In:
SIGSPATIAL Special, Association for Computing Machinery (ACM), Vol. 12, No. 3 ( 2021-01-25), p. 43-45
Abstract:
Safety is vital for people and emergency management helps keep people safe. Emergency management includes four stages: Planning and Mitigation, Preparedness, Response and Recovery. Geospatial applications (including GIS) have been extensively used in each stage of emergency management. Nowadays, on the technical side, artificial intelligence tools like deep learning could be put to good use. For example, one of the main benefits of deep learning over various machine learning algorithms is its ability to generate new features from limited series of features located in the training dataset. Therefore, deep learning algorithms can create new tasks to solve current ones. Decision-makers can utilize the geospatial information to develop planning and mitigation strategies with such advanced techniques. GIS models and simulation capabilities are used to exercise response and recovery plans during non-disaster times. They help the decision-makers sense the near real-time possibilities during an event. Once disaster occurs, GIS will take effect in real time response and recovery activities.
Type of Medium:
Online Resource
ISSN:
1946-7729
DOI:
10.1145/3447994.3448009
Language:
English
Publisher:
Association for Computing Machinery (ACM)
Publication Date:
2021
detail.hit.zdb_id:
2536745-6
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