PROSPECTIVE UPON MULTI-SOURCE URBAN SCALE DATA FOR 3D DOCUMENTATION AND MONITORING OF URBAN LEGACIES

Abstract. The investigation on the built urban heritage and its current transformations can progressively benefit from the use of geospatial data related to urban environment. This is even more interesting when urban design studies of historical and stratified cities meet the contribution of 4D geospatial data within the urban morphology researches, aiming at quickly and accurately identifying and then measuring with a spatial relationship, both localized transformation (volumes demolitions, addition, etc…) and wide-scale substantial modification resulting from urban zones of diversification spaces that incorporates urban legacies. In this domain, the comparison and analysis of multi-source and multi-scale information belonging to Spatial Data Infrastructures (SDI) organized by Municipality and Region Administration (mainly, orthoimages and DSM and digital mapping) are a crucial support for multi-temporal spatial analysis, especially if compared with new DSMs related to past urban situations. The latter can be generated by new solution of digital image-matching techniques applicable to the available historical aerial images. The goal is to investigate the amount of available data and their effectiveness, to later test different experimental tools and methods for quick detection, localization and quantification of morphological macro-transformation at urban scale. At the same time, it has been examined the opportunity to made available, with up-and-coming Mobile Mapping Systems (MMS) based on image- and range-based techniques, a rapid and effective approach of data gathering, updating and sharing at validated urban scales. The presented research, carried out in the framework of the FULL@Polito research lab, applies to urban legacies and their regeneration, and is conducted on a key redevelopment area in northern Torino, the Parco Dora, that was occupied by steel industries actively working up to 1992. The long-standing steel structures of the Ferriere FIAT lot have been refurbished and incorporated in the new urban park, generating a contemporary space with a new evolving urban fabric, and being integrated in the new updated geo-spatial databases as well.</p

Update urban basemap by using the LiDAR mobile mapping system : the case of Abu Dhabi municipal system

Basemaps are the main resource used in urban planning and in building and infrastructure asset management. These maps are used by citizens and by private and public stakeholders. Therefore, accurate, up-to-date geoinformation of reference are needed to provide a good service. In general, basemaps have been updated by aerial photogrammetry or field surveying, but these methods are not always possible and alternatives need to be sought. Current limitations and challenges that face traditional field surveys include areas with extreme weather, deserts or artic environments, and flight restrictions due to proximity with other countries if there is not an agreement. In such cases, alternatives for large-scale are required. This thesis proposes the use of a mobile mapping system (MMS) to update urban basemaps. Most urban features can be extracted from point cloud using commercial software or open libraries. However, there are some exceptions: manhole covers, or hidden elements even with captures from defferent perspective, the most common building corners. Therefore, the main objective of this study was to establish a methodology for extracting manholes automatically and for completing hidden corners of buildings, so that urban basemaps can be updated. The algorithm developed to extract manholes is based on time, intensity and shape detection parameters, whereas additional information from satellite images is used to complete buildings. Each municipality knows the materials and dimensions of its manholes. Taking advantage of this knowledge, the point cloud is filtered to classify points according to the set of intensity values associated with the manhole material. From the classified points, the minimum bounding rectangles (MBR) are obtained and finally the shape is adjusted and drawn. We use satellite imagery to automatically digitize the layout of building footprints with automated software tools. Then, the visible corners of buildings from the LiDAR point cloud are imported and a fitting process is performed by comparing them with the corners of the building from the satellite image. Two methods are evaluated to establish which is the most suitable for adjustment in these conditions. In the first method, the differences in X and Y directions are measured in the corners, where LiDAR and satellite data are available, and is often computed as the average of the offsets. In the second method, a Helmert 2D transformation is applied. MMS involves Global Navigation Satellite Systems (GNSS) and Inertial Measurement Units (IMU) to georeference point clouds. Their accuracy depends on the acquisition environment. In this study, the influence of the urban pattern is analysed in three zones with varied urban characteristics: different height buildings, open areas, and areas with a low and high level of urbanization. To evaluate the efficiency of the proposed algorithms, three areas were chosen with varying urban patterns in Abu Dhabi. In these areas, 3D urban elements (light poles, street signs, etc) were automatically extracted using commercial software. The proposed algorithms were applied to the manholes and buildings. The completeness and correctness ratio, and geometric accuracy were calculated for all urban elements in the three areas. The best success rates (>70%) were for light poles, street signs and road curbs, regardless of the height of the buildings. The worst rate was obtained for the same features in peri-urban areas, due to high vegetation. In contrast, the best results for trees were found in theses areas. Our methodology demonstrates the great potential and efficiency of mobile LiDAR technology in updating basemaps; a process that is required to achieve standard accuracy in large scale maps. The cost of the entire process and the time required for the proposed methodology was calculated and compared with the traditional method. It was found that mobile LiDAR could be a standard cost-efficient procedure for updating maps.La cartografía de referencia es la principal herramienta en planificación urbanística, y gestión de infraestructuras y edificios, al servicio de ciudadanos, empresas y administración. Por esta razón, debe estar actualizada y ser lo más precisa posible. Tradicionalmente, la cartografía se actualiza mediante fotogrametría aérea o levantamientos terrestres. No obstante, deben buscarse alternativas válidas para escalas grandes, porque no siempre es posible emplear estas técnicas debido a las limitaciones y retos actuales a los que se enfrenta la medición tradicional en algunas zonas del planeta, con meteorología extrema o restricciones de vuelo por la proximidad a la frontera con otros países. Esta tesis propone el uso del sistema Mobile Mapping System (MMS) para actualizar la cartografía urbana de referencia. La mayoría de los elementos pueden extraerse empleando software comercial o librerías abiertas, excepto los registros de servicios. Los elementos ocultos son otro de los inconvenientes encontrados en el proceso de creación o actualización de la cartografía, incluso si se dispone de capturas desde diferentes puntos de vista. El caso más común es el de las esquinas de edificios. Por ello, el principal objetivo de este estudio es establecer una metodología de extracción automática de los registros y completar las esquinas ocultas de los edificios para actualizar cartografía urbana. El algoritmo desarrollado para la detección y extracción de registros se basa en parámetros como el tiempo, la intensidad de la señal laser y la forma de los registros, mientras que para completar los edificios se emplea información adicional de imágenes satélite. Aprovechando el conocimiento del material y dimensión de los registros, en disposición de los gestores municipales, el algoritmo propuesto filtra y clasifica los puntos de acuerdo a los valores de intensidad. De aquellos clasificados como registros se calcula el mínimo rectángulo que los contiene (Minimum Bounding Rectangle) y finalmente se ajusta la forma y se dibuja. Las imágenes de satélite son empleadas para obtener automáticamente la huella de los edificios. Posteriormente, se importan las esquinas visibles de los edificios obtenidas desde la nube de puntos y se realiza el ajuste comparándolas con las obtenidas desde satélite. Para llevar a cabo este ajuste se han evaluado dos métodos, el primero de ellos considera las diferencias entre las coordenadas XY, desplazándose el promedio. En el segundo, se aplica una transformación Helmert2D. MMS emplea sistemas de navegación global por satélite (Global Navigation Satellite Systems, GNSS) e inerciales (Inertial Measurement Unit, IMU) para georreferenciar la nube de puntos. La precisión de estos sistemas de posicionamiento depende del entorno de adquisición. Por ello, en este estudio se han seleccionado tres áreas con distintas características urbanas (altura de edificios, nivel de urbanización y áreas abiertas) de Abu Dhabi con el fin de analizar su influencia, tanto en la captura, como en la extracción de los elementos. En el caso de farolas, señales viales, árboles y aceras se ha realizado con software comercial, y para registros y edificios con los algoritmos propuestos. Las ratios de corrección y completitud, y la precisión geométrica se han calculado en las diferentes áreas urbanas. Los mejores resultados se han conseguido para las farolas, señales y bordillos, independientemente de la altura de los edificios. La peor ratio se obtuvo para los mismos elementos en áreas peri-urbanas, debido a la vegetación. Resultados opuestos se han conseguido en la detección de árboles. El coste económico y en tiempo de la metodología propuesta resulta inferior al de métodos tradicionales. Lo cual demuestra el gran potencial y eficiencia de la tecnología LiDAR móvil para la actualización cartografía de referenciaPostprint (published version

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

3D Point Clouds in Urban Planning: Developing and Releasing High-end Methodologies based on LiDAR and UAV Data for the Extraction of Building Parameters

Os dados geográficos têm um papel determinante na formalização do plano urbano, enquanto instrumento de planeamento e documento normativo que define juridicamente as obrigações públicas e vincula os particulares, num determinado período temporal, no que respeita a disciplina urbanística de uma cidade ou de um aglomerado urbano, estabelecendo regras de uso e de ocupação do solo. O plano está associado a um processo, designado processo de planeamento; processo esse que e constituído por um conjunto de fases, dinâmicas e adaptativas, que se iniciam na sua elaboração e terminam na avaliação dos desvios entre o determinado no documento inicial e as metas e objectivos efectivamente atingidos. O plano, o processo e a praxis do planeamento exigem dados geográficos actualizados a cada instante, quer para as acções de monitorização quer para os momentos de avaliação. Um dos aspectos cruciais do plano e a quantificação da volumetria do espaço edificado existente. Outro aspecto, também fundamental, é o da gestão dessa volumetria; quer da volumetria existente quer da volumetria adicional. O tema da volumetria dos espaços edificados tem constituído, aliás, um dos temas mais sensíveis quando se trata da densificação do espaço urbano existente ou do desenho de novos espaços urbanos de expansão. Considerando o quadro teórico apresentado, o tema central da tese trata da modelação de nuvens de pontos 3D obtidas por tecnologia LiDAR e por UAV, para as aplicações na elaboração do plano e no processo de planeamento urbano, designadamente quantificação dos parâmetros urbanísticos altura da fachada e volume dos edifícios.A exploração do tema central da tese suporta-se em dois níveis: o nível da operacionalização e o nível da usabilidade. O nível da operacionalizão concretiza dois objectivos: i) demonstração da relevância e da pertinência da extracção, medição e geovisualização 3D dos parâmetros urbanísticos baseadas na experimentação e implementação de técnicas de geoprocessamento; ii) demonstração da pertinência dos parâmetros urbanísticos extraídos considerando distintas morfologias urbanas. Para o nível da usabilidade de nem-se igualmente dois objectivos: i) demonstração da usabilidade dos parâmetros urbanísticos extraídos avaliando o erro associado a extracção; ii) demonstração da usabilidade dos parâmetros urbanísticos extraídos para planeamento, em particular para o mapeamento dasimétrico de alta precisão. Da investigação decorre uma solução metodol ogica. A solução metodológica nomeada 3D Extraction Building Parameters (3DEBP) destina-se a extracção da área, da altura da fachada e do volume dos edifícios a partir de nuvens de pontos 3D. Esta solução foi criada tendo por base um conjunto de ferramentas FOSS: PostgreSQL/PostGIS, QGIS, GRASS e R-stats. Foram realizados testes em duas áreas urbanas com morfologias distintas: Praia de Faro (morfologia irregular) e Amadora (morfologia regular). O teste sobre a área urbana da Praia de Faro utilizou uma nuvem de pontos LiDAR e uma outra extra da de levantamento realizado por UAV. O teste sobre um quarteirão urbano de Amadora foi realizado apenas sobre nuvem de pontos UAV. Os testes revelaram que a qualidade da informação extra da e dependente da morfologia urbana. Nas conclusões discute-se a medição 3D com base em dados obtidos por tecnologia LiDAR e UAV, questiona-se a implementação de soluções FOSS para diferentes fases do processo de planeamento e defende-se a introdução intensiva da modelação 3D no plano urbano do futuro.Geographical data plays a major role in urban plan development, both as a planning instrument and as a normative document that legally de nes public obligations and binds individuals, in a given period of time, regarding the urban aspect of a city or an urban conglomerate, and establishes standards for land use and land cover. The plan is associated with a process, called the planning process, which consists in a set of dynamic and adaptive phases that begin with its development and end with the evaluation of any discrepancies between the provisions of the original document and the accomplished goals and objectives. The plan, the process, and the planning praxis require up-to-date geographical data at all times, both for monitoring actions and for the evaluation phases. One of the crucial aspects of the plan is the quanti cation of the existing building volume. Another fundamental aspect is managing that volume: both regarding the existing volume and any additional volumes. Actually, the building volume in built areas has been one of the most sensitive topics on the densi cation of existing urban spaces or the design of new growing urban areas. Considering the existing theoretical framework, the central topic of this thesis focuses on 3D point cloud modelling obtained from LiDAR and UAV technologies, employed in the development of a plan and in the urban planning process, namely regarding two speci c building parameters { building height and volume. The explanation of the central topic of this thesis is twofold: implementation and usability. The implementation level has two goals: i) demonstrating the relevance and pertinence of the extraction, measurement, and 3D geovisualization of building parameters based on the experimentation and implementation of geoprocessing techniques; ii) demonstrating the pertinence of the extracted building parameters considering di erent urban morphologies. At the usability level, we de ned two goals: i) demonstrating the usability of the extracted building parameters, evaluating the error associated with the extraction; ii) demonstrating the usability of these parameters for planning, particularly for high precision dasymetric mapping. Based on our research, we propose a methodological solution termed. 3D Extraction Building Parameters (3DEBP) and aimed at extracting areas, fa cade height, and building volumes from 3D point clouds. This solution was created with the following set of FOSS tools: PostgreSQL/PostGIS, GRASS, QGIS, and R-stats. We performed several tests in two urban areas with di erent morphologies: Praia de Faro (irregular morphology) and Amadora (regular morphology). The former (Praia de Faro) used a LiDAR point cloud and another one extracted from a UAV survey, while the latter (urban neighbourhood of Amadora) only used a UAV point cloud. Both experiments reveal that the quality of the information extracted depends on urban morphology. Finally, we discuss 3D measurement based on data obtained from LiDAR and UAV technology, raising questions on the implementation of FOSS solutions for di erent phases of the planning process, and arguing for the intensive introduction of 3D modelling for the future of urban planning

Methodology and Algorithms for Pedestrian Network Construction

With the advanced capabilities of mobile devices and the success of car navigation systems, interest in pedestrian navigation systems is on the rise. A critical component of any navigation system is a map database which represents a network (e.g., road networks in car navigation systems) and supports key functionality such as map display, geocoding, and routing. Road networks, mainly due to the popularity of car navigation systems, are well defined and publicly available. However, in pedestrian navigation systems, as well as other applications including urban planning and physical activities studies, road networks do not adequately represent the paths that pedestrians usually travel. Currently, there are no techniques to automatically construct pedestrian networks, impeding research and development of applications requiring pedestrian data. This coupled with the increased demand for pedestrian networks is the prime motivation for this dissertation which is focused on development of a methodology and algorithms that can construct pedestrian networks automatically. A methodology, which involves three independent approaches, network buffering (using existing road networks), collaborative mapping (using GPS traces collected by volunteers), and image processing (using high-resolution satellite and laser imageries) was developed. Experiments were conducted to evaluate the pedestrian networks constructed by these approaches with a pedestrian network baseline as a ground truth. The results of the experiments indicate that these three approaches, while differing in complexity and outcome, are viable for automatically constructing pedestrian networks

Multitemporal Feature-Level Fusion on Hyperspectral and LiDAR Data in the Urban Environment

publishedVersio

A Pipeline of 3D Scene Reconstruction from Point Clouds

3D technologies are becoming increasingly popular as their applications in industrial, consumer, entertainment, healthcare, education, and governmental increase in number. According to market predictions, the total 3D modeling and mapping market is expected to grow from $1.1 billion in 2013 to$7.7 billion by 2018. Thus, 3D modeling techniques for different data sources are urgently needed. This thesis addresses techniques for automated point cloud classification and the reconstruction of 3D scenes (including terrain models, 3D buildings and 3D road networks). First, georeferenced binary image processing techniques were developed for various point cloud classifications. Second, robust methods for the pipeline from the original point cloud to 3D model construction were proposed. Third, the reconstruction for the levels of detail (LoDs) of 1-3 (CityGML website) of 3D models was demonstrated. Fourth, different data sources for 3D model reconstruction were studied. The strengths and weaknesses of using the different data sources were addressed. Mobile laser scanning (MLS), unmanned aerial vehicle (UAV) images, airborne laser scanning (ALS), and the Finnish National Land Survey’s open geospatial data sources e.g. a topographic database, were employed as test data. Among these data sources, MLS data from three different systems were explored, and three different densities of ALS point clouds (0.8, 8 and 50 points/m2) were studied. The results were compared with reference data such as an orthophoto with a ground sample distance of 20cm or measured reference points from existing software to evaluate their quality. The results showed that 74.6% of building roofs were reconstructed with the automated process. The resulting building models provided an average height deviation of 15 cm. A total of 6% of model points had a greater than one-pixel deviation from laser points. A total of 2.5% had a deviation of greater than two pixels. The pixel size was determined by the average distance of input laser points. The 3D roads were reconstructed with an average width deviation of 22 cm and an average height deviation of 14 cm. The results demonstrated that 93.4% of building roofs were correctly classified from sparse ALS and that 93.3% of power line points are detected from the six sets of dense ALS data located in forested areas. This study demonstrates the operability of 3D model construction for LoDs of 1-3 via the proposed methodologies and datasets. The study is beneficial to future applications, such as 3D-model-based navigation applications, the updating of 2D topographic databases into 3D maps and rapid, large-area 3D scene reconstruction. 3D-teknologiat ovat tulleet yhä suositummiksi niiden sovellusalojen lisääntyessä teollisuudessa, kuluttajatuotteissa, terveydenhuollossa, koulutuksessa ja hallinnossa. Ennusteiden mukaan 3D-mallinnus- ja -kartoitusmarkkinat kasvavat vuoden 2013 1,1 miljardista dollarista 7,7 miljardiin vuoteen 2018 mennessä. Erilaisia aineistoja käyttäviä 3D-mallinnustekniikoita tarvitaankin yhä enemmän. Tässä väitöskirjatutkimuksessa kehitettiin automaattisen pistepilviaineiston luokittelutekniikoita ja rekonstruoitiin 3D-ympäristöja (maanpintamalleja, rakennuksia ja tieverkkoja). Georeferoitujen binääristen kuvien prosessointitekniikoita kehitettiin useiden pilvipisteaineistojen luokitteluun. Työssä esitetään robusteja menetelmiä alkuperäisestä pistepilvestä 3D-malliin eri CityGML-standardin tarkkuustasoilla. Myös eri aineistolähteitä 3D-mallien rekonstruointiin tutkittiin. Eri aineistolähteiden käytön heikkoudet ja vahvuudet analysoitiin. Testiaineistona käytettiin liikkuvalla keilauksella (mobile laser scanning, MLS) ja ilmakeilauksella (airborne laser scanning, ALS) saatua laserkeilausaineistoja, miehittämättömillä lennokeilla (unmanned aerial vehicle, UAV) otettuja kuvia sekä Maanmittauslaitoksen avoimia aineistoja, kuten maastotietokantaa. Liikkuvalla laserkeilauksella kerätyn aineiston osalta tutkimuksessa käytettiin kolmella eri järjestelmällä saatua dataa, ja kolmen eri tarkkuustason (0,8, 8 ja 50 pistettä/m2) ilmalaserkeilausaineistoa. Tutkimuksessa saatuja tulosten laatua arvioitiin vertaamalla niitä referenssiaineistoon, jona käytettiin ortokuvia (GSD 20cm) ja nykyisissä ohjelmistoissa olevia mitattuja referenssipisteitä. 74,6 % rakennusten katoista saatiin rekonstruoitua automaattisella prosessilla. Rakennusmallien korkeuksien keskipoikkeama oli 15 cm. 6 %:lla mallin pisteistä oli yli yhden pikselin poikkeama laseraineiston pisteisiin verrattuna. 2,5 %:lla oli yli kahden pikselin poikkeama. Pikselikoko määriteltiin kahden laserpisteen välimatkan keskiarvona. Rekonstruoitujen teiden leveyden keskipoikkeama oli 22 cm ja korkeuden keskipoikkeama oli 14 cm. Tulokset osoittavat että 93,4 % rakennuksista saatiin luokiteltua oikein harvasta ilmalaserkeilausaineistosta ja 93,3 % sähköjohdoista saatiin havaittua kuudesta tiheästä metsäalueen ilmalaserkeilausaineistosta. Tutkimus demonstroi 3D-mallin konstruktion toimivuutta tarkkuustasoilla (LoD) 1-3 esitetyillä menetelmillä ja aineistoilla. Tulokset ovat hyödyllisiä kehitettäessä tulevaisuuden sovelluksia, kuten 3D-malleihin perustuvia navigointisovelluksia, topografisten 2D-karttojen ajantasaistamista 3D-kartoiksi, ja nopeaa suurten alueiden 3D-ympäristöjen rekonstruktiota

Automatic manhole extraction from MMS data to update basemaps

Basemaps are the main resource used in urban planning, building and infrastructure asset management. Therefore, they must be accurate and up to date to better serve citizens, contractors, property owners and town planning departments. Traditionally, they have been updated by aerial photogrammetry, but this is not always possible and alternatives need to be sought. In such cases, a useful option for large scales is the mobile mapping system (MMS). However, automatic extraction from MMS point clouds is limited by the complexity of the urban environment. Therefore, the influence of the urban pattern is analysed in three zones with varied urban characteristics: areas with high buildings, open areas, and areas with a low level of urbanization. In these areas, the capture and automatic extraction of 3D urban elements is performed using commercial software, which is useful for some elements but not for manholes. The objective of this study is to establish a methodology for extracting manholes automatically and completing hidden buildings' corners, in order to update urban basemaps. Shape and intensity are the main detection parameters for manholes, whereas additional information from satellite image Quickbird is used to complete the buildings. The worst rate of detection for all the extracted urban elements was found in areas of high buildings. Finally, the article analyses the computing cost for manhole extraction, and the economic cost and time consume of the entire process, including the proposed methodolgy using an MMS point cloud and the traditional survey in this case.Peer ReviewedPostprint (updated version