Qattara Depression

Ale

xa

nd

ria

Mediterranean Sea

El-Alamein

Western Desert

Easte

rn D

esert

Matrouh

Matrouh

Moghra Oasis

0 40 80 120 16020Km

29°20'E29°10'E29°0'E

30°50'N

30°40'N

30°30'N

30°20'N

0 5 10 15 202.5Km± OBR core zone

OBR buffer zone

OBR transition zone

29°20'E29°10'E29°0'E

30°50'N

30°40'N

30°30'N

30°20'N

0 5 10 15 202.5Km± OBR core zone

OBR buffer zone

OBR transition zone

Land use/cover change (LUCC) is considered one of the most

important environmental issues of global concern. The

Northwestern desert of Egypt has been subjected to new

activities that may have led to changes in the landscape and

might have influenced the distribution of important species.

The main objectives of the current study are to: 1) Map LULC

in the region between 1988 and 2011; and 2) use the produced

LULC maps to predict the potential changes in the landscape

by year 2023 using the Markov chain-Cellular Automata

integrated approach.

Land use/land cover change analysis and prediction in the northwestern coastal desert of Egypt

Marwa Waseem Halmy1*, Paul E. Gessler2, Jeff Hicke2, Boshra B. Salem1

1Alexandria University, EGYPT; 2University of Idaho, USA (*email: marwa.w.halmy@alexu.edu.eg)

I. Introduction III. Methods

II. Study Area

V. Conclusion

The study area is part of the Western Desert of Egypt located

to the west of Alexandria city extending 40 km westward to El-

Alamein and stretching 70 km from the Mediterranean coast to

Moghra Oasis (Fig. 1). This part of Egypt has been subjected

to different levels of modification. Until recent times grazing

and rain-fed agriculture constituted the main land use activities

in the area. Recently new land use forms have been practiced

in the area including tourism and irrigated agriculture.

Fig 1. Location of study area: a) the administrative boundaries of the

Egyptian governorates; b) part of the Northwestern coastal desert showing

location of the study area; and c) subset of Landsat TM imagery from 2011

representing the study area showing location of Omayed Biosphere

Reserve (OBR), core zones shown in red, buffer zone in green and

transition zone in blue.

Fourteen land use/land cover (LULC) classes were mapped for

three dates, 1988, 1999, and 2011. Landsat TM data and ancillary

data were classified using random forests (RF) ensemble

classification approach (Fig 2). The LULC maps produced were

then used for predicting future land use change using integrated

Markov-CA model. This was conducted in three steps: 1) applying

the Markov chain analysis to the 1988, 1999, and 2011 LULC

maps for calculating transition matrices; 2) calculating transition

potential maps for LULC classes; and 3) application of CA model

to the transition matrices and the transition potential maps to

predict the spatial distribution of LULC.

Fig 2. Framework of the steps used in the analysis of the data.

Random forest (RF) classifier produced LULC classification with

an overall accuracy over 90% and kappa index of more than 0.9.

The use of the Markov Chain-Cellular automata model was

successful in providing prediction of the LULC distribution for the

year 2011 and was comparable to the actual for 2011.

Year

(stage)

Overall

accuracy

Kappa

Mean

omission

/class (%)

Mean

commission/class

(%)

1988 (first) 92.53 0.92 6.96±7.46 7.90± 8.62

1999 (second) 93.77 0.93 5.98±4.07 5.09±6.46

2011 (third) 97.30 0.97 2.75±4.13 3.02±3.51

Table 1. Overall accuracy, kappa statistic, mean per class omission

and commission error for land use/land cover classification of the year

1988, 1999, and 2011.

The analysis of the distribution of LULC classes over the three

dates revealed dynamic changes in LULC (Fig 3 & Table 2). The

developmental activities resulted in three different stags each

dominated by different land uses. Grazing, non-irrigated

agriculture (rain-fed and orchards) and quarrying dominating the

first stage; summer resorts, built-up areas, both non-irrigated

agriculture (rain-fed and orchards) and irrigated agriculture and

quarrying dominating the second stage; and irrigated

agriculture, summer resorts, built-up areas and quarrying

dominating the third stage. The potential distribution of the LULC

classes by 2023 shows predicted expansion in the croplands

westward and northward. An expected increase in quarries and in

residential centers in the area is also revealed.

Fig 3. Land use/land cover distribution in the landscape

resulting from classification of Landsat TM image over three

different stages.

Period Persistence (%) Change (%)

1988-1999 88.50 11.50

1999-2011 88.40 11.60

Table 2. change and persistence percentage of the

landscape over the periods 1988-1999, and 1999-2011.

The analysis of the change in the spatial distribution of the

LULC reveals that the landscape has become patchier and

less naturalized. The natural land cover (rangelands, coastal

dunes, mixed barren lands, and wet & marsh areas) continues

to suffer from dissection and attrition, while the artificial and

semi-artificial land covers (resorts, built-up areas, quarries and

croplands) are undergoing creation and aggregation (Fig 4).

a)

-4-2

02

4

b)

-4-2

02

4

BU RE CR OA RL WT RS SM CD SF BA QR GD

c)

LULC

Are

a (%

) of

the

land

scap

e

-4-2

02

4

Fig 5. Net change for each LULC class as percentage of the

landscape area over the period a) 1988-1999; b) 1999-2011;

and c) 1988-2011.

The natural land cover is experiencing loss to the new land

uses. Built-up areas, croplands, resorts, and quarries each

exhibit gain over the entire study period (Fig 5), while

rangelands, the barren mixed lands and the coastal dunes

are declining. The shift towards the artificialization of the

landscape is expected to continue in the future as revealed

by the index of landscape conservation (ILC) (Fig 6). The

changes the landscape has experienced might continue

and will likely impact the distribution of species in the area.

Random forests succeeded in classifying the LULC using

integrated Landsat TM data with environmental variables.

This indicates the merit of using this technique in mapping

LULC in similar arid ecosystems. The change occurring in the

area is a reflection of the development strategy aiming at

expanding outside the heavily populated Delta through

developing the desert fringes. The resorts development on

the coastal dunes and the establishment of irrigation system

are likely the main causes of changes in the area as revealed

by the study. These changes are expected to continue and

might impact the species distribution in the area. This needs

to be further assessed taking into account the influence of

climate change. Understanding how the changes in the

landscape and climate change might influence important

species distribution will help guide conservation planning in

the area. The study can serve as guidelines for other studies

attempting to project LUCC in arid lands experiencing similar

land use changes.

IV. Results

1999

2011

LULC Maps

1988, 1999, 2011

Landsat TM 5

Integrated

spectral &

ancillary data

Classification

Random

Forests

Breiman (2001)

LULC prediction

using Markov-

chain/Cellular

automata

Projected LULC

maps 2023

1988

Fig 6. Index of Landscape Conservation (ILC) estimated for the

whole landscape over the years 1988, 1999, 2011 and 2023.

Fig 4. Past and potential change processes

working over the studied landscape.

a)

b)

c)

ESA Living Planet Symposium 2013, Edinburgh, UK.

0.8

0.82

0.84

0.86

0.88

0.9

0.92

1988 1999 2011 2023

ILC

Year

1988

2011

1999

Projected 2023

Attrition

Aggregation

Creation

Dissection

1988-1999

1988-2023

1999-2011

1988-2011