世界银行-应用城市化程度_定义城市_城镇和农村地区以进行国际比较的方法手册（英）-2025_102页_13mb

Summary of "Applying the Degree of Urbanisation"

Core Content

This document presents a methodological manual for defining cities, towns, and rural areas in a harmonised manner to support international comparisons. It was developed through collaboration between six international organisations: the European Commission, the Food and Agriculture Organization of the United Nations (FAO), the United Nations Human Settlements Programme (UN-Habitat), the International Labour Organization (ILO), the Organisation for Economic Co-operation and Development (OECD), and The World Bank. The manual provides a global framework to classify areas based on the degree of urbanisation, aiming to improve the quality and comparability of urban and rural statistics across countries.

Main Purpose

The manual is intended to complement existing national definitions used by statistical offices and ministries. It offers a practical guide for data producers, suppliers, and statisticians to implement a standard methodology for classifying areas along an urban-rural continuum. The goal is to enable better monitoring and analysis of Sustainable Development Goals (SDGs) and other global policy objectives by area type.

Key Objectives

• Harmonisation of definitions: Provide a consistent global approach to define cities, towns, and rural areas.
• Support for international comparisons: Enable more accurate and comparable statistics across countries.
• Improved data quality: Offer a method that ensures better data collection, analysis, and interpretation for policy-making.

Main Points and Viewpoints

1. The Degree of Urbanisation Classification

• The classification divides areas into three main categories: cities, towns and semi-dense areas, and rural areas.
• It can be extended to more detailed classifications (Level 2) that include suburban or peri-urban areas, villages, dispersed rural areas, and mostly uninhabited areas.
• It also defines functional urban areas (FUA), which include cities and their surrounding commuting zones.

2. Advantages of the Classification

• Captures the urban-rural continuum: It provides a more nuanced view of urban development by identifying intermediate areas.
• Standard population thresholds: Uses consistent population size and density criteria globally.
• Reduces spatial bias: Starts from a population grid to ensure uniformity across different administrative units.
• Direct measurement of population clusters: Avoids relying on access to services to define areas.
• Cost-effective: Provides a methodology that is feasible for implementation in various contexts.
• Supports SDG monitoring: Allows for the production of indicators by degree of urbanisation, facilitating better policy decisions.

3. Implementation and Data Sources

• The methodology is based on population grids, which can be constructed using aggregated point data, disaggregated population data, or partial micro-censuses.
• It also considers alternative and emerging data sources, such as satellite imagery and digital mapping tools.
• Level 1 classification can be applied with existing data, while Level 2 and FUA require more detailed data collection, often through large sample surveys.

4. Legal and Policy Framework

• The methodology aligns with the 2030 Agenda for Sustainable Development, which includes 17 SDGs and 232 indicators, many of which are relevant to urban and rural areas.
• It also supports the New Urban Agenda, adopted at Habitat III in 2016, which promotes sustainable urban development.
• The manual addresses the need for rural statistics, which are often underdeveloped due to the lack of a consistent international definition.

5. Methodological Approach

• The manual outlines how to construct a population grid and classify small spatial units.
• It discusses how to adjust for geographic issues and select appropriate spatial units for analysis.
• It provides guidance on extending the classification to include functional urban areas and other territorial typologies.

6. Tools and Training

• A range of tools is provided to assist in the implementation of the methodology.
• Training materials are included to help data producers and users understand and apply the classification.
• Online resources are available to support the use of the degree of urbanisation classification.

Conclusion

This manual aims to enhance the comparability and quality of urban and rural statistics worldwide. It supports the production of SDG indicators and offers a flexible yet standardised approach to classifying areas based on the degree of urbanisation. By providing a consistent framework, it helps countries better understand and address the challenges and opportunities of their urban and rural areas, ultimately contributing to more effective and informed policy-making.

Key Information

• Document Title: Applying the Degree of Urbanisation: A Methodological Manual to Define Cities, Towns and Rural Areas for International Comparisons
• Edition: 2021
• Organisations Involved: European Commission, FAO, UN-Habitat, ILO, OECD, World Bank
• Purpose: Harmonise urban and rural area definitions for better international statistical comparisons
• Classification Levels: Level 1 (cities, towns, rural areas), Level 2 (more detailed types), and Functional Urban Areas (FUAs)
• Legal Basis: The Tercet Regulation (EU) 2017/2391 and the NUTS Regulation (EC) No 1059/2003
• SDGs Supported: The methodology supports the monitoring and analysis of SDG indicators, particularly those related to urban and rural development
• Target Audience: National statistical offices, policymakers, researchers, and data producers

References

• UN (2015): Transforming our World: the 2030 Agenda for Sustainable Development
• UN (2019): Expert Group Meeting on Statistical Methodology for Delineating Cities and Rural Areas
• UN-Habitat (2017): New Urban Agenda
• OECD (2012): New way to measure metropolitan areas
• FAO (2018): Guidelines on defining rural areas and compiling indicators for development policy
• UNECE (2015): Recommendations for the 2020 Censuses of Population and Housing