Vegetation Dynamics Analysis Using Normalized Differences Vegetation Index As Indicator of Restoration Or Degradation, South Wollo Zone, Northern Ethiopia

Total Page:16

File Type:pdf, Size:1020Kb

Vegetation Dynamics Analysis Using Normalized Differences Vegetation Index As Indicator of Restoration Or Degradation, South Wollo Zone, Northern Ethiopia ADDIS ABABA UNIVERSITY COLLAGE OF SOCIAL SCIENCES DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL STUDY VEGETATION DYNAMICS ANALYSIS USING NORMALIZED DIFFERENCES VEGETATION INDEX AS INDICATOR OF RESTORATION OR DEGRADATION, SOUTH WOLLO ZONE, NORTHERN ETHIOPIA BY Shewangzaw Moges September, 2014 AAU. 1 ADDIS ABABA UNIVERSITY SCHOOL OF GRADUATE STUDIES This is to certify that project presented by Shewangzaw Moges entitled: Vegetation dynamics analysis using Normalized Differences Vegetation Index as indicator of restoration or degradation, in South Wollo zone, Northern Ethiopia and submitted in partial fulfillments of the requirements for the degree of master of arts in Geography and Environmental Studies with complies with the regulation of the university and meets the accepted standards with respect to originality and quality. Signed by examining committee: Internal examiner ____________________ Signature __________ Date _____________ External examiner ____________________ Signature ___________ Date ____________ Advisor ____________________ Signature ___________ Date ____________ ____________________________________________________________________________ Chair of the department of Geography or Graduate program coordinator 2 Table of content Abstract………………………………………………………………………………………………………………………...iii Acknowledgement…………………………………………………………………………………………………………iv List of Figures………………………………………………………………………………………………………………..v List of Tables………………………………………………………………………………………………………………....vi List of Acronyms…………………………………………………………………………………………………………...vii 1. INTRODUCTION .................................................................................................................................. 1 1.1 Background .................................................................................................................................. 10 1.2 Statement of the problem ........................................................................................................ 11 1.3. Objective of the study .............................................................................................................. 13 1.3.1. General Objective .............................................................................................................................. 13 1.3.2. Specific objectives ............................................................................................................................. 13 1.4. Significance of the study ........................................................................................................... 13 1.5. Scope and Limitation of the study .......................................................................................... 14 1.7. Project outline ............................................................................................................................. 14 2. REVIEW OF RELATED LITERATURE ......................................................................................... 15 2.1. The role of geographical information system and Remote Sensing in Vegetation Dynamics Assessment ...................................................................................................................... 15 2.2. Capabilities and application NDVI on vegetation dynamics ............................................. 17 2.3. Vegetation dynamics in Ethiopia ............................................................................................ 18 2.3.1. De-vegetation and Deforestation in Ethiopia ....................................................................................... 18 2.3.2. VEGETATION RESTORATION IN ETHIOPIA .................................................................... 20 2.4. The positive impacts of soil and water conservation on vegetation restoration ........ 21 2.4.1. Advantages of Area of Enclosure on Vegetation Regeneration .................................................... 23 3. METHODOLOGY ............................................................................................................................... 25 3.1. Description of the study area ............................................................................................................ 25 3.1.1. Location ............................................................................................................................................... 25 3.1.2. Topography ......................................................................................................................................... 26 3.1.3. Climate ................................................................................................................................................. 26 3.1.4. Geology ................................................................................................................................................ 26 3.1.5. Demography ....................................................................................................................................... 26 3.1.6. Land Use/Land Cover of South Wollo........................................................................................... 27 3 3.1.7. Soil and water conservation ........................................................................................................... 27 3.2. Materials and Methods used ............................................................................................................. 27 3.2.1. Normalized Difference Vegetation Index (NDVI) data acquisition ........................................ 27 3.2.2. Preparing and pre-processing NDVI data .................................................................................... 28 3.3. Field Work ................................................................................................................................................ 29 3.4. Data Analysis ........................................................................................................................................... 29 3.4.1. Time analysis ...................................................................................................................................... 29 3.4.2. Yearly dry months average NDVI .................................................................................................. 30 3.4.3. Overall average NDVI (2000 to 2011) of dry months ............................................................... 31 3.4.4. NDVI change across year ................................................................................................................. 31 3.4.5. NDVI change modeling ..................................................................................................................... 31 3.4.6. Accuracy Assessment ....................................................................................................................... 32 4. RESULT AND DISCUSSION ............................................................................................................ 34 4.1. Vegetation dynamics trend Analysis in South Wollo zone .................................................... 34 4.1.1. Spatio-temporal Vegetation dynamics between 2000 and 2005 ........................................... 34 4.2.1. NDVI dynamics by significance level between 2000 and 2005 .............................................. 37 4.2.2. Spatio-temporal Vegetation dynamics from 2006 to 2011 ..................................................... 38 4.2.3. NDVI dynamics by significance level between 2006 and 2011 .............................................. 42 4.2.4. Spatio-temporal Vegetation dynamics from 2000 to 2011 in South Wollo ......................... 42 4.4.5. Average NDVI change that show vegetation dynamics in 2000, 2005, 2011 and over all average ............................................................................................................................................................ 48 4.3. Implication of topography on Vegetation dynamics ................................................................ 50 4.3.1 Spatial-temporal vegetation change across the slope in (2000-2005, 2006-2011 and 2000-2011) .................................................................................................................................................... 50 4.3.2 Cross Tabulation of 2000, 2005 and 2011 Average NDVI with slope classification ........... 51 5. SUMMARY, CONCLUSION AND RECOMMENDATION ........................................................... 57 5.1. Summary ................................................................................................................................................... 57 5.2 Conclusion ................................................................................................................................................. 59 5.3 Recommendation ................................................................................................................................... 60 Reference Appendices 4 Abstract Ethiopia is facing rapid deforestation and degradation of land. To overcome this serious problem, the Government of Ethiopia has taken different measures such as policy interventions, conducted studies, and implemented massive soil and water conservation (SWC) and capacity building programs. The study analyzed normalized difference vegetation index as indicator of vegetation restoration/degradation, in South Wollo, Northern Ethiopia. The study analyzed inter- annual normalized difference vegetation index (NDVI) changes
Recommended publications
  • Districts of Ethiopia
    Region District or Woredas Zone Remarks Afar Region Argobba Special Woreda -- Independent district/woredas Afar Region Afambo Zone 1 (Awsi Rasu) Afar Region Asayita Zone 1 (Awsi Rasu) Afar Region Chifra Zone 1 (Awsi Rasu) Afar Region Dubti Zone 1 (Awsi Rasu) Afar Region Elidar Zone 1 (Awsi Rasu) Afar Region Kori Zone 1 (Awsi Rasu) Afar Region Mille Zone 1 (Awsi Rasu) Afar Region Abala Zone 2 (Kilbet Rasu) Afar Region Afdera Zone 2 (Kilbet Rasu) Afar Region Berhale Zone 2 (Kilbet Rasu) Afar Region Dallol Zone 2 (Kilbet Rasu) Afar Region Erebti Zone 2 (Kilbet Rasu) Afar Region Koneba Zone 2 (Kilbet Rasu) Afar Region Megale Zone 2 (Kilbet Rasu) Afar Region Amibara Zone 3 (Gabi Rasu) Afar Region Awash Fentale Zone 3 (Gabi Rasu) Afar Region Bure Mudaytu Zone 3 (Gabi Rasu) Afar Region Dulecha Zone 3 (Gabi Rasu) Afar Region Gewane Zone 3 (Gabi Rasu) Afar Region Aura Zone 4 (Fantena Rasu) Afar Region Ewa Zone 4 (Fantena Rasu) Afar Region Gulina Zone 4 (Fantena Rasu) Afar Region Teru Zone 4 (Fantena Rasu) Afar Region Yalo Zone 4 (Fantena Rasu) Afar Region Dalifage (formerly known as Artuma) Zone 5 (Hari Rasu) Afar Region Dewe Zone 5 (Hari Rasu) Afar Region Hadele Ele (formerly known as Fursi) Zone 5 (Hari Rasu) Afar Region Simurobi Gele'alo Zone 5 (Hari Rasu) Afar Region Telalak Zone 5 (Hari Rasu) Amhara Region Achefer -- Defunct district/woredas Amhara Region Angolalla Terana Asagirt -- Defunct district/woredas Amhara Region Artuma Fursina Jile -- Defunct district/woredas Amhara Region Banja -- Defunct district/woredas Amhara Region Belessa --
    [Show full text]
  • Nutrition Surveys 1999
    NUTRITION SURVEYS 1999 – 2000 Region/Zone woreda Date of Agency Sample size Methodology Nutrition Indicatorsi survey Tigre throughout August SCF-UK 937 30 cluster Mean WHL <80%WFL W/H<-2 Z score W/H <-3 Z score 1999 92.8% 5.5% 7.7 % 1.0% Tigre Feb 2000 WVI W/H <-2 Z score W/H <-3 Z score Eastern May 2000 Feb 2000 May 2000 Feb 2000 May 2000 Asti Wenberta 685 13.1% 10.9% NA 2.6% Saesi Tsaedaemba 1412 22.3% 20.1% 3.7% 4.4% Amhara: May-June SCF-UK + 2900 58 clusters in Mean WFL < 80% WFL N.Wello Bugna 1999 worst drought 88.8% 4% Wadla affected woredas. 89,4% 7% Gidan 87.8% 3% Delanta Dawnt 89.4% 7% Gubalafto 90.0% 7% S. Wello Dessie Zuria 89.8% 7% Tenta 90.5% 3% Legambo 90.8% 5% Ambassel 90.7% 6% Mekdella 91.2% 4% Wag Hamra Dehana 88.2% 4% Oromyia Chefa 92.8% 2% Amhara Aug - Oct SCF-UK + 2500 50 clusters in Mean WFL < 80% WFL 1999 worst drought Aug Sept Oct Aug Sept Oct N.Wello Bugna affected woredas. 91.2% 88.7% 89.7% 6.6% 10.6% 7.0% Wadla 91.1% 90.7% 90.6% 7.3% 5.5% 5.7% Gidan 88.4% 88.2% 88.4% 8.9% 8.2% 9.6% S. Wello Delanta Dawnt 87.5% 87.6% 87.5% 11.0% 8.0% 7.6% Dessie Zuria 91.9% 90.9% 90.1% 4.0% 6.2% 5.2% Tenta 89.2% 89.1% 88.4% 10.0% 8.3% 11.7% Legambo 89.1% 89.7% 89.6% 8.4% 6.0% 6.4% Wag Hamra Dehana 89.7% 89.5% 90.5% 8.3% 8.2% 6.4% Amhara March- May SCF-UK + 2500 50 clusters in Mean WFL < 80% WFL N.Wello 2000 worst drought March 2000 May 2000 March 2000 May 2000 Bugna affected woredas 90.1% 90.6% Wadla 90.5% 91.1% S.
    [Show full text]
  • Ethnobotany, Diverse Food Uses, Claimed Health Benefits And
    Shewayrga and Sopade Journal of Ethnobiology and Ethnomedicine 2011, 7:19 http://www.ethnobiomed.com/content/7/1/19 JOURNAL OF ETHNOBIOLOGY AND ETHNOMEDICINE RESEARCH Open Access Ethnobotany, diverse food uses, claimed health benefits and implications on conservation of barley landraces in North Eastern Ethiopia highlands Hailemichael Shewayrga1* and Peter A Sopade2,3 Abstract Background: Barley is the number one food crop in the highland parts of North Eastern Ethiopia produced by subsistence farmers grown as landraces. Information on the ethnobotany, food utilization and maintenance of barley landraces is valuable to design and plan germplasm conservation strategies as well as to improve food utilization of barley. Methods: A study, involving field visits and household interviews, was conducted in three administrative zones. Eleven districts from the three zones, five kebeles in each district and five households from each kebele were visited to gather information on the ethnobotany, the utilization of barley and how barley end-uses influence the maintenance of landrace diversity. Results: According to farmers, barley is the “king of crops” and it is put for diverse uses with more than 20 types of barley dishes and beverages reportedly prepared in the study area. The products are prepared from either boiled/roasted whole grain, raw- and roasted-milled grain, or cracked grain as main, side, ceremonial, and recuperating dishes. The various barley traditional foods have perceived qualities and health benefits by the farmers. Fifteen diverse barley landraces were reported by farmers, and the ethnobotany of the landraces reflects key quantitative and qualitative traits. Some landraces that are preferred for their culinary qualities are being marginalized due to moisture shortage and soil degradation.
    [Show full text]
  • British Geological Survey PLANNING
    British Geological Survey TECHNICAL REPORT WC/00/13 Overseas Geology Series PLANNING FOR GROUNDWATER DROUGHT IN AFRICA: TOWARDS A SYSTEMATIC APPROACH FOR ASSESSING WATER SECURITY IN ETHIOPIA Project report on visit to Ethiopia, November-December 1999 British Geological Survey, Wallingford British Geological Survey TECHNICAL REPORT WC/00/13 Overseas Geology Series PLANNING FOR GROUNDWATER DROUGHT IN AFRICA: TOWARDS A SYSTEMATIC APPROACH FOR ASSESSING WATER SECURITY IN ETHIOPIA Project report on visit to Ethiopia, November-December 1999 R C Calow1, A M MacDonald1 and A L Nicol2 1British Geological Survey 2Overseas Development Institute This document is an output from a project funded by the Department for International Development (DFID) for the benefit of developing countries. The views expressed are not necessarily those of the DFID. DFID classification: Subsector: Water and Sanitation Theme: W4 – Raise the well-being of the rural and urban poor through cost-effective improved water supply and sanitation Project Title: Groundwater drought early warning for vulnerable areas Project reference: R7125 Bibliographic reference: Calow, R C, MacDonald, A M and Nicol, A L 2000. Planning for Groundwater Drought in Africa. Towards a Systematic Approach for Assessing Water Security in Ethiopia. Project report on visit to Ethiopia, November – December 1999 BGS Technical Report WC/00/13 Keywords:Ethiopia, groundwater, drought, monitoring Front cover illustration: Looking down onto the River Mille from Abbot Village, Ambassel Woreda. © NERC 2000 Keyworth, Nottingham, British Geological Survey, 2000 Contents Executive Summary iv 1. INTRODUCTION 1 1.1 Visit Objectives 1 1.2 Visit Background 1 1.3 Project Aims and Outputs 3 2. THE STUDY AREA: SOUTH WOLLO 4 2.1 Selection Criteria 4 2.2 Physical Background 5 2.3 Socio-economic Background 5 2.4 Institutions 6 3.
    [Show full text]
  • ETHIOPIA - National Hot Spot Map 31 May 2010
    ETHIOPIA - National Hot Spot Map 31 May 2010 R Legend Eritrea E Tigray R egion !ª D 450 ho uses burned do wn d ue to th e re ce nt International Boundary !ª !ª Ahferom Sudan Tahtay Erob fire incid ent in Keft a hum era woreda. I nhabitan ts Laelay Ahferom !ª Regional Boundary > Mereb Leke " !ª S are repo rted to be lef t out o f sh elter; UNI CEF !ª Adiyabo Adiyabo Gulomekeda W W W 7 Dalul E !Ò Laelay togethe r w ith the regiona l g ove rnm ent is Zonal Boundary North Western A Kafta Humera Maychew Eastern !ª sup portin g the victim s with provision o f wate r Measle Cas es Woreda Boundary Central and oth er imm ediate n eeds Measles co ntinues to b e re ported > Western Berahle with new four cases in Arada Zone 2 Lakes WBN BN Tsel emt !A !ª A! Sub-city,Ad dis Ababa ; and one Addi Arekay> W b Afa r Region N b Afdera Military Operation BeyedaB Ab Ala ! case in Ahfe rom woreda, Tig ray > > bb The re a re d isplaced pe ople from fo ur A Debark > > b o N W b B N Abergele Erebtoi B N W Southern keb eles of Mille and also five kebeles B N Janam ora Moegale Bidu Dabat Wag HiomraW B of Da llol woreda s (400 0 persons) a ff ected Hot Spot Areas AWD C ases N N N > N > B B W Sahl a B W > B N W Raya A zebo due to flo oding from Awash rive r an d ru n Since t he beg in nin g of th e year, Wegera B N No Data/No Humanitarian Concern > Ziquala Sekota B a total of 967 cases of AWD w ith East bb BN > Teru > off fro m Tigray highlands, respective ly.
    [Show full text]
  • DTM Event Tracking Tool 30 (18-24 July 2020)
    DISPLACEMENT TRACKING MATRIX-ETHIOPIA EVENT TRACKING TOOL (ETT) The DTM Event Tracking Tool (ETT) is deployed to track and provide up to date information on sudden displacements and other population movements ETT Report: No. 30 | 18 - 24 July 2020 CoVID-19 Situation Update ERITREA RED SEA YEMEN Wegde Kelela MOVEMENTS WembermaWest Gojam AFAR Gablalu TIGRAY Jama Zone 5 Oromia Hadhagala Ayisha KemashiSUDAN SOMALIA 364,322 12,693 200 5,785 East Gojam Gewane AFAR DJIBOUTI AMHARA GULF OF ADEN AmuruAMHARA Zone 3 Siti Tested Confirmed Deaths Recovered BENISHANGUL GUMUZ Shinile 7,876 IDPs North Shewa Dembel ADDIS ABABA Source: Ministry of Health, 24 July 2020 HARARI North Shewa 180 Kuyu DIRE DAWA GAMBELA Horo Gudru Wellega Amibara 66 Chinaksen OROMIA Jarso Main Highlights SOMALI Dulecha Miesso SNNPR Kombolcha KemashiSOUTH Gursum SUDAN Cobi Sululta Haro Maya Conict (4,202 IDPs) 3,102 Mieso 136 During the reporting period, 3,546 new cases were recorded, which is SOMALIA KENYA West Shewa UGANDA ADDIS ABABA 139 Girawa Fedis Fafan a 146% increase from the previous week. The breakdown by region is East Wellega Babile 162 Ilu Fentale East Hararge listed below. Dawo West Hararge Flash Floods 410 Boset 20 Boke Kuni Nono Merti Addis Ababa continued to record a high number of cases (3,674 IDPs) South West Shewa East Shewa Jeju Buno Bedele Sire within the reporting week with 2,447 new cases while Hawi Gudina Jarar Guraghe Fik Kumbi Degehamedo Oromia recorded 289 new cases, Tigray 236, Gambela 170, PRIORITY NEEDS Silti Sude Jimma Arsi Amigna Lege Hida Erer Yahob Afar 74, Benishangul Gumuz 73, Amhara 68, Dire Dawa 52, Yem Siltie OROMIA Gibe Seru Hamero Somali 47, SNNPR 39, Sidama 31, and Harari 20 new Hadiya Shirka Sagag 1.
    [Show full text]
  • S P E C I a L R E P O
    S P E C I A L R E P O R T FAO/WFP CROP AND FOOD SECURITY ASSESSMENT MISSION TO ETHIOPIA (Phase 2) Integrating the Crop and Food Supply and the Emergency Food Security Assessments 27 July 2009 FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS, ROME WORLD FOOD PROGRAMME, ROME - 2 - This report has been prepared by Mario Zappacosta, Jonathan Pound and Prisca Kathuku, under the responsibility of the FAO and WFP Secretariats. It is based on information from official and other sources. Since conditions may change rapidly, please contact the undersigned if further information is required. Henri Josserand Mustapha Darboe Deputy Director, GIEWS, FAO Regional Director for Southern, Eastern Fax: 0039-06-5705-4495 and Central Africa, WFP E-mail: [email protected] Fax: 0027-11-5171634 E-mail: : [email protected] Please note that this Special Report is also available on the Internet as part of the FAO World Wide Web (www.fao.org ) at the following URL address: http://www.fao.org/giews/ The Special Alerts/Reports can also be received automatically by E-mail as soon as they are published, by subscribing to the GIEWS/Alerts report ListServ. To do so, please send an E-mail to the FAO-Mail-Server at the following address: [email protected] , leaving the subject blank, with the following message: subscribe GIEWSAlertsWorld-L To be deleted from the list, send the message: unsubscribe GIEWSAlertsWorld-L Please note that it is now possible to subscribe to regional lists to only receive Special Reports/Alerts by region: Africa, Asia, Europe or Latin America (GIEWSAlertsAfrica-L, GIEWSAlertsAsia-L, GIEWSAlertsEurope-L and GIEWSAlertsLA-L).
    [Show full text]
  • AMHARA REGION : Who Does What Where (3W) (As of 13 February 2013)
    AMHARA REGION : Who Does What Where (3W) (as of 13 February 2013) Tigray Tigray Interventions/Projects at Woreda Level Afar Amhara ERCS: Lay Gayint: Beneshangul Gumu / Dire Dawa Plan Int.: Addis Ababa Hareri Save the fk Save the Save the df d/k/ CARE:f k Save the Children:f Gambela Save the Oromia Children: Children:f Children: Somali FHI: Welthungerhilfe: SNNPR j j Children:l lf/k / Oxfam GB:af ACF: ACF: Save the Save the af/k af/k Save the df Save the Save the Tach Gayint: Children:f Children: Children:fj Children:l Children: l FHI:l/k MSF Holand:f/ ! kj CARE: k Save the Children:f ! FHI:lf/k Oxfam GB: a Tselemt Save the Childrenf: j Addi Dessie Zuria: WVE: Arekay dlfk Tsegede ! Beyeda Concern:î l/ Mirab ! Concern:/ Welthungerhilfe:k Save the Children: Armacho f/k Debark Save the Children:fj Kelela: Welthungerhilfe: ! / Tach Abergele CRS: ak Save the Children:fj ! Armacho ! FHI: Save the l/k Save thef Dabat Janamora Legambo: Children:dfkj Children: ! Plan Int.:d/ j WVE: Concern: GOAL: Save the Children: dlfk Sahla k/ a / f ! ! Save the ! Lay Metema North Ziquala Children:fkj Armacho Wegera ACF: Save the Children: Tenta: ! k f Gonder ! Wag WVE: Plan Int.: / Concern: Save the dlfk Himra d k/ a WVE: ! Children: f Sekota GOAL: dlf Save the Children: Concern: Save the / ! Save: f/k Chilga ! a/ j East Children:f West ! Belesa FHI:l Save the Children:/ /k ! Gonder Belesa Dehana ! CRS: Welthungerhilfe:/ Dembia Zuria ! î Save thedf Gaz GOAL: Children: Quara ! / j CARE: WVE: Gibla ! l ! Save the Children: Welthungerhilfe: k d k/ Takusa dlfj k
    [Show full text]
  • The Case of Dessie Zuria Woreda
    CORE Metadata, citation and similar papers at core.ac.uk Provided by International Institute for Science, Technology and Education (IISTE): E-Journals Journal of Economics and Sustainable Development www.iiste.org ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) DOI: 10.7176/JESD Vol.10, No.5, 2019 Determinants of Households Saving Capacity and Bank Account Holding Experience in Ethiopia: The Case of Dessie Zuria Woreda Bazezew Endalew College of Business and Economics, Department of Economics, Wollo University, Dessie, Ethiopia Abstract This research has been an attempt to identify the major determinants that affect households saving capacity and their experience of adopting formal financial institutions (banks) in the case of Dessie Zuria Woreda. To do so, an individual base cross-sectional data analysis along with the two stage sampling technique of both purposive and random sampling technique was undertaken. To analyze the data, the study employed two sets of models (logistic and the method of principal component analysis). The econometric results of the study indicates that determinants like lack of credit access, lack of financial planning, complexity of banking system, monthly expenditure on stimulants, sex, significantly and negatively affects households saving capacity, but monthly income, age, bank account holding experience, marital status, and occupation positively and significantly affects saving capacity. In similar fashion, determinants include improper government policy, weak institutional set up, complexity of banking system, distance in Km away from their home to financial institutions, and religion significantly and negatively affect the probability of households to be banked, on the other hand, sex of households, credit access, income, marital status, education and age positively and significantly affects the probability of households to be banked.
    [Show full text]
  • Ethiopia Round 6 SDP Questionnaire
    Ethiopia Round 6 SDP Questionnaire Always 001a. Your name: [NAME] Is this your name? ◯ Yes ◯ No 001b. Enter your name below. 001a = 0 Please record your name 002a = 0 Day: 002b. Record the correct date and time. Month: Year: ◯ TIGRAY ◯ AFAR ◯ AMHARA ◯ OROMIYA ◯ SOMALIE BENISHANGUL GUMZ 003a. Region ◯ ◯ S.N.N.P ◯ GAMBELA ◯ HARARI ◯ ADDIS ABABA ◯ DIRE DAWA filter_list=${this_country} ◯ NORTH WEST TIGRAY ◯ CENTRAL TIGRAY ◯ EASTERN TIGRAY ◯ SOUTHERN TIGRAY ◯ WESTERN TIGRAY ◯ MEKELE TOWN SPECIAL ◯ ZONE 1 ◯ ZONE 2 ◯ ZONE 3 ZONE 5 003b. Zone ◯ ◯ NORTH GONDAR ◯ SOUTH GONDAR ◯ NORTH WELLO ◯ SOUTH WELLO ◯ NORTH SHEWA ◯ EAST GOJAM ◯ WEST GOJAM ◯ WAG HIMRA ◯ AWI ◯ OROMIYA 1 ◯ BAHIR DAR SPECIAL ◯ WEST WELLEGA ◯ EAST WELLEGA ◯ ILU ABA BORA ◯ JIMMA ◯ WEST SHEWA ◯ NORTH SHEWA ◯ EAST SHEWA ◯ ARSI ◯ WEST HARARGE ◯ EAST HARARGE ◯ BALE ◯ SOUTH WEST SHEWA ◯ GUJI ◯ ADAMA SPECIAL ◯ WEST ARSI ◯ KELEM WELLEGA ◯ HORO GUDRU WELLEGA ◯ Shinile ◯ Jijiga ◯ Liben ◯ METEKEL ◯ ASOSA ◯ PAWE SPECIAL ◯ GURAGE ◯ HADIYA ◯ KEMBATA TIBARO ◯ SIDAMA ◯ GEDEO ◯ WOLAYITA ◯ SOUTH OMO ◯ SHEKA ◯ KEFA ◯ GAMO GOFA ◯ BENCH MAJI ◯ AMARO SPECIAL ◯ DAWURO ◯ SILTIE ◯ ALABA SPECIAL ◯ HAWASSA CITY ADMINISTRATION ◯ AGNEWAK ◯ MEJENGER ◯ HARARI ◯ AKAKI KALITY ◯ NEFAS SILK-LAFTO ◯ KOLFE KERANIYO 2 ◯ GULELE ◯ LIDETA ◯ KIRKOS-SUB CITY ◯ ARADA ◯ ADDIS KETEMA ◯ YEKA ◯ BOLE ◯ DIRE DAWA filter_list=${level1} ◯ TAHTAY ADIYABO ◯ MEDEBAY ZANA ◯ TSELEMTI ◯ SHIRE ENIDASILASE/TOWN/ ◯ AHIFEROM ◯ ADWA ◯ TAHTAY MAYCHEW ◯ NADER ADET ◯ DEGUA TEMBEN ◯ ABIYI ADI/TOWN/ ◯ ADWA/TOWN/ ◯ AXUM/TOWN/ ◯ SAESI TSADAMBA ◯ KLITE
    [Show full text]
  • Famine and Survival Strategies Famine and Survival Strategies
    Famine and Survival Strategies Famine and Survival Strategies A Case Study from Northeast Ethiopia Dessalegn Rahmato Nordiska Afrikainstitutet, Uppsala 199 1 (The Scandinavian Institute of African Studies) This book is published with support from The Swedish International Development Authority (SIDA) ISBN 91-7106-314-5 O Dessalegn Rahmato and Nordiska Afrikainstitutet 1991 Typeset and printed in Sweden by Bohuslaningens Boktryckeri AB, Uddevalla 199 1 Contents Abbreviations 6 Glossary 7 Acknowledgements 9 Section I INTRODUCTION 1. Objectives of the Study 13 Community and the ethic of cooperation 18 2. Organization of the Study 35 Sources for the Study 36 Technical problems and usage 43 Section I1 FAMINE: HIDING BEHIND THE MOUNTAINS 3. Wollo and Ambassel: The Setting 47 4. The Economy of Wollo 57 5. The Peasant Mode of Production 69 Farming practices 76 The control of the micro-environment 81 Consumption, marketing and prices 87 6. Famine in Wollo 99 The death toll (1984-85) 107 Section 111 SURVIVAL: COMMUNITY AND COOPERATION 7. The Community in Distress 117 Crisis anticipation 118 Magic and divination 125 Crisis management 141 Exhaustion and dispersal 156 8. Survival Strategies 163 Austerity and reduced consumption 165 Divestment and asset disposal 171 Livestock flows during the famine 176 Normal and abnormal behaviour 182 9. Post Famine Recovery 193 Section IV BEYOND SURVIVAL 10. Neither Feast Nor Famine 21 1 Disaster designation and early warning 219 References 227 Information from Official Records 227 Primary Sources 227 Secondary Sources 230 Annexes 1. Rainfall Data, Haiq Station, Ambassel 1963-1984 2. Livestock Supply and Prices, Haiq Market 3. Grain Prices, Bistima Market, Ambassel 4.
    [Show full text]
  • Heading with Word in Woodblock
    Amhara Region, Area brief Regional Overview The Amhara Region is located in the northwestern part of Ethiopia; its land area is estimated at about 170,000 square kilometers. Amhara borders Tigray Region in the North, Afar in the East, Oromiya in the South, Benishangul-Gumuz in the Southwest and the country of Sudan in the west. Based on the 2007 figures from the Central Statistical Agency (CSA) of Ethiopia, Amhara has an estimated total population of 20,136,000. 88% of the population is estimated to be rural inhabitants, while 12% are urban dwellers. Bahir-Dar is the capital city of the Amhara Regional State. Amhara is divided into 11 zones, and 167 woredas (districts). There are about 3,429 kebeles (the smallest administrative units). Decision-making power has been decentralized to woredas and thus the woredas are responsible for all development activities in their areas. The historic Amhara region contains much of the highland plateaus above 1,500 meters with rugged formations, gorges and valleys, as well as millions of settlements for Amhara villages surrounded by subsistence farms and grazing fields. Located in this region are the world-renowned Blue Nile River and its source, Lake Tana, as well as historic sites including Gonder palace, and the Lalibela rock-hewn churches. The land in Amhara has been cultivated for millennia with no variations or improvement in the farming techniques. The resulting environmental damage has contributed to the trend of deteriorating climate with frequent droughts, loss of crops and the resulting food shortage. Of the 167 woredas in the region, fifty-eight (35%) are drought-prone and chronically food- insecure.
    [Show full text]