气候变化领域集成服务门户(CCPortal): Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review

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DOI	10.3390/rs14143253
	Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review
	Yang, Liping; Driscol, Joshua; Sarigai, Sarigai; Wu, Qiusheng; Chen, Haifei; Lippitt, Christopher D.
发表日期	2022
EISSN	2072-4292
卷号	14 期号:14
英文摘要	Remote sensing (RS) plays an important role gathering data in many critical domains (e.g., global climate change, risk assessment and vulnerability reduction of natural hazards, resilience of ecosystems, and urban planning). Retrieving, managing, and analyzing large amounts of RS imagery poses substantial challenges. Google Earth Engine (GEE) provides a scalable, cloud-based, geospatial retrieval and processing platform. GEE also provides access to the vast majority of freely available, public, multi-temporal RS data and offers free cloud-based computational power for geospatial data analysis. Artificial intelligence (AI) methods are a critical enabling technology to automating the interpretation of RS imagery, particularly on object-based domains, so the integration of AI methods into GEE represents a promising path towards operationalizing automated RS-based monitoring programs. In this article, we provide a systematic review of relevant literature to identify recent research that incorporates AI methods in GEE. We then discuss some of the major challenges of integrating GEE and AI and identify several priorities for future research. We developed an interactive web application designed to allow readers to intuitively and dynamically review the publications included in this literature review.
英文关键词	Google Earth Engine (GEE); artificial intelligence (AI); machine learning; deep learning; computer vision; remote sensing; cloud computing; geospatial big data; review
语种	英语
WOS研究方向	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000831858600001
来源期刊	REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280932
作者单位	University of New Mexico; University of New Mexico; University of New Mexico; University of Tennessee System; University of Tennessee Knoxville; University of New Mexico
推荐引用方式 GB/T 7714	Yang, Liping,Driscol, Joshua,Sarigai, Sarigai,et al. Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review[J],2022,14(14).
APA	Yang, Liping,Driscol, Joshua,Sarigai, Sarigai,Wu, Qiusheng,Chen, Haifei,&Lippitt, Christopher D..(2022).Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review.REMOTE SENSING,14(14).
MLA	Yang, Liping,et al."Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review".REMOTE SENSING 14.14(2022).