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020 _a9789819716852
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024 7 _a10.1007/978-981-97-1685-2
_2doi
050 4 _aQC851-999
072 7 _aRBP
_2bicssc
072 7 _aSCI042000
_2bisacsh
072 7 _aRBP
_2thema
245 1 0 _aBig Data, Artificial Intelligence, and Data Analytics in Climate Change Research
_h[electronic resource] :
_bFor Sustainable Development Goals /
_cedited by Gaurav Tripathi, Achala Shakya, Shruti Kanga, Suraj Kumar Singh, Praveen Kumar Rai.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aVIII, 339 p. 127 illus., 117 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aAdvances in Geographical and Environmental Sciences,
_x2198-3550
505 0 _aExperimental 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.
520 _aThis 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.
650 0 _aClimatology.
_962309
650 0 _aBig data.
_957216
650 0 _aArtificial intelligence.
_958441
650 0 _aQuantitative research.
650 0 _aSustainability.
_957661
650 1 4 _aClimate Sciences.
_967755
650 2 4 _aBig Data.
_957216
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aData Analysis and Big Data.
650 2 4 _aSustainability.
_957661
700 1 _aTripathi, Gaurav.
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700 1 _aShakya, Achala.
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700 1 _aKanga, Shruti.
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700 1 _aSingh, Suraj Kumar.
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700 1 _aRai, Praveen Kumar.
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710 2 _aSpringerLink (Online service)
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aAdvances in Geographical and Environmental Sciences,
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856 4 0 _uhttps://doi.org/10.1007/978-981-97-1685-2
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