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Agro-informatics Platform

How to use the time function








Marini, F. 2025. Agro-informatics Platform – How to use the time function. Rome.


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    This guide introduces you to the process of performing time-series analysis on the FAO Agro-informatics Platform. Time-series analysis allows you to track how data evolve over time within a defined area, helping you identify patterns, trends, and changes that may not be visible in a single snapshot. By comparing data across different years or periods, you can gain valuable insights into long-term developments and their implications for agriculture, land use, and natural resources. With this guide, you will learn how to add datasets, select areas of interest, and generate time-series charts that display variations in key indicators over time. The platform also enables you to compare multiple areas, view data in tabular format, and sort results to better understand the dynamics at play. Whether your aim is to monitor land-use changes, evaluate the effectiveness of agricultural policies, assess the impact of climate variability, or support planning for sustainable development, time-series analysis provides a robust framework for evidence-based decision-making. This guide will help you take your first steps in applying these tools effectively on the platform.
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    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.
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    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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