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010   $a3-031-98095-6
024 7 $a10.1007/978-3-031-98095-4
035   $a(CKB)44769974000041
035   $a(MiAaPQ)EBC32470587
035   $a(Au-PeEL)EBL32470587
035   $a(DE-He213)978-3-031-98095-4
035   $a(OCoLC)1574121339
035   $a(EXLCZ)9944769974000041
100   $a20260102d2026      u|         0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aData Analytics and Remote Sensing-Based Analysis for Sustainable Development /$fedited by Deepak Kumar, Nick P. Bassill, Khushboo Rani
205   $a1st ed. 2026.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026.
215   $a1 online resource (365 pages)
225 1 $aAdvances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development,$x2522-8722
311 08$a3-031-98094-8 
327   $aIntroduction -- Literature Review -- Sustainable Development Goals -- Applications of Data Analytics and Remote Sensing for Sustainable Development -- Conclusion.
330   $aThis book presents analysis of data analytics and remote sensing which are two powerful tools that can be used to support sustainable development. Remote sensing involves the use of sensors to gather data about the environment from a distance, while data analytics refers to the use of statistical and computational techniques to extract insights and patterns from large datasets. Sustainable development and remote sensing are used to monitor changes in the environment, such as deforestation, land use change, and water quality. This information is analyzed using data analytics to identify trends and patterns and to develop strategies for sustainable development. Remote sensing is used to monitor the health of forests, and data analytics is used to identify areas where deforestation is particularly high. This information is then used to develop targeted strategies for reducing deforestation, such as promoting sustainable forestry practices or supporting reforestation efforts. It is alsoused to monitor water quality, and data analytics is used to identify sources of pollution and to develop strategies for improving water quality. This information is particularly important in developing countries, where access to clean water is often a major challenge. Furthermore, data analytics and remote sensing are powerful tools for supporting sustainable development. By gathering and analyzing data about the environment, authors better understand the challenges they face and develop effective strategies for addressing them.
410  0$aAdvances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development,$x2522-8722
606   $aSustainability
606   $aEnvironmental monitoring
606   $aQuantitative research
606   $aUrban ecology (Biology)
606   $aSustainability
606   $aEnvironmental Monitoring
606   $aData Analysis and Big Data
606   $aUrban Ecology
615  0$aSustainability.
615  0$aEnvironmental monitoring.
615  0$aQuantitative research.
615  0$aUrban ecology (Biology)
615 14$aSustainability.
615 24$aEnvironmental Monitoring.
615 24$aData Analysis and Big Data.
615 24$aUrban Ecology.
676   $a304.2
700   $aKumar$b Deepak$01354437
701   $aBassill$b Nick P$01885673
701   $aRani$b Khushboo$01885674
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9911049209403321
996   $aData Analytics and Remote Sensing-Based Analysis for Sustainable Development$94520983
997   $aUNINA