This paper presents a methodological approach to estimation of urban population using the volume of single houses and high-rise residential buildings obtained from an IKONOS-2 ortho-image and light detection and raging (lidar) data. The estimates are directly executed at the finest scale level (i.e. the housing unit) and are then aggregated at the census district level for further validation with the aid of official data supplied by the local and federal governments. Unlike prior works, this study executes a thorough assessment of horizontal and elevation accuracy for the IKONOS-2 and lidar data used in the experiment. The methodological stages are threefold: the construction of a 3D city model, the accuracy assessment of the ortho-image and digital surface models (DSMs), and the quantification of urban population. The validation was accomplished by means of linear regression and associated hypothesis tests, considering the estimated population and the reference data. The results showed that there was a systematic underestimation of population. On average, the conducted estimates assessed 31 fewer inhabitants per district and lie 1.35% below the expected values given by the reference data. In spite of the observed underestimation, the estimated population can be regarded as equivalent to the population provided by the reference data at a 1% level of significance.
ARTICLE HISTORY
Abstract-The assessment of elevation accuracy of digital elevation models (DEM), which comprise digital surface models (DSM) and digital terrain models (DTM), has become a recurrent theme in the scientific literature in the latest decades. Accuracy tests are specifically based on a 10% level of statistical significance and they comprise both trend and precision analyses.
Abstract-The study of the urban environment has raised great interest among researchers and practitioners involved with the use of remote sensing, in face of the challenges for its investigation, like the fast and ongoing changes of its structure and the complexity of its targets. New concepts and analyses have been used for mapping the urban space. Object-based analysis and multi-resolution segmentation have been quite efficient in the discrimination of urban targets in high spatial resolution images. In this context, this paper proposes a methodology employing cognitive approaches for the classification of land cover in urban areas using optical orbital and airborne laser scanning data. The results were presented and discussed, indicating a satisfactory accuracy in the generated mapping products, demonstrating the reliability of the methodology for mapping urban land cover.
O Brasil necessita de métodos alternativos rápidos e baratos que possam ser utilizados em processos de extração de feições cartográficas relevantes, tendo como propósito que estas sejam usadas na atualização de bases cartográficas existentes. Para isso, as imagens de Sensoriamento Remoto têm contribuído de forma decisiva para minimizar estes problemas, juntamente com técnicas de Processamento Digital de Imagens (PDI). Uma destas técnicas é a teoria da Morfologia Matemática - MM. Ela tem por objetivo básico descrever quantitativamente as estruturas geométricas da imagem e funciona como uma técnica na concepção de algoritmos na área de PDI, dispondo de ferramentas básicas, como detectores de bordas e filtros morfológicos. A imagem utilizada é do satélite IKONOS com 1m de resluçºao espacial e contém como feição de interesse o Autódromo de Interlagos - SP. Com o uso da Teoria de Morfologia Matemática, este trabalho tem por objetivo detectar as pistas do autódromo por meio da aplicação de operadores morfológicos. Os operadores utilizados melhoraram a qualidade visual da imagem de entrada, facilitando o processo de detecção das pistas. A manipulação das imagens foi realizada na caixa de ferramentas ("Toolbox") de Morfologia Matemática (MM) desenvolvida pela SDC Information Systems, a qual trabalha acoplada ao software MATLAB. Os resultados obtidos foram interessantes e comprovaram o potencial de uso da MM na área de cartografia na detecção de pistas de autódromo.
This work proposes an alternative method to estimate urban population in the central area of Uberlandia city, located in Minas Gerais State, southeast of Brazil, using the volume of single houses and high-rise residential buildings, obtained from IKONOS-II images and LiDAR data. In the first stage, the residential buildings borders were extracted by digitalization executed on the orthoimage, and a height digital model was derived from LiDAR data. In the second stage, estimates of population within each census district of the study area for the year 2004 were accomplished by means of the calculated residential volume, habitable surface, and population density. This calculation proved that the estimated population can be considered equivalent to the population provided by the reference data at a 1% level of significance.I.
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