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Book (stand-alone)HandbookAgro-informatics Platform
How to use the time function
2025Also available in:
No results found.This guide introduces the time function of the FAO Agro-informatics Platform. The time function allows you to explore how data points evolve over a selected period, making it possible to analyse temporal dynamics directly on the map. By enabling or disabling the time dimension, you can either view all available data points at once or focus on specific time intervals to better understand change over time. This feature is particularly useful for datasets that include point-based information – such as agricultural observations, climate-related records, or socioeconomic indicators – where understanding when events occur is as important as where they occur. With the time function, you can trace developments, identify trends, and assess variations across different timeframes. Using this functionality can support monitoring, research, and planning activities. For example, it can help identify seasonal cycles, detect anomalies, or evaluate the impact of interventions over time. The time function thus provides a dynamic and flexible way to connect spatial data with temporal insights, enhancing evidence-based decision-making. -
Book (stand-alone)HandbookAgro-informatics Platform
How to perform deviations from averages analysis
2025Also available in:
No results found.This guide introduces you to the process of performing deviations from averages analysis on the FAO Agro-informatics Platform. This type of analysis allows you to examine how data in a specific area diverge from long-term averages or baseline values, making it easier to detect anomalies, unusual patterns, or significant changes over time. By using this tool, you can explore whether a region is experiencing conditions above or below expected norms, for example in terms of agricultural production, land cover, or environmental indicators. Such insights are essential for identifying risks, assessing resilience, and supporting timely responses in areas affected by climate variability, resource stress, or policy shifts. Through this guide, you will learn how to add datasets, define or upload your area of interest, and generate charts that highlight deviations from average conditions. The results can be customized, visualized, and downloaded, providing a practical framework for research, monitoring, and decision-making. Whether your objective is to monitor agricultural stability, detect early signs of stress, or evaluate long-term changes against historical baselines, deviations from averages analysis offers a valuable perspective to support data-driven strategies. -
Book (stand-alone)HandbookAgro-informatics Platform
How to create and share a story
2025Also available in:
No results found.This guide introduces the story feature of the FAO Agro-informatics Platform, which allows you to create interactive narratives based on geospatial data. A story is a sequence of captured scenes from the platform – such as maps, datasets, and visualizations – combined to guide viewers through a specific theme, trend, or analysis. By creating a story, you can move beyond static maps and transform data into a visual journey that highlights key insights. You can compare different time periods, showcase geographic patterns, or illustrate the impact of certain changes with clarity and context. Each scene preserves the exact map view and data configuration, enabling you to structure your analysis as a step-by-step narrative. Stories are particularly useful for communication and collaboration. They allow researchers, policymakers, and practitioners to share findings with colleagues, stakeholders, or the public in a clear and engaging format. Instead of providing raw data, you can tell a story that explains why the data matter and what they reveal about agriculture, land, or socioeconomic dynamics. Through this guide, you will learn how to capture, edit, and share scenes to build your own story. This functionality supports evidence-based dialogue, capacity development, and advocacy by turning complex geospatial analysis into accessible narratives that inform action.
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ProjectFactsheetSupport to the Regional Collaboration Platform of the Water Scarcity Initiative to Increase Water Productivity - TCP/RAB/3602 2020
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No results found.The Near East and North Africa (NENA) region is among the areas worst affected by chronic water shortages and, in coming decades, is likely to be faced by the most severe intensification of water scarcity in history. Per capita fresh water availability has decreased by two-thirds over the last forty years and is forecast to decrease by a further 50 percent by 2050. Demographic growth, a tendency to increase food self-sufficiency to reduce vulnerability to imports, price volatility, expanding urbanization, energy demands and overall socio-economic development, exacerbated by the negative impact of climate change and the degradation of water quality, are the main causes behind this intensification of scarcity. Agriculture, which consumes over 85 percent of available fresh water resources in the region, will most likely have to absorb the bulk of this shock, with major consequences for food security and the rural economy. Countries in the region thus need to plan their water resources allocation strategically and to review their water policies to ensure that the best use is made of the water available. To this end, it is essential to quantify the productivity of water use in agriculture. In response to the growing needs of member countries and to help them cope with this enormous challenge, FAO and partners launched in 2013 the Regional Water Scarcity Initiative in the Near East and North Africa. The first output of the Initiative was a Regional Collaborative Strategy (RCS) on Sustainable Agricultural Water Management. This represents a framework to assist countries -
Book (stand-alone)Technical reportFarmer Field School monitoring, evaluation and learning scoping survey
Overview of main results
2025Also available in:
No results found.Monitoring, evaluation and learning (MEL) is an essential component of any programme or project that aims to continuously improve and provide better outcomes. The ultimate purpose of MEL is to track implementation and outputs systematically, measure their effectiveness and allow learning with the aim of improving the quality and effects of Farmer Field School (FFS) implementation while ensuring accountability to beneficiaries and donors. A sound MEL system further helps to track the progress of any project and offers evidence upon which mid-course correction in a programme can be made with a goal of achieving the project objectives and impact targets. This system is built on the premise that the data is of high quality including timeliness, representativeness and reliability; the entire data management process is critical to ensure proper and systematic data collection for decision-making and programme improvement. To ensure systematic high-quality data management processes for MEL systems, the adoption, adaptation and utilization of digital systems becomes critical. Digital systems have proven importance in enhancing real-time data collection, collation and tabulation, which further enables timely evidence-based decision-making and feedback mechanisms. This also contributes to timely learning and quality improvement of the project, as well as accelerated feedback mechanisms to the beneficiaries and various stakeholders, ultimately ensuring improved results. -
Book (stand-alone)Corporate general interestFAO: Challenges and Opportunities in a Global World 2019This illustrated volume identifies the challenges and opportunities facing food and agriculture in the context of the 2030 Agenda, presents solutions for a more sustainable world and shows how FAO has been working in recent years to support its Member Nations in achieving the Sustainable Development Goals.