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Book (stand-alone)Agro-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)Agro-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)Agro-informatics Platform
How to perform time-series analysis
2025Also available in:
No results found.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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