Supported mapping with multi sensor images through strategy focused on customization and integration of generalized classes by GEOBIA

Share/Save/Bookmark

Cruz, C.B.M. and Almeida, P.M.M. and Barros, R.S. and Vicens, R.S. and Souza, E.M.F.R. and Caris, E.P.A. and Fernandes, M.C. and Menezes, P.M.L. (2016) Supported mapping with multi sensor images through strategy focused on customization and integration of generalized classes by GEOBIA. In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) .

[img]
Preview
PDF
448kB
Event: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC)
Abstract:Rio de Janeiro presents itself as a land of contrasts, with the second largest metropolitan area in Brazil and a total area of 43,778 km2. Its landscape consists of remnants of the Atlantic Forest and environments with different levels of anthropic impacts. The complexity of its territory combines natural and anthropic covers related to each other at different intensity levels, being a challenge in defining mapping techniques of land use and land cover with greater spatial and temporal detail. Supported by the Secretary of State for Environment, this initiative accepted the challenge of developing a methodology for mapping about 45% of the state in 1:25,000. This mapping aims to support decision making regarding the land use planning and the monitoring of deforestation actions. Using GEOBIA techniques and images of different resolutions, we structured a methodology for the classification of four macro-classes very different spectrally (Natural Forested Areas, Natural Non-Forested Areas, Anthropic Agropastoral Areas, Anthropic Non-Agropastoral Areas), identifying objects on the ground from 0.5ha, to meet demands from the Rural Environmental Registry (CAR, in portuguese) and the forest monitoring. The mapping was divided into Working Groups (WG) that customized solutions through Process Trees in eCognition environment. This choice is based on the need to minimize inconsistencies in the interpretive process, improving the level of specialization in short time. Thus, each WG is responsible for the classification of a set of functionally related classes. The integration process of the classes in a single mapping was also supported by GEOBIA. It is believed that the presentation of this strategic view may contribute to challenges of similar mapping, allowing the achievement of cartographic goals in short term.
Item Type:Conference or Workshop Item (Paper)
Link to this item:https://doi.org/10.3990/2.446
Conference URL:https://www.geobia2016.com/
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page