A New Approach to Liquefaction Potential Mapping using Satellite Remote Sensing and Support Vector Machine Algorithm. - Thomas Oommen; Laurie G. Baise (IGARSS (3), 2008)

Model Development and Validation for Intelligent Data Collection for Lateral Spread Displacements. - Thomas Oommen; Laurie G. Baise (J. Comput. Civ. Eng., 2010)

Post-Eruption Deformation Processes Measured Using ALOS-1 and UAVSAR InSAR at Pacaya Volcano, Guatemala. - Lauren N. Schaefer; Zhong Lu; Thomas Oommen (Remote. Sens., 2016)

Monitoring and modeling tailings impoundment settlement near Great Salt Lake (UTAH) using multi-platform time-series InSAR observations. - Xie Hu; Zhong Lu; Thomas Oommen; Teng Wang; Jinwoo Kim 004 (IGARSS, 2017)

Effect of Label Noise on the Machine-Learned Classification of Earthquake Damage. - Jared Frank; Umaa Rebbapragada; James Bialas; Thomas Oommen; Timothy C. Havens (Remote. Sens., 2017)

Utilizing satellite radar remote sensing for burn severity estimation. - Priscilla Addison; Thomas Oommen (Int. J. Appl. Earth Obs. Geoinformation, 2018)

A comparative analysis of pixel- and object-based detection of landslides from very high-resolution images. - Ren N. Keyport; Thomas Oommen; Tapas Ranjan Martha; K. S. Sajinkumar; John S. Gierke (Int. J. Appl. Earth Obs. Geoinformation, 2018)

Optimal segmentation of high spatial resolution images for the classification of buildings using random forests. - James Bialas; Thomas Oommen; Timothy C. Havens (Int. J. Appl. Earth Obs. Geoinformation, 2019)

Evaluation of Photogrammetry and Inclusion of Control Points: Significance for Infrastructure Monitoring. - Renee C. Oats; Rüdiger Escobar-Wolf; Thomas Oommen (Data, 2019)

Evidence of Instability in Previously-Mapped Landslides as Measured Using GPS, Optical, and SAR Data between 2007 and 2017: A Case Study in the Portuguese Bend Landslide Complex, California. - El Hachemi Bouali; Thomas Oommen; Rüdiger Escobar-Wolf (Remote. Sens., 2019)

Automated lithological mapping by integrating spectral enhancement techniques and machine learning algorithms using AVIRIS-NG hyperspectral data in Gold-bearing granite-greenstone rocks in Hutti, India. - Chandan Kumar; Snehamoy Chatterjee; Thomas Oommen; Arindam Guha (Int. J. Appl. Earth Obs. Geoinformation, 2020)

Utilizing Hyperspectral Remote Sensing for Soil Gradation. - Jordan Ewing; Thomas Oommen; Paramsothy Jayakumar; Russell Alger (Remote. Sens., 2020)

Characterizing Soil Stiffness Using Thermal Remote Sensing and Machine Learning. - Jordan Ewing; Thomas Oommen; Paramsothy Jayakumar; Russell Alger (Remote. Sens., 2021)

GAF-NAU: Gramian Angular Field encoded Neighborhood Attention U-Net for Pixel-Wise Hyperspectral Image Classification. - Paheding Sidike; Abel A. Reyes; Anush Kasaragod; Thomas Oommen (CVPR Workshops, 2022)

C-PLES: Contextual Progressive Layer Expansion with Self-attention for Multi-class Landslide Segmentation on Mars using Multimodal Satellite Imagery. - Abel A. Reyes; Sidike Paheding; A. Rajaneesh; K. S. Sajinkumar; Thomas Oommen (CVPR Workshops, 2023)

Individual Fairness Under Uncertainty. - Wenbin Zhang 002; Zichong Wang; Juyong Kim 002; Cheng Cheng 001; Thomas Oommen; Pradeep Ravikumar; Jeremy C. Weiss (ECAI, 2023)

Terrain Characterization via Machine vs. Deep Learning Using Remote Sensing. - Jordan Ewing; Thomas Oommen; Jobin Thomas; Anush Kasaragod; Richard Dobson; Colin N. Brooks; Paramsothy Jayakumar; Michael Cole; Tulga Ersal (Sensors, 2023)

Multi-Sensor and Multi-Scale Remote Sensing Approach for Assessing Slope Instability along Transportation Corridors Using Satellites and Uncrewed Aircraft Systems. - Marta Zocchi; Anush Kumar Kasaragod; Abby Jenkins; Chris Cook; Richard Dobson; Thomas Oommen; Dana Van Huis; Beau Taylor; Colin N. Brooks; Roberta Marini; Francesco Troiani; Paolo Mazzanti (Remote. Sens., 2023)

MarsLS-Net: Martian Landslides Segmentation Network and Benchmark Dataset. - Sidike Paheding; Abel A. Reyes; A. Rajaneesh; K. S. Sajinkumar; Thomas Oommen (WACV, 2024)

PyLandslide: A Python tool for landslide susceptibility mapping and uncertainty analysis. - Mohammed Basheer; Thomas Oommen (Environ. Model. Softw., 2024)

Suitability of the height above nearest drainage (HAND) model for flood inundation mapping in data-scarce regions: a comparative analysis with hydrodynamic models. - Navin Tony Thalakkottukara; Jobin Thomas; Melanie Kueber Watkins; Benjamin C. Holland; Thomas Oommen; Himanshu Grover (Earth Sci. Informatics, 2024)

Automated Flood Prediction along Railway Tracks Using Remotely Sensed Data and Traditional Flood Models. - Abdul Rashid Zakaria; Thomas Oommen; Pasi Lautala (Remote. Sens., 2024)