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Accueil du site → Doctorat → Allemagne → 2010 → Fernerkundung und GIS zur Erfassung, Modellierung und Visualisierung orientalischer Stadtstrukturen : das Beispiel Sanaa (Jemen)

Universität Potsdam (2010)

Fernerkundung und GIS zur Erfassung, Modellierung und Visualisierung orientalischer Stadtstrukturen : das Beispiel Sanaa (Jemen)

Abdlhamed Jamil

Titre : Fernerkundung und GIS zur Erfassung, Modellierung und Visualisierung orientalischer Stadtstrukturen : das Beispiel Sanaa (Jemen)

Acquisition, modelling and visualisation of oriental city structures with remote sensing and GIS : the case of Sanaa (Yemen)

Auteur : Abdlhamed Jamil

Université de soutenance : Universität Potsdam

Grade : Doctor Rerum Naturalium (Dr.rer.nat) 2010

This study aims at the development and implementation of a generic procedure for the acquisition, processing, analysis and cartographic visualisation of urban space in arid zone cities based on operational remote sensing imagery. As a proof of concept the Yemeni capital Sanaa has been selected as a use case. The workflow developed is based on standard procedures and systems of spatial information processing and allows for subsequent automation oft its essential processes. Today, high-resolution remote sensing data from operational satellite systems (such as QuickBird, Ikonos etc) facilitate the recognition and mapping of urban objects such as buildings, streets and even cars which, in the past could only be acquired by non-operational aerial photography. The satellite imagery can be used to generate maps and even 3D-representation of the urban space. Both maps and 3D-visualisations can be used for up-to-date land use mapping, zoning and urban planning purposes etc. The 3D-visualisation provides a deeper understanding of urban structures by integrating building height into the analysis. For this study remote sensing data of the Quickbird satellite data of 2005 were used. They show a section of the city of Sanaa in Yemen. The remote sensing data were supplemented and verified by other data, including terrain data. The image data are then subjected to thorough digital image. This procedure consists of a pixel-oriented classification of the satellite image acquisition at class level. In addition, a visual interpretation of the satellite image has been undertaken to identify and label individual objects (areas, surfaces, streets) etc. which were subsequently digitised. The town maps created in both procedures were merged to one. Through this combination of the results, the advantages of both maps are brought together and their respective weaknesses are eliminated or minimized. The digital collection of the contour lines on the orthophoto map of Sanaa allowed for the creation of a digital terrain model, which was used for the three-dimensional representation of Sanaa’s historic district. The 3D-visualisation was created from the classification results as well as from the digital collection of the objects and the results of both visualisations were combined in a city map. In all classification procedures, paved roads, vegetation and single buildings were detected very well. The best overall results with the highest accuracy values achieved in the pixel-oriented classification at class level. Because each class has been classified separately, size belonging to that class can be better understood and optimised. The amount of data could be reduced, thus requiring less memory and resulting in a shorter processing time. The evaluation and validation of the pixel-oriented visual classification results at class level with the original satellite imagery was designed more simply and more accurately than other classification methods implemented. It was also possible by the separate recording of the class building to create a 3D-visualisation. A comparison of the maps created found that the map created from visual interpretation contains more information. The map based on pixel-oriented classification results at class level proved to be less labor- and time-consuming, and the structure of an oriental city with the main features will be worked out better. The 2D-maps and the 3D-visualisation provide a different spatial impression, and certain elements of an oriental city clearly detectable. These include the characteristic dead ends in the old town and the former city wall. The typical high-rise houses of Sanaa are detected in the 3D-visualisation. This work developed a generic procedure to detect, analyse and visualise urban structures in arid zone environments. The city of Sanaa served as a proof of concept. The results show that the workflow developed is instrumental in detecting typical structures of oriental cities. The results achieved in the case study Sanaa prove that the process can be adapted to the investigation of other arid zone cities in the Middle East with minor modifications

Mots clés  : 2D-Stadtmodell ; 3D-Visualisierung ; Fernerkundung ; Klassifikation ; orientalische Stadt — 2D city model ; 3D visualization ; classification ; oriental city ; remote sensing


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Page publiée le 3 janvier 2016, mise à jour le 1er décembre 2018