{"title":"Artificial Intelligence in Landscape Architecture","authors":"Phillip Fernberg, B. Chamberlain","doi":"10.3368/lj.42.1.13","DOIUrl":null,"url":null,"abstract":"The use of artificial intelligence (AI) is becoming increasingly common in landscape architecture. New methods and applications are proliferating yearly and are being touted as viable tools for research and practice. While researchers have conducted assessments of the state of AI-driven research and practice in allied disciplines, there is a knowledge gap for the same in landscape architecture. This literature review addresses this gap by searching and evaluating studies specifically focused on AI and disciplinary umbrella terms (landscape architecture, landscape planning, and landscape design). It includes searches of academic databases and industry publications that combine these umbrella terms with the main subfields of artificial intelligence as a discipline (machine learning, knowledge-based systems, computer vision, robotics, natural language processing, optimization). Initial searches returned over 600 articles, which were then filtered for relevance, resulting in about 100 articles that were reviewed in depth. The work highlights trends in dissemination, synthesizes emergent AI-Landscape (AI-LA) themes, and argues for unifying dissemination and compilation in research and practice so as not to lose relevant AI-LA knowledge and be caught off guard in the built environment profession’s next technological leap.","PeriodicalId":54062,"journal":{"name":"Landscape Journal","volume":"42 1","pages":"13 - 35"},"PeriodicalIF":1.3000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Landscape Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3368/lj.42.1.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
The use of artificial intelligence (AI) is becoming increasingly common in landscape architecture. New methods and applications are proliferating yearly and are being touted as viable tools for research and practice. While researchers have conducted assessments of the state of AI-driven research and practice in allied disciplines, there is a knowledge gap for the same in landscape architecture. This literature review addresses this gap by searching and evaluating studies specifically focused on AI and disciplinary umbrella terms (landscape architecture, landscape planning, and landscape design). It includes searches of academic databases and industry publications that combine these umbrella terms with the main subfields of artificial intelligence as a discipline (machine learning, knowledge-based systems, computer vision, robotics, natural language processing, optimization). Initial searches returned over 600 articles, which were then filtered for relevance, resulting in about 100 articles that were reviewed in depth. The work highlights trends in dissemination, synthesizes emergent AI-Landscape (AI-LA) themes, and argues for unifying dissemination and compilation in research and practice so as not to lose relevant AI-LA knowledge and be caught off guard in the built environment profession’s next technological leap.
期刊介绍:
The mission of landscape architecture is supported by research and theory in many fields. Landscape Journal offers in-depth exploration of ideas and challenges that are central to contemporary design, planning, and teaching. Besides scholarly features, Landscape Journal also includes editorial columns, creative work, reviews of books, conferences, technology, and exhibitions. Landscape Journal digs deeper into the field by providing articles from: • landscape architects • geographers • architects • planners • artists • historians • ecologists • poets