Big data and management of municipal solid waste

被引:0
作者
da Silva, Andrea Diniz [1 ]
Hypolito, Elizabeth Belo [1 ]
de Oliveira, Fabio Lucas Pimentel [2 ]
Borges, Calvin Macedo Ribeiro [3 ]
Gregorio, Dimitrio dos Santos [1 ]
de Oliveira, Fernanda Castilho Gomes [3 ]
Ferreira, Laira Zopellaro Machado Miranda [3 ]
机构
[1] Inst Brasileiro Geog & Estat IBGE, Escola Nacl Ciencias Estat ENCE, Populat Terr & Publ Stat, R Andre Cavalcanti 106, BR-20231050 Rio De Janeiro, RJ, Brazil
[2] Univ Fed Rio De Janeiro IPPUR UFRJ, Inst Pesquisa & Planejamento Urbano & Regiona, Fac Letras, Econ Dev, Sala Joao Do Rio, RJ, Brazil
[3] Inst Brasileiro Geog & Estat IBGE, Escola Nacl Ciencias Estat ENCE, Statist, R Andre Cavalcanti 106, BR-20231050 Rio De Janeiro, RJ, Brazil
来源
REVISTA DE GESTAO E SECRETARIADO-GESEC | 2023年 / 14卷 / 08期
关键词
Big Data; SDG; Agenda; 2030; Solid Waste;
D O I
10.7769/gesec.v14i8.2661
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In Brazil, the collection and management of urban solid waste is the responsibility of municipal governments. In most cases this is done on an informational basis considering population numbers to allocate resources for this purpose. Without having data capable of capturing socioeconomic transformations and/or changes in patterns of land use and occupation occurring in intercensal periods, the dimensioning of service provision is compromised. Thus, unwanted impacts can be caused, such as the irregular disposal of solid waste, affecting the quality of life of the population. The use of alternative data sources, especially big data, has enormous potential to complement data from administrative records and surveys, in addition to filling information gaps generated by disconnection of data with reality as the period since the census reference date lengthens. In this article, procedures and results of the use of big data are presented, more precisely satellite images, as an information alternative capable of better reflecting collective demands for services such as collection of municipal solid waste, and therefore of better guiding the decision-making process at the municipal level.
引用
收藏
页码:14241 / 14261
页数:21
相关论文
共 20 条
[1]  
Akinina NV, 2017, MEDD C EMBED COMPUT, P134
[2]  
Ali Algarni D., 1998, J. King Saud Univ.-Eng. Sci, V10, P15, DOI [10.1016/S1018-3639(18)30685-8, DOI 10.1016/S1018-3639(18)30685-8]
[3]  
BNDES-National Bank for Economic and Social Development, 2018, INT THINGS ACT PLAN
[4]  
BRAZIL, 2021, BRAZ SMART CIT CHART
[5]  
Brazilian Institute of Geography and Statistics (IBGE), BRAZ IND SUST DEV GO
[6]  
Cunha AMBM, 2020, CLIPPING MINERAL EXT
[7]  
Daas P., 2013, M MANAGEMENT STAT IN
[8]   Detection of waste dumping locations in landfill using multi-temporal Landsat thermal images [J].
Gill, Jasravia ;
Faisal, Kamil ;
Shaker, Ahmed ;
Yan, Wai Yeung .
WASTE MANAGEMENT & RESEARCH, 2019, 37 (04) :386-393
[9]  
ITU, 2021, about us
[10]   Agricultural plastic waste spatial estimation by Landsat 8 satellite images [J].
Lanorte, Antonio ;
De Santis, Fortunato ;
Nole, Gabriele ;
Blanco, Ileana ;
Loisi, Rosa Viviana ;
Schettini, Evelia ;
Vox, Giuliano .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2017, 141 :35-45