Result of Service

Under the overall guidance and supervision of the relevant Officer of the Geospatial Analysis and Programme Delivery Section (GPS), the consultant is expected to perform the following tasks: 1.Review historical yield data collected in the field by UNODC, along with corresponding available remote sensing, weather, soil, crop management data. 2.Review literature and existing models on approaches in yield prediction, evaluating their applicability for opium poppy with a special focus on integrating remote sensing data with traditional datasets to enrich the input features for predictive modeling, considering spatial and temporal resolutions and addressing data fusion challenges. 3.Develop predictive models for opium poppy yield estimation based on existing approaches to the extent possible. Validate and refine the models through iterative testing and evaluation, leveraging the provided training datasets and the ancillary data collected. 4.Provide actionable insights and recommendations on the model to be selected, based on its predictive accuracy and practical applicability. 5.Liaise with international organizations (e.g., FAO, IIASA) and Universities that carry out research on yield prediction models. 6.Test the model on Afghanistan opium cultivation data. 7.Produce a technical report, describing in detail the applied methods and tools, with a thorough assessment of performances and prediction accuracy of the model. Deliver all codes/scripts with detailed comments and ready-to-use. 8.Present findings and assure that the model can be replicated by ICMP technical staff, through technical sessions.

Work Location

Home-based with possible travels to Vienna and Rome Estimated dates: May 13 to 17 and/or September 2 to 6 (Vienna); May 27 to June 7 (Rome)

Expected duration

6 May – 9 September 2024

Duties and Responsibilities

UNODC’s Research and Trend Analysis Branch provides technical support on drugs and crime surveys to member states and counterparts and implements several surveys each year. Experts working in the branch are regularly involved in sample design and survey methodology development, data analysis as well as assessing the quality of surveys for which data is reported to UNODC. The Illicit Crop Monitoring Programme (ICMP) provides Member States with the necessary assistance to compile reliable and international comparable data on illicit crop cultivation and related drug production. In Afghanistan, estimates on poppy yield and potential opium gum production are realized on annual basis. Customarily, yield have been estimated by collecting poppy capsule measurements during field missions, and applying the methods described in the UNODC’s “Guidelines for Yield Assessment of Opium Gum and Coca Leaf from brief field visits”. Field data collection represents a great challenge in Afghanistan, because of the uncertain security situation of the country. Therefore, ICMP is looking into ways to predict poppy yield based on remote sensing and other available spatially explicit data. The purpose of the consultancy is to develop, based on historical training datasets provided by UNODC, a reliable model for opium poppy yield prediction in Afghanistan, which integrates remote sensing data and other available spatial explicit information.

Qualifications/special skills

An advanced university (Master’s degree or equivalent) in the fields of data science, statistics, computer science, agricultural science or related studies is required. A first level university degree in similar fields in combination with two additional years of qualifying experience may be accepted in lieu of the advanced university degree. PhD in a relevant area is desirable. A minimum of 10 years of experience in statistical modelling using multivariate analysis is required. Proven experience in developing predictive models and machine learning algorithms, with a focus on agricultural applications is required. Research experience with yield prediction models is required. Experience in working with remote sensing data, including satellite imagery processing, image analysis, and feature extraction techniques is desirable. Relevant scientific publications (books or articles in peer-reviewed journals) and/or conference papers are desirable. Other special skills or knowledge required/desired: Proficiency in programming languages such as Python or R, along with experience in using libraries and frameworks for data analysis and machine learning (e.g., pandas, scikit-learn, TensorFlow, PyTorch) is required. Strong analytical skills and attention to detail, with the ability to interpret complex data sets and extract actionable insights, are required. Knowledge of spatial statistics, geospatial analysis, and GIS (Geographic Information Systems) tools for integrating and analyzing remote sensing data with other spatial datasets is desirable. Excellent communication and collaboration skills, with the ability to work effectively in interdisciplinary teams and engage with stakeholders from diverse backgrounds are desirable.

Languages

English and French are the working languages of the United Nations Secretariat. For this position, fluency in English, with excellent drafting and communication skills, is required. Knowledge of another United Nations official language is an advantage.

Additional Information

The consultant will work in close collaboration with relevant technical staff from GPS and UNODC Information Centre in Tashkent.

No Fee

THE UNITED NATIONS DOES NOT CHARGE A FEE AT ANY STAGE OF THE RECRUITMENT PROCESS (APPLICATION, INTERVIEW MEETING, PROCESSING, OR TRAINING). THE UNITED NATIONS DOES NOT CONCERN ITSELF WITH INFORMATION ON APPLICANTS’ BANK ACCOUNTS.