86 citations as recorded by crossref.

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44. Main Issues for Preserving Mediterranean Soil Resources From Water Erosion Under Global Change D. Raclot et al. https://doi.org/10.1002/ldr.2774
45. An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China G. Su et al. https://doi.org/10.3390/rs70302543
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48. Cost estimation for the monitoring instrumentation of landslide early warning systems M. Sapena et al. https://doi.org/10.5194/nhess-23-3913-2023
49. A transferable remote sensing approach to classify building structural types for seismic risk analyses: the case of Val d'Agri area (Italy) M. Liuzzi et al. https://doi.org/10.1007/s10518-019-00648-7
50. A systematic review of tropical cyclone disaster management research using remote sensing and spatial analysis M. Hoque et al. https://doi.org/10.1016/j.ocecoaman.2017.07.001
51. Automatic identification of buildings vulnerable to debris flows in Sichuan Province, China, by GIS analysis and Deep Encoding Network methods L. Wei et al. https://doi.org/10.1111/jfr3.12830
52. Application of Risk Analysis in the Screening of Flood Disaster Hot Spots and Adaptation Strategies E. Huang et al. https://doi.org/10.3390/land11010036
53. Assessing integrated agricultural livelihood vulnerability to climate change in the coastal region of West Bengal: Implication for spatial adaptation planning S. Das et al. https://doi.org/10.1016/j.rsma.2022.102748
54. From tsunami risk assessment to disaster risk reduction – the case of Oman I. Aguirre-Ayerbe et al. https://doi.org/10.5194/nhess-18-2241-2018
55. Vulnerability Assessment and Differentiated Regulation of Rural Settlement Systems in the Alpine Canyon Area of Western Sichuan Under Geological Hazard Coercion: Taking Maoxian County of Sichuan as an Example X. Xi et al. https://doi.org/10.3390/su17198629
56. A method for modeling the effects of climate and land use changes on erosion and sustainability of soil in a Mediterranean watershed (Languedoc, France) J. Paroissien et al. https://doi.org/10.1016/j.jenvman.2014.10.034
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58. Open Data and Machine Learning to Model the Occurrence of Fire in the Ecoregion of “Llanos Colombo–Venezolanos” J. Barreto & D. Armenteras https://doi.org/10.3390/rs12233921
59. Comparing the Accuracy of sUAS Navigation, Image Co-Registration and CNN-Based Damage Detection between Traditional and Repeat Station Imaging A. Loerch et al. https://doi.org/10.3390/geosciences12110401
60. Aproximación Metodológica para la Evaluación del Riesgo de Salinización de Suelos en Zonas Bajo Riesgo A. Echeverri-Sánchez et al. https://doi.org/10.25054/01247905.1238
61. Benefits of global earth observation missions for disaggregation of exposure data and earthquake loss modeling: evidence from Santiago de Chile C. Geiß et al. https://doi.org/10.1007/s11069-022-05672-6
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63. Social, Economic, Environmental, and Physical Vulnerability Assessment: An Index-Based Gender Analysis of Flood Prone Areas of Koshi River Basin in Nepal U. Guragain & P. Doneys https://doi.org/10.3390/su141610423
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65. Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa T. Mushore et al. https://doi.org/10.3390/rs15235461
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70. Detecting crisis events from unstructured text data using signal words as crisis determinants H. Senaratne et al. https://doi.org/10.1080/17538947.2023.2278714
71. The vulnerability of Antandroy women to droughts in Ambovombe Androy (Madagascar) S. Randriamparany & T. Randrianalijaona https://doi.org/10.1016/j.ijdrr.2022.102821
72. Probabilistic Tsunami Hazard Assessment in Meso and Macro Tidal Areas. Application to the Cádiz Bay, Spain M. González et al. https://doi.org/10.3389/feart.2021.591383
73. Flood Hazard and Flood Risk Assessment Using a Time Series of Satellite Images: A Case Study in Namibia S. Skakun et al. https://doi.org/10.1111/risa.12156
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81. Community participation in flood mapping in the Amazon through interdisciplinary methods M. de Andrade & C. Szlafsztein https://doi.org/10.1007/s11069-015-1782-y
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