sat image

Sensor Type Region Acquisition date

Landsat5 Chittagong 1990/1/16

Landsat7 ETM+ Chittagong 2002-12-27

Landsat8 (OLI) Chittagong 2015/11/5 Source: Information collected through land Sat image

Satellite Image Preprocessing

Satellite images were re-projected to the UTM WGS 84 N (29-North UTM zone) following

a 3rd order polynomial fit and nearest neighbor resampling techniques. Digital numbers (DN)

of Landsat7 ETM and Landsat8 OLI images are stored as 8 bits and 16 bit respectively

(Markham et al., 2006 and Roy et al., 2014).These DNs of each image were converted to the

top of atmospheric (TOA) spectral radiance using sensor specific calibration parameters

directly obtained from the image MTL (metadata) file following the standard spectral

radiance equation (Eq. 1).

𝐿 = 𝐴𝜌

1 − 𝜌𝑒𝑆 +

𝐵𝜌𝑒1 − 𝜌𝑒𝑆

+ 𝐿𝑎 ………………… (𝐸𝑞. 1)

Where, ρ is the pixel surface reflectance, ρe is an average surface reflectance for the pixel

and a surrounding region, S is the spherical albedo of the atmosphere, La is the radiance

back scattered by the atmosphere, A and B are coefficients that depend on atmospheric

and geometric conditions but not on the surface and L is the spectral radiance.The

radiance of the reflective bands was then converted to band interleaved by line (BIL)

format to make them efficient for the atmospheric correction process to reduce

atmospheric effects like water content, dust particles, aerosols, cloud, varying sun angles,

etc. which could significantly influence optical images and thereby degrade their spectral

information.Hence, these are subjected to an atmospheric correction process to be applied

to minimize those effects and produce corrected surface reflectance. The fast line-of-sight

atmospheric analysis of hypercubes (FLAASH) has been applied for the atmospheric

correction process.

FLAASH is as first principles of atmospheric correction tool which generally corrects

wavelengths of visible lights, near-infrared and shortwave infrared.

The overall FLASH method takes input from the radiance and provides output

atmospherically corrected surface reflectance image using through the Eq. 2.

𝐿𝑒 ≈ 𝐴 + 𝐵 𝜌𝑒

1 − 𝜌𝑒𝑆 + 𝐿𝑎 ………………… (𝐸𝑞. 2)


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In this equation, ρeand Le are atmospherically corrected surface reflectance and ground

radiance. The values of A, B, S and La are determined from the MODTRAN calculations

which initially uses the solar zenith angle, sun azimuth, mean surface elevation in

kilometer unit, specific atmospheric model, aerosol type and visibility range. We used the

tropical atmospheric model and maritime aerosol as MODTRAN input. The difference

between ρ and ρe in the above equations stands for the adjacency effect caused by

atmospheric scattering.

Figure 2: Reflectance map of Chittagong Metropolitan Area for the year 1990, 2002 and 2015 respectively

Source: Land sat image processed by researcher

Land Surface Temperature and Urban Heat Island retrieval

In this study, an image-based approach (Lo and Quattrochi, 2003; Weng, 2001) has been

applied to retrieve land surface temperature of different years from satellite images. The

DNs of the TIR bands of each year ETM images were converted to spectral radiance

using the formula adopted by Chander and Markham, 2003) (Eq. 3) and OLI images were

converted using USGS standard equation (Eq. 4).

𝐿𝜆 = 𝐿𝑚𝑖𝑛 +𝐿𝑚𝑎𝑥 − 𝐿𝑚𝑖𝑛

𝑄𝐶𝐴𝐿𝑚𝑎𝑥 − 𝑄𝐶𝐴𝐿𝑚𝑖𝑛 𝐷𝑁 − 𝑄𝐶𝐴𝐿𝑚𝑖𝑛 ………… (𝐸𝑞. 3)

Lλ = ML × Qcal + AL ………………… (𝐸𝑞. 4)

In the above equations Lλ is the spectral radiance in W/(m2srμm) received by the sensor

from each pixel of the image.ML and AL are band specific multiplicative and additive

rescaling factors obtained from image MTL file, Qcal is the DN of each image, QCALmax

is the maximum DN (255) and QCALminis the minimum DN (0). Lmaxand Lminare the top

of atmospheric (TOA) radiances that are scaled to QCALmaxand QCALmin in W/ (m2 srμm)

respectively.

After the conversion of the DNs to the spectral radiance, the radiant images were

converted to the blackbody temperature using Eq. 5.


𝑇𝑏 =𝐾2

ln 𝐾1

𝐿𝜆 + 1

………………… (𝐸𝑞. 5)

Where Tb is the effective at-sensor brightness temperature in Kelvin unit, Lλis spectral

radiance in W/(m 2 srμm) and K1 and K2 are prelaunch calibration constants in Kelvin unit

obtained from the image MTL file.

To retrieve the final land surface temperature (LST), Tb was further corrected for land

surface emissivity (𝜀) using Eq. 6 (Weng,2001).

𝐿𝑆𝑇 =𝑇𝑏

1 + 𝜆𝑇 𝐾

𝜌 × ln 𝜀

………………… (𝐸𝑞. 6)

In the above equation, λ is the wavelength of emitted radiance (11.5μm) (Markham and

Barker, 1986), ρ=hc/σ (mK), K is the Stefan–Boltzmann’s constant (1.38*10-23

JK-1

), h is

the Planck’s constant (6.26 *10-34

Js), c is the velocity of light (2.998 *108 ms

-1) and ε is

the surface emissivity.

Finally, the derived LST values were converted to the conventional Degree Celsius (℃)

unit by adding the absolute zero which is approximately minus 273.5 ℃(Xu and Chen,

2004).

Surface Emissivity (𝜀) Retrieval

The land surface emissivity was retrieved from Normalized Difference Vegetation Index

(NDVI) threshold method proposed by Sobrinoand others (2008) where different

emissivity values were extracted from different ranges of NDVI values. According to the

method when NDVI< 0.2 the pixels are considered as bare lands and the emissivity was

retrieved from the red spectral region. When NDVI> 0.5 the pixels are considered as fully

vegetative coverage and the emissivity value was assumed as 0.99. When 0.2 ≤ NDVI ≤0.5 the pixels are considered as mixed use of soil and vegetation.In this case emissivity is

retrieved using Eq. 7:

𝜀 = 𝜀𝑣𝑃𝑣 + 𝜀𝑠 1 − 𝑃𝑣 + ∆𝜀………………… (𝐸𝑞. 7)

Where 𝜀𝑣the emissivity of vegetation coverage is, 𝜀𝑠 is the emissivity of soil surface and,

𝑃𝑣 is the proportion of vegetation calculated from the Eq. 8 (Carlson and Ripley, 1997).

𝑃𝑣 = 𝑁𝐷𝑉𝐼 − 𝑁𝐷𝑉𝐼𝑠𝑁𝐷𝑉𝐼𝑣 −𝑁𝐷𝑉𝐼𝑠

2

………………… (𝐸𝑞. 8)

Where𝑁𝐷𝑉𝐼𝑠 is the NDVI value of pure soil and 𝑁𝐷𝑉𝐼𝑣is the NDVI values of pure

vegetation extracted from NDVI image.

In Eq.7 the term ∆𝜀 is the indication of the geometrical distribution of the natural surface

as well as the internal reflection which value is considered as negligible for the plain and


57

homogenous surfaces. But in case of rough and heterogeneous surface the values is

assumed as 2% and is expressed by the following Eq. 9.

∆𝜀 = 1 − 𝜀𝑠 1 − 𝑃𝑣 𝐹𝜀𝑣 ………………… (𝐸𝑞. 9)

Where F is the shape factor whose mean value for different geometrical distributions is

assumed as 0.55 (Sobrino et al. 1990).

With summarizing Eq. 7 and Eq. 9 the final equation for emissivity estimation is obtained

as Eq. 10.

𝜀 = 𝑚𝑃𝑣 + 𝑛………………… (𝐸𝑞. 10)

Where m and n co-efficient are calculated as below

𝑚 = 𝜀𝑣 − 𝜀𝑠 − 1 − 𝜀𝑠 𝐹𝜀𝑣and𝑛 = 𝜀𝑠 + 1 − 𝜀𝑠 𝐹𝜀𝑣

Image classification and landuse/land-cover extraction

In this research, we applied the modified Anderson level 1 classification scheme

(Anderson et al, 1976)for selecting the LULC categories of the study areas. According to

this classification scheme we identified 5 major LULC categories (Table 2) from

temporal satellite images of each area. The conventional supervised classification method

with maximum likelihood algorithm was used to obtain the selected LULC categories

from each year image of both study sites. As prerequisite to supervised classification,

training sites were developed from each image using ArcGIS v.10 software. A total of

300 training areas were developed and examined using the two-directional feature plot

ensuring significant difference between each class. Finally, each year’s image of study

areas was classified into desired LULC categories using the training areas.

Table 2: Landuse/land cover classification scheme used in this study

LULC Category Description

Built-up area

Built-up area is comprised of areas of intensive use with much more of the land

covered by structures. Areas such as residential, commercial and services, urban

settlement, rural settlement, transportation network, mixed urban and other urban fall

in this category.

Vegetation

Coverage

This category historically includes the land where the potential natural vegetation is

predominantly grasses, grass like plants, shrubs, bushes and scrub, conifer, mixed

forest lands, herbaceous plants etc.

Agricultural

land

Agricultural land has been defined broadly as land used primarily for production of

food and fiber. On high altitude imagery, the chief indications of agricultural activity

will be distinctive geometric field and road patterns on the landscape and the traces

produced by livestock or mechanized equipment. Agricultural fields, crop fields,

fallow land, hill slope cultivated lands falls in this category.

Exposed land

Exposed land is a land of limited ability to support life and in which one-third of the

area has vegetation or other cover. Generally, it is an area of thin soil, sand or rocks

e.g. open fields, exposed lands, landfill sites, mining and sand fill areas.

Water body

Water is defined by the Bureau of the Census of the United States that includes all

area that persistently is water covered. Areas such as river, permanent open water,

perennial water body, lakes, ponds and other water reservoirs fall in this category. Source: Anderson et al., 1976


Landsat TM/ETM/

OLI image

Thermal bands

Optical bands

NIR and RED

bands

Re-projection to

UTM

Atmospheric

correction

(FLASH model)

Surface

reflectance

images

Collection of

spectral

signatures for

different LULC

Image

classification

(Hybrid

approach)

Final

LULC

maps

3*3 Majority

filtering and

manual editing

NDVI

Pv

Surface

emissivity

Radiance

At sensor

brightness

temperature

Land surface

temperature

(LST)

Urban heat

island (UHI)

Change

analysis and

results Results

Clipped to study

area

Clipped to

study area

LULC

preparation

LST and UHI

estimation

Reflectance of

the Red band

Input

Impact of

LULC on UHI

ProcessingIntermediate

output Results

Landsat TM/ETM/

OLI surface

reflectance imageNon calibrated

Figure 3: Work flow of the research

RESULTS AND DISCUSSION

Existing Landuse and Land cover changes of Chittagong Metropolitan Area

For the current studies LULC classes for the year 1990, 2002 and 2015 has been done

in this research. The study area was classified into 5 landuse/landcover types.

Though the total area by the year 19 90, 2002 and 2015 were almost same, but there

has been a significant difference in the internal landuse/landcover types. Build up

lands contributes larger UHI zones compared to others landuse categories. This map

represents landuse/land cover of Chittagong Metropolitan area.


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Figure 4: Existed LULC categories of different years of CMA area

Source: Obtained from image classification, 2015

From the landuse/land cover analysis, in 1990 built-up area was found only 5615.91 ha. But it increases significantly from5615.91 ha (in 1990)to10801.71 ha (in 2002)which

was 20.14% of the total study area in 1990 increased to 38.73% in 2002. The increasing

trends of built-up area continued and reached to 11893.95 ha and42.65% of the total

area in the year of 201 5. Built-up area is increasing rapidly due to accommodate huge

population in CMA.


Figure 5: Landuse/land cover changes analysis in CMA of the three-temporal period

Source: Graphically analyzed from land use/land cover table obtained from satellite imagery

On the other hand,as depicted in the graph there has been a significant decrease in the

vegetation coverage by 15.41% (4297.95 ha) from 19 90 to 200 2 and 0.86% (242.01

ha) from 2002 to 2015.In total vegetation coverage decreased 4539.96 ha in the 25

years period. These decreasing trends of vegetation are alarming for city duelers because

decreasing of vegetation is the sign of increasing urban heat and it is harmful for

environment and for human civilization.

Agricultural, exposed land and water bodies also decreased noticeably. Agricultural

land was 5099.04 ha (18.28%of total area) in 1990 and increased to6273.81 ha

(22.49%) from 1990 to 200 2 but again decreased to 5686.92 hafrom 2002 to 201 5

covering 20.40% of the total area. In total from 1990 to 2015 agrigultural land

decreased 587.88 ha.

From 1990 to 2002 the region has experienced a dramatic decrease in exposed land

from 5673.06 ha 3241.35 ha (decreasing rate 8.73%) but rose a little from 200 2 to

2015 (0. 15%). Altogether decrease of exposed land was 2475.54 ha in the 25 years

period.

In the year between 1990to 2002 area under inland water bodies have increased while

during 2000 to 2015those areas, decreased significantly. River area increased from

2430.18 ha in 1990 to 2799.27 ha in 2002but reduced considerably to 2579.76 ha in

2015which was only 0.09% of the total area. Thus, water body increased 369.09 ha

from 1990to 2002and decreased up to 219.51 ha from 2002to 2015.

0

2000

4000

6000

8000

10000

12000

14000

1990 2002 2015

Built-up area

Vegetation cover

Agricultural land

Bare land/Sand fill

Water bdy

Area

(ha)


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Change detection analysis of landuse categories of CMA

The Chittagong metropolitan area has undergone noticeable change in landuse/cover

throughout the time period from 1990 to 2015. To understand the change more

specifically change detection analysis has been done throughout the three periods of time.

Figure 6: Change detection map of Chittagong Metropolitan area

Source: Obtained from image classification, 2015

Change detection analysis explicit that major changes have occured in some

landuse/ land cover category. In 19 90 most extensive land cover in the studyarea


were the vegetation coverage (32.52% area), exposedland (20.35% area) and built-up

area (20.14% area).The results showthat vegetation coverage and exposed land decreased

to 16.24% and 11.50% respectively. On the other hand, built-up area drastically increased

to 42.65% in CMA. The huge change has been possible over the years through the

conversion of one LULC category to other but later in the following years significant

change has been noticed in the vegetation coverage, exposed land and built-up area.

Gain-Loss and Net Change Analysis of Chittagong Metropolitan Area

By the continuous analysis of LULC it was able to detect gain-loss and net change

estimation from the three temporal periods: 1990-2002, 2002-2015, and 1990-

2015.Almost all of the class of landuese/land covers showed gain and losse. For

the better understanding, gain and losse graphs for different uses (Figure 7) were

created by category.

Figure 7: Gain and Loss graph of CMA of 1990 and 2002, 2002 and 2015 and 1990 and 2015 Source: Gain and Loss graph analyzed from land sat image by researcher, 2015

Land Surface Temperature Extraction in Chittagong Metropolitan Area

Derived LST results of CMA are summarized in Figure 8for three times. The study

results show that derived maximum LST (°C) remains high in 2002 and 2015 study

periods.


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Table 3:Temporal LST Statistics of Chittagong Metropolitan Area

Study area Year Min

LST (°C)

Max

LST (°C)

Mean

LST (°C)

Standard

Deviation

Chittagong

Metropolitan

Area

1990 18.53 25.12 19.97 0.82

2002 19.70 30.87 21.34 1.04

2015 22.56 33.31 24.81 1.41 Source: Temporal LST analysis from land sat image by researcher, 2015

In 1990 and 2002 LST maximum is observed as 25.12 °C and 30.87°C and it shows a

significant increase as 33.31 °C in 2015 image which is absolutely very high increase.

Minimum values of LST for 1990, 2002 and 2015 image were found as 18.53°C, 19.70°C

and 22.56 °C with mean of 19.57°C, 21.34°C and 24.81 °C respectively. Temperature

rise was higher than the previous year for every land-use category.

Figure 8: Spatial distribution of land surface temperature of CMA

Source: Land surface temperature from land sat processed by researcher, 2015

Detail spatial distribution of the surface ambient temperature by each LULC category

obtained from image has been shown in Fig.9. In 1990 maximum LST was witnessed in

the agricultural land categories (24.26°C) during this time second maximum value was

found in the exposed land areas. The built-up and sparse vegetative areas also show

higher LST thorough the study area. In 2002 highest LST (30.88°C) was observed in the

built-up areas due to rapid growth of urbanization and infrastructure development in the

Chittagong Metropolitan area. Exposed land and water body areas also shown a high

temperature (27.43°C) in this year image (Figure 9). In the second position vegetation

coverage area remains and its value of the maximum LST was observed as 29.09°C.

Built-up areas showed consistently higher temperature than that of the other areas. Third


highest temperature was detected exposed landuse categories in 2015. A slight increase

of temperature was observed in the agricultural land compared to the dense vegetative

areas during this study year.

Figure 9: Land Surface Temperature in Different Land use Category of CMA

Source: Obtained from image based classification by researcher, 2015

URBAN HEAT ISLAND EXTRACTION

UHI is a common thermal phenomenon in urban areas. It is mainly developed due to the

rapid urbanization, excessive using of air conditioner, increasing movement of

automobiles, conversion of LULC, rapid increasing of industrial activities etc. As the

second largest city of Bangladesh,Chittagong Metropolitan Area (CMA) is urbanizing

rapidly with increasing number of automobiles, industries, conversion of land use/land

cover and unplanned growth of built environment. Figure 10 shows that the UHI areas

have mainly developed in the urbanized areas and continue in areal expansion. Some

scattered UHI areas are also observed in the city which is mainly happened due to the

conversion and clearing of vegetation and agricultural land.

It is apparent in the Figure 10 that for the year 1990, heat island intensity was higher in

Patenga, BayejidBostami and Double Mooring area, and was scattered in the Bandar and

central city area. On that time heat island intensity was 4.32 degree higher than the

surrounding area. The figure (10) also shows scattered heat island scenario on the

surrounding edge of the city. In 2002 heat island intensity was 8.49 degree higher than

the surrounding area.

0

5

10

15

20

25

30

35

LST in (°C) 1990

LST in (°C) 2002

LST in (°C) 2015


65

Figure 10: Distribution of UHI areas of different years and associated temperatures in the Chittagong

Metropolitan Area Source: Land surface temperature extracted from land sat image processed by researcher, 2015

Extreme heat island zone has been identified in Double Mooring area in between Bandar

and central part of Chittagong. Along with Double Mooring and central part of

Chittagong city newly added heat island zone has been identified in Bandar and

Chadgaon area.In 2015, significant heat island zone has been identified. The overall heat

on the heat island spot was 7.09 degree higher than the surrounding area which was

slightly lower than 2002. Major heat island zone has been identified in the center of

Chittagong, Double Mooring, Bandar, Pahartali, Bayejid Bostami, Chadgaon and Patenga

area making a total of 7 heat island zones.


Limitations of the study

Multi-year with minimum year gap images was not available, which was

necessary to identify micro changes of landuse/land cover and temperature

variation.

Inability of using high resolution, cloud free and seasonal imagery.

Advance meteorological station with automatic system trapping heat was not

available.

Continuous monitoring cell of those station on daily and hourly basis were not

available.

Enriched satellite image database was not available.

Such a robust research needs continuous field data that was not possible to

collect due to time limitation, besides processing of satellite images also

consumes enough time.

CONCLUSION

The study demonstrates drastic changes of landuse/land cover in the Chittagong

Metropolitan area over the last 25 years period. This study also demonstrates the

temporal changes of land surface temperature and spatial distribution of urban heat island

over the study area. The study has identified land surface temperature and urban heat

island zone for three different year 1990, 2002 and 2015-time period. Changes of land

surface temperature and urban heat island has been identified in response to landuse/land

cover changes, which has modified the radiant surface temperature and consequently

created urban heat island zone. Built-up area was the third highest land cover of

Chittagong Metropolitan area (20.14% of total study area) in 1990 and it was increased

rapidly in 2002 and 2015. In 2015 built-up area become main and major land cover of

CMAindicating 42.65% of total study area; at the same time dominant vegetation

coverage and agricultural land decreased 500 ha and 580 ha respectively.In response to

landuse change Chittagong City has witnessed sever increase of land surface temperature

from 1990 to 2015. CMA had 4 major UHI zones in 1990 which has increased to 7 UHI

zones in 2015. Maximum magnitude of temperature was 7.09°C in Chittagong

Metropolitan Area making it one of the hottest cities of Bangladesh.

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