[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126251-en":3,"doc-seo-126251-105":31,"detail-sidebar-cat-0-en-105":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126251,2336475104362,"Eden","https://ap-avatar.wpscdn.com/avatar/22000c4c46a41b752dd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786595829695023868",8,"Research & Report","Evaluating the Impact of Humanitarian Interventions on Agriculture Productivity in Syria Using Remote Sensing and Machine Learning","Growing attention is focused on creating reliable ways to measure the effects of complex humanitarian interventions in hard-to-reach regions so policy decisions can be better guided. Assessing agricultural intervention impacts after conflict remains difficult, especially where field access is limited. Advances in Earth observation and remote sensing enable timely, precise evaluation of agricultural activity and production in such contexts. This thesis develops a framework using remote sensing and machine learning to assess effectiveness in conflict-affected Syria, comparing vegetation anomalies normalized by rainfall across pre-conflict, conflict, and post-intervention periods.","AMERICAN UNIVERSITY OF BEIRUT  \nEVALUATING THE IMPACT OF HUMANITARIAN INTERVENTIONS ON AGRICULTURE PRODUCTIVITY IN SYRIA USING REMOTE SENSING AND MACHINE  \nLEARNING  \nby  \nLARA HUSSEIN SUJUD  \nA thesis  \nsubmitted in partial fulfillment of the requirements for the degree of Master of Science  \nto the Department of Agriculture  \nof the Faculty of Agricultural and Food Science  \nat the American University of Beirut  \nBeirut, Lebanon  \nJanuary 2023  \nAMERICAN UNIVERSITY OF BEIRUT  \nEVALUATING THE IMPACT OF HUMANITARIAN INTERVENTIONS ON AGRICULTURE PRODUCTIVITY IN SYRIA USING REMOTE SENSING AND MACHINE LEARNING  \nby  \nLARA HUSSEIN SUJUD  \nApproved by:  \nSignature  \nDr. Hadi Jaafar, Associate Professor  \nHadi  \nJaafar  \nDigitally signed by Hadi Jaafar  \nDN: cn=Hadi Jaafar, o=American University of Beirut, ou=Department of Agriculture, [email=hj01@aub.edu.lb](email=hj01@aub.edu.lb), c=LB  \nDate: 2023.02.06 09:41:22 +02'00'  \n\n| Department of Agriculture | Advisor |\n| --- | --- |\n| Dr. Ali Chalak, Associate Professor | Signature\u003Cbr> |\n| Department of Agriculture | Member of Committee |\n| Dr. Rami Zurayk, Professor | Signature\u003Cbr>\u003Cbr>\u003Cbr>Digitally signed by Rami Zurayk DN: cn=Rami Zurayk, o=AUB, ou=FSP, [email=rzurayk@aub.edu.lb](email=rzurayk@aub.edu.lb), c=LB Date: 2023.02.06 13:24:59 +02'00' |\n\nDepartment of Landscape Design and Ecosystem Management Member of Committee  \nDate of thesis defense: January 10, 2023  \nAMERICAN UNIVERSITY OF BEIRUT  \nTHESIS RELEASE FORM  \nStudent Name: Sujud Lara Hussein  \nLast First Middle  \nI authorize the American University of Beirut, to: (a) reproduce hard or electronic copies of my thesis; (b) include such copies in the archives and digital repositories of the University; and (c) make freely available such copies to third parties for research or educational purposes:  \n As of the date of submission  \n One year from the date of submission of my thesis.  \n Two years from the date of submission of my thesis.  \n Three years from the date of submission of my thesis.  \n06/02/2023  \nSignature Date  \nACKNOWLEDGEMENTS  \nI would like to express my deepest appreciation to my advisor, Dr. Hadi Jaafar, for his invaluable guidance and support, and for generously sharing his knowledge and expertise with me. I am extremely grateful to my committee members Dr. Ali Chalak and Dr. Rami Zurayk, for their feedback and comments. Additionally, this work would not have been possible without the generous support of the Foreign, Commonwealth & Development Office (FCDO) of the United Kingdom.  \nI’d like to extend my sincere thanks and appreciation to Dr. Ghassan Baliki and Prof Tilman Bruck – from the International Security and Development Center (ISDC) Berlin, Germany – for their feedback and comments.  \nI am also grateful to my lab mates and classmates, Rim, Roya, Jad, George, and Abed, for their endless support during the past two years. Special thanks to Yara and Adam for helping with imagery and data preparation.  \nLastly, thank you to my family, especially my parents, who always provided me with strength and support. And to the dearest people to my heart, Nagham, Marwa, Aida, and Yasmin, for their tremendous emotional support and belief in me.  \nABSTRACT  \nOF THE THESIS OF  \nLara Husein Sujud for  Master of Science  \nMajor: Irrigation  \nTitle: Evaluating the Impact of Humanitarian Interventions on Agriculture Productivity in Syria Using Remote Sensing and Machine Learning  \nRecently, there has been an increased interest in developing new methods to measure the impact of complex humanitarian interventions in hard-to-reach areas to help guide policy decisions. Quantifying agricultural interventions post-conflict remains a challenge. The advancement in Earth observations and remote sensing techniques can provide a timely and precise evaluation of agricultural activities and production in such settings. Little research has been done on the potential use of remote sensing for impact evaluation of agricultural interventions ","cbCaif2ZARDOX0ja","https://ap.wps.com/l/cbCaif2ZARDOX0ja","pdf",3627520,6,1,53,"English","en",105,"# Background\n## Outcomes of Syrian Conflict and Impact on Agriculture\n## Description of the intervention\n# Materials and Methods\n## Overview of study objectives and methods\n## Study Area\n## Study design and data sources","[{\"question\":\"What problem does the thesis address regarding humanitarian interventions in Syria?\",\"answer\":\"It addresses the difficulty of quantifying the impact of complex agricultural humanitarian interventions after conflict, particularly in hard-to-reach areas.\"},{\"question\":\"What methods does the study use to evaluate agriculture productivity?\",\"answer\":\"It uses remote sensing with vegetation indices normalized by rainfall across pre-conflict, conflict, and post-intervention periods, combined with an unsupervised machine learning classifier.\"},{\"question\":\"What main findings are reported about agriculture and vegetation after the intervention?\",\"answer\":\"Results indicate an overall improvement in vegetation and irrigated areas in intervention villages post-intervention, and remote sensing shows increased irrigated areas in some villages to pre-conflict levels.\"}]","Evaluating the Impact of Humanitarian Interventions on Agriculture Productivity in Syria Using Remote Sensing and Machine Learning | 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