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  • 1.
    Ban, Yifang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Jacob, Alexander
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Gamba, Paolo
    University of Pavia, Pavia, Italy.
    Spaceborne SAR Data for Global Urban Mapping at 30m Resolution Utilizing a Robust Urban Extractor2015In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 103Article in journal (Refereed)
    Abstract [en]

    With more than half of the world population now living in cities and 1.4 billion more people expected to move into cities by 2030, urban areas pose significant challenges on local, regional and global environment. Timely and accurate information on spatial distributions and temporal changes of urban areas are therefore needed to support sustainable development and environmental change research. The objective of this research is to evaluate spaceborne SAR data for improved global urban mapping using a robust processing chain, the KTH-Pavia Urban Extractor. The proposed processing chain includes urban extraction based on spatial indices and Grey Level Co-occurrence Matrix (GLCM) textures, an existing method and several improvements i.e., SAR data preprocessing, enhancement, and post-processing. ENVISAT Advanced Synthetic Aperture Radar (ASAR) C-VV data at 30m resolution were selected over 10 global cities and a rural area from six continents to demonstrated robustness of the improved method. The results show that the KTH-Pavia Urban Extractor is effective in extracting urban areas and small towns from ENVISAT ASAR data and built-up areas can be mapped at 30m resolution with very good accuracy using only one or two SAR images. These findings indicate that operational global urban mapping is possible with spaceborne SAR data, especially with the launch of Sentinel-1 that provides SAR data with global coverage, operational reliability and quick data delivery.

  • 2.
    Fan, Hongchao
    et al.
    Department of Cartography, Technical University of Munich.
    Mao, Bo
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Meng, Liqiu
    Department of Cartography, Technical University of Munich.
    An automatic approach for the typification of façade structuresIn: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235Article in journal (Other academic)
    Abstract [en]

    Typification is a well-established operator of map generalization. Although it is widely used in many existing research fields, less discussion has been devoted to the quality of typification. This paper presents a user survey for the evaluation of different typification results of façade structures under different constraints. The survey shows that preservation of the shape of the features is the most important constraint for a reasonable typification process, which has also been quantitatively verified by calculating the similarities between the typified façades and the original façade using attributed relational graph (ARG) and nested earth mover’s distance (NEMD) algorithms. Based on that, an algorithm is developed to generate perceivably reasonable representation from the original facade with decreasing map scale. The algorithm is implemented and tested on a number of façades. Experiments reveal that the typification can be automatically conducted and can create results which are well associated with the original façades.

  • 3.
    Mao, Bo
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
    Generalisation of textured 3D city models using image compression and multiple representation data structure2013In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 79, p. 68-79Article in journal (Refereed)
    Abstract [en]

    Texture is an essential part of 3D building models and it often takes up a big proportion of the data volume, thus makes dynamic visualization difficult. To compress the texture of 3D building models for the dynamic visualization in different scales, a multi-resolution texture generalization method is proposed, which contains two steps: texture image compression and texture coloring. In the first step, the texture images are compressed in both horizontal and vertical directions using wavelet transform. In the second step, TextureTreeis created to store the building color texture for the dynamic visualization from different distances. To generate TextureTree, texture images are iteratively segmented by horizontal and vertical dividing zone, e.g. edge or background from edge detection, until each section is basically in the same color. Thentexture in each section is represented by their main color and the TextureTree iscreated based on the color difference between the adjacent sections. In dynamic visualization, the suitable compressed texture images or the TextureTree nodes are selected to generate the 3D scenes based on the angle and the distance between user viewpoint and the building surface. The experimental results indicate that the wavelet based image compression and proposed TextureTree can effectively represent the visual features of the textured buildings with much less data.

  • 4.
    Mao, Bo
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Harrie, Lars
    Department of Physical Geography and Ecosystem Analysis, Lund University.
    A Multiple Representation Data Structure for Dynamic Visualisation of Generalised 3D City Models2011In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 66, no 2, p. 198-208Article in journal (Refereed)
    Abstract [en]

    In this paper, a novel multiple representation data structure for dynamic visualisation of 3D city models, called CityTree, is proposed. To create a CityTree, the ground plans of the buildings are generated and simplified. Then, the buildings are divided into clusters by the road network and one CityTree is created for each cluster. The leaf nodes of the CityTree represent the original 3D objects of each building, and the intermediate nodes represent groups of close buildings. By utilizing CityTree, it is possible to have dynamic zoomfunctionality in real time. The CityTree methodology is implemented in aframework where the original city model is stored in CityGML and the CityTree is stored as X3D scenes. A case study confirms the applicability of the CityTree for dynamic visualisation of 3D city models.

  • 5.
    Reshetyuk, Yuriy
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics, Geodesy.
    A unified approach to self-calibration of terrestrial laser scanners2010In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 64, no 5, p. 445-456Article in journal (Refereed)
    Abstract [en]

    In recent years, the method of self-calibration widely used in photogrammetry has been found suitable for the estimation of systematic errors in terrestrial laser scanners. Since high correlations can be present between the estimated parameters, ways to reduce them have to be found. This paper presents a unified approach to self-calibration of terrestrial laser scanners, where the parameters in a least-squares adjustment are treated as observations by assigning appropriate weights to them. The higher these weights are the lower the parameter correlations are expected to be. Self-calibration of a pulsed laser scanner Leica Scan Station was performed with the unified approach. The scanner position and orientation were determined during the measurements with the help of a total station, and the point clouds were directly georeferenced. The significant systematic errors were zero error in the laser rangefinder and vertical circle index error. Most parameter correlations were comparatively low. In part, precise knowledge of the horizontal coordinates of the scanner centre helped greatly to achieve low correlation between these parameters and the zero error. The approach was shown to be advantageous to the use of adjustment with stochastic (weighted) inner constraints where the parameter correlations were higher. At the same time, the collimation error could not be estimated reliably due to its high correlation with the scanner azimuth because of a limited vertical distribution of the targets in the calibration field. While this problem can be solved for a scanner with a nearly spherical field-of-view, it will complicate the calibration of scanners with limited vertical field-of-view. Investigations into the influence of precision of the scanner position and levelling on the adjustment results lead to two important findings. First, it is not necessary to level the scanner during the measurements when using the unified approach since the parameter correlations are relatively low anyway. Second, the scanner position has to be known with a precision of about 1 mm in order to get a reliable estimate of the zero error. (C) 2010 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

  • 6.
    Xiang, Deliang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics. National University of Defense Technology, China.
    Tang, Tao
    National University of Defense Technology, China.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Su, Yi
    Kuang, Gangyao
    Unsupervised polarimetric SAR urban area classification based on model-based decomposition with cross scattering2016In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 116, p. 86-100Article in journal (Refereed)
    Abstract [en]

    Since it has been validated that cross-polarized scattering (HV) is caused not only by vegetation but also by rotated dihedrals, in this study, we use rotated dihedral corner reflectors to form a cross scattering matrix and propose an extended four-component model-based decomposition method for PolSAR data over urban areas. Unlike other urban area decomposition techniques which need to discriminate the urban and natural areas before decomposition, this proposed method is applied on PolSAR image directly. The building orientation angle is considered in this scattering matrix, making it flexible and adaptive in the decomposition. Therefore, we can separate cross scattering of urban areas from the overall HV component. Further, the cross and helix scattering components are also compared. Then, using these decomposed scattering powers, the buildings and natural areas can be easily discriminated from each other using a simple unsupervised K-means classifier. Moreover, buildings aligned and not aligned along the radar flight direction can be also distinguished clearly. Spaceborne RADARSAT-2 and airborne AIRSAR full polarimetric SAR data are used to validate the performance of our proposed method. The cross scattering power of oriented buildings is generated, leading to a better decomposition result for urban areas with respect to other state-of-the-art urban decomposition techniques. The decomposed scattering powers significantly improve the classification accuracy for urban areas.

  • 7.
    Yifang, Ban
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gong, Peng
    Tsinghua University.
    Gini, Chandra
    Global land cover mapping using earth observation satellite data: recent progresses and challenges2015In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 103, no 1, p. 1-6Article in journal (Refereed)
  • 8.
    Zhang, Puzhao
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics. ] Xidian Univ, Minist Educ, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China.
    Nascetti, Andrea
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Gong, Maoguo
    Xidian Univ, Minist Educ, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China..
    An implicit radar convolutional burn index for burnt area mapping with Sentinel-1 C-band SAR data2019In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 158, p. 50-62Article in journal (Refereed)
    Abstract [en]

    Compared with optical sensors, the all-weather and day-and-night imaging ability of Synthetic Aperture Radar (SAR) makes it competitive for burnt area mapping. This study investigates the potential of Sentinel-1 C-band SAR sensors in burnt area mapping with an implicit Radar Convolutional Burn Index (RCBI). Based on multi temporal Sentinel-1 SAR data, a convolutional networks-based classification framework is proposed to learn the RCBI for highlighting the burnt areas. We explore the mapping accuracy level that can be achieved using SAR intensity and phase information for both VV and VH polarizations. Moreover, we investigate the decorrelation of Interferometric SAR (InSAR) coherence to wildfire events using different temporal baselines. The experimental results on two recent fire events, Thomas Fire (Dec., 2017) and Carr Fire (July, 2018) in California, demonstrate that the learnt RCBI has a better potential than the classical log-ratio operator in highlighting burnt areas. By exploiting both VV and VH information, the developed RCBI achieved an overall mapping accuracy of 94.68% and 94.17% on the Thomas Fire and Carr Fire, respectively.

  • 9.
    Zhang, T.
    et al.
    Shanghai Key Lab. of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai, China.
    Jiang, L.
    Shanghai Key Lab. of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai, China.
    Xiang, D.
    National Innovation Institute of Technology, Beijing, China.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Pei, L.
    Shanghai Key Lab. of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai, China.
    Xiong, H.
    Shanghai Key Lab. of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai, China.
    Ship detection from PolSAR imagery using the ambiguity removal polarimetric notch filter2019In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 157, p. 41-58Article in journal (Refereed)
    Abstract [en]

    Ship detection from Polarimetric Synthetic Aperture Radar (PolSAR) imagery has attracted a lot of attention in recent years. Some studies highlight that azimuth ambiguity caused by the Doppler phase aliasing is one of the primary factors degrading the performance of ship detection. To address this problem, a new algorithm is proposed in this paper, which is based on improving the geometrical perturbation-polarimetric notch filter (GP-PNF). Specifically, we first give the explanation of the polarimetric feature pedestal ship height (PSH) and theoretically verify that it can reflect the depolarized energy ratio of targets. Subsequently, the backscattering differences between ship and rough sea surface are analyzed using the Yamaguchi four-component decomposition. Based on these analyses, a new feature vector aimed at removing azimuth ambiguity and detecting ships is finally constructed to improve GP-PNF. In order to demonstrate the effectiveness of proposed algorithm, we carry out five experiments using real PolSAR datasets acquired by the UAVSAR L-Band and AIRSAR C-Band sensors. A sufficient comparison with five other state-of-the-art methods shows that the proposed algorithm is characterized by a better capability to remove azimuth ambiguities and detect ships simultaneously. Last but not least, we also theoretically deduce that the depolarization-only methods are unable to detect ships when sea surface is rough enough.

1 - 9 of 9
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