Use of Image Endmember Libraries for Multi‐Sensor, Multi‐Scale, and Multi‐Site Mapping of Urban Areas

2021 ◽  
pp. 189-215
Author(s):  
Frank Canters ◽  
Sam Cooper ◽  
Jeroen Degerickx ◽  
Uta Heiden ◽  
Marianne Jilge ◽  
...  
Keyword(s):  
Urban Areas ◽  
Multi Scale ◽  
Site Mapping

scholarly journals CIM-Powered Multi-Hazard Simulation Framework Covering both Individual Buildings and Urban Areas

2020 ◽  
Vol 12 (12) ◽  
pp. 5059
Author(s):  
Xinzheng Lu ◽  
Donglian Gu ◽  
Zhen Xu ◽  
Chen Xiong ◽  
Yuan Tian
Keyword(s):  
Urban Areas ◽  
Hazard Analysis ◽  
Practical Method ◽  
High Fidelity ◽  
University Campus ◽  
Simulation Framework ◽  
Multi Scale ◽  
Scientific Simulations ◽  
Improve Analysis ◽  
Disaster Scenario

To improve the ability to prepare for and adapt to potential hazards in a city, efforts are being invested in evaluating the performance of the built environment under multiple hazard conditions. An integrated physics-based multi-hazard simulation framework covering both individual buildings and urban areas can help improve analysis efficiency and is significant for urban planning and emergency management activities. Therefore, a city information model-powered multi-hazard simulation framework is proposed considering three types of hazards (i.e., earthquake, fire, and wind hazards). The proposed framework consists of three modules: (1) data transformation, (2) physics-based hazard analysis, and (3) high-fidelity visualization. Three advantages are highlighted: (1) the database with multi-scale models is capable of meeting the various demands of stakeholders, (2) hazard analyses are all based on physics-based models, leading to rational and scientific simulations, and (3) high-fidelity visualization can help non-professional users better understand the disaster scenario. A case study of the Tsinghua University campus is performed. The results indicate the proposed framework is a practical method for multi-hazard simulations of both individual buildings and urban areas and has great potential in helping stakeholders to assess and recognize the risks faced by important buildings or the whole city.

scholarly journals Multi-Scale and Multi-Sensor 3D Documentation of Heritage Complexes in Urban Areas

2018 ◽  
Vol 7 (12) ◽  
pp. 483 ◽  
Author(s):  
Arnadi Murtiyoso ◽  
Pierre Grussenmeyer ◽  
Deni Suwardhi ◽  
Rabby Awalludin
Keyword(s):  
Urban Areas ◽  
13Th Century ◽  
Heterogeneous Sensors ◽  
Multi Scale ◽  
Heritage Site ◽  
Laser Scanners ◽  
3D Documentation ◽  
Extended Area ◽  
Distinct Features ◽  
Derivative Products

The 3D documentation of heritage complexes or quarters often requires more than one scale due to its extended area. While the documentation of individual buildings requires a technique with finer resolution, that of the complex itself may not need the same degree of detail. This has led to the use of a multi-scale approach in such situations, which in itself implies the integration of multi-sensor techniques. The challenges and constraints of the multi-sensor approach are further added when working in urban areas, as some sensors may be suitable only for certain conditions. This paper describes the integration of heterogeneous sensors as a logical solution in addressing this problem. The royal palace complex of Kasepuhan Cirebon, Indonesia, was taken as a case study. The site dates to the 13th Century and has survived to this day as a cultural heritage site, preserving within itself a prime example of vernacular Cirebonese architecture. This type of architecture is influenced by the tropical climate, with distinct features designed to adapt to the hot and humid year-long weather. In terms of 3D documentation, this presents specific challenges that need to be addressed both during the acquisition and processing stages. Terrestrial laser scanners, DSLR cameras, as well as UAVs were utilized to record the site. The implemented workflow, some geometrical analysis of the results, as well as some derivative products will be discussed in this paper. Results have shown that although the proposed multi-scale and multi-sensor workflow has been successfully employed, it needs to be adapted and the related challenges addressed in a particular manner.

scholarly journals MULTI-SCALE BASED EXTRACION OF VEGETATION FROM TERRESTRIAL LiDAR DATA FOR ASSESSING LOCAL LANDSCAPE

2015 ◽  
Vol II-3/W4 ◽  
pp. 263-270 ◽  
Author(s):  
T. Wakita ◽  
J. Susaki
Keyword(s):  
Urban Areas ◽  
Three Dimensional ◽  
Point Clouds ◽  
Lidar Data ◽  
Data Sets ◽  
Landscape Index ◽  
Terrestrial Lidar ◽  
Multi Scale ◽  
3D Point Clouds ◽  
Set Of Points

In this study, we propose a method to accurately extract vegetation from terrestrial three-dimensional (3D) point clouds for estimating landscape index in urban areas. Extraction of vegetation in urban areas is challenging because the light returned by vegetation does not show as clear patterns as man-made objects and because urban areas may have various objects to discriminate vegetation from. The proposed method takes a multi-scale voxel approach to effectively extract different types of vegetation in complex urban areas. With two different voxel sizes, a process is repeated that calculates the eigenvalues of the planar surface using a set of points, classifies voxels using the approximate curvature of the voxel of interest derived from the eigenvalues, and examines the connectivity of the valid voxels. We applied the proposed method to two data sets measured in a residential area in Kyoto, Japan. The validation results were acceptable, with F-measures of approximately 95% and 92%. It was also demonstrated that several types of vegetation were successfully extracted by the proposed method whereas the occluded vegetation were omitted. We conclude that the proposed method is suitable for extracting vegetation in urban areas from terrestrial light detection and ranging (LiDAR) data. In future, the proposed method will be applied to mobile LiDAR data and the performance of the method against lower density of point clouds will be examined.

Built-up area detection based on a Bayesian saliency model

2017 ◽  
Vol 15 (03) ◽  
pp. 1750027 ◽  
Author(s):  
Qingjie Liu ◽  
Di Huang ◽  
Yunhong Wang ◽  
Hong Wei ◽  
Yuanyan Tang
Keyword(s):  
Urban Growth ◽  
Urban Areas ◽  
Prior Probability ◽  
Visual Saliency ◽  
Saliency Map ◽  
Multi Scale ◽  
Saliency Model ◽  
Edge Distribution ◽  
Land Use Monitoring ◽  
Growth Detection

Built-up area detection is very important for applications such as urban planning, urban growth detection and land use monitoring. In this paper, we address the problem of built-up area detection from the perspective of visual saliency computation. Generally, areas containing buildings attract more attentions than forests, lands and other backgrounds. This paper explores a Bayesian saliency model to automatically detect urban areas. Firstly, prior probability is computed by using fast multi-scale edge distribution. Then the likelihood is obtained by modeling the distributions of color and orientation. Built-up areas are further detected by segmenting the final saliency map using Graph Cut algorithm. Experimental results demonstrate that the proposed method can extract built-up area efficiently and accurately.

scholarly journals Fast Unsupervised Multi-Scale Characterization of Urban Landscapes Based on Earth Observation Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2398
Author(s):  
Claire Teillet ◽  
Benjamin Pillot ◽  
Thibault Catry ◽  
Laurent Demagistri ◽  
Dominique Lyszczarz ◽  
...  
Keyword(s):  
Urban Areas ◽  
Urban Landscapes ◽  
Observation Data ◽  
Validation Data ◽  
Multi Scale ◽  
Macro Scale ◽  
Neighborhood Scale ◽  
Urban Footprint ◽  
Sentinel 2

Most remote sensing studies of urban areas focus on a single scale, using supervised methodologies and very few analyses focus on the “neighborhood” scale. The lack of multi-scale analysis, together with the scarcity of training and validation datasets in many countries lead us to propose a single fast unsupervised method for the characterization of urban areas. With the FOTOTEX algorithm, this paper introduces a texture-based method to characterize urban areas at three nested scales: macro-scale (urban footprint), meso-scale (“neighbourhoods”) and micro-scale (objects). FOTOTEX combines a Fast Fourier Transform and a Principal Component Analysis to convert texture into frequency signal. Several parameters were tested over Sentinel-2 and Pleiades imagery on Bouake and Brasilia. Results showed that a single Sentinel-2 image better assesses the urban footprint than the global products. Pleiades images allowed discriminating neighbourhoods and urban objects using texture, which is correlated with metrics such as building density, built-up and vegetation proportions. The best configurations for each scale of analysis were determined and recommendations provided to users. The open FOTOTEX algorithm demonstrated a strong potential to characterize the three nested scales of urban areas, especially when training and validation data are scarce, and computing resources limited.

scholarly journals Multi-scale atmospheric environment modelling for urban areas

2009 ◽  
Vol 3 (1) ◽  
pp. 53-57 ◽  
Author(s):  
A. A. Baklanov ◽  
R. B. Nuterman
Keyword(s):  
Urban Areas ◽  
Scale Effects ◽  
Urban Setting ◽  
Atmospheric Environment ◽  
Scale Model ◽  
Limited Area ◽  
Nested Models ◽  
Micro Scale ◽  
Multi Scale ◽  
Meso Scale

Abstract. Modern supercomputers allow realising multi-scale systems for assessment and forecasting of urban meteorology, air pollution and emergency preparedness and considering nesting with obstacle-resolved models. A multi-scale modelling system with downscaling from regional to city-scale with the Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM) and to micro-scale with the obstacle-resolved Micro-scale Model for Urban Environment (M2UE) is suggested and demonstrated. The M2UE validation results versus the Mock Urban Setting Trial (MUST) experiment indicate satisfactory quality of the model. Necessary conditions for the choice of nested models, building descriptions, areas and resolutions of nested models are analysed. Two-way nesting (up- and down-scaling), when scale effects both directions (from the meso-scale on the micro-scale and from the micro-scale on the meso-scale), is also discussed.

Multi-scale Target Detection for Underground Spaces with Transient Electromagnetics Based on Differential Pulse Scanning

2019 ◽  
Vol 24 (4) ◽  
pp. 593-607
Author(s):  
Wenhan Li ◽  
He Li ◽  
Kailiang Lu ◽  
Hongliang Cui ◽  
Xiu Li
Keyword(s):  
Urban Areas ◽  
High Performance ◽  
Differential Pulse ◽  
Resolving Power ◽  
Underground Structures ◽  
Extraction Technology ◽  
Multi Scale ◽  
Transient Electromagnetic ◽  
New Type ◽  
Low Efficiency

Improvements in detecting underground spaces in urban areas require improvements to the radiation efficiency and resolving power of the artificial source. Due to the use of bipolar pulse and the low efficiency of the artificial source, the existing artificial sources have difficulty in accurately imaging complex urban underground spaces of varying depths and sizes, to complete the task of “transparent detection” of urban underground spaces to depths of two hundred meters. In this paper, a new type of transient electromagnetic radiation based on a high-performance artificial source and differential pulse is proposed. At the same time, multi-resolution theory and multi-scale information extraction technology are combined to further improve the resolution of the radiation field in imaging complex urban underground structures of varying sizes. With this new method, we are able to achieve our goal of transparent detection of ‘two hundred meters' depths of urban underground space.

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