Deploying artificial intelligence for climate change adaptation

被引：87

作者：

Filho, Walter Leal ^{[1
,2
]}

Wall, Tony ^{[3
]}

Mucova, Serafino Afonso Rui ^{[4
]}

Nagy, Gustavo J. ^{[5
]}

Balogun, Abdul-Lateef ^{[6
,7
]}

Luetz, Johannes M. ^{[8
,9
,10
]}

Ng, Artie W. ^{[11
,12
]}

Kovaleva, Marina ^{[2
]}

Azam, Fardous Mohammad Safiul ^{[13
]}

Alves, Fatima ^{[14
,15
,16
]}

Guevara, Zeus ^{[17
,18
]}

Matandirotya, Newton R. ^{[19
,20
]}

Skouloudis, Antonis ^{[21
]}

Tzachor, Asaf ^{[22
]}

Malakar, Krishna ^{[23
]}

Gandhi, Odhiambo ^{[24
]}

机构：

[1] Manchester Metropolitan Univ, Sch Sci & Environm, All St Bldg,Oxford Rd, Manchester M15 6BH, Lancs, England

[2] Hamburg Univ Appl Sci, Res & Transfer Ctr Sustainable Dev & Climate Chan, Ulmenliet 20, D-21033 Hamburg, Germany

[3] Liverpool John Moores Univ, Liverpool Business Sch, Liverpool L3 5UG, Merseyside, England

[4] Lurio Univ, Fac Nat Sci, Pemba 958, Mozambique

[5] Univ Republica, Inst Ciencias Ambientales & Ecol, Igua 4225, Montevideo 11200, Uruguay

[6] Esri Australia, Serv Dept Resources, 613 King St, West Melbourne, Vic 3003, Australia

[7] Univ Teknol PETRONAS, Dept Civil & Environm Engn, Geospatial Anal & Modelling GAM Res Lab, Seri Iskandar 32610, Perak, Malaysia

[8] Univ New South Wales, Sch Social Sci, Sydney, NSW 2052, Australia

[9] Univ Sunshine Coast, Sch Law & Soc, Maroochydore, Qld 4558, Australia

[10] Alphacrucis Univ Coll, Grad Res Sch, Brisbane, Qld 4102, Australia

[11] Int Business Univ, Toronto, ON M5S 2V1, Canada

[12] Univ Waterloo, Waterloo Inst Sustainable Energy, 200 Univ Ave, West Waterloo, ON N2L 3G1, Canada

[13] Neijiang Normal Univ, Coll Life Sci, Dongtong Rd, Neijiang, Sichuan, Peoples R China

[14] Univ Aberta, Rua Escola Politecn 147, P-1269001 Lisbon, Portugal

[15] Univ Coimbra, TERRA Associated Lab, Rua Escola Politecn 147, P-1269001 Lisbon, Portugal

[16] Univ Coimbra, Ctr Funct Ecol, Rua Escola Politecn 147, P-1269001 Lisbon, Portugal

[17] Tecnol Monterrey, Sch Govt & Publ Transformat, Mexico City, DF, Mexico

[18] Escuela Gobierno & Transformac Publ, Av Revoluc 756,Piso 2, Mexico City 03700, DF, Mexico

[19] Kgotso Dev Trust, Ctr Climate Change Adaptat & Resilience, POB 5, Beitbridge, Zimbabwe

[20] North West Univ, Unit Environm Sci & Management, Private Bag X6001, ZA-2520 Potchefstroom, South Africa

[21] Univ Aegean, Dept Environm, Univ Hill, GR-81132 Mitilini, Lesvos, Greece

[22] Reichman Univ, Sch Sustainabil, HaUniv 8, IL-4610101 Herzliyya, Israel

[23] Indian Inst Technol Madras, Dept Humanities & Social Sci, Chennai 600036, Tamil Nadu, India

[24] Univ Nairobi, Inst Climate Change & Adaptat ICCA, POB 30197-00100, Nairobi, Kenya

来源：

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE | 2022年 / 180卷

关键词：

Artificial intelligence; Digital technologies; Climate change adaptation; BIG DATA; LEARNING ALGORITHMS; DECISION-MAKING; CHALLENGES; CONSERVATION; GENERATION; INSIGHT; IMPROVE; EUROPE; IMPACT;

D O I：

10.1016/j.techfore.2022.121662

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Artificial Intelligence (AI) is believed to have a significant potential use in tackling climate change. This paper explores the connections between AI and climate change research as a whole and its usefulness in climate change adaptation efforts in particular. Using a systematic review of the literature on applications of AI for climate change adaptation and a questionnaire survey of a multinational and interdisciplinary team of climate change researchers, this paper shows the various means via which AI can support research on climate change in diverse regions, and contribute to efforts towards climate change adaptation. The surveyed articles are classified under nine areas, e.g., Global/Earth Related; Water-related Issues and agriculture, 95% of which are related to adaptation. The areas that have attracted the most studies about AI applications are water-related management issues (38%). In terms of the survey results, the most robust agreements were noted concerning the capacity of digitisation and AI to strengthen governance practices and afford policy coherence in climate change. Evidence gathered in the study suggests that, provided that due care is taken, the use of AI can provide a welcome support to global efforts to better understand and handle the many challenges associated with a changing climate.

引用

页数：20

共 129 条

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