Journal of Geographic Information System, 2011, 3, 173-194
doi:10.4236/jgis.2011.33015 Published Online July 2011 (
Copyright © 2011 SciRes. JGIS
Land Use and Land Cover Changes in Arid Region: The
Case New Urbanized Zone, Northeast Cairo, Egypt
Rafat Zaki1, Abotalib Z aki 2, Saad Ahmed3
1Department of Ge o logy, Faculty of Scie nce, Minia University, Minia, Egypt
2Geological A ppl i c at ion s an d Mi neral Reso u rces Divisi o n , National Authority for Remote Sensing and
Space Scienc e , Cairo, Egypt
3Department of Ge o logy, Faculty of Scie nce, Al-Azhar University, Cairo, Egypt
Received January 21, 2011; revised March 15, 2011; accepted April 10, 2011
The spatial characteristics of land cover are useful for understanding the various impacts of human activity
on the overall ecological conditions of the urban environment. The multi-temporal Landsat images (TM)
between the years of 1990 and 2003 were used together with the Geographic Information System (GIS)
techniques to evaluate the environmental changes in the area around Gabal El Hamza and the surrounding
urban expansion in the new urban cities at the northeast side of the Greater Cairo by using the post classifi-
cation change detection technique and field investigation. Five major units were determined including: urban,
cultivated land, Holocene sand dunes, Oligocene basalt and Miocene–Pleistocene sediments. The cultivated
cover changed from 89.6 to 150.4 km2 for the years of 1990 and 2003 respectively. The urban area increased
from 49.5 to 120.9 km2 with a great value of change reached 71.3 km2. The basaltic exposures changed from
3 to 3.75 km2. The sandy cover decreased from 68.9 to 60.1 km2 and the exposures of the rock units changed
from 904.8 to 780.8 km2 with removing 124 km2 in 13 years. The total accuracy of the Landsat-derived land
cover data was 95 and 92% for the years 1990 and 2003 respectively. Landsat TM thermal infrared data in-
dicated that the surface temperature was strongly affected by the land cover changes.
Keywords: Land Cover Changes, Accuracy Assessment, TM Images, Land Surface Temperature, Egypt
1. Introduction
In 1984, the first spark of the urban invasion to the desert
in Egypt was flared-up with the establishment of the
Tenth of Ramadan as a new urban center. Since this time,
new settlements were erected in different parts of the
country from the extreme north (as New Borg El-Arab
near Alexandria) to the south (as El-Minia El-Gedida).
The zone surrounding the Greater Cairo area had the
highest share in urban encroachment in the Egyptian
deserts. This is due to the high population density in
Cairo and is particularly relevant as a result of the ex-
pectation of an increase of population to almost the dou-
ble of its present status by 2050 [1]. Cairo also provides
the highest chances of increase of job opportu- nities in
Egypt as a result of the installation of new factories and
farms around the city, but away from its center. This
necessitates the establishment of dwelling places for the
qualified workin g forces which are generally to be found
near and within the city. The above mentioned reasons,
together with the suitable topographic and geologic set-
ting of the area, make the surroundings of Cairo suitable
for urban e xp ansion.
The northeastern part of Cairo, in which several new
urban settlements were erected, such as the Tenth of
Ramadan, Badr, El-Obour, El-Shorouq and other cities
has suffered from noticeable changes, especially in the
last few decades. These changes were essentially caused
by man-made interference. Therefore, the present study
is particularly important as it will throw light on the im-
pact of human activities on the overall ecological condi-
tions of the urban environment [2]. Land cover change
due to human activities is currently pro- ceeding more
quickly in developing countries than in the developed
world, and this situation will be projected into the year
2020, most of the world’s mega cities will appear in de-
veloping countries [3]. Increasing population in devel-
oping cities has caused rapid changes in land cover and
increased environmental degradation [4]. So Geographic
Information System (GIS) and remote sensing (RS) tech-
niques are powerful and cost-effective tools for assessing
the spatial and temporal dynamics and changes in land
cover and land use [5-7]. Remote sensing data provide
valuable multi- te mpor al data o n the p rocesses and patterns
of land cover and land use change, and GIS is a useful
technique for mapping and anal yzing these patterns [8].
In this work, two Landsat Thematic Mapper (TM)
images (1990 and 2003) were used to detect changes in
the study area. The topographic maps prepared by the
Egyptian Military Surv ey at scale 1: 50,000 with its 2007
update are also used as well as field investigations. Nu-
merous change detection methods have been developed
to assess variations in the land cover using satellite data
and post-classification comparison technique. The accu-
racy of this technique to detect the dynamic changes de-
pends mainly on the accuracy of the individual classifi-
cation of each land cover unit.
Kim, Nichol, Kevin and Timothy, Chen et al., Weng et
al., Wang, Weng and Lu and others ([9-15]), mentioned
the relation between surface temperature and land cover
changes using Landsat TM or ETM thermal infrared
data with a spatial resolution of 120 or 60 meters re-
spectively. Land surface temperature (LST) appears to
be strongly related to the changes of the land cover pat-
terns especially changes concomitant with the urban
expansion. Urbanization is one of the most important
factors affecting the global warming, so studying the
relation between urban surface changes and the land
surface temperature is critical. Ground-based tempera-
ture observations reflect only thermal condition of local
area around the stations. Hence studying thermal distri-
bution in big areas requires a large number of ground
stations and long time of analysis and correlation.
Thermal remote sensing is able to assess the instantly
and accurately temperature distribution over vast areas
economizing time and efforts.
The present study deals with changes of the land
cover between 1990 and 2003 of an area lying in the
northeastern vicinity of Cairo (Gabal El-Hamza area)
and the consequent changes in surface temperature.
Changes include urban and agricultural (cultivated) sur-
faces together with Holocene sand dunes, exposures of
Oligocene basalt and Miocene-Pleistocene sediments. It
is thought that the study can help in understanding the
dynamics of these changes in order to predict and/or
plan for future development.
2. Geologic Setting
The study area lies between 30˚05N - 30˚24N and
31˚28N - 31˚46E. This study examines in detail 36 km
long and 31 km wide (1116 km2). The area is located at
about 25 km from the Greater Cairo along the Cairo-
Ismailia district and is bounded by the Greater Cairo
from the west, the Eastern Delta from the north, the Is-
mailia Governorate from the east and north Eastern De-
sert from the south (Figure 1).
The study area has a low relief with ground elevation
ranging from 0 m in the northwestern part to 240 m
above sea level in the central and southern parts. The
area encounters many new urban cities as Tenth of
Ramadan, El-Obour, El-Shorouq, Badr, El-Nahda and
El-Hikestep (Figure 2). These cities are surrounded by
series of ridges and scarps related to the Oligocene basalt
with gravelly sands; Miocene gravels, sands, clays, sand-
stones, dolomite with limestone; sandy gravels with
limestone of Pliocene age and Holocene sand dunes
(Figure 3).
3. Methodology
The methodology used in this work is summarized in the
flow chart of Figure 4. The used images were extracted
from two Landsat Thematic Mapper (TM) scenes taken
over the eastern portion of the Nile Delta up to the Suez
Canal in August 1990 and June 2003 (Figures 5(a) and
(b)). A subsene covering the study area was digitally cut
for analysis. Ground resolution for these images is 30 m.
Landsat TM image records data in seven different band-
widths. The latter are broken down into portions of the
visible, reflected infrared and thermal infrared regions of
the electromagnetic spectrum. From these various band-
widths, a great deal of information about the land cover
can be displayed and analyzed. These images were geo-
metrically corrected using topographic maps prepared by
the Egyptian Military Survey at scale 1:50,000 as a ref-
erence data. Atmospheric corrections were applied to
remove the effects of the passage of radiation through the
atmosphere using dark pixel subtraction technique, fol-
lowed by haze and noise reduction in order to diminish
the weather effect. Maximum likelihood supervised and
unsupervised classifications were used in the production
of land cover maps for the study area. The post- classifi-
cation change detection technique was applied and the
temporal change maps were produced using a GIS model.
The ground truth points used for assessing the accuracy
of the classifications were selected using high resolution
SPOT images and field investigation with a Global Posi-
tioning System (GPS) unit. Among the software; Arc
GIS Version 9.2, Erdas Imagine Version 9.1, Envi Ver-
sion 4.5 and Microsoft Excel programs were used.
According to Chen, et al. (2002), the land surface
temperature derived from the Landsat TM thermal infra-
red (band 6) image in two steps:
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Figure 1. Location map of the study area.
Figure 2. Base map of the study area showing the distribution of the new urban cities and the main roads.
Figure 3. Geologic map of the study area (modified after Tawfik and Swedan, [16]).
Figure 4. Flow chart showing the procedures of the work.
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Figure 5. (a) and (b) Landsat TM images of the study area in 1990 and 2003.
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5. Unsupervised Classification
The first, the digital numbers (DNs) of band 6 was
converted to radiation luminance , mWcm2sr1)
using the following equation: 6TM
In the unsupervised classification, the computer separates
the pixels into classes with no direction s from the analyst
[17]. This means that unsupervised classification tech-
niques do not require the user to specify any information
about the features contained in the images. The un-
supervised classification technique (isodata) was applied
for the study area using ENVI Version 4.5. Using initial
cluster options, which were calculated from the file
statistics of 6 classes; with (6) Maximum iteration and
(0.950) Converg ence Thresh old as processing option s. In
the study area the unsupervised classification applied to
the six visible and reflected IR bands of the subscene
resulted in 20 classes.
6255 maxminmin
Where: V represents the DN of ban d 6,
max1.896(mW cmsr)R
min0.1534(mW cmsr)R
Secondly, the radiation luminance is converted to abso-
lute temperature in Kelvin , by the following
At this point, the image is difficult to interpret.
Decisions need to be made concerning which land cover
types that each category falls within. To make these
decisions, other materials and knowledge of the area
were useful. Checking in the field, the various areas
discriminated in the digital image should be examined in
the field to obtain more accurate results. If this
knowledge is not available, scientific reasoning may be
used to group the various categories together in to related
land cover units. In the case of the present study the
second probability was more suitable. So, the twenty
classes obtained from the two sets of images were
merged into five major classes. These classes are
referring to the five land use/cover units including
sedimentary rocks outcrops, urban areas and agricultural
land, Holocene sand dun e s and basaltic exposures.
1ln 21
TKK R b
where, 1 1260.56
60.766 and
(mWcm2sr1µm1), b represents the ef-
fective spectral range = 1.239(μm).
Finally, a third step was applied to convert tempera-
ture into Celsius scale using the equation:
Among the software; Arc GIS version 9.2, Erdas
Imagine version 9.1, Envi version 4.5 and Microsoft Ex-
cel programs were used.
4. Supervised Classification for Obtaining
Land Cover Map However, s everal class es were incorr ectly in terpreted .
Some urban settlements have been misclassified as rock
units or basaltic flows due to the fact that they dis-
pl ayed similar spectral characteristics. Post-classification
change refinements were used to improve the accuracy
of the classification as it is simple and effective method
[18], because urban surfaces are heterogeneous and
composed of a complex combination of features as
buildings, roads, grass, trees, soil and water [19]. After
the performance of the po st classification refinement, the
misclassification has been mostly corrected (Figures 8(a)
and (b)). The post-classification transformation of the
classified raster into shape file vector has been done
using ENVI version 4.5 and using ARC GIS tools. The
obtained shape file was converted into a geo-database in
order to introduce the change detection analysis. Before
this step, it is necessary to make sure that the classi-
fication used for change detection procedu re is matching
fact in the field.
Supervised classification has been developed for satellite
image-processing where it has been applied to the
classification of spectral layers. It depends mainly on th e
experience and accuracy of the user in detecting the
signature differences between various units in the
satellite image using his naked eyes. Each difference in
the signature or pixel value in the processed image is
revealed as differences in the unit tone in the satellite
images. (Figures 6(a) and (b)) show selected training
points on the 1990 and th e 2003. Landsat- TM i mage and
the corresponding spectral profile showing the relations
between the pixel value and the image bands for each
different classes.
Using Erdas Imagine version 9.1, new maximum
likelihood supervised classification analyses were carried
out on the TM (1990) and TM (2003) images (Figures
7(a) and (b)) to identify the land use/ cover changes in
the study area. Five different land cover classes were
identified including: agriculture, sand dunes, urban, basalt
flows and sedimentary rocks units of Miocene to Pleis-
tocene age.
6. Accuracy Assessment
The classified thematic maps are produced for a wide
Figure 6. (a) and (b) The different classes can be selected by eye in 1990 and 2003 Landsat TM images and the corresponding
spectral profile of these classes.
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Figure 7. The different land cover units in the 1990 and 2003 Landsat TM images using maximum likehood supervised classi-
variety of resources; soil types or properties, land cover,
land use, forest inventory, and others. These maps are
not very useful without quantitative statements about
their accuracy. Lillesand and Kiefer [20.] remark “a clas-
sification is not complete until its accuracy is assessed’.
Congalton [21] defined the accuracy asse- ssment as the
accordant between the remote sensing data and the ref-
erence information. The accuracy of digital land cover
classifications can be expressed quantitatively by build-
ing and interpreting a classification error matrix. An er-
ror matrix compares information from a classified image
or land cover map to known reference (truth) sites for a
number of sample points. The accuracy assessment of the
land cover maps extracted from Landsat data include the
generation of 100 random references (truth points) for
each land cover map. Accuracy assessment of the land
cover maps after the post-classification refinements and
merging of the 20 classes into 5 classes covering the
major land cover units was then performed using field
data, high resolution SPOT images, topographic maps
and the results were recorded in a confusion matrix.
By applying the accuracy assessment process on the
Figure 8. (a) and (b) The unsupervised classifications of the years 1990 and 2003 Landsat TM images after the enhancements
and post-classification refinements.
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land cover maps before and after the refinement processes.
It is found to be that the rule-based post-classification
refinements were effective and improved accuracy by
8% - 13%. The total accuracy of the Landsat-derived
land cover data was 95 and 92% for the years 1990 and
2003 respectively.
According to Anderson et al. [22], the standard ac-
curacy for (land use/land cover) mapping studies ranging
from 85% - 90%. From the accuracy reports, it is easily
noticeable that the accuracy of the land cover map de-
rived from the 1990 Landsat TM image is higher than the
accuracy of the land cover map derived from the 2003
Landsat -TM image due to the vast urban expansion at the
2003 image which result in the increasing of the spectral
confusion between pixels contain the urban signature and
pixels contain the argillaceous or basaltic signature.
7. Change Detection Techniques
Many remote sensing change detection techniques have
been developed, and the advantages and disadvantages
of each have been reviewed by a number of authors
([23]). However, the new digital change detection tech-
niques are continuing to be developed primarily
in-response to the range of social and environmental
chal- lenges posed by human transformation of the
Earth’s surface ([24,25]) and the potential of remote
sensing in monitoring related processes ([26-28]). All
change detection techniques rely on the basic idea that
changes in the spectral and/or textural characteristics of
geometrically, atmospherically and topographically cor-
rected remote ly sensed imagery r epresen t change s of the
Earth’s surface.
In this study, the post-classifi cation comparison change
detection technique is the most preferable. The mag-
nitude and location of change (from to change detection
matrix, [29]) were determined for the entire studied years
(1990-2003). The major land cover changes were colour
coded. These changes were from rocky land to urban,
from rocky land to agricultural areas, from sand to agri-
cultural areas and from sand to urban areas. Also the
exposed basaltic extrusions have been found to cover
different spaces in the two dates. Table 1 shows the ob-
served major land cover changes and the area of each
land cover class has been given in m2 with the yearly
average change in each type (each class). Using Arc
Toolbox in ARC GIS Version 9.2 a new model has been
developed to map the change through the thirteen years
between the 1990 and 2003 images.
The data obtained are also shown in a chart form to be
easier to understand for the normal observer and the de-
cision maker, so a diagrammatic view displaying a com-
parison between the same land cover classes in both
dates (Figure 9), and the average ratio of each class that
was occupying the surface area between 1990 and 2003
(Figure 10) were d es igned.
8. Interpretation of the Detection of Change
The detection of change analysis is concerned with the
environmental changes and the human impact. These
changes have been detected and identified as the fol-
a) Changes concerning agricultural (cultivated)
The surface of cultivated lands shows big changes
through the urban development of the new cities (as
Tenth of Ramadan, El-Shorouq, Badr and El-Obour cit-
ies), or through new cultivation around El-Obour and
El-Nahda cities and on the edges of the Eastern Delta at
Belbis city. Figures 11(a)-(c) show the steps of changes
of the green cover at various dates. The agricultural
cover increased from 89.6 to150.4 km² between the years
1990 and 2003. This means that the agricultural cover
increased during th e last 13 years by 60.7 km² (Table 1).
b) The urban development
Urban development in the study area plays a very im-
portant role through the environmental changes either
through the en largement of the Tenth of Ramadan city or
through construction of the new urban cities such as
El-Shorouq, El-Obour and Badr between the years of
1990 and 2003 (Figures 12(a)-(c)). The large deve-
lopment of the new urban cities, where the urban area in
1990 was 49.5 km2 to reach 120.9 km2 in 2003 with a
large value of chan g e reached 71.3 km2 (Table 1).
c) The bed rock exposures
Bedrock exposures in the year of 1990 were covering
the bulk of the area of study, amounting to about 904.8
km². But this area was largely covered by new elements
related to the urban development and cultivation of new
surfaces. It reached 780.8 km2 in 2003 (Table 1). This
amounts to a decrease in the exposed bed rock surface of
124 km² in 13 years. The remarkable dynamic change is
shown in Figures 13(a)-(c).
Table 1. The land cover changes in m2 in 1990 and 2003 and
the average of change der year.
Classes 1990 Area
(m2) 2003 Area
(m2) Total
change (m2) Difference
per year
Agriculture89696700 150453900 60757200 4673630.769
Urban 49591800 120913200 71321400 5486261.538
Rock 904880700780877800 –124002900 –9538684.615
Sand 68918400 60105600 –8812800 –677907.6923
Basalt 3020400 3757500 737100 56700
Sum. 11161080001116108000
Figure 9. Each class area in m² at the time of analysis.
Figsure 10. The proportions of each class to the whole studied area at 1990 and 2003.
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Figure 11. (a), (b) The distribution of the agricultural covers in the years of 1990 and 2003, (c) The changed area between the
two dates.
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Figure 12. (a) and (b) The distribution of the Urban covers in the years of 1990 and 2003 respectively, (c) The changed area
between the two date s.
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Figure 13. (a)(b) The distribution of the sediments surfaces in the years of 1990 and 2003; (c) The changed area between the
two dates.
d) The sand dunes
Urban and agriculture developments to gether with san d
movement by the wind caused changes in the surface of
the sandy cover from 68.9 to 60.1 km2 between the years
of 1990 and 2003 respectively (Table 1). This change is
shown in (Figu res 14( a)- (c)).
e) The basaltic exposures
The surface of basaltic exposures increased in the con-
sidered period (1990-2003), because in spite of the loss
of a part of these exposu res throug h qu arrying, ad d itional
areas have been exposed by the removal of the Miocene
sediments and Quaternary sands covering the basaltic
flows in order to prepare new areas for quarrying. The
exposures of basalt increased from 3 to 3.75 km2 be-
tween the years 1990 and 2003 (Figures 15( a) -(c)).
9. Land Surface Temperature
Land surface temperature maps (LST) were derived from
the TM images that have been acquired nearly in the
same time of year (4 August 1990 and 8 August 2003) in
order to neglect the seasonal mutations of temperature
and nearly at the same time of day (8.00 and 7.45 AM) to
avoid the effect of the diurnal temperature cycle. In
1990, the land surface temperatures range between 24.05
and 39.45˚C (Figure 16) and from 21.8 and 42.11˚C at
year 2003 (Figure 17).
Superimposing the land surface temperature maps
over the land cover maps indicate that the spatial distri-
bution of LST depends mainly on the land co ver type. In
1990, the rock types were the most common factor af-
fecting the LST distribution. The basaltic exposures and
the surrounding highly ferruginous sandstones are indi-
cated by the pink colour referring to the highest tem-
peratures (36.6˚C - 39.45˚C). The most abundant yel-
lowish colour, which represents the set of temperatures
from 33.6 to 36.5˚C, refers to the non-clastic formations
and sand dunes. The greenish, light green and bright
green colors referring to cultivated lands of different
densities. The urban settlements in 1990 affected the
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Figure 14. (a)(b) The distribution of the sand cover in the years of 1990 and 2003; (c) The changed area between the two
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Figure 15. (a)(b) The distribution of the basaltic flow in the years of 1990 and 2003; (c) The changed area between the two
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Figure 16. The distribution of the land surfaces temperature of the year 1990.
Figure 17. The distribution of the land surfaces temperature of the year 2003.
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LST to some extent; along the Cairo-Ismailia, Cairo-
Suez high roads and through the urban built up spaces of
the Tenth of Ramadan city. These urban settlement were
characterized by the highest temperature range (36.6˚C -
39.45˚C) as discordant with the surroundings.
In 2003, the spatial distribution of the land cover units
has suffered much change with the urban invasion. Con-
sequently LST patterns were changed and their distribu-
tions were mostly controlled by the urban distributions.
There is no change in land cover area (the rural culti-
vated lands) at the northwestern part of the study area
corresponds to no change LST values with exiguous de-
crease in temperatures in some parts (from 24.5˚C -
27.8˚C to 21.8˚C - 24.4˚C and from 27.9˚C - 30.7˚C to
24.5˚C - 27.8˚C) give indication that the colder weather
conditions of this day corresponding to the day of 1990.
On the other hand, the central and southern parts that
involved the bulk urban expansion have been covered by
the higher temperature set (36.5 - 39.4). The wind
movement has the north- east direction, so the hot spots
(with the red color) at the southern part may be carried
out the wind from the industrial settlements at the desert
back of Nasr city, which located at the south- west of the
study area.
10. Conclusions
Using remote sensing data in conjunction with Geogra-
phic Information System analytical tools, the present
study enables to monitor sp atial and temporal land cover
changes in the region around Gabal El-Hamza and to
evaluate the dynamics of urban expansion in the new
urban cities at the northeastern side of the Greater Cairo
area. This study was conducted using two Landsat The-
matic Mapper (TM) images acquired in the years 1990
and 2003. The acquisition time of th e two images was in
the same season to keep the weather factor as constant as
possible. The images were taken in August 1990 and
June 2003 respectively. Different procedures of image
enhancement have been performed on the two images to
obtain the land cover maps at the two dates using likely-
hood supervised and unsupervised classifications. The
maps obtained revealed that the unsupervised classi- fi-
cation are more accurate in distinguishing the land cover
units because of human error in digitizing, lack of
knowledge of study area, and other factors generally
contribute to give inaccurate results in the supervised
classification method. These drawbacks are not affecting
the unsupervised classification method. After refinement
of the unsupervised classification, accuracy assessment
analysis had been performed to determine the accuracy
of the classification. The total accuracy of the Landsat-
derived land cover data was 92 and 95% for the years
1990 and 2003 respectively. The obtained results indi-
cate that the accuracy decreased with the increasing of
the urban expansion because the expansion results in the
increasing of spectral confusion between some pixels of
the urban signature and pixels including of argillaceous,
rocky or basaltic exposures. In order to determine the
change in the land cover units through the thirteen years
between the two acquisitio n dates, the post-classification
comparison technique were used. The agricultural cover
changed from 89.6 to 150.4 km2 for the years of 1990
and 2003 respectively. The urban areas show a large in-
creased from 49.5 to 120.9 km2. The basaltic flows cover
changed from 3 to 3.75 km2. The sandy cover decreased
from 68.9 to 60.1 km2 and the exposures of the rocks
decreased from 904.8 to 780.8 km² (i.e., a decrease of
124 km2 in 13 years).
This study shows that an integrated use of GIS and
Remote Sensing data can be effectively used to under-
stand spatial and temporal dynamics of land cover
changes. The interpretation and classification of remote
sensing data could also be useful for estimating the rate
and spatial pattern of the urban expansion around old
cities that have a desert back-ground as Greater Cairo,
Alexandria, El Minia and others. The land cover maps
produced in this study could contribute to both the de-
velopment of sustainable urban land use planning deci-
sions and also for forecasting possible future changes in
growth patterns by using the Polychotomous Regression
modeling and predicting the land cover in the future.
Landsat TM thermal infrared data indicated that the sur-
face temperature is strongly affected by the land cover
changes and needs further research to correlate with Me-
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