GeoAI: a review of artificial intelligence approaches for the interpretation of complex geomatics data

Pierdicca, Roberto; Paolanti, Marina

doi:10.5194/gi-11-195-2022

Cited by 10 publications

(5 citation statements)

References 146 publications

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“…Geo-computation has the advantage of using computational methods and tools to explore geospatial data and earth data to generate new knowledge (Janowicz et al, 2020). Meanwhile, GeoAI provides learning algorithms and techniques, such as machine learning, deep learning (Li, 2021), and knowledge transfer, to develop effective and innovative solutions for geospatial and earth problems (PS Chauhan & Shekhar, 2021), (Pierdicca & Paolanti, 2022), (Liu & Biljecki, 2022). Mapping is an important component of GIS and earth observation, which helps in understanding the natural and built environment.…”

Section: Included (Meta-analysis)mentioning

confidence: 99%

“…GeoAI, which is a field that is constantly evolving and aims to assist in the processing and spatial analysis of big data, can also be described as a new discipline that combines innovations in spatial science, AI methods such as Machine Learning (ML), and Deep Learning (DL), data mining (data mining), and high-performance computing (high-performance computing. According to Gartner, GeoAI is the use of artificial intelligence (AI) methods, including ML and DL (Pierdicca & Paolanti, 2022), to generate knowledge through spatial and image data analysis. The increasing availability of geographic data, the development of AI, and the availability of large computational capacities have all contributed to the increased significance and potential of GeoAI.…”

Section: Introductionmentioning

confidence: 99%

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A Review Geospatial Artificial Intelligence (GEO-AI): Implementation Of Machine Learning On Urban Planning

Fauzi

2024

JMI

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Geospatial Artificial Intelligence (Geo-AI) is an interesting topic in its development and application in our lives. One of them is spatial planning, which contributes to the economic and social development of a region or country. Spatial data is the main thing in this research, which maximizes the effectiveness of land use spatial data on the area as upstream data and develops GIS-based urban planning applications to display the results of analysis and predictions of urban objects automatically. On the other hand, to maximize tourism revenue, the government plans urban areas for both spatial and land use and makes a lot of spatial data based on geographical and environmental conditions. This study will analyze the benefits of Geo-AI in urban planning and the tourism sector. The method used in this study is the Systematic Literature Review (SLR), where the search for the required articles comes from electronic databases obtained using the NVivo software with article sources from Publish or Perish. This study discusses the main steps for the analysis of geospatial data that have been successful in the main areas, namely the development of applications and models, including visualization. By treating issues in geospatial artificial intelligence, the overall aim of the research is to improve the quality of life for Indonesia's growing urban population. The results of the study with the systematic literature review of Geo-AI found a gap in the research implementation of the machine learning model used where five models were compared and relevant to the geospatial dataset displayed in the form of a literature review matrix and visually included in the relevant keywords in the bibliometric analysis. Interdisciplinary results are developing and are urgently needed by both government and private stakeholders in the development of smart cities to prepare spatial planning in urban areas and strategies in optimizing technology in the field of spatial planning in implementing systems based on Geo-AI.

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Section: Included (Meta-analysis)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Review Geospatial Artificial Intelligence (GEO-AI): Implementation Of Machine Learning On Urban Planning

Fauzi

2024

JMI

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“…The combination of geomatics and AI has opened up new possibilities for the management of digital cultural heritage (DCH) (Pierdicca and Paolanti, 2022). AI algorithms can analyze and interpret large datasets of geospatial and historical data, providing insights into the significance a nd c ontext o f C H s ites and artifacts.…”

Section: Ai For Chmentioning

confidence: 99%

Artificial Intelligence and Cultural Heritage: Design and Assessment of an Ethical Framework

Pansoni,

Tiribelli,

Paolanti

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The pioneering use of Artificial Intelligence (AI) in various fields and sectors, and the growing ethical debate about its application have led research centers, public and private institutions to establish ethical guidelines for a trustworthy implementation of these powerful algorithms. Despite the recognized definition of ethical principles for a responsible or trustworthy use of AI, there is a lack of a sector-specific perspective that highlights the ethical risks and opportunities for different areas of application, especially in the field of Cultural Heritage (CH). In fact, there is still a lack of formal frameworks that evaluate the algorithms’ adherence to the ethical standards set by the European Union for the use of AI in protecting CH and its inherent value. Because of this, it is necessary to investigate a different sectoral viewpoint to supplement the widely used horizontal approach. This paper represents a first attempt to design an ethical framework to embody AI in CH conservation practises to assess various risks arising from the use of AI in the field of CH. The contribution presents a synthesis of the different AI applications to improve the preservation process of CH. It explores and analyses in depth the ethical challenges and opportunities presented by the use of AI to improve CH preservation. In addition, the study aims to design an ethical framework of principles to assess the application of this ground-breaking technology at CH.

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“…GeoAI has potential applications in predictive modelling for health and neighbourhoods, transportation monitoring, land use, and cartography (Srivastava & Saxena, 2023). It also enables the handling of big data in geospatial analysis, allowing for the derivation of deep understandings and information from high-resolution remote sensing and other environmental sensors (Pierdicca & Paolanti, 2022). The concept of GeoAI has led to the development of new techniques for analyzing and interpreting complex geomatics data, such as RGB images, thermal images, 3D point clouds, trajectories, and hyperspectral/multispectral images (Yingjie et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Rethinking Geographic Thought in the Digital Space; A Review of the Arguments for Sustainability and Resilience

Arthur

2023

Preprint

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The study delves into the realm of Geographic Thought, emphasizing its significance in the context of contemporary global digital spaces. It also explores the intersection of Geographic Thought with artificial intelligence (AI) and its potential impact on sustainability and resilience within the field of geography. Employing the document analysis approach, the research scrutinizes this subject, demonstrating the method's pertinence in geography and various other academic domains. Document analysis, as the chosen research method, aids in unearthing valuable insights within the realm of geography. Whether investigating historical transformations, spatial patterns, environmental concerns, or other geographical themes, document analysis plays a pivotal role. The study methodically identifies research questions and assesses content in alignment with these inquiries, considering elements such as patterns, themes, trends, and connections across diverse sources. Spatial and temporal aspects, including location, scale, and temporal changes, are also examined to provide a comprehensive understanding of geographical issues. Thematic summaries extracted from this analysis contribute significantly to comprehending the geographical problem at hand. The research underscores AI as a potent tool for unravelling the intricate web of life exploration, human behaviour, urban dynamics, and human-environment interaction. However, it cautions users about the challenges that may arise when applying AI to sustainability and resilience studies, particularly when handling vast datasets. Nevertheless, AI is seen as a catalyst for enhancing geographic thought, enabling more nuanced interpretations and applications in the realm of sustainability and resilience. The study suggests a critical fusion of resilience and sustainability with geographic thought to effectively address the multifaceted socio-environmental challenges of our time. In essence, Geographic Thought, in conjunction with AI, can pave the way for a more comprehensive and insightful approach to geography's pivotal role in promoting sustainable and resilient solutions.

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GeoAI: a review of artificial intelligence approaches for the interpretation of complex geomatics data

Cited by 10 publications

References 146 publications

A Review Geospatial Artificial Intelligence (GEO-AI): Implementation Of Machine Learning On Urban Planning

A Review Geospatial Artificial Intelligence (GEO-AI): Implementation Of Machine Learning On Urban Planning

Artificial Intelligence and Cultural Heritage: Design and Assessment of an Ethical Framework

Rethinking Geographic Thought in the Digital Space; A Review of the Arguments for Sustainability and Resilience

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