GeoDMA - Geographic Data Mining Analyst

GeoDMA is a toolbox for integrating remote sensing imagery analysis methods with data mining techniques producing a user-centered, extensible, rich computational environment for information extraction and knowledge discovery over large geographic databases.

Last release from March, 27, 2014: TerraView 4.2.2 with GeoDMA 0.2.2

• Current version
• Previous versions

The toolbox integrates the following techniques:

• image segmentation
• feature extraction and selection
• classification
• landscape-based metrics
• multi-temporal methods for change detection
• spatial data mining with decision-tree based strategies
• simulation methods to accuracy assessment

GeoDMA is developed in C++ under the Free and Open Source Software (FOSS) foundation, and works as a plugin for TerraView GIS.

GeoDMA has already been used to classify deforestation dynamics in Brazilian Amazonia.

[250px](Image:deforestation_dynamics_geodma.png) [250px](Image:decision_tree_deforestation.png)

GeoDMA works also with high spatial resolution urban imagery.

[200px](Image:urban_semi_classified.png)

The system's workflow is the following:

[500px](Image:data_flow_geodma.png)

• Thales Sehn Körting, source-code maintainer
• Leila Maria Garcia Fonseca, project manager

• Gilberto Câmara
• Maria Isabel Sobral Escada
• Antônio Miguel Vieira Monteiro

• Marcelino Pereira dos Santos Silva
• Alexandre Noma

• Márcio Azeredo
• Alexandre Copertino Jardim
• Wanderson Costa
• Maurício de Paulo

GeoDMA is free software, developed using TerraLib library. It works as a plugin for TerraView, also free software. If you want to download the source code of GeoDMA, try the following:

• Download TerraLib 4, TerraView and GeoDMA sources using SVN

  <https://svn.dpi.inpe.br/terralib/trunk/>

• Use Cmake to create your building files (Windows or Linux)

/path/to/terralib/trunk/build/cmake/

We are currently using Microsoft Visual Studio 2010 with QT 3.2 to compile GeoDMA in Windows, and gcc to compile in Linux. More information about compilation issues, please visit http://www.terralib.org/.

• GeoDMA user manual
• Attributes description

• GeoDMA: A toolbox integrating data mining with object-based and multi-temporal analysis of satellite remotely sensed imagery. http://bit.ly/slides-thales - PhD thesis in Remote Sensing program (INPE) from Thales Sehn Körting, presented in August, 20th, 2012.
• Classification of remote sensing images with GeoDMA - Geographic Data Mining Analyst (pdf) - Presentation at the “Short Meeting with Prof. Randolph Franklin”.
• Interpreting Images with GeoDMA ppt - Presentation at GEOBIA 2010.
• GeoDMA - discovering patterns from spatio-temporal data (pdf) - Presentation at the “Mini-Colloquium with Dr. Max Egenhofer”.
• GeoDMA video
• Geographical Data Mining - Presentation at the “Joint Research Seminar - GISciente for Dynamic” (ppt)

How to reference software GeoDMA in your paper?

GeoDMA <version number>. São José dos Campos, SP: Brazil's National Institute for Space Research (INPE), 2011. Available at <http://www.dpi.inpe.br/geodma>. Accessed in yyyy/mm/dd.

• Körting, T.S., Fonseca, L.M.G., Câmara, G. GeoDMA - Geographic Data Mining Analyst. Computers & Geosciences. 2013.
• Körting, T.S., Fonseca, L.M.G., Câmara, G. Interpreting images with GeoDMA. Geographic Object-Based Image Analysis (GEOBIA). Ghent, Belgium. 2010.
• Körting, T.S., Fonseca, L.M.G., Escada, M.I.S., Câmara, G. GeoDMA - Um sistema para mineração de dados de sensoriamento remoto. XIV SBSR. Natal, RN, Brazil. 2009.
• Körting, T.S., Fonseca, L.M.G., Escada, M.I.S., Silva, F.C., Silva, M.P.S. GeoDMA - A novel system for spatial data mining. Data Mining Workshops, 2008. ICDMW '08. IEEE International Conference on. Pisa, Italy. 2008.

• Maciel, A.M., Silva, M.P.S., Escada, M.I.S., França, F.S. Uma Metodologia para Descoberta de Relacionamentos Frequentes Entre Dados Espaciais de Desmatamento Usando Mineração de Grafos. Simpósio Brasileiro de Bancos de Dados, SBBD. São Paulo, Brazil. 2012.
• Pinho, C.M.D., Fonseca, L.M.G., Körting, T.S., Almeida, C.M., Kux, H.J.H. Land-cover classification of an intra-urban environment using high-resolution images and object-based image analysis. International Journal of Remote Sensing, 2012.
• Meneghetti, G., Rodrigues, C. S. Object-oriented classification in urban areas using GeoDMA plugin. Geographic Object-Based Image Analysis (GEOBIA). Rio de Janeiro, Brazil. 2012.
• Sousa, W., Bandeira, C., Ribeiro, E., Castro, A., Bustos, H., Silva, M.P.S. Monitoring of desertification processes through trend estimates of time series. Geographic Object-Based Image Analysis (GEOBIA). Rio de Janeiro, Brazil. 2012.
• Maciel, A.M., França, F.S., Silva, M.P.S. Discovery of frequent correlations among deforestation objects using graph mining. Geographic Object-Based Image Analysis (GEOBIA). Rio de Janeiro, Brazil. 2012.
• Saito, E.A., Fonseca, L.M.G., Escada, M.I.S., Körting. T.S. Efeitos da mudança de escala em padrões de desmatamento na Amazônia. Revista Brasileira de Cartografia, 63, 401-414. 2011.
• Gavlak, A.A., Escada, M.I.S., Monteiro, A.M.V. Dinâmica de padrões de mudança de uso e cobertura da terra na região do Distrito Florestal Sustentável da BR-163. XV SBSR. Curitiba, Brazil. 2011.
• Saito, E. A., Escada, M.I.S., Fonseca, L. M. G., Körting, T.S. Análise de padrões de desmatamento e trajetória de padrões de ocupação humana na Amazônia usando técnicas de mineração de dados. XV SBSR. Curitiba, Brazil. 2011.
• Sato, L.Y., Martins, F.S.R.V., Cantinho, R.Z., Körting, T.S., Fonseca, L.M.G., Almeida, C., Valeriano, D.M. Classificação de áreas exploradas por sistema de corte seletivo na Amazônia. XV SBSR. Curitiba, Brazil. 2011.
• Saito, E.A., Körting, T.S., Fonseca, L.M.G., Escada, M.I.S. Mineração em Dados Espaciais de Desmatamento do Prodes Utilizando Métricas da Paisagem: Caso de Estudo Município de Novo Progresso - PA. III SIMGEO. Recife, Brazil. 2010.
• Pinho, C.M.D., Silva, F.C., Fonseca, L.M.G., Monteiro, A.M.V. Urban Land Cover Classification from High-Resolution Images Using the C4.5 Algorithm. XXI Congress of the International Society for Photogrammetry and Remote Sensing, Pequim, 2008.
• Silva, M.P.S, Câmara, G. Escada, M.I.S., Souza, R.C.M. Remote Sensing Image Mining: Detecting Agents of Land Use Change in Tropical Forest Areas. International Journal of Remote Sensing, 2007.