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Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urbanization in Brazil occurred in a disorganized way and without observing criteria that could ensure the sustainability of this process, resulting in high population concentrations in large urban centers. In this way, it is recognized the need for an adequate planning that contemplates the economic and social interests and respects the environmental demands. Thus, the present work aims to map the land use and occupancy, with an emphasis in an urban area, having as a case study the municipality of Novo Hamburgo, RS. The methodology is established in two levels of detailing of classes, in which supervised classification and manual vectorization were used, seeking a more accurate specification of the urban areas. Validation was established through two databases: Google Earth and Remotely Piloted Aircraft System (RPAS), using the confusion matrix and the Kappa index. The results show the efficiency of the hybrid method for high-resolution images, besides highlighting the existing anthropogenic differences in urban areas. In relation to the use of different databases for validation, close values are also perceived between the two processes, with a Kappa index of 0.928 for data obtained from Google Earth and 0.943 for the RPAS.