Jie Shan

Followers

Following

Co-authors

Public Views

Interests

Uploads

Papers by Jie Shan

3D Modeling and Visualization of Single Tree Lidar Point Cloud Using Matrixial Form

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Dec 31, 2023

Tree modeling and visualization still represent a challenge in the Light Detecting And Ranging (L... more Tree modeling and visualization still represent a challenge in the Light Detecting And Ranging (LiDAR) area. Starting from the segmented tree point clouds, this paper presents an innovative tree modeling and visualization approach. The algorithm simulates the tree point cloud by a rotating surface. Three matrixes, X, Y, and Z are calculated by considering the middle of the projected tree point cloud on the horizontal plane. This mathematical form not only allows tree modeling and visualization, but also permits the calculation of geometric characteristics and parameters of the tree. The superimposition of the tree point cloud over the constructed model confirms its high accuracy where all the points of the tree cloud are within the constructed model. The tests with multiple single trees demonstrate an overall average fit between 0.3 and 0.89 m. The built tree models are also compliant with the Open Geospatial Consortium (OCG) City GML standards at the level of a physical model. This approach opens a door to numerous applications for visualization, computation, and study of forestry and vegetation in urban as well as rural areas.

Download

Urban building extraction through object-based image classification assisted by digital surface model and zoning map

International Journal of Image and Data Fusion, Jan 2, 2016

This study develops an object-based image classification methodology for urban land covers classi... more This study develops an object-based image classification methodology for urban land covers classification, using very high resolution aerial images, elevation data and city zoning maps. Logically structured classification rules based on spectral, spatial and contextual features of the segmented objects are first created and tested over a small urban area. The same rule set is then transferred and tested on two similar images covering larger urban areas. The land cover classification results through the transferability of the rule set prove the effectiveness of the methodology and produce satisfactory classification results with an overall accuracy of 91% as against 96% that was achieved over the small representative training area. The classification methodology based on the integrated use of multiple data produces satisfactory land cover classification. Its transferability considerably reduces both the processing time and the analyst’s efforts.

Segmentation and Reconstruction of Polyhedral Building Roofs From Aerial Lidar Point Clouds

IEEE Transactions on Geoscience and Remote Sensing, Mar 1, 2010

This paper presents a solution framework for the segmentation and reconstruction of polyhedral bu... more This paper presents a solution framework for the segmentation and reconstruction of polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The eigenanalysis is first carried out for each roof point of a building within its Voronoi neighborhood. Such analysis not only yields the surface normal for each lidar point but also separates the lidar points into planar and nonplanar ones. In the second step, the surface normals of all planar points are clustered with the fuzzy k-means method. To optimize this clustering process, a potential-based approach is used to estimate the number of clusters, while considering both geometry and topology for the cluster similarity. The final step of segmentation separates the parallel and coplanar segments based on their distances and connectivity, respectively. Building reconstruction starts with forming an adjacency matrix that represents the connectivity of the segmented planar segments. A roof interior vertex is determined by intersecting all planar segments that meet at one point, whereas constraints in the form of vertical walls or boundary are applied to determine the vertices on the building outline. Finally, an extended boundary regularization approach is developed based on multiple parallel and perpendicular line pairs to achieve topologically consistent and geometrically correct building models. This paper describes the detail principles and implementation steps for the aforementioned solution framework. Results of a number of buildings with diverse roof complexities are presented and evaluated.

Download

Principal Component Analysis for Hyperspectral Image Classification

The availability of hyperspectral images expands the capability of using image classification to ... more The availability of hyperspectral images expands the capability of using image classification to study detailed characteristics of objects, but at a cost of having to deal with huge data sets. This work studies the use of the principal component analysis as a preprocessing technique for the classification of hyperspectral images. Two hyperspectral data sets, HYDICE and AVIRIS, were used for the study. A brief presentation of the principal component analysis approach is followed by an examination of the information contents of the principal component image bands, which revealed that only the first few bands contain significant information. The use of the first few principal component images can yield about 70 percent correct classification rate. This study suggests the benefit and efficiency of using the principal component analysis technique as a preprocessing step for the classification of hyperspectral images.

Download

Building Extraction from LiDAR Point Clouds Based on Clustering Techniques

Urban Terrain and Building Extraction from Airborne LIDAR Data

Object-Based Data Integration and Classification for High-Resolution Coastal Mapping

Taylor & Francis series in remote sensing applications, Dec 9, 2009

Color correction of texture images for true photorealistic visualization

Isprs Journal of Photogrammetry and Remote Sensing, May 1, 2010

Photorealistic visualization combines 3-D geometric models with their texture images to render th... more Photorealistic visualization combines 3-D geometric models with their texture images to render the virtual world. This paper points out that the texture images should be radiometrically corrected to achieve a true realistic appearance. Such a correction should include not only the color adjustment among images of the same object, but also the shade variation caused by the illumination change. The objective of this study is to correct the input texture images such that their shade varies when being rendered under different illumination directions. To achieve this goal we first apply the specular-to-diffuse mechanism based on the dichromatic reflection model to remove the specular component from the texture image. The resultant diffusion-only image then undergoes a shade correction to produce a normalized shadefree texture image. In the final step, shades under any illumination are produced to achieve a true photorealistic effect. Presented in the paper are the principles and methods for such corrections, along with a performance evaluation based on the graphic and numerical results for roof texture images.

Download

The International Charter and Flood Mapping

Download

An Approach to Single Image Automatic Orientation and Point Determination by Using Ortho‐Images and a Dtm

Photogrammetric Record, Oct 1, 2001

This paper describes an approach to single image automatic orientation and point determination by... more This paper describes an approach to single image automatic orientation and point determination by using current ortho-images and a DTM, and the experience gained in its implementation. The procedure proposed automatically extracts and matches feature points in evenly distributed patches on aerial images and ortho-images. A large number of image measurements (up to several thousand) are obtained in this process and are included in a robust space resection to determine the orientation parameters of the aerial image. For point determination with a single image, a method is formalised which integrates the DTM interpolation into the space resection so that the 3D ground coordinates of the image points can be determined in a unified mathematical model. Tests and analyses of this method show that the large number of automatic image measurements relieves the requirement for complicated and precise feature extraction and matching methods. The ground points obtained from single image intersection have an accuracy of approximately 1 pixel in planimetry, which fulfils the requirement for ortho-image updating. The elevation accuracy is mainly dependent on the quality of the current DTM and the interpolation method applied to it. K: DTM, image orientation, ortho-image, point determination I R from government and commercial organisations shows that the ortho-image is becoming an indispensable component in geographical information systems (GISs) and its cycle for updating is shortening to 4 to 5 years or less (Baltsavias, 1993; Knabenschuh, 1999). Therefore, an efficient method is required which can best utilise existing database information, such as ortho-images and digital terrain models (DTMs), to update the current GIS database. Exterior image orientation is the first step in this process. One of the main concerns in automatic processing is its accuracy (Ackermann, 1996). In order to achieve a high accuracy, the proposed approach is based on the extraction of

Download

Statistical analysis on the evolution of OpenStreetMap road networks in Beijing

Physica D: Nonlinear Phenomena, Feb 1, 2015

ABSTRACT In recent years, extensive efforts have been paid on the investigation of OpenStreetMap ... more ABSTRACT In recent years, extensive efforts have been paid on the investigation of OpenStreetMap (OSM) in developed countries, but little attention has been given to the cities in developing countries. This paper presents the results regarding the evolution of OSM road networks in Beijing, China, from four aspects. First, findings from general analysis indicate that (1) the overall growth pattern could be mainly explained by the increasing number of volunteers and their mapping contributions. Second, findings from geometric analysis suggest: (2) mapping intensity exhibits heavy-tailed pattern both for a certain time period and across time; (3) mapping direction moves from outskirts to downtown distinguished from other regions; and (4) mapping behaviors are mainly constrained by the underlying structure of road networks. Third, results of topological analysis indicate that (5) OSM road networks resemble the growth of real road networks and are undergoing an evolution process depicted by exploration and densification. Last, from the perspective of centrality analysis, (6) two kinds of nodes are identified with the ones accounting for the exploration and the other ones for the densification, which further hints the evolution process of continuous strong exploration accompanied by weak densification.

Urban DEM Generation from Raw Lidar Data

Photogrammetric Engineering and Remote Sensing, Feb 1, 2005

This paper addresses the separation of ground points from raw lidar data for bald ground digital ... more This paper addresses the separation of ground points from raw lidar data for bald ground digital elevation model (DEM) generation in urban areas. This task is considered to be a labeling process through which a lidar point is labeled as either a ground point or a non-ground point. Mathematical formulation is presented to define the ground. A new approach is proposed that conducts one-dimensional labeling in two opposite directions followed by a linear regression, both along the lidar scan line profile. The study shows that the one-dimensional characteristic makes the calculation efficient, and the reliability is assured by the bidirectional labeling process. Lidar data over suburban and downtown Baltimore (Maryland), Osaka (Japan), and Toronto (Canada) are used for the study. Quality assessment is designed and conducted to investigate the performance of the labeling approach by using manually-selected ground truth. It is shown that 2.7 percent ground points are wrongly labeled as building points, and 2.6 percent building points are mistakenly labeled as ground points over the four study areas. Detailed graphic and numerical results are provided to illustrate the proposed labeling approach and its performance for complex urban areas.

Download

An algorithm for object reconstruction without interior orientation

Isprs Journal of Photogrammetry and Remote Sensing, Dec 1, 1996

This paper presents a novel algorithm for object reconstruction without interior orientation. Fir... more This paper presents a novel algorithm for object reconstruction without interior orientation. First we introduce the Thompson and Longuet-Higgins equation as well as the fundamental matrix. After defining the affine model, we show that some of its components can be linearly withdrawn from the findamental matrix, which in turn is linearly determined up to a scale factor by minimal eight

Study on Accuracy of 1-Degree DEM Versus Topographic Complexity Using GIS Zonal Analysis

Journal of Surveying Engineering-asce, May 1, 2003

Zonal analysis in geographic information systems is a useful and convenient tool to study the acc... more Zonal analysis in geographic information systems is a useful and convenient tool to study the accuracy of the digital elevation model ͑DEM͒ in terms of topographic complexity, which is defined in this paper as the change in terrain slope or slope change. The accuracy of the U.S. Geological Survey 1-degree DEM over two test areas is studied by comparing it with the USGS 7.5-min DEM. The statistical quantities of the DEM errors are studied and modeled using various mathematical functions. It is shown that the standard deviation of the 1-degree DEM can be largely approximated with a linear function of the slope change, while its minimum and maximum errors remain almost unchanged and occur in all slope change zones as a behavior independent of the terrain complexity.

Download

Detection and Tracking of Pedestrians Using Doppler LiDAR

Remote Sensing, Jul 27, 2021

Pedestrian detection and tracking is necessary for autonomous vehicles and traffic management. Th... more Pedestrian detection and tracking is necessary for autonomous vehicles and traffic management. This paper presents a novel solution to pedestrian detection and tracking for urban scenarios based on Doppler LiDAR that records both the position and velocity of the targets. The workflow consists of two stages. In the detection stage, the input point cloud is first segmented to form clusters, frame by frame. A subsequent multiple pedestrian separation process is introduced to further segment pedestrians close to each other. While a simple speed classifier is capable of extracting most of the moving pedestrians, a supervised machine learning-based classifier is adopted to detect pedestrians with insignificant radial velocity. In the tracking stage, the pedestrian’s state is estimated by a Kalman filter, which uses the speed information to estimate the pedestrian’s dynamics. Based on the similarity between the predicted and detected states of pedestrians, a greedy algorithm is adopted to ...

Download

Modeling Multi-Rotunda Buildings at LoD3 Level from LiDAR Data

Remote Sensing

The development of autonomous navigation systems requires digital building models at the LoD3 lev... more The development of autonomous navigation systems requires digital building models at the LoD3 level. Buildings with atypically shaped features, such as turrets, domes, and chimneys, should be selected as landmark objects in these systems. The aim of this study was to develop a method that automatically transforms segmented LiDAR (Light Detection And Ranging) point cloud to create such landmark building models. A detailed solution was developed for selected buildings that are solids of revolution. The algorithm relies on new methods for determining building axes and cross-sections. To handle the gaps in vertical cross-sections due to the absence of continuous measurement data, a new strategy for filling these gaps was proposed based on their automatic interpretation. In addition, potential points associated with building ornaments were used to improve the model. The results were presented in different stages of the modeling process in graphic models and in a matrix recording. Our wor...

Download

Detection and Tracking of Pedestrians Using Doppler LiDAR

Remote Sensing

Download

An exploratory analysis on the evolution of the US airport network

Physica A: Statistical Mechanics and its Applications, 2014

ABSTRACT Airport network has a nontrivial impact on shaping the development of a country or regio... more ABSTRACT Airport network has a nontrivial impact on shaping the development of a country or region, and decision makers or researchers can benefit from its evolution characteristics. This paper presents an exploratory analysis on the evolution of the US airport network from 1990 to 2010. Generally, we find that (1) the USAN has experienced a drastic change in both its structure and traffic amount in the year 2002. Particularly, regarding the entire USAN, we show that (2) it preserves the scale-free, small-world, and disassortative mixing properties over time which is consistent with the previous studies. Thereafter, the evolution of the USAN is examined from two perspectives: stable cities that never disappear in the time period and new cities that only appear in certain years. Findings from the first perspective imply that (3) stable cities form the backbone of the USAN over time and their structural similarity over time shows regularity. On the other hand, results from the second one indicate that (4) the USAN is undergoing a process of continuous densification intertwined with intense exploration in 1991 and 2002, which consequently leads to a stable USAN.

Object-based urban land cover classification using rule inheritance over very high-resolution multisensor and multitemporal data

GIScience & Remote Sensing, 2015

Very high spatial and temporal resolution remote sensing data facilitate mapping highly complex a... more Very high spatial and temporal resolution remote sensing data facilitate mapping highly complex and diverse urban environments. This study analyzed and demonstrated the usefulness of combined high-resolution aerial digital images and elevation data, and its processing using object-based image analysis for mapping urban land covers and quantifying buildings. It is observed that mapping heterogeneous features across large urban areas is time consuming and challenging. This study presents and demonstrates an approach for formulating an optimal land cover classification rule set over small representative training urban area image, and its subsequent transfer to the multisensor, multitemporal images. The classification results over the training area showed an overall accuracy of 96%, and the application of rule set to different sensor images of other test areas resulted in reduced accuracies of 91% for the same sensor, 90% and 86% for the different sensors temporal data. The comparison of reference and classified buildings showed ±4% detection errors. Classification through a transferred rule set reduced the classification accuracy by about 5%–10%. However, the trade-off for this accuracy drop was about a 75% reduction in processing time for performing classification in the training area. The factors influencing the classification accuracies were mainly the shadow and temporal changes in the class characteristics.

Building Extraction from LiDAR Point Clouds Based on Clustering Techniques

Principles and Processing, 2008

Jie Shan

Uploads

Papers by Jie Shan

Log In