A Spatio-Temporal Conceptual Model for Sound Representation in Geographic Information Systems

Geographic information systems have traditionally focused on the representation of visual and geometric aspects of geographic phenomena, while auditory information has largely been ignored or reduced to simple numerical attributes. Although numerous spatio-temporal data models have been proposed to describe dynamic geographic processes, few of them provide explicit semantic constructs for representing sound and its evolution over space and time. This paper extends the Modeling of Application Data with Spatio-Temporal Features (MADS) conceptual model by introducing an explicitly defined acoustic semantic dimension. The extension separates source-intrinsic acoustic emission (soundfeature), source–receiver propagation and exposure (AFFECTS and associated EXPOSUREZONE instances), and receiver-centered contextual perception (PERCEPTIONASSESSMENT). These complementary constructs enable acoustic emission, propagation, temporal dynamics, spatial exposure, and perceptual assessment to be represented within a unified spatio-temporal semantic framework. The applicability of the proposed approach is illustrated through a proof-of-concept scenario and representative database queries, demonstrating how the proposed acoustic constructs can be mapped, stored, and queried using standard GIS database infrastructure.

Authors

Institutions

Publication Details

Journal
ISPRS International Journal of Geo-Information
Published
2026-09-11
DOI
https://doi.org/10.3390/ijgi15090418
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Spatio-Temporal Conceptual Model for Sound Representation in Geographic Information Systems

Abbass Nasser, Bilel Neji, Chadia Sawaya, Chamseddine Zaki et al.
ISPRS International Journal of Geo-Information
Geographic Information Systems Studies
article

A Spatio-Temporal Conceptual Model for Sound Representation in Geographic Information Systems

Abbass Nasser, Bilel Neji, Chadia Sawaya, Chamseddine Zaki, Mostafa Rizk, Houssein Taleb, Hussein Sheaib
article en

Abstract

Geographic information systems have traditionally focused on the representation of visual and geometric aspects of geographic phenomena, while auditory information has largely been ignored or reduced to simple numerical attributes. Although numerous spatio-temporal data models have been proposed to describe dynamic geographic processes, few of them provide explicit semantic constructs for representing sound and its evolution over space and time. This paper extends the Modeling of Application Data with Spatio-Temporal Features (MADS) conceptual model by introducing an explicitly defined acoustic semantic dimension. The extension separates source-intrinsic acoustic emission (soundfeature), source–receiver propagation and exposure (AFFECTS and associated EXPOSUREZONE instances), and receiver-centered contextual perception (PERCEPTIONASSESSMENT). These complementary constructs enable acoustic emission, propagation, temporal dynamics, spatial exposure, and perceptual assessment to be represented within a unified spatio-temporal semantic framework. The applicability of the proposed approach is illustrated through a proof-of-concept scenario and representative database queries, demonstrating how the proposed acoustic constructs can be mapped, stored, and queried using standard GIS database infrastructure.

ISPRS International Journal of Geo-InformationVol. 15(9)
Lebanese University (LB), Saint Joseph University (LB), Holy Spirit University of Kaslik (LB), American University of the Middle East (KW), Lebanese American University (LB), American University of Science and Technology (LB), American University of Beirut (LB)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Geographic Information Systems Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.