Proceedings of ACRS 2013
APPLICATION OF REMOTE SENSING AND GIS IN MONITORING
AND MAPPING OF SAND ENCROACHMENT IN WHITE NILE STATE, SUDAN
Mohamed Eltom Elhaja1*, Ibrahim Saeed Ibrahim2, Hassan Elnour Adam3, Elmar Csaplovics4
1
Faculty of Natural Resources and Environmental Studies (FNATRES)
University of Kordofan, Gamma Street, Elobeid, Sudan, [email protected]
2
Faculty of Agriculture, University of Khartoum (U of K), Shambat, Sudan, [email protected]
3
Faculty of Natural Resources and Environmental Studies (FNATRES)
University of Kordofan, Gamma Street, Elobeid, Sudan, [email protected]
4
Institute of Photogrammetry and Remote Sensing (IPF)
Technische Universitaet Dresden, D-01062 Dresden, [email protected]
*Corresponding author: [email protected]
ABSTRACT
Sand encroachment in the White Nile State has been recognized as the serious environmental
problem facing the study area, The objective of this study is to monitor and map the encroachment of
sand dunes, using remotely sensed imagery and GIS techniques for the period 1974-2008 and
moreover to evaluate the efficiency of remote sensing, GIS and GPS in achieving this objective. For
this purpose four satellite images (MSS 1974, TM 1986, ETM+ 2000 and 2008) were used, in addition
to field survey for ground control point collection. Visual interpretation, supervised classification and
change detection were applied. The result of the study revealed that the shifting dunes during 19742008 increased while the fixed dunes decreased by an annual rate of 0.31% and 0.44%, respectively.
The vegetation cover (dense vegetation + pasture land) in the study area has decreased by an annual
rate of 0.48%.
Keywords: GIS, sand encroachment, remote sensing, vegetation cover, White Nile State
INTRODUCTION
Sudan is confronted with a number of serious environmental problems, which include drought,
desertification (land degradation in dry-lands), and loss of biodiversity. Drought and desertification
have become major environmental problems in the northern and western parts of the country.
Desertification in Sudan is overwhelmingly visible only in the northernmost states.
Sand encroachment refers to removal or deposition of grains of sand or soil material. It is more of
a problem in dry areas than humid ones, but can also be significant in areas of seasonal rainfall if
vegetation is sparse or absent during the dry season. This phenomenon is caused by wind which can
remove, transport and deposit soil from steeping level as well as sloping lands. The conditions
conducive to sand encroachment are dry, loose and finely divided soil, with little or no vegetative
cover, relatively smooth surface, a wind of sufficient velocity, and a relatively large expanse of open
land (FAO, 1960).
In central Sudan (including White Nile State) sand encroachment poses a real threat to arable
lands. Therefore, this phenomenon should be given more attention. The primary source of the sand
which invades irrigation canals and degrades cropland is the Libyan desert. Generally speaking, overcultivation, woodland destruction, poor irrigation practices, overgrazing, unsustainable
development/public policy, alienated land ownership structure/ legislations, and wasteful energy
policy all add to accelerate the processes already common in the dry land. The physical and biological
degradation of soils is caused by wind and water erosion as well as soil salinization, even though the
intensity and combination of causes and processes differ under different land uses.
Desertification as a continuous process cannot be mapped and monitored by occasional
inspections. Space-borne Earth Observation (EO) is the only reliable system to collect systematic
qualitative and quantitative information at frequent rates on the variations of geo- and biophysical
parameters over large areas (Sarmap, 2003). However Khiry (2007) and Adam (2011) manifested that
spaceborne remote sensing is capable of monitoring vegetation cover through time series and is one of
the most reliable devices with high capability for information and data collection concerning different
SC04 - 722
Proceedings of ACRS 2013
fields.
MATERIALS AND METHODS
The study area lies within two localities of the White Nile state; El Gutayna locality east of the White
Nile and Ed Dueim locality west of the White Nile. The study area is located about 50 km south of
Khartoum, with following coordinate: latitude from 13° 58' 37'' N to 15°14'29'' N and longitude from
31°54'38'' E to 32°53'50'' E. It borders Kosti locality from the southern boundary, El Kartoum state
from the northern boundary, El Gazira state from the eastern boundary and North Kordofan state from
the western boundary of the study area (Figure 1). The area extends from the semi-arid climatic zone
in the north to the dry monsoon zone in the south (Van der Keive, 1973) with an average rain fall of
250–350 mm. The White Nile is running from the south to the north in the study area and divides it
into two parts, the eastern and the western bank of the White Nile. It covers an area of approximately
9955.79 km2. A generalized map of the geology of the research area shows only a small portion of
outcropping of solid rock formations belonging to the Basement Complex or the Nubian Sandstone
Series. The more recent superficial deposits in the area fall conveniently into three groups: the Umm
Ruwaba Series, the qoz sands, and clay deposits. Generally, the vegetation cover in the study area as
described by Obeidala (1982) is characterized by a mixture of grasses and herbs with scattered bushes,
interspersed with bare areas.
El Gutaina
Ad duwaym
White Nile State
Study area
Figure 1. Location of the study area
Materials
Four subsets of imagery from Landsat MSS, TM and ETM+ covering 9955.79 km² were used in
this study in colour-infrared band combination (G+R+n-IR). The image of 1974 (four bands in G, R
and n-IR) acquired by the Multispectral Scanner (MSS) sensor was used as the reference data set. The
image of 1986 was acquired by the Thematic Mapper (TM) sensor (seven bands in visible, n-IR, m-IR
and th-IR) while imagery of 2000 and 2008 was acquired by the Enhanced Thematic Mapper (ETM+)
sensor. The image of Landsat ETM+ (2008) was used as a base to assess changes and to combine other
images in addition to the topographical map of White Nile State dated 1978.
ERDAS Imagine 9.1 was used for imagery pre-processing, processing and analysis. ArcGIS 9.3
was used for geostatistical analysis and integration of the analysis of collected soil samples.
Methods
The study was conducted through geographical information system (GIS) techniques using
remote sensing and conventional field survey.
SC04 - 723
Proceedings of ACRS 2013
Field work and representative training sites
Field work, as one of the most important steps, was carried out in order to get an overall
impression of the landscape and for general inspection of the study area, nevertheless to compare the
features in satellite imagery with their in-situ characteristics in the study area, as well as to collect soil
samples.
Image pre-processing
All information extracted from remotely sensed data is obtained based on a consistent technical
work flow, considering geometric rectification, image registration and image matching. The Maximum
Likelihood method was used for the land use and land cover classification performed by ERDAS
IMAGINE 9.1 software.
Image classification and accuracy assessment
Training samples used to evaluate the spectral characteristics of land use classes were carefully
selected and represent each class with a high accuracy. MSS, TM, and ETM+ band combinations were
examined for classification by the same method (Maximum Likelihood). The confusion matrix was
created by comparing error values for each class that was classified with its respective value in the
ground truth data. The producer's and the user's accuracy are calculated for each class, as well as the
overall accuracy and the accuracy estimate that removes the effect of random change on accuracy,
referred to as the Kappa statistic.
Soil analysis
Particles Size Distribution (PSD) (sand/silt/clay) was analyzed to determine the texture according
to USDA salinity laboratory staff using hydrometer method (Soil Survey Staff 1999).
RESULTS AND DISCUSSION
Land cover and land use changes over the three periods covered by Landsat imagery (1974-1986,
1986-2000 and 2000-2008) were classified using supervised classification. The histograms of imagery
for each band show an acceptable pattern of normal distribution of pixels over the spectral space.
The results of classification allowed for the separation of ten classes, explicitly: water body, dense
vegetation, shifting dunes, fixed dunes, rain-fed agriculture on sand soil, rain-fed agriculture on clay
soil, irrigated agriculture, pasture land, settlement, and bare land.
Table 1. Summary of accuracy (%) and Kappa statistics of MLC maps
LULC classes
1974
1986
2000
2008
1
2
Producers
%
95.35
82.14
Users
%
91.11
82.14
Producers
%
100
88.46
Users
%
100
92
Producers
%
100
81.82
Users
%
100
81.82
Producers
%
98.04
100
Users
%
100
91.67
3
83.91
83.91
87.80
86.75
83.93
90.38
93.17
86.71
4
93.96
86.42
91.30
86.60
91.40
87.63
71.11
86.49
5
78.95
81.82
91.43
84.21
94.74
87.80
86.75
88.89
6
86.11
81.58
93.62
91.67
92.16
91.26
94.50
92.79
7
100
97.87
100
100
93.33
100
100
100
8
87.71
86.74
93.94
95.38
88.13
88.68
87.50
90.91
9
100
100
95.24
95.24
96.43
100
95.24
97.56
10
51.11
85.19
74.47
87.50
57.14
80.00
80
80
Overall
86,41%
91.90%
90.43%
91.34%
86,41%
91.90%
90.43%
91.34%
Classification
Accuracy
Overall Kappa
0,8394
0.9041
0.8838
0.9056
0,8394
0.9041
0.8838
0.9056
Statistics
1 Water body, 2 Density vegetation, 3 Shifting dunes, 4 Fixed dunes, 5 Rain-fed agriculture on sand soil, 6 Rain-fed
agriculture on clay soil, 7 Irrigated agriculture, 8 Pasture land, 9 Settlement, 10 Bare land
SC04 - 724
Proceedings of ACRS 2013
The overall accuracies of the LU/LC maps for 1974, 1986, 2000, and 2008 produced by
a supervised classification approach (i.e. Maximum Likelihood) are 86.41%, 91.90%, 90.43% and
91.34%, respectively. The Kappa indices are 0.8394, 0.9041, 0.8838, and 0.9056, respectively (Table
1). According to Jensen (2005) the accuracy assessment indicates a strong agreement of the results of
classification with ground reference data.
Results of soil analysis
The texture of surface soils in the northwestern part of the study area is fine sand, coarse sand and
loamy fine sand with some fine and coarse sandy loam pockets, while sandy clay and clay soil
dominate in the far south-west. Soils which are located in the eastern part of the study area are
characterized by a range of textures from sandy clay, clay, sandy clay loam, clay loam and loam in the
far southeast to coarse sandy loam and find sandy loam in the center to loamy fine sand and coarse
sand in the far northeast, except some areas adjacent to the El jazeera agricultural project, in which the
soil is predominated by clay textures (figure 2).
Figure 2. Soil texture map of the study area (Survey of the author)
Results of GIS analysis
The results in tables (2and 3) showed that the shifting dunes increased during the first period
(1974-1986) from 11.42% to 12.31% at an annual rate of 0.07%. This meant new 88.89 km2 were
added to the area of shifting dunes. In the second periods (1986-2000) the area of shifting dunes
decreased from 12.31% to 7.78%, which meant that 450.88 km2 of the shifting dunes changed to fixed
dunes and to others LU/LC classes. The third period (2000 – 2008) could be described as the worst
period during the whole study period (34 years). That was because the area of shifting dunes increased
rapidly, whether of a mutant of the fixed dunes already in the study area or as new incoming sand from
Kordofan regions toward the study area. The area of shifting sand dunes increased from 7.78% in 2000
to 21.88% in 2008, equivalent to 1403.92 km2 with an annual rate of increase 1.8%.
While the area of fixed dune decreased from 21.85% in 1974 to 13.35% in 1986 with annual rate
of decrease of 0.71%. While in the same period the shifting dunes area increased, indicating the
occurrence of sand encroachment in some areas. The evidence was clear in the figure (3) which
SC04 - 725
Proceedings of ACRS 2013
reflected that, most of the fixed dunes, which were located in the eastern upper part of the study area
specifically north east of the Al Gutaina town, had been converted into shifting dunes during the
period from 1974 to 1986. During the period 1986-2000 the proportion of fixed dunes increased from
13.35% to 26.9% with an annual rate of increase 0.37%. This meant that new 55 km2 were added to
the area of fixed dunes. While in the period of 2000 -2008 the proportion of fixed dunes decreased
again to 6.95% instead of 26.97%. This large percentage of decrease in the area of fixed dunes was a
warning of "a creeping disaster" because, in fact the fixed dunes were converted to the shifting dunes
and then toward the far eastern part of the study area (particularly at the border with Al jazeera project
had already penetrated into Al jazeera project.
Table 2. Distribution of LU/LC classes in the study area during 1974- 2008
LU/LC type
1974
1986
%
2000
%
2008
1
Area
(Km2)
634.10
6.37
Area
(Km2)
661.18
6.64
668.41
Area
(Km2)
6.71
%
2
395.45
3.97
352.56
3.54
154.85
1.56
280.68
2.82
3
1136.76
11.42
1225.65
12.31
774.77
7.78
2178.68
21.88
4
2175.38
21.85
1328.93
13.35
2685.30
26.97
691.44
6.95
5
843.32
8.47
643.75
6.47
372.16
3.74
1139.66
11.45
6
650.21
6.53
1397.85
14.04
1682.78
16.90
1641.85
16.49
7
640.61
6.43
486.35
4.89
510.85
5.13
1422.00
14.28
8
2766.55
27.79
2984.40
29.98
2378.85
23.89
1224.89
12.30
9
155.91
1.57
276.65
2.78
425.25
4.27
525.94
5.28
10
557.51
5.60
598.45
6.01
302.59
3.04
209.41
2.10
641.24
Area
(Km2)
6.44
Total
9955.79
100.00 9955.79
100.00
9955.79
100.00
9955.79
100.00
1 Water body, 2 Density vegetation, 3 Shifting dunes, 4 Fixed dunes, 5 Rain-fed agriculture on sand soil, 6 Rain-fed
agriculture on clay soil, 7 Irrigated agriculture, 8 Pasture land, 9 Settlement, 10 Bare land
Table 3. Land use and land cover classes change during (1974-2008)
LU/LC type
1974-1986
1986-2000
%
1
Area
(km2)
27.09
2
-42.89
-0.43
-197.71
-2.42
125.83
1.26
3
88.89
0.89
-450.88
-3.64
1403.92
14.10
4
-846.45
-8.50
1356.36
5.12
-1993.86
-20.03
5
-199.57
-2.00
-271.59
-4.73
767.50
7.71
6
747.64
7.51
284.93
10.37
-40.93
-0.41
7
-154.25
-1.55
24.50
-1.30
911.15
9.15
8
217.85
2.19
-605.56
-3.89
-1153.95
-11.59
9
120.75
1.21
148.59
2.71
100.69
1.01
10
40.94
0.41
-295.86
-2.56
-93.18
-0.94
0.27
Area
(km2)
7.22
2000-2008
%
0.34
Area
(km2)
-27.17
%
-0.27
Total
0.00
0.00
0.00
0.00
0.00
0.00
1 Water body, 2 Density vegetation, 3 Shifting dunes, 4 Fixed dunes, 5 Rain-fed agriculture on
sand soil, 6 Rain-fed agriculture on clay soil, 7 Irrigated agriculture, 8 Pasture land, 9 Settlement,
10 Bare land
SC04 - 726
Proceedings of ACRS 2013
Figure 3. Land use and land cover distribution in the study area
The comparison of dense vegetation cover from 1974 to 2008 shows that there was a slight
deterioration over the preceding years, as dense vegetation cover decreased from 3.97% in 1974 to
2.82 % in 2008 with an annual rate of deterioration of 0.03 %, while the pasture land decreased from
27.79% in 1974 to 12.30% in 2008 with an annual rate of deterioration of 0.45%.
Figure (3) highlights the land cover changes regarding sand dunes (fixed and shifting) during the
period 1974 - 2008 in addition to the respective change patterns of the other land use land cover
classes in the study area. Generally a comparison of maps shows that less area of shifting sand dunes,
especially in the eastern part of the study area, is evidenced by the map of 2000, while the map of
2008 shows the extensive distribution of sand dunes, especially in the eastern part of the study area
along the fringes of the El jazeera project with partial invasion into the project area itself.
Figure (4) also showed that there was an inverse relationship between the fixed dunes and shifting
dunes in the study area. When the area of fixed dunes increased the shifting dune decreased and vice
versa. This might be attributed to the mutual change of the type of dune to the other type, and the
seasonal presence of vegetation covers which is mostly dominant by the annual grasses.
SC04 - 727
Proceedings of ACRS 2013
% A rea
30
20
10
0
1970
1980
1990
2000
2010
Time
Shifting dune
Fixed
dune
Fixe
dune
Figure 4. Relationship between fixed and shifting sand dune in the study area during (19742008).
CONCLUSION
The results of the study prove that the methodology applied in this study is effective in monitoring
and mapping encroachment of sand dunes based on multi-temporal Landsat satellite imagery. The
discrimination between fixed sand dunes (cover by annual grasses) and rainfed agriculture on sandy
soils is difficult which is mainly caused by the similarity of spectral signatures of the both laand cover
types. The study also demonstrates the seriousness of the encroachment of sand dunes which already
threatens the El Gazera project being a pilot project for agricultural production in the Sudan.
REFERENCES
[1] Adam H.E., (2011). Integration of remote sensing and GIS in studying vegetation trends and
conditions in the gum arabic belt in North Kordofan, Sudan. PhD thesis. Faculty of Forest, Geo
and Hydro Sciences, Dresden, Germany.
[2] FAO, (1960). Soil erosion by wind and measures for its control, Rome.
[3] Jensen J.R., (2005).Thematic map accuracy assessment. In: Introductory digital image
processing.A Remote Sensing Perspective, 3rd ed.; Keith, C.C., Ed.; Prentice Hall Series in
Geographic information science: Saddle River, NJ, USA, 2005; Sect. C, (495–515).
[4] Khiry M.A., (2007). Application of remote sensing in monitoring drylands, North Kordofan
State, Sudan. PhD thesis. Faculty of Forest, Geo and Hydro Sciences, Dresden, Germany.
[5] Obeidala A., (1982). The Kheiran rural development project, district. Kordofan regional ministry
of agriculture and natural resources, El Obeid, Sudan.
[6] Sarmap, (2003). Treaty Enforcement Services using earth obsevation – Desertification,
University of Valencia, EOS.D2C, Chinese academy of forest, final report, ESA/ESRIN.
[7] Soil Survey Staff, (1999). Soil Taxonomy a basic system of soil classification for making and
interpreting soil surveys, 2nd edition. Agricultural Handbook 436, Natural Resources
Conservation Service, USDA, Washington DC, USA, 869p.
[8] Van Der Kevie W., (1973). Climatic Zones in Sudan. Soil Survey Administration, Wad Medani,
Sudan.
SC04 - 728