Big-Data to Support the Study of the Environmental Disaster in Mariana, MG: From VGI to Social Media Geographic Information
Revista Brasileira de Cartografia – Ano 2017
Autores desta publicação
- BORGES, Júnia – Júnia Lúcio de Castro Borges - Ex-Bolsista de Doutorado
- MOURA, Ana Clara M. – Prof. Ana Clara Mourão Moura - COORDENADORA
- PAULA, Priscila L. – Priscila Lisboa de Paula - Ex-Bolsista Iniciação Científica
- CASAGRANDE, Pedro – Pedro Benedito Casagrande - Aluno de Doutorado em Geologia
Resumo da publicação
Big-Data to Support the Study of the Environmental Disaster in Mariana, MG: From VGI to Social Media Geographic Information. Revista Brasileira de Cartografia (2017), No 69/8, Edição Especial “Geovisualização, mídias sociais e participação cidadã: apoio à representação, análise e gestão da paisagem”: 1586-1597.
Sociedade Brasileira de Cartografia, Geodésia, Fotogrametria e Sensoriamento Remoto
Abstract (english text)
The use of Social Media Geographic Information in a planning process would improve our knowledge about local values, urban and landscape development and could support decision-making. This paper presents a case study of an environmental disaster that happened recently in one of the most important social economic areas in Brazil to understand how this type of information could be used as a systematized planning input. The authors seek to understand if it is possible to use VGI and SMGI (Volunteered Geographic Information and Social Media Geographic Information) to capture social values, such as genius loci (the essence of the place)and expectations, the values that should be considered in a disaster recovery plan. To do that, we tested an active VGI platform and passive SMGI posts’ analysis. Our best results so far relied on a proposal for image analysis from Instagram posts to separate them in the themes of “everyday life”, “landscape” and “memes”. Presenting a logic and a tool to do this classification automatically, we provide a first step to be used in big-data, as they are characterized by a big amount of data, and we can develop a first analysis in the main pictures posted by people from that area. It is a contribution to use social media to measure values and collective expectations from a place.