Using ontology and rules to retrieve the semantics of disaster remote sensing data

doi:10.23919/JSEE.2024.000024

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (5): 1211-1218.doi: 10.23919/JSEE.2024.000024

收稿日期:2022-11-02 出版日期:2024-10-18 发布日期:2024-11-06

Using ontology and rules to retrieve the semantics of disaster remote sensing data

Yumin DONG¹^,²(), Ziyang LI¹^,*(), Xuesong LI¹, Xiaohui LI¹()

¹ Key Laboratory of Quantitative Remote Sensing Information Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
² School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2022-11-02 Online:2024-10-18 Published:2024-11-06
Contact: Ziyang LI E-mail:dongyumin21@mails.ucas.ac.cn;zyli@aircas.ac.cn;xhli@aircas.ac.cn
About author:
DONG Yumin was born in 1998. He received his B.E. degree in safety engineering from University of Science and Technology Beijing in 2021. He is a Ph.D. student in Aerospace Information Research Institute, Chinese Academy of Sciences. His research interests include remote sensing ground system, remote sensing image processing and knowledge engineering. E-mail: dongyumin21@mails.ucas.ac.cn

LI Ziyang was born in 1977. He received his Ph.D. degree in signal and information processing from University of Chinese Academy of Sciences in 2013. He is a researcher in Aerospace Information Research Institute, Chinese Academy of Sciences. His research interests include remote sensing data processing, and aerospace ground systems. E-mail: zyli@aircas.ac.cn

LI Xuesong was born in 1987. He received his M.S. degree in electric engineering from California State University, Northridge in 2014. He is an assistant researcher in Aerospace Information Research Institute, Chinese Academy of Sciences. His research interests are complex information system design and development, and ground system software development. E-mail: lixs101485@ aircas.ac.cn

LI Xiaohui was born in 1971. She received her M.E. degree in communications and electronic systems from University of Science and Technology of China in 1997. She is a researcher in Aerospace Information Research Institute, Chinese Academy of Sciences. Her research interests include remote sensing data processing and remote sensing ground system. E-mail: xhli@aircas.ac.cn
Supported by:
This work was supported by the National Key Research and Development Program of China (2020YFC1512304).

摘要/Abstract

Abstract:

Remote sensing data plays an important role in natural disaster management. However, with the increase of the variety and quantity of remote sensors, the problem of “knowledge barriers” arises when data users in disaster field retrieve remote sensing data. To improve this problem, this paper proposes an ontology and rule based retrieval (ORR) method to retrieve disaster remote sensing data, and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge, on this basis, and realizes the task suitability reasoning of earthquake disaster remote sensing data, mining the semantic relationship between remote sensing metadata and disasters. The prototype system is built according to the ORR method, which is compared with the traditional method, using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.

Key words: remote sensing data, disaster, ontology, semantic reasoning

. [J]. Journal of Systems Engineering and Electronics, 2024, 35(5): 1211-1218.

Yumin DONG, Ziyang LI, Xuesong LI, Xiaohui LI. Using ontology and rules to retrieve the semantics of disaster remote sensing data[J]. Journal of Systems Engineering and Electronics, 2024, 35(5): 1211-1218.

图/表 11

参考文献 35

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Relation	Expression	Paraphrase
Has-subclass	Has-subclass(A, B)	B is a subclass of A
Has-related	Has-related(A, B)	A is related to B
Induces	Induces(A, B)	A includes B
Induces-by	Induces-by(A, B)	A is induced by B
After	After(A, B)	A is after B
Before	Before(A, B)	A is before B
During	During(A, B)	A is during B

Properties name	Data type	Data format
Start-time	Xsd:datatime	YYYY-MM-DDThh:mm:ss
End-time	Xsd:datatime	YYYY-MM-DDThh:mm:ss
Center-latitude	Xsd:float	Float
Center-longitude	Xsd:float	Float
Magnitude	Xsd:float	Float
Depth-of-focus	Xsd:float	Float
Response-level	Xsd:int	Int

Standard	Reference content
ISO-19107, 2019	Spatial representation of geographic information data
ISO-19108, 2002	Temporal representation of geographic information data
ISO-19115-2, 2008	Metadata structure for raster data
ISO-19130, 2018	Description framework for remote sensing sensors

Rule	Explanation
EventInstances(?a) ^ Magnitude(?a,?b) ^ swrlb:greaterThan (?b, “8.0”^^xsd:float) -> ImpactRange (?a, “240”^^xsd:float)	If the magnitude is greater than 8.0, the impact range is 240 km
EventInstances(?a) ^ Magnitude(?a,?b) ^ swrlb:greaterThan (?b, “7.0”^^xsd:float) -> ImpactRange (?a, “120”^^xsd:float)	If the magnitude is greater than 7.0, the impact range is 120 km
EventInstances(?a) ^ Magnitude(?a,?b) ^ swrlb:greaterThan (?b, “6.0”^^xsd:float) -> ImpactRange (?a, “60”^^xsd:float)	If the magnitude is greater than 6.0, the impact range is 60 km

Using ontology and rules to retrieve the semantics of disaster remote sensing data

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