In response to a growing demand for high-quality and internationally-comparable statistics, FAO develops, implements and promotes methods and standards to guide national data producers in generating and using sound statistics. In particular, the Organization is committed to provide national statistical systems with internationally recognized definitions, concepts and classifications as well as methodological guidance for the production of high quality statistics related to food and agriculture.
This interface allows you to search for statistical classifications, guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources. You can search by SUBJECT (general, agriculture, forestry, fishery and aquaculture, and natural resources) or use the ADVANCED SEARCH to search by keyword, country, language and lead authoring unit/office. Comments, suggestions and inquiries can be addressed to: [email protected].
You can access here all the statistical guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources.
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Comments, suggestions and inquiries can be addressed to: [email protected].
Abstract: The national forest monitoring system (NFMS) assessment tool has been developed under the project “Building global capacity to increase transparency in the forest sector (CBIT-Forest)” implemented by Food and Agriculture Organization of the United Nations (FAO) and funded by the Capacity-Building Initiative for Transparency (CBIT) trust fund of the Global Environment Facility (GEF). The tool aims to assist countries in carrying out a comprehensive capacity assessment of forest monitoring across three complementary themes – institutional arrangements, measurement and estimation, and reporting and verification.
Lead authoring unit/office: Forestry Division (NFO)
Abstract: This document reflects the latest reference metadata information available on SDG-indicator 6.4.1 "Change in water use efficiency over time". Last updated: February 2021.
Lead authoring unit/office: FAO
Abstract: This e-learning course is part of a series which introduce the FAO Damage and Loss (D&L) methodology, developed to support countries to generate precise and holistic data for the agricultural sector, in response to climate- and weather-related disasters. This course introduces the formulae which are used to compute damage and loss in the agricultural sectors (crops, livestock, forestry, aquaculture and fisheries). It then considers the data requirements and possible sources, and how the data can be used both to report on Sendai and SDG targets, and at national level. (Released in: December 2020; 2 h of learning)
Lead authoring unit/office: FAO
Abstract: The CWP Handbook covers the concepts, definitions, classifications and data exchange protocols – and not least the codes as applied to fishery statistics globally. Many of these concepts and definitions are applied in a wider context, but the user is advised to check the validity of such applications. The handbook indicates the principles applied by the international agencies and no attempt has been made to include details of national systems, many of which, having been developed for specific national purposes, may differ from those employed internationally.
Lead authoring unit/office: Fisheries Division (NFI)
Abstract: In recent decades, the occurrence of climate- and weather-related disasters has increased, and globally, a vast number of agricultural livelihoods are compromised each year, with far-reaching effects on food security and ecosystems. This course is part of a series which aim to introduce the FAO Damage and Loss (D&L) methodology, developed by FAO to support countries to generate precise and holistic data for the agricultural sector. This can be used for national Disaster Risk Reduction/Management, resilience and to help monitor the achievement of global targets. (Released in: September 2020; 55 min of learning)
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This e-learning course provides an overview of the System of Environmental Economic Accounting (SEEA) Central Framework, the statistical standard to measure the relationship between the economy and the environment. The System of Environmental-Economic Accounting 2012—Central Framework is a multipurpose conceptual framework for measuring the interactions between the environment and the economy. By providing an internationally agreed standard with agreed concepts, definitions and classifications, the SEEA is an invaluable tool for compiling integrated statistics on the economy and the environment and deriving coherent and comparable indicators to measure progress towards sustainable development.
Lead authoring unit/office: United Nations Statistics Division (UNSD)
Abstract: The objective of this course is to learn about the Enhanced Transparency Framework (EFT) under the Paris Agreement. It will be useful to those wishing to understand the importance of forest-related data collection, analysis and dissemination in meeting the Enhanced Transparency Framework requirements.
Lead authoring unit/office: Forestry Division (NFO)
Abstract: This course focuses on SDG Indicator 14.4.1 - Fish stocks sustainability: “Proportion of fish stocks within biologically sustainable levels”. It introduces basic fisheries concepts and definitions, illustrates some technical aspects of classical and data-limited stock assessment and provides detailed guidance on process and tools for the analysis and reporting of the Indicator.
Lead authoring unit/office: FAO
Abstract: The course provides guidance on the rationale and the main characteristics of Indicator 6.4.1, and on how to compute the two dimensions constituting the indicator: the hydrologic and the economic component. It also highlights possible challenges related to data availability, and the impact that monitoring results may have on national decision-making and identification of development policies.
Lead authoring unit/office: FAO
Abstract: This document contains a comprehensive list of terms and definitions as well as explanatory notes for FRA 2020 reporting variables.
Lead authoring unit/office: Forestry Division (NFO)
