Abstract: This paper evaluates the data quality of road axes using the OpenStreetMap (OSM) collaborative mapping platform. OSM was chosen owing to the abundance of data and registered contributors (~ 6 million). We assumed the OSM collaborative data could complement the reference mappings by its quality parameters. We used the cartographic quality indicators of positional accuracy, thematic accuracy, and completeness to validate vector files from OSM. We analyzed the positional accuracy of linear features and we developed the automation of the positional accuracy process. The tool verified the completeness of road axes and thematic accuracy. The positional accuracy of linear features was also used, performed to obtain a range of scales, which reflected the characteristics of mapped areas and varied from 1:22,500 to 1:25,000. The completeness of road axes was 82% of the checked areas. By evaluating the thematic accuracy, we found that the absence of road axes toponymy in editions caused errors in the OSM features (i.e., 58% of road axes without information). As such, we concluded that collaborative data complements the reference cartography by measuring the heterogeneity of information in various regions and filtering the OSM data, despite its being useful for certain analyses.

RESUMO A investigação foi conduzida para a análise da aplicação de modelos de superfície derivados de levantamentos de varredura laser aerotransportada contribuiriam para o monitoramento de florestas. O foco foi mais especificamente a análise do estrato arbóreo, que contém a parte mais elevada da vegetação de um dado tipo florestal, também descrito como superfície acima da copa dossel. É analisada uma região de Floresta ombrófila mista entre os estados de São Paulo e Paraná no Brasil. A proposta é utilizar o sistema ALS- Airborne Laser Scanner, que fornece informações ligadas a diferentes estratos da cobertura vegetal, para analisar o comportamento e alcançar uma estimativa para a altura do estrado mais elevado. A metodologia elaborada baseia-se na diferenciação de superfícies identificadas no conjunto de dados originais e na utilização dessas superfícies com uma estrutura matricial "raster". Essa estrutura é obtida a partir da interpolação dos diferentes conjuntos de pontos das superfícies de interesse. A estrutura matricial, ao contrário da vetorial, permite o uso de processamento digital de imagens, com isso o uso de filtros digitais sobre os dados. Estes filtros são utilizados para reduzir a influência de erros ocorridos durante a classificação e aproximar a superfície obtida da superfície teórica. Os resultados revelam um relacionamento coerente com aspectos externos de influência sobre a vegetação. Obtiveram-se estimativas que podem ser correlacionadas, por exemplo, com influências antrópicas. Assim, a altura da vegetação poderia ser um índice de conservacionismo adotado por cadastros e licenciamentos ambientais.

ABSTRACT This research was aimed at providing a study of digital elevation models from Airborne Laser Scanner (ALS) data. The goal was to improve the forest monitoring, or more specifically, arboreal canopy monitoring, which contains the most elevated vegetation of the forest. It is also described as the surface above the canopy top. The region of rain forest between the states of São Paulo and Paraná in Brazil was analyzed. The proposed method employs the ALS system that provides information related to different vegetative cover bedding, to analyze it and reach to estimate for the most elevated stage. The methodology is based on differentiating the identified surfaces in the original set of data. It uses these surfaces with a raster, which was obtained from an interpolation of different sets of points from the surfaces of interest. The raster structure, unlike vector data, allows for processes linked to the digital processing of images. It enables implementation of digital filters over the data. The method helped in reducing the influence of errors during classification and achieving the theoretical surface. The results revealed a coherent relationship with anthropogenic influence such as the introduction of exotic vegetation. We concluded that arboreal vegetation could be an index of conservation for environmental registration and licensing organizations.