TY - JOUR
T1 - Role of green infrastructure planning in achieving sustainable development goals through an environmental efficiency lens
T2 - an integrated literature review
AU - Lin, Zih Hong
AU - Laffan, Shawn W.
AU - Metternicht, Graciela
PY - 2025/5
Y1 - 2025/5
N2 - Green infrastructure (GI) planning is a strategy to cope with climate change and can potentially contribute directly or indirectly to all Sustainable Development Goals (SDGs). Given resource limitations, integrating the concept of environmental efficiency into GI planning is essential for enhancing cost-effectiveness. However, there is limited research on the environmental efficiency of GI, as well as its specific contributions to SDG targets. This study aims to explore how the planning of GI can help achieve the SDGs by applying an environmental efficiency perspective and identifying existing research gaps. A bibliographic analysis of 427 scientific articles is used to identify current trends in the field. The key findings highlight that a) GI can contribute directly to SDG 2, 3, 6, 10, 11, 13, 14, and 15; b) GI has the potential to benefit 32 SDG targets; c) the Data Envelopment Analysis (DEA) method may be suitable for assessing environmental efficiency; and d) integrating machine learning algorithms with DEA can enhance the reliability of environmental efficiency measurement. In summary, environmental efficiency plays a vital role in planning GI and helps decision-makers realise the SDG targets.
AB - Green infrastructure (GI) planning is a strategy to cope with climate change and can potentially contribute directly or indirectly to all Sustainable Development Goals (SDGs). Given resource limitations, integrating the concept of environmental efficiency into GI planning is essential for enhancing cost-effectiveness. However, there is limited research on the environmental efficiency of GI, as well as its specific contributions to SDG targets. This study aims to explore how the planning of GI can help achieve the SDGs by applying an environmental efficiency perspective and identifying existing research gaps. A bibliographic analysis of 427 scientific articles is used to identify current trends in the field. The key findings highlight that a) GI can contribute directly to SDG 2, 3, 6, 10, 11, 13, 14, and 15; b) GI has the potential to benefit 32 SDG targets; c) the Data Envelopment Analysis (DEA) method may be suitable for assessing environmental efficiency; and d) integrating machine learning algorithms with DEA can enhance the reliability of environmental efficiency measurement. In summary, environmental efficiency plays a vital role in planning GI and helps decision-makers realise the SDG targets.
KW - Environmental efficiency
KW - Green infrastructure
KW - Machine learning
KW - Sustainable Development Goals (SDGs)
UR - http://www.scopus.com/inward/record.url?scp=105002804718&partnerID=8YFLogxK
U2 - 10.1016/j.ecolind.2025.113471
DO - 10.1016/j.ecolind.2025.113471
M3 - Article
AN - SCOPUS:105002804718
SN - 1470-160X
VL - 174
JO - Ecological Indicators
JF - Ecological Indicators
M1 - 113471
ER -