James Bethel

CLASS-GUIDED BUILDING EXTRACTION FROM IKONOS IMAGERY

ofstereoIkonosimagery showsthat5-to10-mcontour linescan Recent high-resolution satellite images provide a valuable new bederivedwith thehighesttopographicstandard(Toutin etal., data source for geospatial information acquisition. This paper 2001). As forgeospatial feature extraction for topographicmapaddresses building extraction from Ikonos images in urban ping, Baltsaviaset al.(2001a) andFraser etal.(2001;2002) presareas. The proposed approach uses the classification results ent results on building extraction from Ikonos stereo images. A of Ikonos multispectral images to provide approximate loca- comparative study withthe results obtained fromaerial phototion and shape for candidate building objects. Their fine graphs concludes that about 15 percent of the building areas, as extraction is then carried out in the corresponding panchro- measured in aerial images, cannot be modeled using Ikonos matic image through segmentation and squaring. The ECHO images. An assessment based on 19 GPS surveyed check points classifier is used for supervised classification while the ISODATA atroofcorners suggeststhattheIkonos-derivedbuilding model algorithm is used for unsupervised classification and subse- can reach an accuracy of better than 1 meter both in planimetry quent image segmentation. The classification performance is and elevation (Baltsavias et al., 2001a). Sohn and Dowman evaluated using the classification confusion matrix, while the (2001) used a local Fourier transformation to analyze the domifinal building extraction results are assessed based on the nantorientation angleina buildingcluster andextractrectilinmanually delineated results. A building squaring approach ear building outlines from Ikonos imagery based on a binarybased on the Hough transformation is developed that detects space partitioning tree. Dial et al. (2001) present an investigaand forms the rectilinear building boundaries. A number of tion on automated road extraction in wide suburban roads. sample results are presented to illustrate the approach and Regarding the fundamental methodology in geospatial feademonstrate its efficiency. It is shown that about 64.4 percent ture extraction from aerial and space images, abundant experiof the buildings can be detected, extracted, and accurately ence hasbeen gainedin thepast few years.A collectionof stateformed through this process. Remaining difficulties are high of-the-art articles can be found in the periodical proceedings

Georegistration of airborne hyperspectral image data

A suite of geometric sensor and platform modeling tools has been developed which have achieved consistent subpixel accuracy in orthorectification experiments. Aircraft platforms in turbulent atmospheric conditions present unique challenges and have required creative modeling approaches. The geometric relationship between an image point and a ground object has been modeled by rigorous photogrammetric methods. First and second order Gauss-Markov processes have been used to estimate the platform trajectory. These methods have been successfully applied to HYDICE and HyMap data sets. The most important contributors to the subpixel rectification accuracy have been the first order Gauss-Markov model with control linear features.

Extracting Urban Road Networks from High-resolution True Orthoimage and Lidar

Automated or semi-automated feature extraction from remotely collected, large scale image data has been a challenging issue in digital photogrammetry for many years. In the feature extraction field, fusing different types of data to provide complementary information about the objects is becoming increasingly important. In this paper, we present a newly developed approach for the automatic extraction of urban area road networks from a true orthoimage and lidar assuming the road network to be a semi-grid pattern. The proposed approach starts from the subdivision of a study area into small regions based on homogeneity of the dominant road directions from the true orthoimage. Each region’s road candidates are selected with a proposed free passage measure. This process is called the “acupuncture” method. Features around the road candidates are used as key factors for an advanced “acupuncture method” called the region-based acupuncture method. Extracted road candidates are edited to avoid collocation with non-road features such as buildings and grass fields. In order to produce a building map for the prior step, a first-last return analysis and morphological filter are used with the lidar point cloud. A grass area thematic map is generated by supervised classification techniques from a synthetic image, which contains the three color bands from the true orthoimage and the lidar intensity value. Those non-road feature maps are used as a blocking mask for the roads. The accuracy of the result is evaluated quantitatively with respect to manually compiled road vectors, and a completeness of 80 percent and a correctness of 79 percent are obtained with the proposed algorithm on an area of 1,081,600 square meters.

Geometric alignment and calibration of a photogrammetric image scanner

Abstract A description is given of the architecture of a high resolution, photogrammetric image scanner. A sequence of steps is given to mutually align a linear sensor, an objective lens, and a two-axis stage. The recommended alignment sequence is supported by derivations from geometric optics. The overall system geometry is then verified by scanning and analyzing a grid plate yielding RMS errors of 5 μm in X and Y.

A Study of Trajectory Models for Satellite Image Triangulation

Many Spaceborne imagery products are provided with metadata or support data having diverse types, representations, frequencies, and conventions. According to the variability of metadata, a compatible physical sensor model approach must be constructed. Among the three components of the sensor model, i.e., trajectory model, projection equations, and parameter subset selection, the construction of the position and attitude trajectory is closely linked with the availability and type of support data. In this paper, we show how trajectory models can be implemented based on support data from six satellite image types: QuickBird, Hyperion, SPOT-3, ASTER, PRISM, and EROS-A. Triangulation for each image is implemented to investigate the feasibility and suitability of the different trajectory models. The results show the effectiveness of some of the simple models while indicating that careful use of dense ephemeris information is necessary. These results are based on having a number of high quality ground control points.

DEM alignment and registration in interferometric SAR processing and evaluation

Interferometric synthetic aperture radar (InSAR) processing, if lacking high quality ground control points (GCPs), may produce large errors in the final DEM. Some kind of alignment or registration can reduce these errors. This paper evaluates the accuracy of InSAR processed digital elevation models (DEM), against a high resolution DEM. InSAR DEMs were aligned and least-squares registered with USGS, 1/3 arc second NED. The accuracy evaluations after registration show InSAR DEMs alignment and registration can eliminate DEM errors caused by lack of accurate GCPs. In some cases, this process improves the accuracy of the InSAR DEM even more efficiently than including GCPs into InSAR processing.

Principles and Evaluation of Autostereoscopic Photogrammetric Measurement

Stereoscopic perception is a basic requirement for photogrammetric 3D measurement and accurate geospatial data collection. Ordinary stereoscopic techniques require operators wearing glasses or using eyepieces for interpretation and measurement. However, the recent emerging autostereoscopic technology makes it possible to eliminate this requirement. This paper studies the principles and implementation of autostereoscopic photogrammetric measurement and evaluates its performance. We first describe the principles and properties of the parallax barrier-based autostereoscopic display used in this study. As an important metric property, we quantitatively present the autostereoscopic geometry, including viewing zones and the boundary of a viewer’s movement for autostereoscopic measurement. A toolkit AUTO3D is developed that has common photogrammetric functions. The implementation principles are described by addressing the differences compared to the ordinary stereoscopic technology. To evaluate the performance of the autostereoscopic measurement, images at a resolution of 25 � m and 50 � m are measured by a group of seven (7) operators, who are asked to digitize 18 well-defined roof points and 18 ground points. These results are evaluated by comparing the same measurements obtained from a popular stereoscopic photogrammetric workstation. It is shown that the precision of autostereoscopic measurement is about 16 percent to 25 percent lower than the conventional stereo workstation.

Modern Technologies for Design Data Collection

Design data collection involving the use of Lidar instrument, in conjunction with Global Positioning System (GPS) proves to be very effective. Data required to model two bridges over the I-70 were collected on a single day, involving five and six sessions with Lidar equipment. Even though the data were collected on two bridges, it did not cause any disruption of the traffic, either on the Interstate or on the bridges. A major cause of concern during survey activities, particularly along interstates is safety, both for the motorists as well as the people involved in data collection. Lidar data collection was found to be extremely safe in both aspects. The whole process of collecting Lidar data and GPS coordinates for control was completed in 2 days for both bridges. Office work involved combining the GPS data with conventional survey data to bring control on six pre-selected points within the Lidar point cloud. This control information was later used to bring the point cloud into a geographic coordinate system. This survey provided the means to compare the 3D point cloud with bridge designs that were created using other methods of data collection. It was found that the 3D point cloud exhibits a very high degree of accuracy, both internally and also when georeferenced independently using GPS and conventional control survey. The Lidar model was compared to the MXRoad data model provided by Indiana Department of Transportation (INDOT). The discrepancies between the two models were not larger than 0.125 ft/3.81 cm horizontally and 0.05 ft/1.52 cm vertically. The data collected completely modeled the bridge and the accuracy of the data ensures that any model of the bridge, either as a whole or in part, will correctly reflect the current state of the bridge. The data collected can also be used for various applications including cut-and-fill estimates, modeling the state of the bridge, making measurements on various parts of the bridge. A cause of concern is the amount of data involved. As millions of 3D points are collected, popular Computer Aided Design/Geographic Information System (CAD)/(GIS) packages are unable to deal with it. For this reason proprietary software, designed particularly to handle such huge volumes of data involved, was used for analyzing this data. However, it is possible to export data from this software to other commonly used CAD packages. Using satellite imagery instead of aerial photos may provide faster results to investigate the project area. Conversion of the MXROAD data into the ArcGIS system is not easy, but it is hoped that this problem can be solved very easily. The Lidar point cloud should be processed and a CAD model of the data should be obtained to obtain more useful information. With the help of the GIS a variety of data sources and types can be integrated, visualized and used to make about resource management, and perform modeling and analysis. GIS helps organize bridge management information contained in various forms, such as inspection reports, rehab plans, and CAD files. Maintenance management and asset valuation may be enhanced with GIS and linear referencing systems.

Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization

Abstract. Light detection and ranging (LIDAR) has become a widely used tool in remote sensing for mapping, surveying, modeling, and a host of other applications. The motivation behind this work is the modeling of piping systems in industrial sites, where cylinders are the most common primitive or shape. We focus on cylinder parameter estimation in three-dimensional point clouds, proposing a mathematical formulation based on angular distance to determine the cylinder orientation. We demonstrate the accuracy and robustness of the technique on synthetically generated cylinder point clouds (where the true axis orientation is known) as well as on real LIDAR data of piping systems. The proposed algorithm is compared with a discrete space Hough transform-based approach as well as a continuous space inlier approach, which iteratively discards outlier points to refine the cylinder parameter estimates. Results show that the proposed method is more computationally efficient than the Hough transform approach and is more accurate than both the Hough transform approach and the inlier method.

Laser Mobile Mapping Standards and Applications in Transportation

This report describes the work that was done to support the development of a chapter for the Indiana Department of Transportation (INDOT) Survey Manual on Mobile Mapping. The work includes experiments that were done, data that were collected, analysis that was carried out, and conclusions that were drawn about accuracy of Mobile Terrestrial Laser Scanning (MTLS) systems. The resulting Manual chapter, located in the appendix, defines standards and procedures for preparing, collecting, editing, delivering, exploiting, and archiving electronic mapping data that were created for the INDOT. The purpose of the standards and procedures within this manual is to obtain statewide uniformity within the INDOT combined Aerial/Ground Survey process, to establish and maintain MTLS Standards for INDOT and contracted consultants, and to allow for all of the project data to be effectively managed from conception to completion. These standards apply to all projects delivered to INDOT by contracted consulting firms, or exchanged internally within INDOT or between state agencies. The standards and procedures are the result of mobile terrestrial laser scanning surveys of two test sites - one urban and one freeway - created for this project. After establishing reference control points on the sites, each site was surveyed by four mobile terrestrial laser scanning vendors. The results from the vendor data over the test sites, in addition to information in published literature, are the basis for the specifications manual. The proposed chapter for the Survey Manual is in Appendix E of this report.