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Estimating Cultivable Areas in Central and Southern Somalia Using Remote Sensing

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Estimating Cultivable Areas in Central and Southern Somalia Using Remote Sensing ESTIMATING CULTIVABLE AREAS IN CENTRAL AND SOUTHERN SOMALIA USING REMOTE SENSING Technical Report No. RSM-02 November 2012 Somalia Water and Land Information Management Ngecha Road, Lake View. P.O Box 30470-00100, Nairobi, Kenya. Tel +254 020 4000300 - Fax +254 020 4000333, 1 Email: [email protected] Website: http//www.faoswalim.org. Funded by the European Union and implemented by the Food and Agriculture Organization of the United Nations DISCLAIMER & LIST OF AUTHORS The designations employed and the presentation of material in this document do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) and the SWALIM Programme concerning the legal status of Somalia, its territory, city or area of its authorities, or concerning the delimitation of its frontiers or boundaries. This document should be cited as follows: Oduori, S. M., Oroda A. S., Gadain H., and F. Rembold, 2012: Estimating Cultivable Areas in Central and Southern Somalia using Remote Sensing by FAO-SWALIM. Project Report No. RSM 02 Nairobi, Kenya. ACKNOWLEDGMENTS We would like to give special thanks to Sergio Innocente, Thomas Gabriel, Dario Cipolla, Tamara Nanitashvili, and Jeremiah Njeru for their technical thoughts and support that led to the formulation and implementation of this work. Many thanks and acknowledge to the United States Geological Survey (USGS) who provided (free of charge) the ASTER and Landsat images that were instrumental in the implementation of this work. We are, particularly grateful to Messrs James Roland and Michael (Mike) Budde, both of USGS, who facilitated the provision of the satellite images and Dr. Hussein Gadain for the good link with USGS. We are also grateful to the Joint Research Centre (JRC) who provided supplementary images and technical support during the implementation of this work. The images were provided by Andreas Brink of the MONDE action, while technical inputs for the definition of the sampling scheme were received from Olivier Leo and Javier Gallego of the MARS Unit. The Landsat images were originally obtained free of charge from the Global Land Survey (GLS) partnership between USGS and NASA (http://gls/umd.edu). We are grateful to, and acknowledge the immense contributions from our colleagues at FAO-SWALIM, especially John Mwanzia and Mary Cherono for image interpretation, Mr. Antony Ndubi for his tireless efforts in processing and providing all the necessary images required for this work and all the other staff involved, especially Dr. Hussein Gadain, James Ngochoch, and Margaret Mugo for their technical contributions as well as moral support that made the implementation of this exercise a success. We also wish to acknowledge the technical support from Ms. Julie Maingi of the Regional Centre for Mapping of Resources for Development (RCMRD) who conducted training on the Rapid Land Cover Mapper methodology at the inception of this exercise, and final editing of all the district maps. Zoltan Balint, Chief Technical Advisor, SWALIM for technical advise, logistical support and professional input. Lastly, many thanks go to Dr. Luca Alinovi, the Officer in Charge of FAO-Somalia for his technical and financial support. ii Table of Contents DISCLAIMER & LIST OF AUTHORS ............................................................................................................ i ACKNOWLEDGMENTS ............................................................................................................................. ii 1. INTRODUCTION ................................................................................................................................... 1 1.1. Background .................................................................................................................................. 1 1.2. Rationale ...................................................................................................................................... 1 1.3. Objectives of the study ................................................................................................................ 2 2. METHODOLOGY .................................................................................................................................. 3 2.1. The study area .............................................................................................................................. 3 Climate ............................................................................................................................................ 4 Landform/Soils ................................................................................................................................ 5 Land Cover ...................................................................................................................................... 5 Land Use .......................................................................................................................................... 5 2.2. Materials ...................................................................................................................................... 6 2.3. Methods ....................................................................................................................................... 7 Sampling error and choice of dot interval in the dot grid ............................................................ 10 Interpretation error ...................................................................................................................... 13 3. RESULTS, DISCUSSION AND CONCLUSION ........................................................................................ 14 3.1. Results ........................................................................................................................................ 14 Table 5: Summary of the results from the study area ...................................................................... 15 Comparison between dot-grid cultivable areas and FSNAU crop area estimates ........................ 17 3.2. Discussions and conclusions ............................................................................................................ 1 Reference ................................................................................................................................................ 2 ANNEXES ................................................................................................................................................. 3 ANNEX 1 .............................................................................................................................................. 3 Results by District ............................................................................................................................ 3 Annex 2: ............................................................................................................................................ 40 iii ASTER image coverage of the study area ..................................................................................... 40 Annex 3: ............................................................................................................................................ 41 ASTER satellite image index .......................................................................................................... 41 iv 1. INTRODUCTION 1.1. Background Somalia is largely a hot, arid and semi-arid country with rainfall amounts averaging between 50 and 500 - 600 mm per annum (even though some areas may receive slightly higher amounts). The prolonged civil war which culminated in the fall of the Somali Government in 1991 and the subsequent lack of a functional government led to a situation of dysfunctional public institutions. This has subjected the country to extreme environmental degradation both natural and man-made. The subsequent economic crisis coupled with high population pressure, competition over limited resources and poverty have resulted in ecosystems and natural resources destruction that has affected survival and well-being (Omuto et al 2007). Livestock is the main source of income for most Somalis, while agriculture is concentrated mainly in the South along and between the two main rivers of Shabelle and Juba. 1.2. Rationale The Food and Agriculture Organization (FAO) is supporting smallholder farmers in the whole of Somalia through a large number of rural development projects but due to insecurity and accessibility difficulties, the information on agriculture in Somalia is mainly based on oral tradition, assumptions, rough estimates and historical data. Most of these data are inaccurate and in a number of cases obsolete. To support FAO and other institutions agricultural interventions, there is a need to know, based on actual data, the total cultivable land in Somalia, especially in the southern and central regions where agricultural activities are concentrated. Ideally, agricultural area should be assessed for each crop season in order to make available exact agricultural statistics for further analysis such as production estimation and for planning of rural development projects. However, at an assumed cost for VHR archive imagery of 18USD/sqkm, the image acquisition only would cost already 3,6 Mio. USD for Southern Somalia only. Furthermore recent investigations of SWALIM and partners on the availability of VHR imagery for Southern Somalia led to the results that only a limited fraction of the country
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