000 04721nam a22005895i 4500
001 978-981-97-2296-9
003 DE-He213
005 20251030112038.0
007 cr nn 008mamaa
008 240512s2024 si | s |||| 0|eng d
020 _a9789819722969
_9978-981-97-2296-9
024 7 _a10.1007/978-981-97-2296-9
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aK
_2bicssc
072 7 _aBUS061000
_2bisacsh
072 7 _aPBT
_2thema
072 7 _aK
_2thema
100 1 _aSato, Aki-Hiro.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976695
245 1 0 _aEvaluation Platform of Sustainability for Global Systems
_h[electronic resource] :
_bStatistical Approach to Geospatial Information for Big Data Integration /
_cby Aki-Hiro Sato, Hiroe Tsubaki.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXVI, 143 p. 51 illus., 27 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- Methods and Concepts about Evaluation -- Grid Squares and Grid Square statistics -- Statistical foundations about Grid Square statistics -- How to construct data infrastructure based on Grid Square statistics.
520 _aThe authors of this book assert that Grid Square statistics, a method of aggregating data within a geographically defined Grid, may be an effective solution to approach geospatial data for big data integration. Grid Square statistics is a technique that allows us to collect and analyze data based on Grids and makes it easier to understand patterns and trends. Sustainability, a key concern for the future of our society, often involves balancing multiple independent objectives. These objectives and key performance indicators must be shared to solve multi-dimensional optimization problems with some constraints related to sustainability issues. However, many of these sustainability issues are challenges that are part of global systems, which are modeled as a complex system consisting of many components. Social, economic, and environmental aspects in our socio-economic systems require solutions designed for the sustainability of our society. These conditions imply that Big Data must contribute to evaluating our current situation, actions, and changes to continuously change our behavior and society based on a Plan-Do-Check-Action (PDCA) cycle. The PDCA cycle, also known as the Deming cycle, is a four-step management method used to improve processes and products continuously. We must understand how to construct a platform by using Big Data to do so. Thus, extracting meaningful information from Big Data is crucially important in the advanced information society. This book provides case studies based on Grid Square statistics. It shows their applications to socio-economic and environmental problems such as tourism, where we analyze visitor patterns to optimize resource allocation, SDGs indicator, where we monitor the sustainability of our socio-economic systems, and disaster management, where we face natural disaster to enhance preparedness. Finally, the book proposes a World Grid Square Statistics Reference Architecture for constructing data applications across organizations and domains and reports on design concepts, system architecture, and the implication of a data platform for World Grid Square data and statistics.
650 0 _aStatistics .
_965982
650 0 _aQuantitative research.
650 0 _aSocial sciences
_xStatistical methods.
_975236
650 0 _aLabor economics.
650 0 _aPopulation
_xEconomic aspects.
_958573
650 1 4 _aStatistics in Business, Management, Economics, Finance, Insurance.
_969738
650 2 4 _aData Analysis and Big Data.
650 2 4 _aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
_975237
650 2 4 _aLabor and Population Economics.
_971978
700 1 _aTsubaki, Hiroe.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976696
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819722952
776 0 8 _iPrinted edition:
_z9789819722976
776 0 8 _iPrinted edition:
_z9789819722983
856 4 0 _uhttps://doi.org/10.1007/978-981-97-2296-9
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c59797
_d59797