2015 Joint Urban Remote Sensing Event (JURSE)最新文献_第3页

Traffic queue length measurement by using combined methods of Photogrammetry and digital image processing 基于摄影测量与数字图像处理相结合的交通队列长度测量

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120531

Lingli Zhu, E. Khoramshahi, Tuomas Turppa, Eero Salminen

{"title":"Traffic queue length measurement by using combined methods of Photogrammetry and digital image processing","authors":"Lingli Zhu, E. Khoramshahi, Tuomas Turppa, Eero Salminen","doi":"10.1109/JURSE.2015.7120531","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120531","url":null,"abstract":"Real-time measurement of traffic parameters is increasingly demanded for monitoring the traffic status and adjusting the timings of traffic lights. In this paper, we propose an economic and operable approach to measure a traffic queue length on real-time by employing the combination of photogrammetry and image processing methods. The requirement for our development is rather simple: one camera which is fixed in a proper place and a 2D digital vector map. Therefore, it is fairly economic and feasible. There are four steps needed to acquire traffic queue length: control points are derived from a 2D digital vector-map; the interior orientation (IO) and exterior orientation (EO) parameters are extracted; the image is processed and coordinates of vehicle headlights are calculated; vehicles are separated into each lane and the length of traffic queue is calculated. Steps and are only implemented once when a camera is installed. After the parameters of IO and EO are obtained, they can be applied repeatedly. Therefore, this method can be operative in real-time. In addition, separating vehicles into each lane has been a challenging work in the traffic queue study. Our method has solved this problem and achieved a promising result.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"8 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114094009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Relationship between land cover type and Body Mass Index in Geneva 日内瓦地区土地覆盖类型与身体质量指数的关系

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120542

E. Rochat, S. Duruz, I. Widmer, A. Clemence, O. Desrichard, D. Rappo, O. Ertz, J. Ingensand, J. Theler, I. Guessous, S. Joost

引用次数: 2

The robust InSAR optimization framework with application to monitoring cities on volcanoes 鲁棒InSAR优化框架及其在火山城市监测中的应用

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120466

Yuanyuan Wang, Xiaoxiang Zhu

{"title":"The robust InSAR optimization framework with application to monitoring cities on volcanoes","authors":"Yuanyuan Wang, Xiaoxiang Zhu","doi":"10.1109/JURSE.2015.7120466","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120466","url":null,"abstract":"This paper introduces the Robust InSAR Optimization (RIO) framework to the multi-pass InSAR techniques, such as PSI, SqueeSAR and TomoSAR whose current optimal estimators were derived based on the assumption of Gaussian distributed stationary data, with seldom attention towards their robustness. The RIO framework effectively tackles two common problems in the multi-pass InSAR techniques: 1. treatment of images with bad quality, especially those with large uncompensated phase error, and 2. the covariance matrix estimation of non-Gaussian and non-stationary distributed scatterer (DS). The former problem is dealt with using a robust M-estimator which effectively down-weight the images that heavily violate the phase model, and the latter is addresses with a new method: the Rank M-Estimator (RME) by which the covariance is estimated using the rank of the DS. RME requires no flattening/estimation of the interferometric phase, thanks to the property of mean invariance of rank. The robustness of RME is achieved by using an M-estimator, i.e. amplitude-based weighing function in covariance estimation. The RIO framework can be easily extended to most of the multi-pass InSAR techniques.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115098908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Allocating tree crown pruning with ALS-data - A case study in the city of Helsinki 利用als数据分配树冠修剪——以赫尔辛基市为例

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120523

V. Luoma, Topi Tanhuanpää, M. Holopainen, M. Vastaranta, N. Saarinen, V. Kankare, J. Hyyppä

{"title":"Allocating tree crown pruning with ALS-data - A case study in the city of Helsinki","authors":"V. Luoma, Topi Tanhuanpää, M. Holopainen, M. Vastaranta, N. Saarinen, V. Kankare, J. Hyyppä","doi":"10.1109/JURSE.2015.7120523","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120523","url":null,"abstract":"Trees are an essential part of urban environments. In urban areas trees are located for example among buildings, on roadsides and in parks. When growing outside of their typical natural forest habitat, the trees need to be actively managed to ensure their well-being and the safety of the citizens. One example of urban tree management is the need to make sure that the street areas are sufficiently lit. It means that trees growing very close to street-lamps need to be pruned occasionally. In this case study the need of pruning the urban trees in the city of Helsinki was studied by means of airborne laser-scanning (ALS) and GIS-analysis. An ALS-based tree register containing the main attributes and the spatial location of the trees was compared in the analysis to a lamppost register. The lamppost register included the types and the xy-locations of the lampposts. The aim of the analysis was to map the trees and more specifically tree crowns that had an effect on the lampposts and thus needed to be pruned. First, tree crowns were delineated from the ALS-data. A GIS-analysis was used to map the trees that had a crown segment influencing to a lamppost and then the tree was classified to be pruned. The classification was then compared to a field data collected from the same areas to validate the results. Based on the results, it seems it is possible to use ALS-data and GIS in planning of the tree management in urban areas.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129921093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Template based matching of optical and SAR imagery 基于模板的光学和SAR图像匹配

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120349

G. Palubinskas, P. Reinartz

引用次数: 8

Environment mapping & interpretation by drone 无人机环境制图和解释

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120454

M. Sanfourche, B. L. Saux, A. Plyer, G. L. Besnerais

引用次数: 11

Developing a community-based worldwide urban morphology and materials database (WUDAPT) using remote sensing and crowdsourcing for improved urban climate modelling 开发基于社区的全球城市形态和材料数据库(WUDAPT)，利用遥感和众包改进城市气候模型

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120501

L. See, C. Perger, M. Dürauer, S. Fritz, B. Bechtel, J. Ching, P. J. Alexander, G. Mills, Micheal Foley, Martin O'Connor, Iain Stewart, J. Feddema, V. Masson

引用次数: 34

Height estimation for high-rise buildings based on InSAR analysis 基于InSAR分析的高层建筑高度估计

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120530

Wen Liu, Kentaroh Suzuki, F. Yamazaki

引用次数: 8

Urban water body detection from the combination of high-resolution optical and SAR images 高分辨率光学影像与SAR影像相结合的城市水体检测

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120525

Chuiqing Zeng, Jinfei Wang, Xiaodong Huang, S. Bird, J. Luce

引用次数: 4

Feature selection for urban impervious surfaces estimation using optical and SAR images 基于光学和SAR影像的城市不透水面估算特征选择

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120483

Hongsheng Zhang, Hui Lin

{"title":"Feature selection for urban impervious surfaces estimation using optical and SAR images","authors":"Hongsheng Zhang, Hui Lin","doi":"10.1109/JURSE.2015.7120483","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120483","url":null,"abstract":"Urban impervious surfaces, such as transport related land (e.g., roads, streets, and parking lots) and building roof tops (commercial, residential, and industrial areas), have been widely recognized as important indicator for urban environments. Numerous methods have been proposed to estimate impervious surfaces from remotely sensed images. However, most of these approaches were proposed with optical remote sensing images, and accurate estimation of impervious surfaces remains challenging due to the diversity of urban land covers. This study presents the effort to synergistically combine optical and SAR data to improve the mapping of impervious surfaces using the Random Forest (RF). The Multilayer Perceptron, Support Vector Machine, and RF are compared for impervious surfaces mapping with the single use of optical image and with the combined optical and SAR images. Experiment shows some interesting results: 1) synergistic use of SPOT-5 and TerraSAR-X images produced more accurate classification of impervious surface mapping, no matter what combinations of features are used; 2) The SAN-based features appeared to provide effective complementary information to the conventional GLCM-based features for the classification, increasing the accuracy by about 0.6% by using supervised classifiers; 3) SVM and RF tended to be superior to MLP for the fusion of SPOT-5 and TerraSAR-X images for LULC classification and ISE. RF is better for the LULC classification as it better handled the spectral confusion among sub types of impervious and non-impervious land covers, while SVM appeared more stable before and after the combination of sub land cover types, and thus is more suitable for the ISE with the classification strategies of mapping impervious surface.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131096974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3