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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. -
BookletSpatio-temporal dynamics of air pollution and the delineation of hotspots in the Lao People's Democratic Republic
Executive summary
2023Also available in:
No results found.Southeast Asia faces a heavy burden in terms of air pollution and haze (Association of Southeast Asian Nations, 2021). Out of the seven million deaths worldwide attributed to household and ambient pollution in 2016, two million occurred in Southeast Asia (WHO, 2018). Crop residue burning, slash and burn practices, and waste burning, among other sources, contribute to emissions in the agricultural sector. In Lao PDR, as in other countries in Southeast Asia, the dynamics and the contribution of air pollution from the agricultural sector are not well known. With a focus on the mitigation and adaption to climate change, Lao PDR has joined numerous conventions and policies, including the United Nations Framework Convention on Climate Change (UNFCCC), the United Nations Sustainable Development Goals, the Paris Agreement, the National Green Growth Strategy, the Reducing Emissions from Deforestation and Forest Degradation (REDD+) framework, and the Advancing the Clean Air, Health and Climate Integration Agenda in the Association of Southeast Asian Nations (ASEAN) Region project. However, there is still a lack of comprehensive and routine monitoring of air pollution and its sources in the country. Strengthening technical capacities to monitor air pollution through innovative and integrated approaches has the potential to guide actions towards sustainable development and improve environmental and life conditions. -
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.
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