Big data in natural disaster management: a review

M Yu, C Yang, Y Li - Geosciences, 2018 - mdpi.com
Undoubtedly, the age of big data has opened new options for natural disaster management,
primarily because of the varied possibilities it provides in visualizing, analyzing, and …

Big Earth data analytics: A survey

C Yang, M Yu, Y Li, F Hu, Y Jiang, Q Liu, D Sha… - Big Earth …, 2019 - Taylor & Francis
Big Earth data are produced from satellite observations, Internet-of-Things, model
simulations, and other sources. The data embed unprecedented insights and spatiotemporal …

[HTML][HTML] Damage-augmented digital twins towards the automated inspection of buildings

BG Pantoja-Rosero, R Achanta, K Beyer - Automation in Construction, 2023 - Elsevier
Current procedures for the rapid inspection of buildings and infrastructure are subjective,
time-consuming, and cumbersome to document, necessitating new technologies to …

Tourism and natural disaster management process: perception of tourism stakeholders in the case of Kumamoto earthquake in Japan

CS Chan, K Nozu, TOL Cheung - Current Issues in Tourism, 2020 - Taylor & Francis
Tourism has a reciprocal relationship with natural disasters. The study aims to investigate
the role of tourism as a strategy in the disaster phases based on (2001. Towards a …

[HTML][HTML] Detection of the pine wilt disease tree candidates for drone remote sensing using artificial intelligence techniques

M Syifa, SJ Park, CW Lee - Engineering, 2020 - Elsevier
Pine wilt disease (PWD) has recently caused substantial pine tree losses in Republic of
Korea. PWD is considered a severe problem due to the importance of pine trees to Korean …

[HTML][HTML] 轻小型无人机测绘遥感系统研究进展

张继贤, 刘飞, 王坚 - 遥感学报, 2021 - ygxb.ac.cn
地球空间信息是人工智能, 大数据时代的重要数据基础, 轻小型无人机测绘遥感技术作为中国
当前和未来获取厘米级分辨率, 实时响应遥感数据的主要手段, 必将发挥更加重要的作用 …

Transferability of convolutional neural network models for identifying damaged buildings due to earthquake

W Yang, X Zhang, P Luo - Remote Sensing, 2021 - mdpi.com
The collapse of buildings caused by earthquakes can lead to a large loss of life and
property. Rapid assessment of building damage with remote sensing image data can …

Building-damage detection method based on machine learning utilizing aerial photographs of the Kumamoto earthquake

S Naito, H Tomozawa, Y Mori, T Nagata… - Earthquake …, 2020 - journals.sagepub.com
This article presents a method for detecting damaged buildings in the event of an
earthquake using machine learning models and aerial photographs. We initially created …

An artificial intelligence application for post-earthquake damage mapping in Palu, central Sulawesi, Indonesia

M Syifa, PR Kadavi, CW Lee - Sensors, 2019 - mdpi.com
A Mw 7.4 earthquake hit Donggala County, Central Sulawesi Province, Indonesia, on 28
September 2018, triggering a tsunami and liquefaction in Palu City and Donggala. Around …

Geoscientists in the sky: Unmanned aerial vehicles responding to geohazards

R Antoine, T Lopez, M Tanguy, C Lissak, L Gailler… - Surveys in …, 2020 - Springer
This article presents a review of the use of unmanned aerial vehicles (UAVs) in the context
of geohazards. The pluri-disciplinary role of UAVs is outlined in numerous studies …