World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
10341
World Ranking
3837
National Ranking
79

Environmental Sciences

D-Index
55
Citations
10973
World Ranking
3856
National Ranking
100

Overview

Norman Kerle is affiliated with the University of Twente in the Netherlands. Their research spans multiple intersecting fields, primarily focusing on engineering, computer science, and environmental science. Within these disciplines, Kerle has contributed extensively to subfields such as computer vision and pattern recognition, aerospace engineering, environmental engineering, global and planetary change, and sociology and political science.

Kerle's scholarly output includes a range of publications emphasizing topics related to remote sensing, flood risk assessment, robotics, disaster management, and advanced neural network applications. Main themes featured in their work encompass:

  • Remote Sensing and LiDAR Applications
  • Flood Risk Assessment and Management
  • Robotics and Sensor-Based Localization
  • Disaster Management and Resilience
  • Advanced Neural Network Applications
  • Advanced Vision and Imaging
  • 3D Surveying and Cultural Heritage

Their recent papers illustrate a focus on disaster response and the use of unmanned aerial vehicles (UAVs) and remote sensing data. Notable papers include:

  • Accuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing, 2020, Geo-spatial Information Science
  • Agent-based modelling of post-disaster recovery with remote sensing data, 2021, International Journal of Disaster Risk Reduction
  • Post-Disaster Building Damage Detection from Earth Observation Imagery Using Unsupervised and Transferable Anomaly Detecting Generative Adversarial Networks, 2020, Remote Sensing
  • Post-Disaster Recovery Monitoring with Google Earth Engine, 2020, Applied Sciences
  • Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images, 2022, Remote Sensing

Kerle frequently collaborates with other researchers. Frequent co-authors include Francesco Nex, George Vosselman, Marc van den Homberg, Saman Ghaffarian, and Sofia Tilon. These collaborations indicate engagement with experts in related areas of geospatial analysis, remote sensing, and disaster risk management.

Their work is published in a variety of journals and conference proceedings, with multiple publications in venues such as:

  • International Journal of Disaster Risk Reduction
  • Remote Sensing
  • ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
  • Drones
  • The international archives of the photogrammetry, remote sensing and spatial information sciences

Best Publications

  • Object-oriented mapping of landslides using Random Forests

    André Stumpf;André Stumpf;Norman Kerle

  • Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods

    Tapas R. Martha;Tapas R. Martha;Norman Kerle;Victor Jetten;Cees J. van Westen

  • Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information

    Linda See;Peter Mooney;Giles Foody;Lucy Bastin

  • An ontology of slums for image - based classification

    Divyani Kohli;Richard Sliuzas;Norman Kerle;Alfred Stein

  • Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis

    T. R. Martha;N. Kerle;C. J. van Westen;V. Jetten

  • Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran

    Hamid Reza Pourghasemi;Norman Kerle

  • Object-Oriented Change Detection for Landslide Rapid Mapping

    Ping Lu;André Stumpf;Norman Kerle;Nicola Casagli

  • Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning

    Anand Vetrivel;Markus Gerke;Norman Kerle;Francesco Nex

  • Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation

    Unknown

  • UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    J. Fernandez Galarreta;N. Kerle;M. Gerke

  • Urban social vulnerability assessment with physical proxies and spatial metrics derived from air- and spaceborne imagery and GIS data

    Annemarie Ebert;Norman Kerle;Alfred Stein

  • Object-oriented analysis of multi-temporal panchromatic images for creation of historical landslide inventories

    T.R. Martha;N. Kerle;C.J. van Westen;V.G. Jetten

  • Image-based mapping of surface fissures for the investigation of landslide dynamics

    André Stumpf;André Stumpf;Jean-Philippe Malet;Norman Kerle;Uwe Niethammer

  • Landslide hazard and risk assessment using semi-automatically created landslide inventories

    Tapas R. Martha;Tapas R. Martha;Cees J. van Westen;Norman Kerle;Victor Jetten

  • Object-based gully feature extraction using high spatial resolution imagery

    Rajesh B.V. Shruthi;Norman Kerle;Victor Jetten

  • UAV-Based Structural Damage Mapping: A Review

    Norman Kerle;Francesco Nex;Markus Gerke;Diogo Duarte

  • Catastrophic precipitation‐triggered lahar at Casita volcano, Nicaragua: occurrence, bulking and transformation

    Kevin M. Scott;James W. Vallance;Norman Kerle;Jose Luis Macías

  • Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models

    Iswar Das;Iswar Das;Alfred Stein;Norman Kerle;Vinay K. Dadhwal

  • Object-oriented identification of forested landslides with derivatives of single pulse LiDAR data

    Miet Van Den Eeckhaut;Norman Kerle;Jean Poesen;Javier Hervás

  • Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images

    Anand Vetrivel;Markus Gerke;Norman Kerle;George Vosselman

  • Structural Building Damage Detection with Deep Learning: Assessment of a State-of-the-Art CNN in Operational Conditions

    Francesco Nex;Diogo Duarte;Fabio Giulio Tonolo;Norman Kerle

  • Volcano instability induced by strike-slip faulting

    A. M. F. Lagmay;B. van Wyk de Vries;N. Kerle;D. M. Pyle

  • Optimal region growing segmentation and its effect on classification accuracy

    Yan Gao;Jean Francois Mas;Norman Kerle;Jose Antonio Navarrete Pacheco

Frequent Co-Authors

Francesco Nex
Francesco Nex University of Twente
George Vosselman
George Vosselman University of Twente
Jean-Philippe Malet
Jean-Philippe Malet University of Strasbourg
Alfred Stein
Alfred Stein University of Twente
Victor Jetten
Victor Jetten University of Twente
C.J. van Westen
C.J. van Westen University of Twente
Sébastien Lefèvre
Sébastien Lefèvre Institut de Recherche en Informatique et Systèmes Aléatoires
Linda See
Linda See International Institute for Applied Systems Analysis
Giles M. Foody
Giles M. Foody University of Nottingham
Tatiana Filatova
Tatiana Filatova Delft University of Technology

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