Faculty of Business Administration, Shanxi University of Finance and Economics, Taiyuan, China.
Shanxi University of Finance and Economics Huashang College, Taiyuan, China.
Big Data. 2022 Jun;10(3):246-261. doi: 10.1089/big.2020.0411.
Besides many impacts, climate change and the rise of harsh weather have a huge hit that jeopardizes agricultural sectors. Natural catastrophes, including flooding and wildfires, are the sources of significant declines in crop production. National governments make an essential commitment, and foreign institutions work together to mitigate disasters' resilience vulnerability. These hazards have pushed catastrophe management to the forefront and made it an expanding scholarly area of study. The remarkable growth of information technology has motivated the scientific group to integrate this technology into emergency management. In this article, agricultural disaster risk management (ADRM) is offered to decide the status quo of the research on agriculture disaster management and the significance of big data. This article's primary objective is to provide technical metric analysis to analyze the body of research carried out in the past decade on different forms of disasters and the use of significant volumes. For the data assessment, the annual growth of publication outcomes, the corresponding categories of topics, and the productivity study specifications was determined. The flux of raw and analytical data from comprehensive data is so established that another effect is heavily affected in the final performance of forecasting. The assessment of ADRM proposed would have been based on data provided by the Department of Indian Meteorology, and improvement is illustrated in incorporating the mechanism proposed in flood prediction long before the occurrence of floods.
除了许多影响外,气候变化和恶劣天气的增加也对农业部门造成了巨大的冲击。自然灾害,包括洪水和野火,是导致作物产量大幅下降的主要原因。各国政府做出了重要承诺,外国机构也共同努力减轻灾害的脆弱性。这些灾害将灾害管理推向了前沿,成为一个不断扩大的学术研究领域。信息技术的显著增长促使科学界将这项技术融入到应急管理中。本文提出了农业灾害风险管理(ADRM),以确定农业灾害管理研究的现状和大数据的重要性。本文的主要目的是提供技术指标分析,以分析过去十年中针对不同形式灾害和大数据使用的研究成果。为了进行数据评估,确定了出版物成果的年度增长率、相应的主题类别以及生产力研究规范。从综合数据中建立原始和分析数据的通量,以便在最终的预测性能中受到另一个影响的严重影响。所提出的 ADRM 评估将基于印度气象局提供的数据,并且在洪水发生之前就已经在洪水预测中加入了所提出的机制,从而得到了改进。