Advances in Remote Sensing, 2013, 2, 276-281 Published Online September 2013 (
Monitoring and Change Detection along the Eastern Side
of Qena Bend, Nile Valley, Egypt Using GIS
and Remote Sensing
Ahmed Omar Abd El-Aziz1,2
1Senior of Geomatics-Al-Amar Consulting Group, Cairo, Egypt
2UNIGIS-Salzburg University, Vienna, Austria
Received July 30, 2013; revised August 28, 2013; accepted September 3, 2013
Copyright © 2013 Ahmed Omar Abd El-Aziz. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This Article is set to track and monitor changes through spatial dependence of remote sensing data and GIS analysis, the
suggested working method in this research is by sub pixel classification techniques. Change detection is a central task
for land cover monitoring by remote sensing. It uses multi temporal image data sets in order to detect land cover
changes from spectral discrepancies [1] (Rafael, et al.). It discusses the study perception of the situation in the past as
well as the current and finally the future status of changes that land uses in Eastern Qena meander specifically in places
of estuary floods, and the most important estuary leading to Qena, and whether these changes in land are used in direc-
tion of the mouth of the stream or not, especially that when it happened before, it caused destruction of both activities,
urban & agricultural land. It will rely on Landsat images in years of (1972-2012), conduct analysis, different classifica-
tions integration with geographic information systems (GIS), and field as well as samples for the accuracy assessment.
Keywords: Sub Pixel-Change Detection
1. Introduction
The idea monitors spatial changes to observe changes
between two different periods. In this study, it will be
relying on visuals Landsat in different years starting from
1972, and visualization with sensor Mss. until 2012 and
sensor ETM+, that are used in many periods of time to
clarify what is the direction of spatial changes that have
occurred in Eastern pagan Qena, especially since that
region has been exposed to continuous flash flood before.
The study comes to support the direction of sustainable
development; particularly, since the area has large agri-
cultural land that may be subject to corrosion from ex-
pansions Urbanism.
The sub-pixel approach gives information about dif-
ferent classes within a pixel. Using a scene-derived envi-
ronmental correction process enables you to develop a
reference signature in one scene and then to apply that
signature to other scenes from different dates and geo-
graphic locations as fully integrated.
Sub pixel Classifier is an advanced image exploitation
tool designed to detect materials that are smaller than an
image pixel, using multispectral imagery. It is also useful
for detecting materials that cover larger areas mixed with
other materials which complicate accurate classification.
It is considered as a powerful, low cost alternative to
ground surveys, field sampling, and high-resolution im-
agery. It addresses the “mixed pixel problem” by suc-
cessfully distinguishing a specific material when there are
materials other than the one you are looking for combin-
ing in a pixel. It discriminates between spectrally similar
materials, such as individual plant species, specific water
types, or distinctive man-made materials. It allows you to
develop spectral signatures that are scene-to-scene trans-
ferable [2] (Erdas 2013).
2. The Study Area
The study area is located between 25˚30' N to 28˚30' N
and longitudes 32˚ E to 33˚45' E. The study area extends
to up to about 45,000 square kilometers bordered to the
North along the Eastern Desert and the Nile Valley and
South along the Eastern Desert to the South and the Nile
Valley and the Red Sea and East West Nile Figure 1.
The region can be divided into two: First, adjacent to
the River Nile (flood plain), which represents a mix be-
opyright © 2013 SciRes. ARS
A. O. A. EL-AZIZ 277
tween green agricultural spaces as well as urban areas,
inside large canals and drains that take water from the
River Nile-scale. Second, adjacent to the scope of the
first, a home in the band Desert and has set of valleys
pour water for correspond to urban areas on the edge of
the desert. Here the problem can be detected, in the first
region, the change tracts of green areas (farmland), which
exist on the River Nile across thousands of Sunnis turned
into urban areas. In the second region, the trend of ex-
pansion of urban areas towards valleys and estuaries,
which sweep in front of everything. The changes will be
studied by highlighting them on both sides to clarify the
extent of the problem.
3. Methodology
Based research methodology is using Sub pixel Classi-
fication Method, one of the best ways that are monitored
rating them on the level of a sub pixel which results ac-
curate work and results [3]. Relying on image satellites
of Landsat from the years of (1972 to 2013) Figure 2
with sensors (MSS-TM-ETM+-OLI) which gives an im-
portant dimension, that the evolution of land uses in the
study area and trends of increase or decrease in the land
use and that the region matching with the east moun-
tainous area.
Represent the mouth of Valleys at the time of the floods.
The above figure represents action steps and methodol-
By using Finding other ways of classifications for com-
parison and to reach the utmost precision [4,5], such as
supervised classification and unsupervised classification
were done.
Over the years, which have studied them in addition to
the calibration of these classifications using topographic
maps covering the study area. Comparing the results of
those categories with those of the method used in the
search (sub pixel classification). Research also included
the use of equation to derive water surfaces and com-
Figure 1. Study area.
Copyright © 2013 SciRes. ARS
Figure 2. Change detection flow chart.
paring them with those of other classification methods
that relied-in the calculation of water surfaces and the
equation-on Erdas program according to the following
equation (0.5 × image name + (1 0.5) × image name ×
22.958) as Figure 3. As well as the points that were
monitored by GPS points for many areas within the area
of study to compare the effect of the land use in the same
places on the results of classification of work accuracy
assessment [6].
4. Remote Sensing Data
Objectives of the study require knowledge of the ele-
ments that have been reliable in the study in terms of di-
mensions, and clearly show that both in the remote sens-
ing data, as well as methods of use and analysis [7].
Depends on satellite data (a) with different stages as it
is shown in Table 1.
To achieve the objectives of this study, there were three
groups selected for rating; which are the use of urban
land for urban area, cultivated area, and water surfaces
represented in the River Nile including some of the side
channels observed changes that have emerged in those
places and trends of change.
5. Results and Discussion
When we look at the change in land use in the study area,
it is found that the change covers two important
Figure 3. Extract water surface from land sat images.
Table 1. Land sat data sources.
Landsat satellite images information
year sensorResolution Bands number satellite
1972 MSS 56 meter 4 bands Landsat 1,2,3
1984 TM 30 meter 7 bands Landsat 4,5
1998 ETM+14.25 meter 8 bands Landsat 7
2006 ETM+14.25 meter 8 bands Landsat 7
2013 JuneOLI 14.25 11 bands Landsat 8
aspects: what item has been changed and in which
direction if we compare or note the difference. There are
important elements which are the construction and cover
agriculture that is changing from year to year depending
Copyright © 2013 SciRes. ARS
A. O. A. EL-AZIZ 279
on the developments of the system of living. In the study
area since the period following the construction of the
High dam till now.
It is through the Figure 4 can be observed extent of
change between the two components regulars in the study
area, and it seems stable, but now evolved Area Urban of
up to 150 kilometers Km2, while decreased agricultural
area to reach to 553 km, that is due to the increasing
Crawl of Urban agricultural areas.
In the past, there had been change, with the exception
of the period from 1972 until 1984, the agricultural area
increased by 64 km as a result of the construction of the
High Dam and the evolution of the cultivated area and
regularity of Agriculture in the study area.
The second element, a trend changes and through the
study illustrated the direction of those changes, and the
expansion of tenderness urban and agricultural as it
appears from the study of evolution in the land use of
study area (Figure 5).
This represents a serious indication in the study of the
dangers of floods then that most of those moving expan-
sions in the mouths of the valleys, making it vulnerable
to drifting in the face of any flash flood occur, which is
what happened in previous times where roads collapsed
and sank agricultural land and displaced thousands of
Changes can be observed through the following forms
for years (1972-1984-2005-2013).
As these changes can be seen more clearly in the pe-
riod between 1984 to 2005 in the East in the mouth of the
valleys that pour from the east and north-east to the west
as shown in Figure 6. Between 2005 to 2013, we find an
increase in the development of human urban activity.
More obvious than before, as in Figure 7. As appears
from the previous the changes take varying proportions
and different directions and show area changes (Figure
Figure 4. Land use of Qena eastern 1972.
Figure 5. Land use of Qena ester between (1972-1984).
Copyright © 2013 SciRes. ARS
Risk lies in directions those changes to the east where
mouths valleys especially the mouth of Wadi Qena and
matulla Valley, which displays these developments Ur-
ban mankind constantly dangerous when flash flood oc-
6. Conclusions
Decision-maker needed a clear vision for the dimensions
of the current situation and the future planning when
making the decision. Landsat data have been used in this
study to discuss and follow up the changes in human
activity from 1972 and until 2013 they has been proven
its worth in the analysis and monitoring of changes
through the style category and advanced sub pixel classi-
fication through calibration of these data with more ac-
curacy, compared with the situation in the field (GPS
The study puts a warning and an indication of trends in
changes of the need to address urban and agricultural
development in the direction of the mouths of valleys
Figure 6. Land use of Qena ester between (1984-2005).
Figure 7. Land use of Qena ester between (2005-2013).
Copyright © 2013 SciRes. ARS
A. O. A. EL-AZIZ 281
Figure 8. Land use changes in study area for urban and
ed to sudden flash floods i
[1] M. El Hajj, A.Hagolle, G. Dedieu,
ssifier™, 2013.
t of Nile
. Speck, D. Kulbach, H. Spitzer and J.
c Change Detection for Road-
Techniques Using
agriculture ar ea.
at are constantly exposthf we
are going to talk about sustainable development to pre-
serve the human activity of environmental disasters.
Begue, B. Lafrance, O.
and M. umeau, “Relative Radiometric Normalization and
Atmospheric Orrection of a SPOT 5 Time Series,” Sen-
sors, Vol. 8, 2008, pp. 2774-2791.
[2] IMAGINE Subpixel Cla
[3] M. Flanagan and D. L. Civco, “Subpixel Impervious Su
face Mapping,” Proceedings of 2001 ASPRS Annual
Convention, St. Louis, 23-27 April 2001, 13 p.
[4] A. A. Haggag, “Soil Classification of North Coas
Delta,” Doctoral Thesis, Mansoura University, Mansoura,
1994, 300 p.
[5] R. Wiemker, A
Bienlein, “Unsupervised Robust Change Detection in
Multispectral Imagery Using Spectral and Spatial Fea-
tures,” Proceedings of the 2nd International Airborne
Remote Sensing Conference and Exhibition, San Fran-
cisco, 1997, pp. 640-647.
[6] H. G. Sui (2002) “Automati
Networks Base on Features,” Ph.D. Dissertations, Wuhan
University, Wuhan, in Chinese.
[7] A. Singh, “Digital Change Detection
Remotely Sensed Data,” International Journal of Remote
Sensing, Vol. 10, No. 6, 1989, pp. 989-1003.
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