Related Experiment Video
Updated: Sep 8, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Agricultural Disaster Risk Management and Capability Assessment Using Big Data Analytics
Caili Wang1, Yuwen Gao2, Asad Aziz3
1Faculty of Business Administration, Shanxi University of Finance and Economics, Taiyuan, China.
Abstract:
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.
More Related Videos
15:30A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
Published on: August 5, 2020
11:53Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Related Concept Videos
Applications of GIS: Disaster Management and Emergency Response
Responses to Drought and Flooding
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Manipulation and Analysis
What is Climate?
Steps in Outbreak Investigation