Remote sensing and Earth observation data in natural hazard and risk studies
Remote sensing and Earth observation data in natural hazard and risk studies
Editor(s): Paolo Tarolli, Mahdi Motagh, Kuo-Jen Chang, Antonio Montuori, and Michelle Parks
Remote sensing and Earth observations (EOs) are used increasingly in different phases of risk management and in development cooperation, due to the challenges posed by contemporary issues such as climate change, population pressure, and increasingly complex social interactions. EO-based applications have a number of advantages over traditional fieldwork expeditions including safety, the provision a synoptic view of the region of interest, the availability of data extending back several years, and, in many cases, cost savings. Fortunately, the advent of new, more powerful sensors and more finely tuned detection algorithms provides the opportunity to image, assess, and quantify natural hazards, their consequences, and vulnerable regions more comprehensively than ever before.

For these reasons, civil protection organizations, development agencies, and space agencies now permanently use applications of EO data to risk management. During the preparedness and prevention phase, EO has proven invaluable, especially in data-scarce environments, for hazard, vulnerability, and risk mapping. EO data are applicable during both the forecasting and early emergency response phases, thanks to the possibility of rapid mapping and interpretation. EO data are also increasingly being used for planning operations during the recovery phase. This special issue is dedicated to multidisciplinary contributions in particular focused on the demonstration of the benefit of the use of EO for risk management. The research presented might focus on

  • addressed value of EO data in risk/hazard forecasting models (observation of possible precursory events and evaluation of potential predictive capabilities);
  • innovative applications of EO data for rapid mapping;
  • innovative applications of EO data for hazard, vulnerability, and risk mapping;
  • innovative applications of EO data for the post-disaster recovery phase;
  • innovative applications in support of disaster risk reduction strategies (e.g. landscape planning);
  • development of tools and platforms for assessment and validation of hazard/risk models.
The use of different types of remote sensing observations (e.g. thermal, visual, radar, laser, and/or the fusion of these) might be considered, with an evaluation of their respective pros and cons. Evaluation of current sensors, data capabilities, and algorithms will be welcomed, as will suggestions for future sensor considerations, algorithm developments, and opportunities for emergency management agency buy-in. Authors are discouraged from submitting solely engineering papers that do not also deal with remote applications for natural hazard studies.

A note: in 2017, a special issue on the use of remotely piloted aircraft systems (RPAS) in monitoring applications and management of natural hazards was published in NHESS (https://www.nat-hazards-earth-syst-sci.net/special_issue859.html). The authors should be aware that this is not a special issue again on RPAS; the number of papers on this technique will be limited while focusing more on other types of platforms.

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09 Mar 2022
Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine
Alexander L. Handwerger, Mong-Han Huang, Shannan Y. Jones, Pukar Amatya, Hannah R. Kerner, and Dalia B. Kirschbaum
Nat. Hazards Earth Syst. Sci., 22, 753–773, https://doi.org/10.5194/nhess-22-753-2022,https://doi.org/10.5194/nhess-22-753-2022, 2022
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22 Nov 2021
Multiscale analysis of surface roughness for the improvement of natural hazard modelling
Natalie Brožová, Tommaso Baggio, Vincenzo D'Agostino, Yves Bühler, and Peter Bebi
Nat. Hazards Earth Syst. Sci., 21, 3539–3562, https://doi.org/10.5194/nhess-21-3539-2021,https://doi.org/10.5194/nhess-21-3539-2021, 2021
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13 Sep 2021
Multi-decadal geomorphic changes of a low-angle valley glacier in the East Kunlun Mountains: remote sensing observations and detachment hazard assessment
Xiaowen Wang, Lin Liu, Yan Hu, Tonghua Wu, Lin Zhao, Qiao Liu, Rui Zhang, Bo Zhang, and Guoxiang Liu
Nat. Hazards Earth Syst. Sci., 21, 2791–2810, https://doi.org/10.5194/nhess-21-2791-2021,https://doi.org/10.5194/nhess-21-2791-2021, 2021
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08 Sep 2021
Timely prediction potential of landslide early warning systems with multispectral remote sensing: a conceptual approach tested in the Sattelkar, Austria
Doris Hermle, Markus Keuschnig, Ingo Hartmeyer, Robert Delleske, and Michael Krautblatter
Nat. Hazards Earth Syst. Sci., 21, 2753–2772, https://doi.org/10.5194/nhess-21-2753-2021,https://doi.org/10.5194/nhess-21-2753-2021, 2021
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28 Sep 2021
UAV survey method to monitor and analyze geological hazards: the case study of the mud volcano of Villaggio Santa Barbara, Caltanissetta (Sicily)
Fabio Brighenti, Francesco Carnemolla, Danilo Messina, and Giorgio De Guidi
Nat. Hazards Earth Syst. Sci., 21, 2881–2898, https://doi.org/10.5194/nhess-21-2881-2021,https://doi.org/10.5194/nhess-21-2881-2021, 2021
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31 Jan 2022
Index establishment and capability evaluation of space–air–ground remote sensing cooperation in geohazard emergency response
Yahong Liu and Jin Zhang
Nat. Hazards Earth Syst. Sci., 22, 227–244, https://doi.org/10.5194/nhess-22-227-2022,https://doi.org/10.5194/nhess-22-227-2022, 2022
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15 Feb 2021
Leveraging time series analysis of radar coherence and normalized difference vegetation index ratios to characterize pre-failure activity of the Mud Creek landslide, California
Mylène Jacquemart and Kristy Tiampo
Nat. Hazards Earth Syst. Sci., 21, 629–642, https://doi.org/10.5194/nhess-21-629-2021,https://doi.org/10.5194/nhess-21-629-2021, 2021
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11 Jan 2021
Assessing the accuracy of remotely sensed fire datasets across the southwestern Mediterranean Basin
Luiz Felipe Galizia, Thomas Curt, Renaud Barbero, and Marcos Rodrigues
Nat. Hazards Earth Syst. Sci., 21, 73–86, https://doi.org/10.5194/nhess-21-73-2021,https://doi.org/10.5194/nhess-21-73-2021, 2021
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14 Dec 2020
Assessments of land subsidence along the Rizhao–Lankao high-speed railway at Heze, China, between 2015 and 2019 with Sentinel-1 data
Chuanguang Zhu, Wenhao Wu, Mahdi Motagh, Liya Zhang, Zongli Jiang, and Sichun Long
Nat. Hazards Earth Syst. Sci., 20, 3399–3411, https://doi.org/10.5194/nhess-20-3399-2020,https://doi.org/10.5194/nhess-20-3399-2020, 2020
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27 Nov 2020
Detecting precursors of an imminent landslide along the Jinsha River
Wentao Yang, Lianyou Liu, and Peijun Shi
Nat. Hazards Earth Syst. Sci., 20, 3215–3224, https://doi.org/10.5194/nhess-20-3215-2020,https://doi.org/10.5194/nhess-20-3215-2020, 2020
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12 May 2021
HazMapper: a global open-source natural hazard mapping application in Google Earth Engine
Corey M. Scheip and Karl W. Wegmann
Nat. Hazards Earth Syst. Sci., 21, 1495–1511, https://doi.org/10.5194/nhess-21-1495-2021,https://doi.org/10.5194/nhess-21-1495-2021, 2021
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25 May 2021
Assimilation of Himawari-8 imager radiance data with the WRF-3DVAR system for the prediction of Typhoon Soudelor
Feifei Shen, Aiqing Shu, Hong Li, Dongmei Xu, and Jinzhong Min
Nat. Hazards Earth Syst. Sci., 21, 1569–1582, https://doi.org/10.5194/nhess-21-1569-2021,https://doi.org/10.5194/nhess-21-1569-2021, 2021
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09 Nov 2021
Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region
Paulo Victor N. Araújo, Venerando E. Amaro, Leonlene S. Aguiar, Caio C. Lima, and Alexandre B. Lopes
Nat. Hazards Earth Syst. Sci., 21, 3353–3366, https://doi.org/10.5194/nhess-21-3353-2021,https://doi.org/10.5194/nhess-21-3353-2021, 2021
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15 Mar 2021
Evolution of surface deformation related to salt-extraction-caused sinkholes in Solotvyno (Ukraine) revealed by Sentinel-1 radar interferometry
Eszter Szűcs, Sándor Gönczy, István Bozsó, László Bányai, Alexandru Szakacs, Csilla Szárnya, and Viktor Wesztergom
Nat. Hazards Earth Syst. Sci., 21, 977–993, https://doi.org/10.5194/nhess-21-977-2021,https://doi.org/10.5194/nhess-21-977-2021, 2021
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