evaluations of land use/land cover changes and land degradation in dera district, ethiopia: gis and...

International Journal of Scientific Research in Environmental Sciences, 2(6), pp. 199-208, 2014

Available online at http://www.ijsrpub.com/ijsres

ISSN: 2322-4983; ©2014 IJSRPUB

http://dx.doi.org/10.12983/ijsres-2014-p0199-0208

199

Full Length Research Paper

Evaluations of Land Use/Land Cover Changes and Land Degradation in Dera

District, Ethiopia: GIS and Remote Sensing Based Analysis

Temesgen Gashaw1*

, Amare Bantider2, Abraham Mahari

1

1Department of Natural Resource Management, Adigrat University, Ethiopia

2Center for Food Security Studies, College of Development Studies, Addis Abeba University, Ethiopia

*Corresponding Author: [email protected]

Received 23 February 2014; Accepted 29 April 2014

Abstract. Evaluation of land use/land cover changes and land degradation in Dera District, Ethiopia were undertaken using

two remotely sensed datasets (Landsat 5 TM of 1985 and Landsat 7 ETM+ imagery 2011). Land use/land cover change

detection and Normalized Difference Vegetation Index analysis was carried out on the two images. Global positioning system

and topographical maps of scale 1:50,000 for ground verification and ERDAS Imagine 9.1 and ArcGIS 9.2 software for

satellite image processing and analysis were used for the study. Field observations and focus group discussions were also

conducted to obtain addition information. The result of this study showed that cultivated and degraded lands were increased by

25.79% and 398% respectively at the expense of forest, shrub and grazing lands. Normalized Difference Vegetation Index

analysis has also indicated the increased of land degradation between 1985 and 2011 images which mainly aggravated by land

use/land cover changes.

Keywords: land use/land cover change, land degradation, NDVI

1. INTRODUCTION

Land use and land cover (LU/LC) change is a major

issue of global environment change (Prakasam, 2010).

The terms “land use” and “land cover” are often

confused. Land use change is defined as the alteration

of land use due to human intervention for various

purposes, such as for agriculture, settlement,

transportation, infrastructure and manufacturing, park

recreation uses, mining and fishery. In contrast, land

cover change refers to the conversion of land cover

from one category of land cover to another and/ or the

modifications of conditions within a category (Meyer

and Turner, 1992).

Land use dynamics is one of the major

environmental problems in Ethiopia (Berhan, 2010).

Studies conducted in different parts of the country

reported a significant decrease of vegetation cover due

to the expansion of cultivated land (Gete and Hurni,

2001; Belay, 2002; Gessesse and Kleman, 2007;

Abate, 2011). Estimates of deforestation in Ethiopia,

which is mainly for expansion of rain fed agriculture,

vary from 80,000 to 200,000 ha per annum (EPA,

1997). While, some studies conducted in the

previously degraded parts of north Ethiopia, revealed

improvement of vegetation cover due to plantation

and enclosure of the previously degraded hillsides in

the period since the 1980s. For example, a study

conducted by Woldeamlak (2002) in Chemoga

watershed, East Gojjam revealed the increased of

forest cover at a rate of 11 ha per annum from 1957-

1998, even though it is eucalyptus plantation. Similar

study by Amare (2007) and Amare et al. (2011) in

Eastern Escarpment of Wello, Ethiopia and Munro et

al. (2008) in Tigray highlands disclosed that

vegetation cover improved since the 1980s owing to

land rehabilitation efforts of the community supported

by the government and multilateral donor agencies.

Land degradation includes all process that

diminishes the capacity of land resources to perform

essential functions and services in ecosystems (Hurni

et al., 2010) are caused by two interlocking complex

systems: the natural ecosystem and the human social

system. Interactions between the two systems

determine the success or failure of resource

management (Berry, 2003). The major causes of land

degradation in Ethiopia are rapid population increase,

severe soil loss, deforestation, low vegetative cover

and unbalanced crop and livestock production (Girma,

2001). In this case, the Ethiopian highlands are highly

affected by land degradation, which have eroded the

Gashaw et al.

Evaluations of Land Use/Land Cover Changes and Land Degradation in Dera District, Ethiopia: GIS and Remote

Sensing Based Analysis

200

natural resource bases of the area (Tilahun et al.,

2001).

LU/LC changes and land degradation are

interrelated (Gete and Hurni, 2001; Lambin et al.,

2003; Kiage et al., 2007; Messay, 2011) because

LU/LC changes are associated with deforestation,

biodiversity loss and land degradation (Maitima et al.,

2009). As rightly noted by Abate (2011) it is taken as

a serious problem in changing the environment.

Similarly, Desta et al. (2000); Tilahun et al. (2001);

Belay (2002) stated that LU/LC changes towards

cultivated land aggravates soil erosion problems

unless proper management are undertaken. A study by

Hurni and Ludi (2000) also reveals that human land

use around the Simen Mountains National Park has

accelerated the degradation of vegetation and soils.

Thus, evaluating the existing LU/LC and its periodic

change and land degradation is useful for urban

planners, policy makers and natural resource

managers (Tahir et al., 2013). In this case, GIS and

remote sensing provides an ability to characterize

large assessment areas and establish reference

conditions (Abate, 2011). However, studies on

evaluation of LU/LC dynamics and land degradation

and their linkage are rare in Ethiopia in general and in

the study area in particular. Thus, this study aims to

evaluate the pattern of LU/LC changes and land

degradation and to analysis their link.

2. MATERIALS AND METHODS

2.1. Study area

This study was conducted in Dera district, Ethiopia

which is located between 12°

92' - 13°

12' N latitude

and 34°

40' - 35°

80' E longitude and elevation from

1798 m to 2118 m above sea level. Topographically,

the area exhibited plateau at the upper limit to plain in

the lower limit. The average annual rainfall and

temperature is 1250 mm and 19 ᵒC respectively.

Agriculture is the major economic activity which is

characterized by rain-fed and predominantly

subsistence nature. Both crops and livestock

productions are equally important at Dega and

Woinadega agro-ecological zones of the study area.

The main soil types of the study area are Nitisols,

Vertisols, Gleysols, Luvisols and Cambisols. The

dominant vegetation type includes: Eucalyptus

species, Croton macrostachyus, Juniperus procera,

Cordia africana and Ficus vasta.

2.2. Data collection

Two years multi-temporal satellite imageries (Landsat

5 TM of 1985 and Landsat 7 ETM+ imagery 2011)

were used for the study. Field observations and focus

group discussions with farming households (HHs)

were also conducted to obtain additional information.

Global positioning system and topographical maps of

scale 1:50,000 were used for ground verification.

Table 1: Types of landsat and toposheet used in the study

Image Path Row Sensor Resolution or

Scale

No of Bands Date of

acquisition

Source

Landsat5 169 52 TM 30 X 30 7 25/12/1985 GLCF

Landsat7 169 52 ETM + 30 X 30 8 12/1/2011 GLCF

Toposheet 1:50,000 EMA

2.3. Image Classification Methods

The overall objective of image classification

procedures is to automatically categorize all pixels in

an image into LU/LC classes to extract useful

thematic information (Boakye et al., 2008). Multi–

spectral image classification is one of the most used

methods to extract thematic information from satellite

images (Sarma et al., 2008). Image preprocessing

including band ratio, radiometric correction (haze

reduction), Tasseled Cap and post classification

comparisons were performed to correct the surface

features reflectance characteristics. Then, the LU/LC

maps were produced from Landsat5 TM of 1985 and

Landsat7 ETM+ of 2011.

Image classification was undertaken using hybrid

classification method involving both unsupervised and

supervised techniques. The hybrid classification

method was chosen because it improves the accuracy

and efficiency of the classification which involves

feature identification through both spectral and spatial

pattern recognition (Lillesand and Kiefer, 2000).

Using signature editor of unsupervised classes,

supervised categorization of image pixels were made

on the basis of their pixel by pixel spectral reflectance

and spatial relationships of pixels with pixels

surrounding them through geo-linking techniques.

Among different classification algorithms, maximum

likelihood was used for supervised classification by

taking 60 training areas for six major LU/LC class

categories (10 training points for each LU/LC class).


201

The LU/LC classes include forest land, shrub land,

grass land, cultivated land, degraded land and water

body (Table 2).

ERDAS Imagine 9.1 and ArcGIS 9.2 software

were used for satellite image processing and LU/LC

change analysis. The rate of change was calculated for

each LU/LC following the formula stated by Abate

(2011): Rate of change (ha/year) = (A-B)/C

Where: A = Recent area of LU/LC in ha, B =

Previous area of LU/LC in ha, C = Time interval

between A and B in years.

Fig. 1: Flow chart of LU/LC classification

2.4. Accuracy assessment

The fact that accuracy assessment is so important that

it tells us to what extent the truth on the ground is

represented on the corresponding classified image. In

this study, accuracy assessment was done for the

recent satellite image of Landsat7 ETM+

2011, for

which the ground truth data is likely corresponding.

An overall accuracy was calculated by summing the

number of pixels classified correctly and dividing by

the number of pixels. Thus, an overall accuracy of

84% with a Kappa coefficient of 0.82 was achieved.

Gashaw et al.



202

Table 2: Description of Land use and land cover classes (Adopted from Abate, 2011) Land use/Land cover

classes

Description

Cultivated land Areas allotted to rain fed and irrigated cultivation, including fallow plots, cultivated land mixed

with some bushes, trees and the scattered rural settlements included within the cultivated fields.

Forest land Areas covered by trees forming closed or nearly closed canopies; Forest;

Plantation forest; Dense (50-80% crown cover).

Shrub land Land covered by small trees, bushes, and shrubs, in some cases mixed with grasses; less dense than

forests.

Grass land Areas of land where small grasses are the predominant natural vegetation usually used for grazing.

Water body Areas covered by manmade small dams, seasonal water bodies and permanent water bodies.

Degraded land Are parts of the land surface which is mainly covered by bare soil and exposed rocks.

2.5. Methods of vegetation stress detection

In order to recognize the vegetation trend which is an

indicator of both environmental stress and land cover

degradation, the TM imagery of 1985 and ETM+ of

2011 acquired on December and January respectively

were used to calculate Normalized Difference

Vegetation Index (NDVI). NDVI is an empirical

formula designed to separate green vegetation from

other surfaces based on the vegetation reflectance

properties of the area. NDVI value of the result will

be between -1 and 1. NDVI values greater than zero

indicate the presence of vegetation. The higher the

vegetation index value, the higher the probability that

the corresponding area on the ground has a dense

coverage of green vegetation. Negative values

indicating no vegetation and correspond to the

presence of water bodies (Kiage et al., 2007). The

final NDVI map of the study area were categorized

into four parts that is water bodies (NDVI value < 0),

highly stressed (0 < NDVI value ≤ 0.2), moderately

stressed (NDVI value 0.2 < NDVI value ≤ 0.4) and

low stressed areas (NDVI value > 0.4). Thus, it is

possible to know the vegetation trend of the area from

1985 and 2011. ERDAS Imagine 9.1 for calculating

NDVI values and ArcGIS 9.2 for NDVI mapping

were used.

By using the NDVI result of two different years

image (1985 and 2011) vegetation changes were

detected which is calculated as NDVI= (NIR-RED)/

(NIR+RED)

Where NIR is the near infrared band response for a

given pixel and RED is the red response

3. RESULTS AND DISCUSSIONS

3.1. Land use/Land cover change analysis

The result of this study showed that cultivated and

degraded land had increased at a rate of 38.29 ha/year

and 15.2 ha/year respectively in the last 26 years

(1985-2011). These changes were at the expense of

forest, shrub and grass land (Table 3). In addition,

farmers in the area are encroaching and cultivating

sloppy and marginal areas, which aggravate land

degradation. LU/LC changes are complex and

interrelated that is the expansion of one land use type

is at the expense of others (Belay, 2002; Abate, 2011).

In relation to this finding, recent watershed based land

use studies has showed that land use change is brutal

and there has been agricultural land size expansion at

the expense of natural vegetation cover lands and

marginal areas without any appropriate conservation

measures (Woldeamlak, 2002; Amsalu et al., 2006;

Gessesse and Kleman, 2007). Similarly, Gete and

Hurni (2001) have also documented the expansion of

cultivated land at the expense of forestland between

1957 and 1982 in Dembecha area, northwestern

Ethiopia.


203

Table 3: LU/LC changes of the study area between 1985 and 2011 LU/LC class 1985 2011 Change in ha

(1985-2011)

Rate of change in

ha/year (1985-2011)

Percentage change

(1985-2011)

Area (ha) % Area (ha) %

Water body 38.79 0.53 35.64 0.48 -3.15 -0.12 -8.12%

Forest 706.41 9.6 310.14 4.22 -396.27 -15.24 -56.09%

Shrub 1408.32 19.14 464.4 6.31 -943.92 -36.3 -67.07%

Grass 1243.98 16.91 1196.46 16.26 -47.52 -1.83 -3.81%

Cultivated 3859.74 52.47 4855.23 66 +995.49 +38.29 +25.79%

Degraded 99.36 1.35 494.73 6.72 +395.37 +15.2 +398%

Total area 7356.6 100 7356.6 99.99

Fig. 2: LU/LC map of the study area (1985 and 2011)

3.2. Land degradation assessment

The statistics and visual observation of the NDVI

images over the subsequent periods were an evidence

for land cover changes that may well indicate

increased deforestation and land degradation in the

study area. As it can be visually compared, the

amount of green vegetation is falling. Taking the

maximum value, it dramatically decreases from 0.83

in 1985 to 0.58 in 2011. To this effect, the standard

deviation value decreases in certain value in 2011

image as compared to 1985 because of the change in

vegetation cover (Table 4). Overall, there was an

increase in the size of the land cover class classified as

severely stressed area. Similar study conducted by

Kiage et al. (2007) the Lake Baringo catchment,

Kenya, East Africa and Brhane (2010) in Dendi

district case study, Ethiopia reported the decline of

total vegetation cover and the increase of land

degradation in the study periods. Similarly, a study by

Ochego (2003) in Aberdares (Kenya) is also in

agreement with the findings of this study, who stated

that a positive mean of stressed area in the

period1987-2000. NDVI differencing is an indication

of reduction in biomass within this period of study

which implies a decline in vegetation.

Gashaw et al.



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Table 4: NDVI result of the study area

Statistics 1985 2011

Minimum -0.91 -0.09

Maximum 0.83 0.58

Mean 0.108 0.05

Standard Deviation 0.125 0.08

Fig. 3: NDVI map of 1985

3.3. LU/LC changes and land degradation in the

study area

Change in LU/LC doesn’t always give necessary

result in land degradation. But if LU/LC change is

towards cultivated and degraded land, the soil is easily

susceptible to erosion than forest, shrub and grass land

(Gete and Hurni, 2001; Belay, 2002; Woldeamlak,

2002; Maitima et al., 2009).

The change detected in the study area in

accordance with the classified classes between 1985

and 2011 revealed that forest, shrub and grass land

cover were transformed into cultivated and degraded

land. This showed how changes in LU/LC aggravate

land degradation. In addition, NDVI analysis has also

proved that there had been change in land use and

land cover and increase of land degradation between

1985 and 2011 images. Conversion of forest, shrub

and grazing land into cultivated land on steep slopes is

one of the causes for soil erosion and degraded land

(i.e. land out of cultivation). Thus, the study reveals

the existed LU/LC changes aggravated land

degradation. Similarly, Belay (1995) illustrated that

the expansion of agriculture towards the steeper

slopes has accelerated soil erosion in Ethiopia.

Tilahun et al. (2001) also accounted that declining

vegetative cover and increased farming on steep

slopes in Ethiopian highlands have eroded and

depleted soils in situ, so that soil degradation is now a

widespread environmental problem. Some impacts of

land degradation which are caused by LU/LC changes

include: increase of poverty and migration, land

productivity decline, loss of biodiversity, decline of

ground water recharge and carbon storage capacity,

change in population size, and spatial distribution

(Abate, 2011). As stated by Abbas et al. (2010), more

recent significant effects of land use change include

urban sprawl, soil erosion, soil and land degradation,

salinization and desertification. As discussed above,

the present research has shown complex linkages of

land use and land cover change with land degradation

(Fig 5).


205

Fig. 4: NDVI map of 2011

Fig. 5: Conceptual linkages of LU/LC changes and land degradation in the study area (Adapted from Maitima et al., 2009)

4. CONCLUSIONS

Evaluation of LU/LC changes and land degradation

using GIS and remote sensing applications in the

study area verified that forest, shrub and grazing land

were transformed into cultivated land. NDVI analysis

has also proved the increased of land degradation

between 1985 and 2011 images. These imply the

observed LU/LC changes are a cause for the observed

land degradation. Thus, creating off-farm job

opportunities, increasing family planning activities,

appropriate soil and water conservation measures,

appropriate use of soil fertility improving mechanisms

and also proper management of the land will reduce

the problem. Furthermore, the land use policy of the

country should be effectively implemented to reverse

the trend of LU/LC changes and land degradation and

at the same time to enhance the livelihood of farming

households.

REFERENCES

Abate S (2011). Evaluating the land use and land

cover dynamics in Borena Woreda of South

Wollo highlands, Ethiopia. Journal of

Sustainable Development in Africa, 13 (1): 87-

105.

Abbas I, Muazu M, Ukoje J (2010). Mapping land

use-land cover and change detection in Kafur

local government, Katsina, Nigeria (1995-2008)

using remote sensing and GIS. Research

Gashaw et al.



206

Journal of Environmental and Earth Sciences,

2(1): 6-12.

Amare B (2007). Landscape Transformation and

Opportunities for Sustainabable Land

Managewment Along the Escarpmemts of

Wello, Ethiopia. PhD Thesis, Bern University,

Bern.

Amare B, Hurni H, Gete Z (2011). Responses of rural

households to the impacts of population and

land-use changes along the Eastern Escarpment

of Wello, Ethiopia. Norwegian Journal of

Geography, 65:42-53.

Amsalu A, Leo S, Jan de G (2006). Long-term

dynamics in land resource use and the driving

forces in Beressa watershed, highlands of

Ethiopia. Journal of Environmental

management, 83: 13-32.

Berry L (2003). Land degradation in Ethiopia: its

impact and extent in Berry L, Olson J. and

Campbell D (ed): Assessing the extent, cost and

impact of land degradation at the national level:

findings and lessons learned from seven pilot

case studies. Commissioned by global

mechanism with support from the World Bank,

1-12.

Belay T (2002). Land-cover/land-use changes in the

Derekolli catchment of the South Welo Zone of

Amhara Region, Ethiopia. Michigan State

University Press, 18(1): 1-20.

Berhan G (2010). The role of Geo-information

technology for predicting and mapping of forest

cover spatio-temporal variability: Dendi district

case study, Ethiopia. Journal of Sustainable

Development in Africa, 12(6): 9-33.

Boakye E, Odai N, Adjei A, Annor O (2008). Landsat

images for assessment of the impact of land use

and land cover changes on the Barekese

Catchment in Ghana. European Journal of

Scientific Research, 22(2): 269-278.

Desta L, Menale K, Benin S, Pender J (2000). Land

degradation and strategies for sustainable

development in the Ethiopian high land,

Amhara region: socio-economic and policy

research working paper 32. International

Livestock Research Institute.

EPA (1997). Environmental Policy of Ethiopia.

Environmental Protection Authority in

collaboration with the Ministry of Economic

Development and cooperation. Environmental

Impact Assessment guidelines. The Federal

Environmental Protection Authority.

Gessesse D, Kleman J (2007). Pattern and Magnitude

of Deforestation in the South Central Rift

Valley Region of Ethiopia. Mountain Research

and Development, 27: 162-168.

Gete Z, Hurni H (2001). Implications of land use and

land cover dynamics for mountain resource

degradation in the Northwestern Ethiopian

Highlands. Mountain Research and

Development. 21 (2): 184-191.

Girma T (2001). Land degradation: A challenge to

Ethiopia. International Livestock Research

Institute, Addis Ababa, Ethiopia, 815-823.

Hurni H, Ludi E (2000). Reconciling Conservation

with Sustainable Development: a Participatory

Study inside and around the Simen Mountains

National Park, Ethiopia. With the assistance of

an interdisciplinary group of contributors,

University of Berne, Switzerland.

Hurni H, Solomon A, Amare B, Berhanu D, Ludi E,

Portner B, Birru Y, Gete Z (2010). Land

degradation and sustainable land management

in the highlands of Ethiopia. In: Hurni H,

Wiesmann U, editors; with an international

group of co-editors. Global change and

sustainable development: A synthesis of

regional experiences from research

partnerships. Georaphica Bernensia, 5: 187-

201.

Kiage L, Liu K, Walker N, Lam N, Huh O (2007).

Recent land-cover/use change associated with

land degradation in the Lake Baringo

catchment, Kenya, East Africa: evidence from

Landsat TM and ETM+. International Journal of

Remote Sensing, 28(19): 4285- 4309.

Lambin E, Geist H, Lepers E (2003). Dynamics of

land use and land cover change in tropical

regions. Annu. Rev. Environ. Resour., 28: 206-

232.

Lillesand T and Kiefer R (2000). Remote Sensing and

Image Interpretation. 4th ed. John Wiley and

Sons inc. New York.

Maitima J, Mugatha S, Reid R, Lyaruu H, Pomery D,

Gachimbi L, Mathai S, Mugisha S, Majule A

(2009). The linkages between land use change,

land degradation and biodiversity across East

Africa. International Livestock Research

Institute, 3(10): 310-325.

Munro R, Deckers J, Mitiku H, Grove A, Poesen J,

Nyssen J (2008). Soil landscapes, land cover

change and erosion features of the Central

Plateau region of Tigrai, Ethiopia: Photo-

monitoring with an interval of 30 years. Catena.

75: 55–64.

Messay M (2011). Land-use/land-cover dynamics in

Nonno district, Central Ethiopia. Journal of

Sustainable Development in Africa, 13(1): 123-

139.

Meyer W, Turner IIB (1992). Human Population

Growth and Global Land-Use/Cover Change.


207

Annual Review of Ecology and Systematics,

23: 39-57.

Ochego H (2003). Application of remote sensing in

deforestation monitoring: A case study of the

Aberdares (Kenya). 2nd FIG Regional

Conference. Marrakech, Morocco, December 2-

5, 2003.

Prakasam C (2010). Land use and land cover change

detection through remote sensing approach: A

case study of Kodaikanal taluk, Tamil nadu.

International journal of Geomatics and

Geosciences, 1(2): 150-158.

Sarma P, Lahkar B, Ghosh S, Rabha A, Das J, Nath

N, Dey S, Brahma N (2008). Land-use and

land-cover change and future implication

analysis in Manas National Park, India using

multi-temporal satellite data. Current science,

95(2): 1-5.

Tahir M, Imam E, Hussain T (2013). Evaluation of

land use/land cover changes in Mekelle City,

Ethiopia using Remote Sensing and GIS.

Computational Ecology and Software, 3(1): 9-

16.

Tilahun A, Takele B, Endrias G (2001). Reversing the

degradation of arable land in the Ethiopian

Highlands. Managing Africa’s Soils No. 23.

International center for research in agro

forestry.

Woldeamlak B (2002). Land cover dynamics since the

1950s in Chemoga Watershed, Blue Nile Basin,

Ethiopia. Mountain Research and Development,

22(3): 263-269.

Gashaw et al.



208

Temesgen Gashaw graduated his first degree from Jigjiga University, Ethiopia in Geography and

Environmental Studies (2009). Then, he employed his M.SC degree from Dilla University,

Ethiopia with specialization in Sustainable Natural Resource Management (2012). He completed

his first and second degree with Great Distinction. Currently, He is a lecture at Adigrat University,

Ethiopia in Natural Resource Management department since July 2012.

Amare Bantider (PhD) is Assistant Professor of Geography and Land Resource Management at

the Center for Food Security Studies, College of Development Studies, Addis Ababa University.

He obtained his first and second degrees from the Department of Geography and Environmental

Studies at Addis Ababa University (Ethiopia) in 1987 and 1996 respectively. He obtained his PhD

degree University of Bern, Switzerland in 2007. He was an Assistant Professor of Geography and

Land Resource Management at Dilla University, Ethiopia (2007-2013) and was Director for

Research and Community Service Directorate Office of Dilla University. He coordinated and

participated in several collaborative research projects such as Integrated River Basin Management

in Ethiopia, Doing Development with Young People, Soil and Water Conservation, and

Integrated Watershed Management. He published research articles on several reputable journals

and peer reviewed books.

Abraham Mahari received his first degree from Jimma University, Ethiopia in Natural Resource

Management in 2007. He later obtained his Master’s degree from Mekelle University with

specialization in Tropical Land Resources Management in 2011. Currently, he is working for

Adigrat University, Ethiopia as a lecturer under the department of Natural Resource Management

and has published numerous refereed articles in professional journals.

evaluations of land use/land cover changes and land degradation in dera district, ethiopia: gis and...

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