• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Institut de Recherche de l’École navale (IRENAV)
  • View Item
  • Home
  • Institut de Recherche de l’École navale (IRENAV)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A location-based model using GIS with machine learning, and a human-based approach for demining a post-war region

Article dans une revue avec comité de lecture
Author
SALIBA, Adib
13094 Institut de Recherche de l'Ecole Navale [IRENAV]
ccTOUT, Kifah
303340 الجامعة اللبنانية [بيروت] = Lebanese University [Beirut] = Université libanaise [Beyrouth] [LU / ULB]
ZAKI, Chamseddine
303340 الجامعة اللبنانية [بيروت] = Lebanese University [Beirut] = Université libanaise [Beyrouth] [LU / ULB]
ccCLARAMUNT, Christophe
13094 Institut de Recherche de l'Ecole Navale [IRENAV]

URI
http://hdl.handle.net/10985/25189
DOI
10.1080/17489725.2023.2298803
Date
2024-01-04
Journal
Journal of Location Based Services

Abstract

Locating and removing landmines and other ERW (Explosive Remnants of War) is dangerous, hazardous, and time-consuming. It requires implementing multilevel on-site surveys: general non-technical surveys to mark the areas affected and technical surveys to determine the perimeter of related minefields. This paper introduces a landmine location-based prediction model, combining military experience with machine-learning techniques and spatiotemporal data, by introducing a new approach for area selection and adding military-based features for context modelling and model training. Besides predicting landmine’s location areas, this model classifies the affected regions by priority and difficulty of clearance, in such a way as to minimise the long time needed by surveys and reduce the danger related to that task, thus providing the clearance organisations with a good resource allocation for their operations. We applied several machine learning techniques that combine Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBOOST), taking into consideration the imbalanced data problem and tweaking for the best performance and accuracy. The experimental results show that the model has the potential to provide reliable predictions and valuable services for demining operations on the field.

Files in this item

Name:
IRENAV_JLBS_2024_SALIBA.pdf
Size:
15.76Mb
Format:
PDF
Embargoed until:
2024-07-15
View/Open

Collections

  • Institut de Recherche de l’École navale (IRENAV)

Related items

Showing items related by title, author, creator and subject.

  • A semantic and language-based representation of an environmental scene 
    Article dans une revue avec comité de lecture
    LE YAOUANC, Jean-Marie; SAUX, Eric; ccCLARAMUNT, Christophe (Springer Verlag, 2010)
    The modeling of a landscape environment is a cognitive activity that requires appropriate spatial representations. The research presented in this paper introduces a structural and semantic categorization of a landscape ...
  • Design of a spatial database to analyze the forms and responsiveness of an urban environment using an ontological approach 
    Article dans une revue avec comité de lecture
    SILAVI, Tolue; HAKIMPOUR, Farshad; NOURIAN, Farshad; ccCLARAMUNT, Christophe (Elsevier, 2015)
    This paper introduces a spatial database and ontology-enabled framework that models and operationalizes the relation between urban forms and their responsiveness to the needs of its user. The objective is to offer a framework ...
  • A qualitative modelling approach for the representation of trajctories: application to the analysis of flight patterns 
    Article dans une revue avec comité de lecture
    WU, Jing; ccCLARAMUNT, Christophe; BELOUAER, Lamia; DENG, Min (Taylor & Francis, 2015)
    Over the past few years a series of computational and semantic frameworks have been developed to model and represent the spatial and temporal properties of moving entities. Despite the interest of these contributions it ...
  • Local and global spatio-temporal entropy indices based on distance- ratios and co-occurrences distributions 
    Article dans une revue avec comité de lecture
    LEIBOVICI, Didier G.; ccCLARAMUNT, Christophe; LE GUYADER, Damien; ccBROSSET, David (Taylor & Francis, 2014)
    When it comes to characterize the distribution of ‘things’ observed spatially and identified by their geometries and attributes, the Shannon entropy has been widely used in different domains such as ecology, regional ...
  • A Geographical - Based Multi - Criteria Approach for Marine Energy Farm Planning 
    Article dans une revue avec comité de lecture
    MASLOV, Nicolas; ccBROSSET, David; ccCLARAMUNT, Christophe; CHARPENTIER, Jean-Frederic (MDPI, 2014)
    The objective of this paper is to devise a strategy for developing a flexible tool to efficiently install a marine energy farm in a suitable area. The current methodology is applied to marine tidal current, although it can ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales