A Brief Review of Recent Developments in the Integration of Deep Learning with GIS

• Autorzy: Mohan Shyama , Giridhar M.V.S.S

Identyfikatory

DOI

10.7494/geom.2022.16.2.21

• Języki publikacji: EN

Abstrakty

EN

The interaction of Deep Learning (DL) methods with Geographical Information System (GIS) provides the opportunity to obtain new insights into environmental processes through the spatial, temporal and spectral resolutions as well as data integration. The two technologies may be connected to form a dynamic system that is incredibly well adapted to the evaluation of environmental conditions through the interrelationships of texture, size, pattern, and process. This perspective has acquired popularity in multiple disciplines. GIS is significantly dependant on processors, particularly for 3D calculations, map rendering, and route calculation whereas DL can process huge amounts of data. DL has received a lot of attention recently as a technology with a plethora of promising results. Furthermore, the growing use of DL methods in a variety of disciplines, including GIS, is evident. This study tries to provide a brief overview of the use of DL methods in GIS. This paper introduces the essential DL concepts relevant to GIS, the majority of which have been published in recent years. This research explores remote sensing applications and technologies in areas such as mapping, hydrological modelling, disaster management, and transportation route planning. Finally, conclusions on contemporary framework methodologies and suggestions for further studies are provided.

Słowa kluczowe

EN

deep learning; GIS; integration; classification; remote sensing

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Geomatics and Environmental Engineering
• Rocznik: 2022
• Tom: Vol. 16, no. 2
• Strony: 21--38
• Opis fizyczny: Bibliogr. 55 poz.

Twórcy

autor

Mohan Shyama

• Research Scholar, Centre for Water Resources, Institute of Science and Technology, Jawaharlal Nehru Technological University Hyderabad, Kukatpally, Hyderabad, India

• https://orcid.org/0000-0002-7935-448X

autor

Giridhar M.V.S.S

• Centre for Water Resources, Institute of Science and Technology, Jawaharlal Nehru Technological University Hyderabad, Kukatpally, Hyderabad, India

• https://orcid.org/0000-0001-9029-9621

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu „Społeczna odpowiedzialność nauki” - moduł: Popularyzacja nauki i promocja sportu (2022-2023)