Overview
I am a PhD student working in the Environment and Sustainability Institute (ESI). I am interested in applying remote sensing methods for the digital preservation of cultural and archaeological landscapes. I use range-based approaches and digital photogrammetry to derive spatial attributes of cultural heritage features and detect potential archaeological remains.
Qualifications
MSc in Civil Engineering, University of Southampton
Career
2018 -present PhD Student, University of Exeter
2016-2017 MSc in Civil Engineering, University of Southampton
2010- 2014 BSc (Hons) in Surveying Engineering, University of Baghdad
Publications
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Kadhim I, Abed FM, DeSilvey C (In Press). Combining remote sensing approaches for detecting marks of archaeological and demolished constructions in Cahokia’s Grand Plaza, South-Western Illinois. Remote Sensing
Kadhim I, Abed FM (2023). A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology.
Sensors,
23(6), 2918-2918.
Abstract:
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g. laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multiple RS datasets to overcome limitations and produce comparatively detailed outcomes. However, there are still knowledge gaps in examining the effectiveness of these RS approaches in enhancing the detection of archaeological remains/areas. Thus, this review paper is likely to deliver valuable comprehension for archaeological studies to fill knowledge gaps and further advance exploration of archaeological areas/features using RS along with DL approaches.
Abstract.
Kadhim I, Abed FM (2021). The Potential of LiDAR and UAV-Photogrammetric Data Analysis to Interpret Archaeological Sites: a Case Study of Chun Castle in South-West England.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,
10(1).
Author URL.
Kadhim I, Abed FM (2021). The Potential of LiDAR and UAV-Photogrammetric Data Analysis to Interpret Archaeological Sites: a Case Study of Chun Castle in South-West England (vol 10, 41, 2021).
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,
10(8).
Author URL.
Publications by year
In Press
Kadhim I, Abed FM, DeSilvey C (In Press). Combining remote sensing approaches for detecting marks of archaeological and demolished constructions in Cahokia’s Grand Plaza, South-Western Illinois. Remote Sensing
2023
Kadhim I, Abed FM (2023). A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology.
Sensors,
23(6), 2918-2918.
Abstract:
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g. laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multiple RS datasets to overcome limitations and produce comparatively detailed outcomes. However, there are still knowledge gaps in examining the effectiveness of these RS approaches in enhancing the detection of archaeological remains/areas. Thus, this review paper is likely to deliver valuable comprehension for archaeological studies to fill knowledge gaps and further advance exploration of archaeological areas/features using RS along with DL approaches.
Abstract.
2021
Kadhim I, Abed FM (2021). The Potential of LiDAR and UAV-Photogrammetric Data Analysis to Interpret Archaeological Sites: a Case Study of Chun Castle in South-West England.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,
10(1).
Author URL.
Kadhim I, Abed FM (2021). The Potential of LiDAR and UAV-Photogrammetric Data Analysis to Interpret Archaeological Sites: a Case Study of Chun Castle in South-West England (vol 10, 41, 2021).
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,
10(8).
Author URL.
Israa_Kadhim Details from cache as at 2023-03-29 15:40:52
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