LandUse/LandCoverChangeandItsDrivingForcesinShenkolla ...

Research ArticleLand UseLand Cover Change and Its Driving Forces in ShenkollaWatershed South Central Ethiopia

Belayneh Bufebo 12 and Eyasu Elias2

1Department of Natural Resource Management Wachemo University PO Box 667 Hosanna Ethiopia2Center for Environmental Science College of Natural and Computational Sciences Addis Ababa UniversityAddis Ababa Ethiopia

Correspondence should be addressed to Belayneh Bufebo belaytummagmailcom

Received 24 May 2020 Revised 2 February 2021 Accepted 8 February 2021 Published 19 February 2021

Academic Editor Richard A Smith

Copyright copy 2021 Belayneh Bufebo and Eyasu Elias is is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in anymedium provided the original work isproperly cited

Land use change is one of the challenges that aggravate environmental problems Understanding the scope of land use changedriving forces and consequences is very crucial for proper management of land resources We investigated land useland coverchanges using remote sensing data (for the years 1973 1995 and 2017) and field observation household survey key informantinterview and focus group discussion were used to determine the drivers and consequences of land useland cover changes inShenkolla watershed south central Ethiopia Unsupervised and supervised classification techniques were employed to getthematic information from satellite imagery ArcGIS 103 and QGIS v 30 softwares were used to accomplish the analysis eresults disclosed that Shenkolla watershed has changed significantly during the past 4 decades between 1973 and 2017 isobserved change indicates a reduction in forest land and an increase in agricultural land Forest land was reduced from 2951 in1973 to 2052 in 2017 but agricultural land was expanded from 7049 in 1973 to 7948 in 2017 Agricultural expansion policychange and social unrest population pressure shortage of farm land and biophysical factors were major driving forces of the LULC changes Environmental implications such as climate change biodiversity loss scarcity of basic forest products habitatalteration decline in quality and availability of water and crop yield reduction are the consequences of the LULC change eexpansion of agricultural land at the expense of forest cover in Shenkolla watershed has negative implications on the naturalresources and the livelihood of local people Hence appropriate measures need to be employed to reduce the dramatic change inland use and to harmonize environmental conservation with human livelihood

1 Introduction

e complex and dynamic land useland cover change atvarious scales has environmental implications [1 2] emain driving forces of LULC change can be traced to theconsumption demands of the increasing population that is amajor issue of concern in relation to change in the naturalenvironment [3ndash5] Land use change can trigger soil deg-radation and soil erosion which changes watershed prop-erties that may cause flooding in nearby areas [6]Desertification loss of biodiversity habitat destruction soildegradation and a reduced ability of the watershed tosustain natural resources and ecosystem services are theconsequences of land useland cover change [7ndash9] e

consequences of land use change challenge conservationmanagement and rehabilitation activities [10] e rela-tionship between land useland cover change and its drivingfactors is complicated and dynamic Some of the previousstudies suggest that demographic changes contribute morethan any other causative factors of land useland coverchanges [11] Other studies suggest economic factors to bethe major drivers of LULC change [12]

Over the past few decades considerable LULC changehas been happening in the highlands of Ethiopia Previousstudies indicated that the decrease of forest cover and ex-pansion of agricultural land into steep slope areas notsuitable for cultivation are significant forms of LULCchange in most highlands of Ethiopia [13ndash15] ere was a

Hindawie Scientific World JournalVolume 2021 Article ID 9470918 13 pageshttpsdoiorg10115520219470918

substantial increase in cultivated land at the expense of forestcover in northwest [13] northeastern [16] and eastern[17 18] Ethiopia e loss of natural vegetation from 1973 to2000 in Abijata Shala National Park and Zway-Awasa Basinwas 834 and 701 respectively [19] On the other handsome studies revealed the improvement of forest cover dueto afforestation and land rehabilitation activities carried outby the community [20 21] Most previous studies on LULCchanges were concentrated in specific areas mainly in theNorthern highlands and some areas in the rift valley lakebasin of Ethiopia and quantified only the extent of land useland cover changes using remote sensing images howeverthey did not provide explanations on local people perceptionof driving forces of LULC change and associated conse-quences [22] In addition studies on land useland coverchanges are still very limited in the Omo Gibe river basin ofsouth central Ethiopia In order to implement measures tominimize LULC changes it is important to understand howthe community perceives the causes and consequences ofLULC changes [23]

LULC change is more recognized as an important driverof environmental degradation and loss of quality on spatialand temporal scales LULC change contributes significantlyto climate change reduction in forest cover and biodiversityloss [24] In addition LULC change is one of the factors thatinfluences runoff soil loss and stream flow [20] Remotesensing data analysis has a limitation to explain nonspatialdata such as derivers and consequences of land uselandcover change As LULC change increases linking infor-mation obtained through Earth observation with humanperception is significant in gaining a comprehensive un-derstanding of pattern of LULC changes driving forces andconsequences [22 25] e study area Shenkolla is knownto be productive in cereal production but the area is exposedto sever erosion and soil loss triggered by LULC changeHence a thorough understanding of the extent of LULCchange driving forces and consequences of LULC changeis crucial to design more effective environmental policiesand appropriate land management strategies for the entirewatershed and beyond [26] However land useland coverchange of Shenkolla watershed is not investigated so far asthe result the extent of such change its driving forces andconsequences are poorly understood erefore the mainobjective of the study was to analyze the LULC changesfrom 1973 to 2017 and its driving forces and consequencesand to evaluate the coherence of community perception tothe changes observed through the interpretation of remotesensing images in the study watershed

2 Materials and Methods

21 Description of the Study Area e study was conductedin Shenkolla watershed covering 1457 ha in south centralEthiopia e geographical location of the area falls withinthe coordinates of 7deg24prime30Primendash7deg27prime0Prime N latitude and37deg43prime30Primendash37deg46prime30Prime E longitude (Figure 1) e altituderanges from 2200ndash2830m which is characterized by gently

sloping to rolling plateaus with moderate to high relief hillsand dissected side slopes

e climate of the watershed is characterized generally asa tepid submoist midhighland with a long-term averagerainfall of about 1107mm with bimodal pattern having Belg(traditional division of the year with light rain) usually fromMarch toMay and theMeher (traditional division of the yearwith heavy rain) from June to September e annual av-erage temperature of the study area is 172degC (Figure 2)

Geological formation is dominated by the quaternaryvolcanics composed of acidic parent materials (rhyolitestrachytes etc) [27] Nitisols are the most dominant soil typesalong with Vertisols Cambisols and Planosols that coverextensive areas of agricultural fields [27]

Subsistence farming is the major source of livelihoodrelying on rain-fed crop cultivation with the major cropsbeing wheat (Triticum aestivum L) teff (Eragrostis tef )(Zucc Trotter) maize (Zea mays L) barley (Hordiumvulgare L) sorghum (Sorghum bicolor L) horse beans(Vicia faba L) and potato (Solanum tuberosum L) ehomestead garden fields are characterized by Enset (Enseteventricosum) and with interspersed trees that increase thefertility of the soil Under normal climatic conditions thecultivation of crops is possible during both Belg (traditionaldivision of the year with light rain) and Meher (traditionaldivision of the year with heavy rain)

Due to the intense pressure of population growth andland scarcity it is almost impossible for farmers to practicethe appropriate fallow length is resulted in dramatic landuseland cover changes in the watershed e current landuseland cover types of the study area were categorizedbroadly into two categories forest land and agricultural lande forest cover of the study area also comprises natural andplantation forests while the agricultural land includes cul-tivated land small plots of grazing lands and scattered ruralsettlements During the past four decades the conversion offorest into agricultural land in the Shenkolla watershed wasquite intense As a result the agricultural land use classcovers the largest proportion of the study area

22 Data Sources e main data sources for this researchwere semistructured questionnaires complemented withfield observations remote sensing imagery topographicmaps supportive data such as GPS records and relatedliteratures is study involved the use of mixed methodsto complement each other since the methods have theirown weaknesses and strengths Primary data were col-lected through extensive field observation key informantinterview and focus group discussions Ancillary data(training sites and ground control points) consisting ofdifferent LULC features and their location points wererecorded using a Global Positioning System (GPS) in-strument [28] e images were freely obtained (down-loaded) from the USGS Glovis website (httpglovisusgsgov) ArcGIS 103 and QGIS v 30 software were used toclassify the image and to delineate the study area e

2 e Scientific World Journal

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Figure 1 Map of the study site in southern Ethiopia

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acquisition dates sensor pathrow resolution and thesource of the images used in this study are summarized inTable 1

23 Image Preprocessing and Classification Methods Allsatellite images were geometrically corrected to the Uni-versal Transfer Mercator coordinate system and georefer-enced to the data in which Ethiopia has selected by the WGS(World Geodetic System) (zone 84) Moreover pre-processing activity such as radiometric correction and a falsecolor grid composite image are developed before classifyingthe images [29 30]

Image classification was carried out by sorting pixels intoa finite number of individual categories of data based ontheir data file values [31ndash33] All pixels in an image wereplaced into LULC classes to draw out useful thematic in-formation [34] First unsupervised classification was used toget the major land parcels which then used for supervisedclassification A total of 150 training sites were selected basedon image interpretation keys during the field survey andfrom interviews with the local inhabitants Reference pointsin different land useland cover types were randomlyrecorded during the field survey using a hand-held GlobalPosition System (GPS) for the 2017 images the same as theprocedure followed by [35 36] Supervised classificationwith maximum likelihood algorithm was used to classify theindividual images independently using the ground controlpoints collected from each LULC category [37 38] ArcGIS103 and QGIS v 30 software were used for overall imageprocessing e way of classification of this study wasadopted in such a way that it suits the purpose of the studyFinally two land useland cover classes were identified usingindependent classification of individual images from dif-ferent dates for the same geographic location ese includeagricultural land and forestland e dispersed rural set-tlement and small scattered plots of grazing land werecategorized as agricultural land use class Land uselandcover classes of Shenkolla watershed and the correspondingdescription are displayed in Table 2

24 Classification Accuracy Assessment To perform accu-racy assessment for the classified images 100 randomsample points (50 for each land use) in Arc GIS 103 werecreated for LULC mapping for the years 1973 1995 and2017 respectively Ground control points recorded by usinga hand-held GPS were used as the reference data to evaluatethe results In addition reference points collected from thetopographic map of 1973 and visual interpretation of the rawLandsat TM 1995 images as well as the personal knowledgeof the study area and Google Earth images were used eclassification accuracy assessments of the resulting LULClayers were performed by examining the sample LULC classof the classified layer and the reference layer to discoversimilarities and differencesis means the classified imageswere compared with the reference images by creating anerror matrix [38] By comparing the datasets the proportionof pixels correctly classified was estimated Error matriceswere plotted as cross tabulations of the classified data versus

the reference data and were used to assess the classificationaccuracy Afterwards the overall accuracy userrsquos and pro-ducerrsquos accuracies and the kappa coefficient were thenderived from the error matrices Overall accuracy was cal-culated using the following formula [39] as shown inequation (1) while the Kappa coefficient was calculatedusing the formula [40] shown in equation (2)

A x

ylowast 100 (1)

where A is the overall accuracy x is the number of correctvalues in the diagonals of the matrix and y is the totalnumber of values of a reference point

e Kappa coefficient is a measure of overall agreementof a matrix e Kappa coefficient takes also nondiagonalelements into account [41] e Kappa coefficient whichmeasures the difference between the actual agreement ofclassified map and chance agreement of random classifiercompared to reference data was calculated as follows

K N 1113936

ri1 xii minus 1113936

ri1(xi + lowast x + i)

N2

minus 1113936ri1(xi + lowast x + i)

(2)

where K is the Kappa coefficient r is the number of rows inthe matrix xii is the number of observations in row i andcolumn i xi + are the marginal totals of row i x+ i are themarginal totals of column i and N is the total number ofobservations

25 LULC Change Detection e pattern of changes interms of hectares for land useland cover classes wascomputed for each mentioned time period and the extent ofalteration in land use types within and between time periodswas compared e rate of change in hectares per year [42]and percentage share [43] of each land use class werecomputed to demonstrate the magnitude of the changesexperienced between the periods using the followingequations

CA() X2 minus X1

X11113888 1113889lowast 100 (3)

Rate of changehayear

1113888 1113889 X2 minus X1

y1113888 1113889

(4)

where CA () percentage change in the area of land useand land cover type between initial timeX1 and final timeX2X1 area of land useland cover type at the initial yearX2 area of land useland cover type at the final yearY time interval between the final and initial years

26 Exploring the Drivers and Consequences of LULCChanges Household survey key informant interviews andfocus group discussions were conducted to prove the cor-rectness of the classified images and further come to knowthe possible major driving factors and consequences of landuse change in the watershed A questionnaire with


semistructured questions was used to assess the perceptionof local people on LULC change its drivers and conse-quences e most appropriate age was decided to be 55 andabove erefore 100 respondents with age 55 and abovewere purposively selected to identify LULC changes drivingforces and consequences Respondents were requested toexplain how they perceived LULC dynamics in the wa-tershed in different time periods assessed in this study eyevaluated the status of the land useland cover change itsdrivers and consequences Finally the driving forcesconsequences and the direction of land use change wereidentified Subsequently the perceived LULC changes werecompared with the land useland cover changes observedfrom the remote sensing images interpretation (Figure 3)

3 Results and Discussion

31 Classification Accuracy Assessment e reliability andaccuracy of the classification was measured using a confu-sion matrix e confusion matrix worked out the overallaccuracy producer and user accuracy and kappa statisticswith mathematical precision Correctly classified values areshown on diagonals of thematrix while incorrectly classifiedvalues are away from the diagonals e overall accuracy forthe classified images of the 1973 1995 and 2017 was 85 83and 87 respectively (Table 3) e kappa statistic for 19731995 and 2017 LULC maps was 070 066 and 074respectively showing a good level of agreement between theclassified images and the referenced data is image-processing approach was found to be effective in producingcompatible data of LULC changes e report of the overallaccuracy and accuracy of the individual groups of the threeclassified images is presented in Table 3

32 Land UseLand Cover Change Analysis e land useland cover change analysis showed that the study area hasexposed to a marked land use change over the past fourdecades LULC change detection between 1973 1995 and2017 of the study area indicated that there were significantconversions from forest land use to agricultural land eloss of forest cover has been the most visible evidence of landuseland cover change in the Shenkolla watershed for the last

40 years e land useland cover classes of the study areawere classified in to two classes namely forest land andagricultural land e change detection statistics for fourdecades of the study area are presented in Table 4

According to the produced LULCmap (Figure 4) it wasfound that agricultural land was the dominant type of LULC class for the years 1973 and 1995 and 2017 e highestexpansion of agricultural land at the expense of forest landwas recorded in 1995 e map of the years 1973 1995 and2017 showing change in land useland cover through overtime due to various causes is presented in Figure 4

33 Land UseLand Cover Conversions between 1973 and1995 e rate and trend of land useland cover trans-formations varied to a significant degree between the timeintervals under investigation Land useland coverchanges are dynamic and nonlinear that is the conver-sion from forest land use class to agricultural land doesnot follow a similar pattern of change in different periods[44] Change detection results of the first period(1973ndash1995) showed an increasing trend of agriculturalland on the contrary forest land showed a decreasingtrend In 1973 there were 430 ha (2951) and 1027 ha(7049) of forest and agricultural land respectivelyHowever forest land decreased from 430 ha (2951) to346 ha (2375) is indicated that 576 of forest landhas been converted to agricultural land use class and as aresult the area coverage of the agricultural land was in-creased in the year 1995 (Table 4) ese changes in landuseland cover systems have important environmentalconsequences through their impacts on soil water bio-diversity and microclimate [7] e annual rate of changein forest land from 1973 to 1995 was minus195 but agri-cultural land increased annually by 82 (Table 5) enegative change in the forest area implies a decline in thearea coverage of forest whereas agricultural land waspositive suggesting increasing area extent Agriculturalland gained from forest land as the result there was asignificant loss of forest land in the watershed (Table 6)is result is in agreement with reports elsewhere in theEthiopian highlands that showed agricultural land ex-pansion at the expense of forest and grazing lands [45]

Table 1 Characteristics of images used for land useland cover change analysis

Satellite image Sensor Pathrow Resolution (m) Bands used Acquisition date SourceLandsat 1 MSS 18155 57lowast 57 1 2 3 and 4 31011973 USGSLandsat 5 TM 16955 30lowast 30 1 2 3 4 5 and 7 21011995 USGSLandsat 8 OLI_TIRS 16955 30lowast 30 1 2 3 4 5 6 and 7 2022017 USGS

Table 2 Descriptions of land useland cover types for the period 1973ndash2017

Land useland coverclass Description

Forest land Land covered with natural and plantation forests

Agricultural land Areas of land which include cultivated outfields (areas of land used for growing various crops) homestead gardenfields rural settlements and small scattered plots of grazing lands


34 Land UseLand Cover Conversions between 1995 and2017 In the second period (1995 to 2017) the extent offorest land decreased from 346 ha (2375) to 299 ha(2052) and agricultural land increased from 1111 ha(7625) to 1158 ha (7948) (Table 4) is showed thatagricultural land increased with the expense of forest land inthe study area In this period 47 ha of forest land waschanged into agricultural land in 22 years is showed that

agricultural land gained from forest land (Table 7) As aresult the area coverage of agricultural land class in thestudy area was increased by 47 hectares During the secondperiod from 1995 to 2017 the annual rate of change in thearea of forest land and agricultural land showed a decreasingand increasing trend by minus214 and +214 respectivelye decreasing trend of forest land is associated with theexpansion of agricultural land to meet the food demands of

Observed LULC changes

Perceived LULC changes

Perceived drivers of LULC changes

Perceived consequences of LULC changes

Comparison of observedLULC changes and

perceived LULC changes

Remote sensing images

Topographic mapsfield observations

List of questions usedto gather information on historical LULC

changes

List of questions usedto gather information on driving forces of

LULCC

List of questions used to gather information onconsequences ofLULC changes

Discovering similarities and differencesbetween observed and perceived LULC changes

Datasources

Analysis

Figure 3 Methodology of comparison between observed and perceived LULC changes

Table 3 Accuracy assessment (in percent) of the 1973 1995 and 2017 LULC maps

Land useland cover1973 1995 2017

Accuracy ()Userrsquos Producerrsquos Userrsquos Producerrsquos Userrsquos Producerrsquos

Agricultural land 88 83 86 81 90 85Forest land 82 87 80 85 84 89Overall accuracy () 85 83 87Kappa coefficient 070 066 074


Table 4 Areas and percentages of LULC classes for the years 1973 1995 and 2017

LULC category1973 1995 2017

Area (ha) Area (ha) Area (ha) Agricultural land 1027 7049 1111 7625 1158 7948Forest land 430 2951 346 2375 299 2052Total 1457 100 1457 100 1457 100

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Figure 4 Land useland cover changes of Shenkolla in the years (a) 1973 (b) 1995 and (c) 2017

Table 5 Percent and rate of land use changes in the Shenkolla watershed from 1973 to 2017

Land useland coverPercent changeyear Rate of change in hayear

1973ndash1995 1995ndash2017 1973ndash2017 1973ndash1995 1995ndash2017 1973ndash2017Agricultural land 82 42 128 +382 +214 +298Forest minus195 minus136 minus305 minus382 minus214 minus298


the growing population e negative and positive changesin change detection correspond to the gain or loss of thatparticular land cover

35 Land UseLand Cover Conversions between 1973 and2017 Over the whole period of investigation (1973ndash2017)agricultural land increased from 7049ndash7948 On theother hand forest land decreased from 2951ndash2052(Table 4) Generally within these 44 years 131 ha of forestland were changed into agricultural land During this periodthe annual rate of change of forest and agricultural land wasminus298 and +298 respectively (Table 5) Agricultural landgained from forest land as a result there was a significantloss of forest land in the watershed (Table 8) is shows thatagricultural land was increasing significantly whereas forestland was shrinking in Shenkolla watershed

36 =e Transition Matrix Evidences from this studyshowed that a substantial portion of the Shenkolla watershedundergoes great changes in land useland cover Agriculturalexpansion the most prominent phenomenon is most as-sociated with the decline in forest lands is is possibly asimilar trend in that most studies pointed out the expansionof agricultural land to be at the expense of forestland in mostareas in the Ethiopian highlands [15] e findings of thisstudy also visualized the most improperly used forest landuse class needs urgent protection and conservation inter-ventions Information from this study on a significant re-duction of forest land over time is important for land useplanners and policy makers to take any intervention actionstoward forest conservation Moreover the transition matrixcan aid to know the altered land use due to conversion andhelps to design good implementation strategies and to makea good decision for better management

Generally the results of the image classification areconsistent with the findings of previous research conductedin different parts of the country For example the increase incropland and decline in woodland were also observed in[1 46]

37 Perception of LULC Change Inhabitants interviewedwere the heads of the household and with ages of 55 yearsand above so that all interviewees have lived through thecomplete study period and were able to answer questionsabout all periods All the interviewees correctly mentionedthat currently forest cover of the study area has been de-clined as compared to the beginning of the study periodissuggests that the respondents generally had a good per-ception of the historical land cover pattern of the study arearoughout the study period the high increase in agricul-tural land at the expense of forest cover was perceivedcorrectly by all respondents in the 1973ndash2017 period eoverall perception of the respondents on the decline of forestcover as the result of agricultural expansion was consistentwith the LULC change observed in the remote sensing datainterpretation

38 Driving Forces of LULC Change in the ShenkollaWatershed Understanding the causes and consequences ofdeforestation is critical to researchers policy makers andland managers because it helps to take appropriate measures[47] Interviewees have indicated that agricultural expansionwas identified as proximate causes of deforestation Pop-ulation increase biophysical factors policy changes andsocial unrest were identified as underlying forces that led tooccurrence of proximity causes of deforestation (LULCchange) in the study area According to the EthiopianCentral Statistics Report [48] the population of the studyarea has been increased at an alarming rate in the past fourdecades leading to a similar increase in high demand forfoodstuffs from agricultural expansion

As clearly indicated in the LULC change analysis ag-ricultural land showed significant increase in the Shenkollawatershed over the last 44 year period (1973ndash2017) Simi-larly a significant number of respondents (854) indicatedthat human interference mainly agricultural expansion wasthe main causes of land useland cover change (Figure 5)Substantial increase in demand for food has resulted in anexpansion of agricultural lands by encroaching on uncul-tivated areas of forest lands

Table 6 Land useland cover change matrix (ha) between 1973 and 1995

1995LULC Agricultural land Forest Total

1973Agricultural land 861 166 1027

Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457


Increase in population has implications for land re-sources as the need to produce food and the demand forsettlement and fuel wood increase in response to growingpopulation needs In other words the shortage of farm landstimulated by population growth forced local community toclear forest on steep slopes which aggravated erosionproblem and soil fertility decline Rapid population growthof the study area resulted in expansion of a farmland andthreatened the land covered with forest Fast populationgrowth and the consequent high pressure on resources areexpected to have an adverse effect on the existing naturalresources of the area Household survey focus group dis-cussion and key informant interview confirmed that pop-ulation growth is an important indirect driver of land useland cover change Accordingly 728 of the respondentspointed out high population pressure as the driver of landuseland cover change Moreover the shortage of farmlandtriggered by population growth is perceived as a driver ofland use change by 68 of the respondents (Figure 5)

e ownership of all lands by the state in the wholecountry during the 1974ndash1991 led to a lack of sense ofbelongingness to natural resources by the individualfarmers which in turn triggered significant deforestationand agricultural expansion [49] Moreover the informationobtained from key informants and focus group discussionsrevealed that there was a high conversion of forest cover toagricultural land especially during periods of social unrestand regime change to meet the demands of the growingfamily size at each household level Failure of institutions todeliver its responsibility and law enforcement led to highdeforestation and agricultural land expansion Based on the

analysis of the response of the questionnaire survey 276 ofthe total respondents revealed that the regime change ac-companied with social unrest as the indirect driver of landuse change (Figure 5)

Biophysical (natural) factors as drivers of LULC changewere mentioned most often in relation to anthropogenicdrivers For example soil degradation is most often linked toanthropogenic activities (intensive cultivation and inade-quate soil management) and poor natural conditions suchas the sloping nature of landscapes aggravates soil erosionthat result in soil fertility decline Climate variability wasexplained in relation to weather extremes Generally 34 ofthe respondents perceived biophysical or natural factors(topography climate change and soil type) as direct driversof land useland cover change (Figure 5) Biophysical factorssuch as soils rainfall variability and prolonged drought alsohave an impact on land use changes Soils vary in theirresistance to erosion partly based on texture and amount oforganic matter On steep slopes soils are generally shallowerand their nutrient and water storage capacities are limitedDrought and floods are two important climatic events re-sponsible for soil chemical and physical degradation ebiophysical factors may act as constraints to agricultureproduction as they offer certain kinds of limitations toproduction rough focus group discussion and key in-formant interviews it was revealed that the deterioration ofsoil fertility with continuous cultivation and climate ex-tremes consequently declined agricultural productivity Asthe result the local people seek extra land by clearing landcovered by forest as opposed to increasing production andproductivity on existing areas of agricultural land




Forest 306 124 430Total 1158 299 1457

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Agriculturalexpansion

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factors

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Driving forces of LULC change

Figure 5 Driving forces of land use change based on community perception


In general many driving forces were responsible for theobserved changes in land use however agricultural ex-pansion farmland shortage that has a direct relation withpopulation pressure land tenure policy and social unrestduring the transition period and natural (biophysical)factors were identified by respondents as the driving forcesof land use change in Shenkolla watershede respondentsrsquoperception of drivers of LULC change was in agreementwith the findings of previously conducted research in dif-ferent parts of the country for example population pressure[50] deforestation agricultural expansion lack of alterna-tive livelihoods and land policy [1]

39 Consequences of LULC Change in the ShenkollaWatershed Land useland cover changes have wide range ofconsequences at all spatial and temporal scales Because ofthese effects LULC change has become one of the majorproblems for environmental change as well as natural re-source management e conversion of forest cover intoagricultural land of the study area has great ecologicalconsequences Respondents have mentioned climate changebiodiversity loss scarcity of basic forest products habitatalteration leading to human-wildlife conflicts decline inquality and availability of water reduction in crop yield as aresult of accelerated runoff and soil fertility decline to be themajor consequences of land useland cover change in thestudy watershed

Majority of the respondents (75) mentioned that thelocal climate change (erratic rain and drought) is caused bythe ongoing land useland cover change (Figure 6) More-over the interviewees indicated that LULC change andassociated climate change over time directly affects thelivelihood of the subsistent farmers by affecting crop pro-duction since most of them are completely dependent onrain-fed agriculture

Another consequence of the LULC change was the lossof biodiversity Changes in environmental conditions andnatural setting of the land and its cover greatly affected thelife cycle and the survival of various plants and animalsMore than 62 of the respondents said that some species ofplants and animals previously found in the study areadisappeared mainly as a result of unregulated deforestationand agricultural expansion (Figure 6) e respondentsbelieved that the diversity of both plants and animals wasdeclined in the study watershed

Forest products are very essential in the daily life of theinhabitants of Shenkolla watershed since most of themdepend on forest products for construction cookingheating and light However continuous deforestation led tothe scarcity of forest products More than 78 of the re-spondents mentioned the occurrence of scarcity of forestproducts in the watershed (Figure 6)

Land cover (vegetation cover) highly controls the runoffLand useland cover change can influence soil chemical andphysical properties because of different anthropogenic ac-tivities namely deforestation and agricultural expansionassociated with intensive cultivation More than 96 of therespondent farmers have also perceived that crop yield has

been declined due to accelerated runoff soil fertility declineand erratic rain which is mainly caused by the change in LULC (deforestation) (Figure 6)

LULC change was also mentioned as a cause of declinein quality and availability of water A majority of the re-spondents indicated that LULC change from forest to in-tensively cultivated land increased the overall immediatesurface runoff and sediment concentration in rivers Morethan 94 of the interviewed farmers indicated that drying upof springs and decline in river water quality and quantity area major problem caused by land use change (unsustainableland management practices) (Figure 6) ey quoted theamount of water in the rivers seasonality of the springschanges in rainfall patterns distances to water collectionpoints and depth of water wells as indicators of changes inwater quantityWater scarcity was most prevalent during thedry months of the year (December to March)

LULC change (deforestation) by altering habitat greatlyaffected the wildlife in Shenkolla watershed e results ofdescriptive statistics indicate that the respondents wereaware about the effects of habitat alteration on wildlife Morethan 80 of the respondents said as a result of habitatdestruction some species of wild animals and birds previ-ously found in the study area disappeared (Figure 6)

310 Visual Indicators of Soil Degradation Caused by LULCChange One of the adverse effects of land useland coverchange in the study watershed was soil degradation Some ofthe observed visual indicators of soil degradation (loss) inthe study area were intensive erosion land slide deep gullyformation river water pollution tree root exposure and thepiling up of sediment (Figure 7)

Other notable indicators of soil degradation in the studyarea include stunted crop growth which results in yielddecline and stones on the surface of cultivated lands makingplough difficult As a result subsistence farming andsmallholder agriculture that is most common in the studywatershed is less productive in terms of yield per unit area ofland Similarly in [51 52] it was explained that rapid ex-pansion of agricultural land into a steeper slopes and de-struction of vegetation cover have aggravated soil erosionand degradation in the highlands of Ethiopia which resultedin the depletion of fertile soil

Land degradation resulted from LULC change re-stricts people from accessing important ecosystem ser-vices influences the livelihoods of the people andincreases the risk of poverty e vulnerability of peoplethat depend on land can be determined by their sus-tainable use of land and the effectiveness of their attemptto address land degradation through sustainable landmanagement practices Success in fighting land degra-dation requires an improved understanding of its causesand severity of consequences us our study provided acomplete picture of the watershed through com-plementing remote sensing data with qualitative datacollected from a local community through interview anddiscussion is study suggests that maintaining sus-tainable use of natural resource and promoting


sustainable agriculture will only be achieved when theperceptions of local people are understood well in order toact accordingly e local people deserve to be supportedto promote sustainable land management practices that isused to their environment and socioecological contextsince they have an important role and responsibility asstewards of land

4 Conclusions

Analysis of remote sensing data revealed that a remarkabledecline in forest cover and a significant expansion of agri-cultural land in Shenkolla watershed during the past 4 de-cades e extent of forest land was reduced from 2951 in1973 to 2052 in 2017 Agricultural land was expandedfrom 7049 in 1973 to 7948 in 2017 is shows that

agricultural land increased at the expense of forest land edirection of LULC changes perceived by the respondentswas consistent with the result obtained from remote sensingimage interpretation Agricultural expansion policy changeand social unrest population pressure shortage of farmland and biophysical factors were themajor driving forces ofthe LULC changes Environmental implications such asclimate change biodiversity loss scarcity of basic forestproducts habitat alteration decline in quality and avail-ability of water and crop yield reduction are resulted fromthe LULC change If this tendency of LULC changecontinued it will have serious environmental and economicconsequences with impact on livelihood of local peopleus appropriate measures that ensure wise use of naturalresources and efficient utilization of land are very muchcritical

0102030405060708090

100

Climatechange

Biodiversityloss

Scarcity ofbasic forest

products

Habitatalteration

Decline inquality andavailability

of water

Yielddecline

Perc

enta

ge o

f res

pond

ents

Figure 6 Consequences of LULC change based on perceptions of respondents

(a) (b)

(c) (d)

Figure 7 (a) Deep gully (b) sediment at the bottom slope (c) tree root exposure and (d) river water polluted with eroded soil in Shenkollawatershed (source photo taken during field work 2017)


Data Availability

e data used to support the findings of this study areavailable upon request from the corresponding author

Conflicts of Interest

e authors declare no conflicts of interest

Acknowledgments

e authors wish to thank the Center for EnvironmentalSciences Addis Ababa University for providing funds andfacilities Financial support from the Wachemo University isgratefully acknowledged Generous support from MrMarkos Dae and Mr Dilamo Woldeyohannes during thefield work is highly appreciatede authors are also gratefulto Mr Meseret Demeke and Nesibu Yahya for their assis-tance in remote sensing and GIS Software e authors areindebted to the local people who were willing to beinterviewed

References

[1] M B Molla ldquoLand useland cover dynamics in the central RiftValley region of Ethiopia the case of arsi negele districtrdquoAcademia Journal of Environmental Sciences vol 2 no 5pp 74ndash88 2014

[2] R B Brandon Mapping Rural Land Use and Land CoverChange in Carroll County Arkansas Utilizing Multi-TemporaLandsat =ematic Mapper Satellite Imagery University ofArkansas Fayetteville AR USA 1998 httpwwwcoloradoeduresearchciresbanffpubpaper

[3] M C Cheruto M K Kauti P D Kisangau and P Kariuki ldquoAcase study of Makueni County Kenyardquo Journal of RemoteSensing ampGIS Assessment of Land Use and Land Cover ChangeUsing GIS and Remote Sensing Techniques vol 5 no 4 2016

[4] A F Bennett and D A Saunders ldquoHabitat fragmentation andlandscape changerdquo in Conservation Biology for All S N Sodhiand R P Ehrlich Eds Oxford University Press New YorkNY USA 2010pp 88ndash104 ISBN 15434060

[5] D I Carr ldquoTropical deforestationrdquo in Geographical Per-spective in 100 Problems D Janelle and K Hansen EdsKluwer Academy London UK 2004

[6] T Gashaw T Tulu M Argaw and AWWorqlul ldquoModelingthe hydrological impacts of land useland cover changes in theAndassa watershed Blue Nile Basin Ethiopiardquo Science of theTotal Environment vol 619-620 pp 1394ndash1408 2018

[7] A Woldeyohannes M Cotter G Kelboro andW DessalegnldquoLand use and land cover changes and their effects on thelandscape of Abaya-Chamo basin Southern Ethiopiardquo Landvol 7 2018

[8] G Muriuki L Seabrook C McAlpine C Jacobson B Priceand G Baxter ldquoLand cover change under unplanned humansettlements a study of the Chyulu hills squatters KenyardquoLandscape and Urban Planning vol 99 no 2 pp 154ndash1652011

[9] W B Meyer and B L Turner ldquoHuman population growthand global land use and land cover changerdquo Annual Review ofEcology Evolution and Systematics vol 23 pp 39ndash61 1995

[10] K F Ayele K V Suryabhagavan and B SathishkumarldquoAssessment of habitat changes in Holeta watershed central

Oromiya Ethiopiardquo International Journal of Earth Sciencesand Engineering vol 7 pp 1370ndash1375 2014

[11] A S Mather and C L Needle ldquoe relationships of pop-ulation and forest trendsrdquo=e Geographical Journal vol 166no 1 pp 2ndash13 2000

[12] E F Lambin and H J Geist What Drives Tropical Defor-estation A Metaanalysis of Proximate and Underlying Causesof Deforestation Based on Sub-National Case Study EvidencesLUCC International project Office Louvain-la-Neuve Bel-gium 2001

[13] G Zeleke and H Hurni ldquoImplications of land use and landcover dynamics for mountain resource degradation in thenorthwestern Ethiopian highlandsrdquo Mountain Research andDevelopment vol 21 no 2 pp 184ndash191 2001

[14] E Feoli L G Vuerich and Z Woldu ldquoProcesses of envi-ronmental degradation and opportunities for rehabilitation inAdwa Northern Ethiopiardquo Landscape Ecology vol 17 no 4pp 315ndash325 2002

[15] M Lemenih E Karltun and M Olsson ldquoSoil organic matterdynamics after deforestation along a farm field chronose-quence in southern highlands of Ethiopiardquo AgricultureEcosystems amp Environment vol 109 no 1-2 pp 9ndash19 2005

[16] T Kebrom and L Hedlund ldquoLand cover changes between1958 and 1986 in Kalu South Wollo Ethiopiardquo MountainResearch and Development vol 20 pp 42ndash51 2000

[17] A Aklilu Caring for the Land Best Practices in Soil andWaterConservation in Beressa Watershed Highlands of Ethiopia(Tropical Resource Management Papers No 76) WageningenUniversity and Research Center Wageningen Netherlands2006

[18] A Mohammed ldquoLand usecover dynamics and its implicationin the drier lake Alemaya watershed eastern EthiopiardquoJournal of Sustainable Development in Africa vol 13pp 96ndash109 2011

[19] S Bedru ldquoRemote sensing and GIS for land usecover changedetection and analysis in the semi natural ecosystem andagricultural landscape of the central ethiopian Rift ValleyrdquoUnpublished Ph D dissertation Dresden University Dres-den Germany 2006

[20] B Woldeamlak ldquoLand cover dynamics since the 1950s inChemoga watershed Blue Nile basin Ethiopiardquo MountainResearch and Development vol 22 pp 263ndash269 2002

[21] S Amare and K Kao ldquoImpacts of land usecover dynamics ofthe gilgel abbay catchment of lake Tana on climate variabilityNorthwestern Ethiopiardquo Application of the Geomat vol 3pp 155ndash163 2012

[22] M Burgi C Bieling K von Hackwitz et al ldquoProcesses anddriving forces in changing cultural landscapes across EuroperdquoLandscape Ecology vol 32 no 11 pp 2097ndash2112 2017

[23] P Meyfroidt ldquoEnvironmental cognitions land change andsocial-ecological feedbacks an overviewrdquo Journal of Land UseScience vol 8 2013

[24] B Fu L Chen K Ma H Zhou and J Wang ldquoe rela-tionships between land use and soil conditions in the hilly areaof the loess plateau in northern Shaanxi Chinardquo Catenavol 39 no 1 pp 69ndash78 2000

[25] Y Grinblat G J Kidron A Karnieli and I BenensonldquoSimulating land-use degradation in West Africa with theALADYN modelrdquo Journal of Arid Environments vol 112pp 52ndash63 2015

[26] A Larigauderie and H A Mooney ldquoe Intergovernmentalscience-policy Platform on Biodiversity and Ecosystem Ser-vices moving a step closer to an IPCC like mechanism for


biodiversityrdquo Current Opinion in Environmental Sustain-ability vol 2 2010

[27] E Elias ldquoSoils of Ethiopian high lands geomorphology andpropertiesrdquo Cascape project Altera Wageningen Universityand Research Centre (Wageningen UR) WageningenNetherlands 2016

[28] B Alemu E Garedew Z Eshetu and H Kassa ldquoLand use andland cover changes and associated driving forces in northwestern lowlands of Ethiopiardquo International Research Journalof Agricultural Science and Soil Sciencersquos vol 5 no 1pp 28ndash44 2015

[29] E Teferi S Uhlenbrook W Bewket J Wenninger andB Simane ldquoe use of remote sensing to quantify wetland lossin the Choke Mountain range Upper Blue Nile basinEthiopiardquo Hydrology and Earth System Sciences vol 14no 12 pp 2415ndash2428 2010

[30] S Reis ldquoAnalyzing Land UseLand Cover Changes UsingRemote Sensing and GIS in Rize North-East Turkeyrdquo Sensorsvol 8 pp 6188ndash6202 2008

[31] M Muke and B Haile ldquoLand-usecover change analysis usingremote sensing techniques in the landscape of majang zone ofgambella region Ethiopiardquo African Journal of EnvironmentalScience and Technology vol 12 no 4 pp 141ndash149 2017

[32] A Bogoliubova ldquoAccuracy assessment of automatic imageprocessing for land cover classification of st PetersburgProtected Arealowastrdquo Acta Scientiarum Polonorum vol 13pp 5ndash22 2014

[33] M S Boori and V Vozenılek ldquoRemote sensing and land useland cover trajectoriesrdquo Geophysics amp Remote Sensing vol 3no 3 pp 1ndash7 2014

[34] M S Aduah and P E Baffoe ldquoRemote sensing for mappingland-usecover changes and urban sprawl in Sekondi-Takoradi Western Region of Ghanardquo =e InternationalJournal Of Engineering And Science vol 2 pp 66ndash73 2013

[35] A Tilahun and B Teferie ldquoA GIS based slope analysis forrecommended soil and water conservation techniques inSekela District Amhara State Ethiopiardquo International Journalof Advance Agriculture Research vol 3 pp 45ndash54 2015

[36] T H M Rientjes A T Haile E Kebede C M M MannaertsE Habib and T S Steenhuis ldquoChanges in land cover rainfalland stream flow in Upper Gilgel Abbay catchment Blue Nilebasin - Ethiopiardquo Hydrology and Earth System Sciencesvol 15 no 6 pp 1979ndash1989 2011

[37] J S Rawat V Biswas and M Kumar ldquoChanges in land usecover using geospatial techniques a case study of Ramnagartown area district Nainital Uttarakhand Indiardquo EgyptianJournal of Remote Sensing and Space Sciences vol 16 2013

[38] A T Ariti J van Vliet and P H Verburg ldquoLand-use andland-cover changes in the Central Rift Valley of Ethiopiaassessment of perception and adaptation of stakeholdersrdquoApplied Geography vol 65 pp 28ndash37 2015

[39] R Congalton ldquoematic and positional accuracy assessmentof digital remotely sensed datardquo in Proceedings of the SeventhAnnual Forest Inventory and Analysis Symposium pp 149ndash154 Portland Oregon October 2005

[40] R G Congalton ldquoA review of assessing the accuracy ofclassifications of remotely sensed datardquo Remote Sensing ofEnvironment vol 37 no 1 pp 35ndash46 1991

[41] G Rosenfield and K Fitzpatrick-Lins ldquoA coefficient ofagreement as a measure of thematic classification accuracyrdquoPhotogrammetric Engineering and Remote Sensing vol 52no 2 pp 223ndash227 1986

[42] S Abate ldquoEvaluating the land use and land cover dynamics inBorena Woreda of South Wollo highlands Ethiopiardquo Journal

of Sustainable Development in Africa vol 13 no 1 pp 87ndash105 2011

[43] E E Hassen and M Assen ldquoLand usecover dynamics and itsdrivers in Gelda catchment Lake Tana watershedrdquo Envi-ronmental Systems Research vol 6 2017

[44] G Tesfaye ldquoLand use pattern and its implication on hydrology climate and degradation in Ethiopia rdquo A Review vol 3pp 418ndash426 2017

[45] M Minta K Kibret P orne T Nigussie and L NigatuldquoGeoderma land use and land cover dynamics in dendi-jelduhilly-mountainous areas in the central Ethiopian highlandsrdquoGeoderma vol 314 2018

[46] E Garedew M Sandewall U Soderberg and B M CampbellldquoLand-use and land-cover dynamics in the central Rift Valleyof Ethiopiardquo Environmental Management vol 44 no 4pp 683ndash694 2009

[47] J M Olsonm S Misana D J Campbell M Mbonile andS Mugisha ldquoLand use change impacts and dynamics (LU-CID)rdquo Project Working Paper Number 48 InternationalLivestock Research Institute Nairobi Kenya 2004

[48] CSA (Central Statistical Agency) Population Projection ofEthiopia for All Regions at Wereda Levels from 2014ndash2017CSA (Central Statistical Agency) Addis Ababa Ethiopia2014

[49] E Yeshaneh WWagner M Exner-Kittridge D Legesse andG BlӧschI ldquoIdentifying land usecover dynamics in the Kogacatchment Ethiopia from multi-scale data and implicationsfor environmental changerdquo ISPRS International Journal ofGeo-Information vol 2 p 302e323 2013

[50] D Meshesha A Tsunekawa and M Tsubo ldquoContinued landdegradation cause-effect in Ethiopiarsquos CRVrdquo Land Degra-dation Development vol 23 pp 130ndash143 2012

[51] T W Meshesha and S K Tripathi ldquoAn evaluation of wa-tershed management practice in Ethiopia rdquo A PreliminaryReview vol 4 no 1 pp 24ndash30 2015

[52] T Worku M S K Tripathi and D Khare ldquoAnalyses of landuse and land cover change dynamics using GIS and remotesensing during 1984 and 2015 in the Beressa WatershedNorthern Central Highland of Ethiopiardquo Modeling EarthSystems and Environment vol 2 no 4 pp 1ndash12 2016


substantial increase in cultivated land at the expense of forestcover in northwest [13] northeastern [16] and eastern[17 18] Ethiopia e loss of natural vegetation from 1973 to2000 in Abijata Shala National Park and Zway-Awasa Basinwas 834 and 701 respectively [19] On the other handsome studies revealed the improvement of forest cover dueto afforestation and land rehabilitation activities carried outby the community [20 21] Most previous studies on LULCchanges were concentrated in specific areas mainly in theNorthern highlands and some areas in the rift valley lakebasin of Ethiopia and quantified only the extent of land useland cover changes using remote sensing images howeverthey did not provide explanations on local people perceptionof driving forces of LULC change and associated conse-quences [22] In addition studies on land useland coverchanges are still very limited in the Omo Gibe river basin ofsouth central Ethiopia In order to implement measures tominimize LULC changes it is important to understand howthe community perceives the causes and consequences ofLULC changes [23]

LULC change is more recognized as an important driverof environmental degradation and loss of quality on spatialand temporal scales LULC change contributes significantlyto climate change reduction in forest cover and biodiversityloss [24] In addition LULC change is one of the factors thatinfluences runoff soil loss and stream flow [20] Remotesensing data analysis has a limitation to explain nonspatialdata such as derivers and consequences of land uselandcover change As LULC change increases linking infor-mation obtained through Earth observation with humanperception is significant in gaining a comprehensive un-derstanding of pattern of LULC changes driving forces andconsequences [22 25] e study area Shenkolla is knownto be productive in cereal production but the area is exposedto sever erosion and soil loss triggered by LULC changeHence a thorough understanding of the extent of LULCchange driving forces and consequences of LULC changeis crucial to design more effective environmental policiesand appropriate land management strategies for the entirewatershed and beyond [26] However land useland coverchange of Shenkolla watershed is not investigated so far asthe result the extent of such change its driving forces andconsequences are poorly understood erefore the mainobjective of the study was to analyze the LULC changesfrom 1973 to 2017 and its driving forces and consequencesand to evaluate the coherence of community perception tothe changes observed through the interpretation of remotesensing images in the study watershed

2 Materials and Methods

21 Description of the Study Area e study was conductedin Shenkolla watershed covering 1457 ha in south centralEthiopia e geographical location of the area falls withinthe coordinates of 7deg24prime30Primendash7deg27prime0Prime N latitude and37deg43prime30Primendash37deg46prime30Prime E longitude (Figure 1) e altituderanges from 2200ndash2830m which is characterized by gently

sloping to rolling plateaus with moderate to high relief hillsand dissected side slopes

e climate of the watershed is characterized generally asa tepid submoist midhighland with a long-term averagerainfall of about 1107mm with bimodal pattern having Belg(traditional division of the year with light rain) usually fromMarch toMay and theMeher (traditional division of the yearwith heavy rain) from June to September e annual av-erage temperature of the study area is 172degC (Figure 2)

Geological formation is dominated by the quaternaryvolcanics composed of acidic parent materials (rhyolitestrachytes etc) [27] Nitisols are the most dominant soil typesalong with Vertisols Cambisols and Planosols that coverextensive areas of agricultural fields [27]

Subsistence farming is the major source of livelihoodrelying on rain-fed crop cultivation with the major cropsbeing wheat (Triticum aestivum L) teff (Eragrostis tef )(Zucc Trotter) maize (Zea mays L) barley (Hordiumvulgare L) sorghum (Sorghum bicolor L) horse beans(Vicia faba L) and potato (Solanum tuberosum L) ehomestead garden fields are characterized by Enset (Enseteventricosum) and with interspersed trees that increase thefertility of the soil Under normal climatic conditions thecultivation of crops is possible during both Belg (traditionaldivision of the year with light rain) and Meher (traditionaldivision of the year with heavy rain)

Due to the intense pressure of population growth andland scarcity it is almost impossible for farmers to practicethe appropriate fallow length is resulted in dramatic landuseland cover changes in the watershed e current landuseland cover types of the study area were categorizedbroadly into two categories forest land and agricultural lande forest cover of the study area also comprises natural andplantation forests while the agricultural land includes cul-tivated land small plots of grazing lands and scattered ruralsettlements During the past four decades the conversion offorest into agricultural land in the Shenkolla watershed wasquite intense As a result the agricultural land use classcovers the largest proportion of the study area

22 Data Sources e main data sources for this researchwere semistructured questionnaires complemented withfield observations remote sensing imagery topographicmaps supportive data such as GPS records and relatedliteratures is study involved the use of mixed methodsto complement each other since the methods have theirown weaknesses and strengths Primary data were col-lected through extensive field observation key informantinterview and focus group discussions Ancillary data(training sites and ground control points) consisting ofdifferent LULC features and their location points wererecorded using a Global Positioning System (GPS) in-strument [28] e images were freely obtained (down-loaded) from the USGS Glovis website (httpglovisusgsgov) ArcGIS 103 and QGIS v 30 software were used toclassify the image and to delineate the study area e


0 04 08 16kms

24 32

N

S


Ethiopia SNNPR

Hadiya zone

Soro district


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

Shenkolla_Boundary


14

145

15

155

16

165

17

175

18

185

19

0

20

40

60

80

100

120

140

160

180

Tem

pera

ture

(degC)

Rain

fall

(mm

)


Janu

ary

Febr

uary

Mar

ch

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r








A x

ylowast 100 (1)



K N 1113936



N2


(2)



CA() X2 minus X1

X11113888 1113889lowast 100 (3)


1113888 1113889 X2 minus X1

y1113888 1113889

(4)





























changes


LULCC



Datasources

Analysis










N


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(a)

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



N

0 05 1 2 km

Study area boundary

Forest

Agricultural land

(b)

N

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(c)
















Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457









Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References


























































0 04 08 16kms

24 32

N

S


Ethiopia SNNPR

Hadiya zone

Soro district


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

Shenkolla_Boundary


14

145

15

155

16

165

17

175

18

185

19

0

20

40

60

80

100

120

140

160

180

Tem

pera

ture

(degC)

Rain

fall

(mm

)


Janu

ary

Febr

uary

Mar

ch

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r








A x

ylowast 100 (1)



K N 1113936



N2


(2)



CA() X2 minus X1

X11113888 1113889lowast 100 (3)


1113888 1113889 X2 minus X1

y1113888 1113889

(4)





























changes


LULCC



Datasources

Analysis










N


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(a)

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



N

0 05 1 2 km

Study area boundary

Forest

Agricultural land

(b)

N

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(c)
















Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457









Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References































































A x

ylowast 100 (1)



K N 1113936



N2


(2)



CA() X2 minus X1

X11113888 1113889lowast 100 (3)


1113888 1113889 X2 minus X1

y1113888 1113889

(4)





























changes


LULCC



Datasources

Analysis










N


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(a)

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



N

0 05 1 2 km

Study area boundary

Forest

Agricultural land

(b)

N

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(c)
















Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457









Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References



















































































changes


LULCC



Datasources

Analysis










N


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(a)

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



N

0 05 1 2 km

Study area boundary

Forest

Agricultural land

(b)

N

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(c)
















Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457









Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References





























































N


7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(a)

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



N

0 05 1 2 km

Study area boundary

Forest

Agricultural land

(b)

N

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN

7deg27

prime0Prime

N7deg

26prime3

0PrimeN

7deg26

prime0Prime

N7deg

25prime3

0PrimeN

7deg25

prime0Prime

N7deg

24prime3

0PrimeN



0 05 1 2 km

Study area boundary

Forest

Agricultural land

(c)
















Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457









Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References




































































Forest 250 180 430Total 1111 346 1457




Forest 146 200 346Total 1158 299 1457









Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References

































































Forest 306 124 430Total 1158 299 1457

0102030405060708090



factors

Policychange and

social unrest

Populationpressure

Farmlandshortage

Perc

enta

ge o

f res

pond

ents


















4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References








































































4 Conclusions



0102030405060708090

100

Climatechange

Biodiversityloss


products

Habitatalteration


of water

Yielddecline

Perc

enta

ge o

f res

pond

ents


(a) (b)

(c) (d)



Data Availability




Acknowledgments


References


























































Data Availability




Acknowledgments


References


























































LandUse/LandCoverChangeandItsDrivingForcesinShenkolla ...

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