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1.
为更好地发挥遥感技术在城市规划地图制作中的应用，高分辨率遥感影像成为城市地图制作中最重要的数据源。面对地物信息复杂、建筑物众多的城市地区，如何快速提取高分辨率遥感影像地图制作过程中相邻两景影像之间的镶嵌线具有重要意义。本文以国产卫星中分辨率最高、幅宽最小的GF-2影像为数据源，融合建筑物轮廓数据，研究了基于最短路径的A*搜索算法，实现了遥感影像地图制作的镶嵌线自动提取技术。结果表明，该方法能够自动生成避让建筑物的镶嵌线，速度快、镶嵌质量高，可广泛应用于城市地区高分辨率遥感影像地图制作。 相似文献
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谭金石 《测绘与空间地理信息》2015,(6):81-83
机载LiDAR作为一种新兴的对地观测技术,能够快速地获取地表三维信息。如何从海量LiDAR点云数据中提取建筑物是数据处理中的一项关键工作。本文结合LiDAR数据和航空影像的数据特点,提出了一种航空影像辅助的LiDAR点云建筑物提取方法,首先,采用面向对象方法从航空影像中提取建筑物的轮廓;然后,以建筑轮廓信息为参考,从LiDAR点云中提取建筑物的点云数据;最后,通过实验证明该方法的有效性与可行性。 相似文献
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Mohammad Awrangjeb Mehdi Ravanbakhsh Clive S. Fraser 《ISPRS Journal of Photogrammetry and Remote Sensing》2010,65(5):457-467
This paper presents an automatic building detection technique using LIDAR data and multispectral imagery. Two masks are obtained from the LIDAR data: a ‘primary building mask’ and a ‘secondary building mask’. The primary building mask indicates the void areas where the laser does not reach below a certain height threshold. The secondary building mask indicates the filled areas, from where the laser reflects, above the same threshold. Line segments are extracted from around the void areas in the primary building mask. Line segments around trees are removed using the normalized difference vegetation index derived from the orthorectified multispectral images. The initial building positions are obtained based on the remaining line segments. The complete buildings are detected from their initial positions using the two masks and multispectral images in the YIQ colour system. It is experimentally shown that the proposed technique can successfully detect urban residential buildings, when assessed in terms of 15 indices including completeness, correctness and quality. 相似文献
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Buildings, as impervious surfaces, are an important component of total impervious surface areas that drive urban stormwater response to intense rainfall events. Most stormwater models that use percent impervious area (PIA) are spatially lumped models and do not require precise locations of building roofs, as in other applications of building maps, but do require accurate estimates of total impervious areas within the geographic units of observation (e.g. city blocks or sub-watershed units). Two-dimensional mapping of buildings from aerial imagery requires laborious efforts from image analysts or elaborate image analysis techniques using high spatial resolution imagery. Moreover, large uncertainties exist where tall, dense vegetation obscures the structures. Analyzing LiDAR point-cloud data, however, can distinguish buildings from vegetation canopy and facilitate the mapping of buildings. This paper presents a new building extraction approach that is based on and optimized for estimating building impervious areas (BIA) for hydrologic purposes and can be used with standard GIS software to identify building roofs under tall, thick canopy. Accuracy assessment methods are presented that can optimize model performance for modeling BIA within the geographic units of observation for hydrologic applications. The Building Extraction from LiDAR Last Returns (BELLR) model, a 2.5D rule-based GIS model, uses a non-spatial, local vertical difference filter (VDF) on LiDAR point-cloud data to automatically identify and map building footprints. The model includes an absolute difference in elevation (AdE) parameter in the VDF that compares the difference between mean and modal elevations of last-returns in each cell.
The BELLR model is calibrated for an extensive inner-city, highly urbanized small watershed in Columbia, South Carolina, USA that is covered by tall, thick vegetation canopy that obscures many buildings. The calibration of BELLR used a set of building locations compiled by photo-analysts, and validation used independent building reference data. The model is applied to two residential neighborhoods, one of which is a residential area within the primary watershed and the other is a younger suburban neighborhood with a less-well developed tree canopy used as a validation site. Performance results indicate that the BELLR model is highly sensitive to concavity in the lasboundary tool of LAStools® and those settings are highly site specific. The model is also sensitive to cell size and the AdE threshold values. However, properly calibrated the BIA for the two residential sites could be estimated within 1% error for optimized experiments.
To examine results in a hydrologic application, the BELLR estimated BIAs were tested using two different types of hydrologic models to compare BELLR results with results using the National Land Cover Database (NLCD) 2011 Percent Developed Imperviousness data. The BELLR BIA values provide more accurate results than the use of the 2011 NLCD PIA data in both models. The VDF developed in this study to map buildings could be applied to LiDAR point-cloud filtering algorithms for feature extraction in machine learning or mapping other planar surfaces in more broad-based land-cover classifications. 相似文献
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随着无人机航空摄影的不断发展和成熟,利用无人机航摄制作高分辨率数字正射影像图在测绘生产中应用日益广泛。但在城市区域制作大比例尺正射影像图时存在建筑物倾斜、遮挡严重、不能和GIS矢量数据进行很好套合等问题,而数字真正射影像图能很好地解决这些问题。本文基于INPHO软件对城市无人机航摄影像进行真正射影像制作,总结出无人机航摄影像制作真正射影像的作业流程和需要注意的关键问题。 相似文献
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崔胜涛 《测绘与空间地理信息》2017,(8)
根据测绘地理信息行业"十三五"规划,如何利用国情普查数据进行地理国情监测监测,成为未来几年测绘技术的一个重要课题。本文的实施以地理国情普查数据利用高分辨率航空影像确定和采集滩涂地表空间数据为范围,对为滩涂变化监测提供基础数据源进行了研究。 相似文献
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Abstract Information on the number and type of new building structures is required by urban and transportation planners and the real estate industry. The goal of this paper is to explore the potential of high resolution imagery for meeting public and private sector demands for information on new buildings. The value of 1 m, 5 m, and 10 m panchromatic and 1 m color scanned aerial photography images acquired in 1997 and 1998 for a study area within the City of San Diego, California is assessed for general change detection and building enumeration. Both semi‐automated and interactive change‐detection approaches are evaluated. We demonstrate that interactive, visual‐based approaches appear to be the most accurate (within 1% of actual count) and efficient approach for generating information on the number of new buildings associated with single family residential land use. More automated approaches to detecting and enumerating image microfeatures may be useful as enhancements for visual‐based assessments and may be practical in areas composed mostly of large buildings associated with commercial and industrial land use. The highest accuracy for automated approaches was an undercounting of 11% for residential buildings and overcounting of 20% for those associated with commercial and industrial land use. 相似文献
9.
Automatic Registration Between Low-Altitude LiDAR Point Clouds and Aerial Images Using Road Features
Peipei He Xinjing Wang Youchuan Wan Jingzhong Xu Wei Yang 《Journal of the Indian Society of Remote Sensing》2018,46(12):1963-1973
Among the many means of acquiring surface information, low-altitude light detection and ranging (LiDAR) systems (e.g., unmanned aerial vehicle LiDAR, UAV-LiDAR) have become an important approach to accessing geospatial information. Considering the lower level of hardware technology in low-altitude LiDAR systems compared to that in airborne LiDAR, and the greater flexibility in-flight, registration procedures must be first performed to facilitate the fusion of laser point data and aerial images. The corner points and edges of buildings are frequently used for the automatic registration of aerial imagery with LiDAR data. Although aerial images and LiDAR data provide powerful support for building detection, adaptive edge detection for all types of building shapes is difficult. To deal with the weakness of building edge detection and reduce matching-related computation, the study presents a novel automatic registration method for aerial images, with LiDAR data, on the basis of main-road information in urban areas. Firstly, vector road centerlines are extracted from raw LiDAR data and then projected onto related aerial images with the use of coarse exterior orientation parameters (EOPs). Secondly, the corresponding image road features of each LiDAR vector road are determined using an improved total rectangle-matching approach. Finally, the endpoints of the conjugate road features obtained from the LiDAR data and aerial images are used as ground control points in space resection adjustment to refine the EOPs; an iterative strategy is used to obtain optimal matching results. Experimental results using road features verify the feasibility, robustness and accuracy of the proposed approach. 相似文献
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Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with “change”, “non-change” and “uncertain change” status labeled through a voting strategy. The “uncertain changes” are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are extracted combining the multispectral images and the DSM by morphological operators, and the new buildings are determined by excluding the verified unchanged buildings from the second step. Both the synthetic experiment with Worldview-2 stereo imagery and the real experiment with IKONOS stereo imagery are carried out to demonstrate the effectiveness of the proposed method. It is shown that the proposed method can be applied as an effective way to monitoring the building changes, as well as updating 3D models from one epoch to the other. 相似文献
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Remotely-sensed data products have got unique advantage over conventional data-gathering techniques in the study of urban morphology. The physical parameters like built-up area density, street pattern, population density, urban structure as well as functional characteristics which can be derived from land use/land cover map, are clearly visible on aerial data products. This technique provides synoptic view of the area which makes the study comprehensive and uniform. Sequential aerial photographs and satellite imagery help in studying the growth of urban area and temporal changes in urban structure. These informations are very useful in the planning of city extension. Here an attempt has been made to study the urban morphology of Saharanpur city by using panchromatic aerial photographs on scale 1∶10,000, IRS-1B LISS II geocoded imagery on 1∶50,000 scale and photo-maps on 1∶4000 scale, and the results are very encouraging. 相似文献
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A method for monitoring building construction in urban sprawl areas using object-based analysis of Spot 5 images and existing GIS data 总被引：3，自引：0，他引：3
Laurent Durieux Erwann Lagabrielle Andrew Nelson 《ISPRS Journal of Photogrammetry and Remote Sensing》2008,63(4):399-408
Urban sprawl has been identified as one of the most negative effects of global population growth on the environment and biodiversity. Frequent monitoring of urban sprawl is needed to limit the impact of this ongoing phenomenon. This paper proposes precise monitoring of building construction using an object-based classification methodology applied to Spot 5 images with a 2.5 m resolution. An application at a regional scale on Reunion Island in the Indian Ocean shows that this building extraction methodology has limitations in the production of reference urban maps because of difficulties in defining the shape and the number of buildings compared to classical photo-interpretation of aerial photography. However, these results are of great value for planning in urban sprawl areas where up-to-date information is lacking because of the rapid pace of house construction and residential development. 相似文献
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N. D. Sharma R. Thakur G. L. Kippa B. Marak 《Journal of the Indian Society of Remote Sensing》1984,12(2):1-11
The aerial remote sensing data can be reliable source to obtain an estimate of urban population. A study was carried out in the city of Coimbatore (municipal area) using aerial photoghraphs of scale 1:4000 taken by a metric camera of 300 mm. focal length in the year 1979. The findings obtained by photo-interpretation compared very favourably with the interpolated population census figures for the year 1979, for the municipal area of the city Coimbatore. Dwelling units counted on the aerial photograph for different types of residential areas classified on the basis of size, shape and pattern are the physical indicators of population. Occupancy rate of dwelling units was determined by sampling survey carried out during field visit itself in this particular study. 相似文献
14.
Virtual Cities From Digital Imagery 总被引：1，自引：0，他引：1
E. Gülch 《The Photogrammetric Record》2000,16(96):893-903
Increasing interest is being expressed in the use of virtual cities for many fields of application, ranging from planning and simulation to business, advertising and the games industry. Currently, the extraction of buildings from imagery is costly. However, recent developments in digital photogrammetry aim to produce more rapid and efficient methods of modelling three dimensional objects in urban environments. This paper presents a semi-automatic system for the extraction of buildings from digital aerial imagery with the aid of volumetric primitives. The user is supported by automated tools, for example matching tools, in order to reach the necessary efficiency. With an extraction time of about 20 s per building primitive, this method is competitive in terms of the performance of classical photogrammetric procedures, and also offers additional features for analysis, texture mapping and Internet applications. 相似文献
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利用雷达干涉数据进行城市不透水层百分比估算 总被引：2，自引：0，他引：2
人工不透水层是城市地区的重要特征.作为城市生态环境的关键指数,不透水层百分比(Impervious Surfaces Percentage, ISP)常用于城市水文过程模拟、水质面源污染及城市专题制图等研究中.本文利用ERS-1/2 重复轨道雷达干涉数据,采用分类与回归树(CART)算法探究了雷达遥感在城市ISP估算中的可行性和潜力,并与SPOT5 HRG光学遥感图像的估算结果进行了分析比较.香港九龙港岛实验区的初步研究结果表明,雷达干涉数据在城市不透水层研究中具有一定的应用潜力,特别是裸土和稀疏植被的ISP估算结果要好于光学遥感,这主要得益于雷达干涉数据(特别是长时间相干图像)在人工建筑物和裸土或稀疏植被之间具有很强的区分能力,另外,雷达干涉数据和光学遥感数据间的融合能够提高ISP估算精度. 相似文献
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Urban area building extraction is one of the most challenging problems in photogrammetry. Well-extracted buildings are needed for a variety of applications, such as cartography, building GIS databases for cities, and urban planning. This paper presents a new technique to extract 3D building wire-frames using a robust multi-image line-matching algorithm. Although one pair of images is adequate to find the 3D position of two visibly corresponding image features, it is not sufficient to solve the general building extraction problem due to obscured parts in the building. Four images are used in this research to extract the building wire-frames. First the images are segmented into regions. Regions are then classified into roof regions and non-roof regions based on their size, shape, and intensity values. The roof region boundary pixels are located and used to find the region perimeters. Region correspondence is solved in a pair-wise mode over all images using the epipolar constraint, region size, region shape, and region intensity values. Image lines within the corresponding regions are matched over all images simultaneously by first creating a plane for each region line. Planes are then intersected simultaneously and geometric consistency is used to determine acceptance or rejection. Results with high overlap and sidelap aerial images are presented and evaluated. The results show the completeness and accuracy that this method can provide for extracting complex urban buildings. The average coordinate accuracy is about 0·8 m using 1:4000 scale aerial photographs scanned at 30 μ m. Six buildings were examined; the line detection rate is 98%. 相似文献
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Highly detailed 3D urban terrain models are the base for quick response tasks with indispensable human participation, e.g., disaster management. Thus, it is important to automate and accelerate the process of urban terrain modeling from sensor data such that the resulting 3D model is semantic, compact, recognizable, and easily usable for training and simulation purposes. To provide essential geometric attributes, buildings and trees must be identified among elevated objects in digital surface models. After building ground-plan estimation and roof details analysis, images from oblique airborne imagery are used to cover building faces with up-to-date texture thus achieving a better recognizability of the model. The three steps of the texturing procedure are sensor pose estimation, assessment of polygons projected into the images, and texture synthesis. Free geographic data, providing additional information about streets, forest areas, and other topographic object types, suppress false alarms and enrich the reconstruction results. 相似文献
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Konstantin Greger 《Transactions in GIS》2015,19(1):129-150
Detailed population information is crucial for the micro‐scale modeling and analysis of human behavior in urban areas. Since it is not available on the basis of individual persons, it has become necessary to derive data from aggregated census data. A variety of approaches have been published in the past, yet they are not entirely suitable for use in the micro‐scale context of highly urbanized areas, due mainly to their broad spatial scale and missing temporal scale. Here we introduce an enhanced approach for the spatio‐temporal estimation of building populations in highly urbanized areas. It builds upon other estimation methodologies, but extends them by introducing multiple usage categories and the temporal dimension. This allows for a more realistic representation of human activities in highly urbanized areas and the fact that populations change over time as a result of these activities. The model makes use of a variety of micro‐scale data sets to operationalize the activities and their spatio‐temporal representations. The outcome of the model provides estimated population figures for all buildings at each time step and thereby reveals spatio‐temporal behavior patterns. It can be used in a variety of applications concerning the implications of human behavior in urban areas. 相似文献