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Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research : For Sustainable Development Goals / edited by Gaurav Tripathi, Achala Shakya, Shruti Kanga, Suraj Kumar Singh, Praveen Kumar Rai.
Author
Tripathi, Gaurav
[Browse]
Format
Book
Language
English
Εdition
1st ed. 2024.
Published/Created
Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Description
1 online resource (339 pages)
Details
Subject(s)
Climatology
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Big data
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Artificial intelligence
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Quantitative research
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Sustainability
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Related name
Shakya, Achala
[Browse]
Kanga, Shruti
[Browse]
Singh, Suraj Kumar
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Rai, Praveen Kumar
[Browse]
Series
Advances in Geographical and Environmental Sciences,
[More in this series]
Advances in Geographical and Environmental Sciences, 2198-3550
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Summary note
This book explores the potential of big data, artificial intelligence (AI), and data analytics to address climate change and achieve the Sustainable Development Goals (SDGs). Furthermore, the book covers a wide range of related topics, including climate change data sources, big data analytics techniques, remote sensing, renewable energy, open data, public–private partnerships, ethical and legal issues, and case studies of successful applications. The book also discusses the challenges and opportunities presented by these technologies and provides insights into future research directions. In order to address climate change and achieve the SDGs, it is crucial to understand the complex interplay between climate and environmental factors. The use of big data, AI, and data analytics can play a vital role in this effort by providing the means to collect, process, and analyze vast amounts of environmental data. This book is an essential resource for researchers, policymakers, and practitioners interested in leveraging these technologies to tackle the pressing challenge of climate change and achieve the SDGs.
Contents
Experimental analysis of Precipitation Forecasting Using Machine Learning and Distributed Machine Learning Approach
Analysis of Inherent Memory in Hydroclimatic Time Series: Implications for Statistical Tests and Long-Term Data Generation
Intelligent Solutions for Flood Management: Integrating Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning based building solutions: Pathways to ensure occupants comfort and energy efficiency with climate change
Deep Learning models for fine-scale Climate Change prediction: enhancing spatial and temporal resolution using AI
Exploring streamflow variation in the Subarnarekha River basin, Jharkhand, India
Geoinformatics Based Land Degradation Susceptibility Analysis and Sustainability of Palghar Sea Coastal Areas
Climate Change and Maritime Security in the Indo-Pacific Region: A Strategic Approach
Climate Change and Renewable Energy
Sustainable Development Goals and Indian Himalayan Region
Climate Change and Energy Aspects
Mustard Yield forecast using Radiation use efficiency method
Public Private Partnership for Climate Change Research
Groundwater and Sustainable Development Goals: Water Table Characteristics in Varanasi City
Approach of Hydro geomorphological Mapping for Groundwater Resource Management in Mirzapur District, Uttar Pradesh
Soil erosion assessment of Rohru C.D. Block of Himachal Pradesh using Geospatial Tools
Impact of Sarangkheda Dam construction on the downstream reach of Tapi River, Nandurbar District, Maharashtra.
Show 14 more Contents items
ISBN
981-9716-85-3
Doi
10.1007/978-981-97-1685-2
Statement on responsible collection description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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