Showing 2,441 - 2,460 results of 2,698 for search '"disasters"', query time: 0.06s Refine Results
  1. 2441

    CBGS-YOLO: A Lightweight Network for Detecting Small Targets in Remote Sensing Images Based on a Double Attention Mechanism by Zhenyuan Wu, Di Wu, Ning Li, Wanru Chen, Jie Yuan, Xiangyue Yu, Yongqiang Guo

    Published 2024-12-01
    “…The significance of detecting small targets in remote sensing images lies in enhancing the ability to identify small and elusive targets and the detection accuracy against complex backgrounds, holding significant application value in military reconnaissance, environmental monitoring, and disaster early-warning systems. Firstly, the minuteness of certain targets in relation to the entire image in which they occur, particularly when the camera is situated at a higher altitude, renders them difficult to detect. …”
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    Evaluation of Shannon Entropy and Weights of Evidence Models in Landslide Susceptibility Mapping for the Pithoragarh District of Uttarakhand State, India by Nguyen Duc Dam, Mahdis Amiri, Nadhir Al-Ansari, Indra Prakash, Hiep Van Le, Hanh Bich Thi Nguyen, Binh Thai Pham

    Published 2022-01-01
    “…Landslide susceptibility mapping is considered a useful tool for planning, disaster management, and natural hazard mitigation of a region. …”
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  3. 2443

    LoRa Resource Allocation Algorithm for Higher Data Rates by Hossein Keshmiri, Gazi M. E. Rahman, Khan A. Wahid

    Published 2025-01-01
    “…However, its inherent low data rate poses a challenge for applications that require higher throughput, such as video surveillance and disaster monitoring, where large image files must be transmitted over long distances in areas with limited communication infrastructure. …”
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  4. 2444

    Weather identification using models based on deep learning by Afroza Nahar, Rifat Al Mamun Rudro, Bakhtiar Atiq Faisal, Md. Faruk Abdullah Al Sohan, Laveet Kumar

    Published 2025-01-01
    “…Researchers are working on precise weather forecasting to improve our preparedness, enabling fast response to any disaster. Among other techniques, deep learning is a prudent method to predict weather forecasts since it can automatically learn and train from a vast amount of data to generate and portray accurate features of an incident. …”
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  5. 2445

    Integrating a multi-dimensional deep convolutional neural network with optimized sample selection for landslide susceptibility assessment by Yueyue Wang, Xueling Wu, Kun Zhou, Guo Lin, Bo Peng, Zhice Fang

    Published 2025-01-01
    “…In this work, the negative samples determined by RFR-CFM and the Information Quality Model (IQM) were combined with historical disaster points to form a total modeling sample, and modeled at different ratios. …”
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  6. 2446

    Time-Series Change Detection Using KOMPSAT-5 Data with Statistical Homogeneous Pixel Selection Algorithm by Mirza Muhammad Waqar, Heein Yang, Rahmi Sukmawati, Sung-Ho Chae, Kwan-Young Oh

    Published 2025-01-01
    “…The methodology effectively identified urban changes, highlighting the potential of KOMPSAT-5 data for post-disaster monitoring and urban change detection. Future improvements are suggested, focusing on the stability of InSAR orbits to further enhance detection precision. …”
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  7. 2447

    Rapid Landslide Detection Following an Extreme Rainfall Event Using Remote Sensing Indices, Synthetic Aperture Radar Imagery, and Probabilistic Methods by Aikaterini-Alexandra Chrysafi, Paraskevas Tsangaratos, Ioanna Ilia, Wei Chen

    Published 2024-12-01
    “…This rapid detection technique provides essential data for emergency services and disaster management teams, enabling them to prioritize areas for immediate response and recovery efforts.…”
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  8. 2448

    Forecasting Precipitation Using a Markov Chain Model in the Coastal Region in Bangladesh by Al Mamun Pranto, Usama Ibn Aziz, Lipon Chandra Das, Sanjib Ghosh and Anisul Islam

    Published 2024-12-01
    “…These results underscore the importance of understanding the temporal evolution of precipitation patterns, which is crucial for effective water resource management, agricultural planning, and disaster preparedness in the region. The study highlights the dynamic nature of rainfall patterns and the necessity for adaptive strategies to mitigate the impacts of climate variability. …”
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    A classification scheme of active faults in engineering. by Qingyun Zhou, Suge He, Zhenyu Zou

    Published 2025-01-01
    “…Fault displacement hazard, along with ground shaking hazard and earthquake-induced geohazard, are the primary forms of disaster in major earthquakes. Buildings located on areas of strong seismic surface displacement are likely to be damaged if anti-displacement design is not carried out. …”
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    Analysis of Temporal and Spatial Evolution Characteristics of Rainfall in Dongguan in the Past 30 Years by WANG Qiuliang, SUN Xiang, GAN Dufen, MEI Xinpei, CHENG Jie, ZAN Xiongfeng

    Published 2022-01-01
    “…Dongguan is an important city in the Guangdong-Hong Kong-Macao Greater Bay Area,which is a major contributor to the economic development of this area.However,its urban planning,rational allocation of water resources,flood prevention and disaster reduction are severely affected by torrential rain and floods,and thus its high-quality economic development is seriously hindered.Therefore,by using the 32-year daily rainfall data of 30 hydrological stations in Dongguan,this paper adopts methods such as GIS,the Mann-Kendall test,moving average,and cumulative anomaly to discuss the temporal and spatial distribution of rainfall in Dongguan.The results reveal that in the past 32 years,the temporal and spatial distribution of annual rainfall has gradually increased from west to east with a significant rising trend over time.During the flood season,the rainfall increases sequentially from west to east and gradually decreases from the central part to west,and from the central part to east,it drops before it rises.Rainfall in the flood season accounts for about 60%~95% of the annual total.The rainfall in the non-flood season is prominent in the central part,with great differences between east and west,namely that the rainfall in the central part tends to decrease gradually to both sides,and the southwestern part registers the smallest.The center of the maximum rainfall in the four seasons moves from the central part to the northeast,east,and central,and the southwest still records the minimum rainfall.The monthly average rainfall generally shows an increasing trend from west to east:Many years of data indicates that the average rainfall in June is the largest,accounting for 18.58% of the rainfall all year,while December sees the smallest,accounting for 1.88% of the yearly total.The research results can provide reference and support for the later development of Dongguan.…”
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  14. 2454

    Evolution of Dry/Wet Climate in Xichang from 1961 to 2016 by XIAO Xiwen, ZHANG Yunlu, LIU Chunhong, WANG Yuefeng

    Published 2022-01-01
    “…Regional climate analysis can optimize and supplement global climate research,and it is of vital significance for predicting regional climate changes and extreme weather.Based on the daily temperature and precipitation data from 1961 to 2016 in Xichang city,this paper systematically reveals the characteristics of temperature,precipitation,and dry and wet climate changes at annual and inter-annual scales by using the cumulative anomaly method,nonparametric trend analysis of time series (innovative trend analysis (ITA) method and ITA-change boxes (ITA-CB) method) and standardized precipitation evaporation index (SPEI).The results show that:① The distribution characteristics of annual temperature and precipitation in Xichang are similar,with the maximum value of both appearing in July.Moreover,the minimum temperature and precipitation appear in January and February,respectively.The average inter-annual and inter-decadal temperatures increase obviously,and the average inter-decadal precipitation improves slowly.② For the past 56 years,Xichang has witnessed apparent dry and wet climate changes.SPEI has dropped in a fluctuating tendency.In addition,it is negatively correlated with temperature (p<0.05) but positively correlated with precipitation (p<0.01).As temperature increases significantly,the drought degree has become more and more serious since 2003,and the negative value of SPEI accounts for 78.6%.The proportion of drought to extreme drought has increased to 28.6% in 2010.③ The average annual precipitation increases in low-value regions but decreases in high-value regions.The average annual temperature rises both in low-value regions and high-value regions and basically maintains an increasing tendency in median regions.SPEI increases in low-value regions but decreases in median and high-value regions.The research results can provide a reference for Xichang in dealing with climate change and formulating disaster prevention and mitigation plans.…”
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