logo
ResearchBunny Logo
A big data approach to assess progress towards Sustainable Development Goals for cities of varying sizes

Environmental Studies and Forestry

A big data approach to assess progress towards Sustainable Development Goals for cities of varying sizes

Y. Liu, B. Huang, et al.

Discover a groundbreaking method to assess Sustainable Development Goal (SDG) progress in 254 Chinese cities using open-source big data, revealed by Yu Liu, Bo Huang, Huadong Guo, and Jianguo Liu. Their findings suggest that big data can effectively track SDG advancements, especially in smaller, data-scarce urban areas.

00:00
Playback language: English
Abstract
This study presents a systematic method for assessing Sustainable Development Goal (SDG) progress using open-source big data for 254 Chinese cities, comparing results with those obtained using statistical data. The authors find big data a promising alternative for tracking SDG progress, even in data-scarce cities. Analysis reveals a correlation between decreasing SDG Index scores and decreasing city size, highlighting the need for improved SDG progress in smaller cities for balanced national sustainability.
Publisher
Communications Earth & Environment
Published On
Mar 10, 2023
Authors
Yu Liu, Bo Huang, Huadong Guo, Jianguo Liu
Tags
Sustainable Development Goals
big data
urban sustainability
SDG Index
Chinese cities
data scarcity
city size

Related Publications

Explore these studies to deepen your understanding of the subject.

Measuring museum sustainability in China: a DSR model-driven approach to empower sustainable development goals (SDGs)
Interdisciplinary Studies

Measuring museum sustainability in China: a DSR model-driven approach to empower sustainable development goals (SDGs)

S. Wang, L. Yu, et al.

Responses to the COVID-19 pandemic have impeded progress towards the Sustainable Development Goals
Environmental Studies and Forestry

Responses to the COVID-19 pandemic have impeded progress towards the Sustainable Development Goals

C. Li, Z. Deng, et al.

Quantitative evidence of the community of shared future for mankind as a driver of sustainable development in human society
Economics

Quantitative evidence of the community of shared future for mankind as a driver of sustainable development in human society

Z. Cai and W. Zhang

Finding pathways to synergistic development of Sustainable Development Goals in China
Environmental Studies and Forestry

Finding pathways to synergistic development of Sustainable Development Goals in China

J. Zhang, S. Wang, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny