A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters

By Karen E. Joyce, S. Belliss, S. Samsonov, S. McNeill, P. Glassey. 2009

521 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Management, Monitoring, Policy and Law, Media Technology

View Paper: https://www.semanticscholar.org/paper/ac8e55f9c237e42ae3f5d351cf0edde6c31310ed

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Jie Shan
2. Laigen Dong

In Management, Monitoring, Policy and Law

1. Ataollah Shirzadi
2. Baharin bin Ahmad
3. Himan Shahabi
4. Marten Geertsema
5. Khabat Khosravi
6. John J. Clague
7. Omid Rahmati
8. Ebrahim Omidvar

In Media Technology

1. Xiaoyu Chen
2. Rongjun Qin
3. H. Yao
4. Jie Shan
5. Thomas Skjødeberg Toftegaard
6. Jacob Hoxbroe Jeppesen
7. Laigen Dong
8. Rune Hylsberg Jacobsen

Citations in the corpus

• On the Use of Unmanned Aerial Systems for Environmental Monitoring (2018, unknown): “In fact, flood observation is a considerable challenge for space-borne passive imagery, mostly due to the presence of dense cloud cover, closed vegetation canopies, and the satellite revisit time and viewing angle [133,148].”
• Unmanned Aerial Vehicle for Remote Sensing Applications - A Review (2019, methodology): “RS is seen as an important tool for risk assessment and rescue operations [169,170].”
• A cloud detection algorithm for satellite imagery based on deep learning (2019, background): “…particular, automated classification is crucial in many use cases, such as harvest yield estimation (Prasad et al., 2006; Ferencz et al., 2004), change detection (Verbesselt et al., 2010; Sakamoto et al., 2005), and disaster management (Voigt et al., 2007; Tralli et al., 2005; Joyce et al., 2009).”
• A comprehensive review of earthquake-induced building damage detection with remote sensing techniques (2013, methodology): “For instance, thermal infrared imagery can be used for earthquake prediction (Tronin et al., 2002; Ouzounov et al., 2006; Joyce et al., 2009); InSAR (Interferometric Synthetic Aperture Radar) for measuring Earth’s surface deformation (Gabriel et al., 1989; Massonnet et al., 1993); optical, SAR,…”
• Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier (2020, background): “SAR can collect data during day or night, either independently or together with other remote sensors [14].”