Xutong Niu

Impact of Imaging Geometr y on 3D Geopositioning Accuracy of Ster eo Ikonos Imager y

Special Ikonos data acquisition and investigation were conducted to study the relationship between three-dimensional (3D) geopositioning accuracy and stereo imaging geometry, in particular, convergence angles. Six Ikonos images (four on one track and two on another track) were collected for a test site at Tampa Bay, Florida, in 2004 and 2007, respectively. Different combinations of Ikonos stereo image pairs, both along-track and cross-track, were formed. Using the highresolution satellite image processing system developed at The Ohio State University, DGPS (Differential Global Positioning System) controlled ground control points, and a number of check points, we demonstrated: (a) The convergence angle plays an important role in along-track or cross-track stereo mapping, especially in improvement of the accuracy in the vertical direction; (b) Regardless of stereo configuration (alongtrack or cross-track), the accuracy in the X (cross-track) direction is better than that in the Y (along-track) direction; and (c) Although there is a slight correlation between the convergence angle and the accuracy in the Y (along-track) direction in the case of along-track stereo configuration, no distinct relationship is found in the X (cross-track) direction. Similarly, improvement of the horizontal accuracies is found with increased convergence angles when dealing with crosstrack stereo pairs.

Geometric Integration of Aerial and High-Resolution Satellite Imagery and Application in Shoreline Mapping

This paper investigates the geopositioning accuracy achievable from integrating IKONOS and QuickBird satellite stereo image pairs with aerial images acquired over a region at Tampa Bay, Florida. The results showed that the accuracy is related to a few factors of imaging geometry. For example, the geopositioning accuracy of a stereo pair of IKONOS or QuickBird images can be improved by integrating a set of aerial images, even just a single aerial image or a stereo pair of aerial images. Shorelines derived from the IKONOS and QuickBird stereo images, particularly the vertical positions, are compared with the corresponding observations of water-penetrating LiDAR and water gauge stations and proved that differences are within the limit of the geopositioning uncertainty of the satellite images.

Digitalization of coastal management and decision making supported by multi-dimensional geospatial information and analysis

This paper summarizes the results and outcomes of our NSF Digital Government project. During four years, this project concentrated on investigating, integrating and developing geospatial technologies to enhance the operational capabilities of federal, state, and local agencies responsible for coastal management and decision making. Successful collaborations have been established among research laboratories and government agencies in the areas of data collection and analysis, hydrodynamic modeling, development of web-based systems, and real-world applications of research results.

A Vision for Cyberinfrastructure for Coastal Forecasting and Change Analysis

This paper gives an overview of a recently initiated cyberinfrastructure project at The Ohio State University. This project proposes to develop and evaluate a cyberinfrastructure component for environmental applications. This will include developments in middleware, model integration, analysis, and mining techniques, and the use of a service model for supporting two closely related applications. These applications will be real-time coastal nowcasting and forecasting, and long-term coastal erosion analysis and prediction.

A webGIS for spatial data processing, analysis, and distribution for the MER 2003 mission

During the Mars Exploration Rover (MER) 2003 mission, the twin rovers Spirit and Opportunity have been sending immense amounts of valuable imagery and data to Earth, enabling scientists and engineers to find evidence of water on Mars and to conduct exciting Mars research. This paper presents the results of efforts made at the Mapping and GIS Laboratory of The Ohio State University (OSU) for the development and application of a web-based GIS, the OSU Mars WEBGIS, to support rover localization (i.e., position determination) and topographic mapping activities of the mission. Global and local spatial information and map products of the two landing sites are provided through the WEBGIS. The products include mosaics, orthophotos and digital terrain models (DTMs) derived from orbital and rover images; ground information is supplied as traverse maps, traverse profiles and 3D coordinates, slope maps, and energy index maps; analysis tools are also developed for effective visualization and exploration of the spatial information and products. The system has been successfully applied to the 2003 MER mission and has the potential for future Mars landed missions such as the 2009 Mars Science Laboratory (MSL) mission.

Integration of mobile GIS and wireless technology for coastal management and decision-making

Geographic Information Systems (GIS) have become a crucial support tool for governmental decision makers at many levels. Internet-based GIS applications provide unique services for the presentation of spatial data and mapping products to a broad range of audiences. Furthermore, compact and portable mapping devices provide new opportunities for the expansion of Internet-based GIS applications. In this paper, we present results of the research and development of a web-based, mobile, spatial system for coastal management, and decision-making that integrates these technologies. The developed system consists of an on-site mobile spatial subsystem, a web-based shoreline erosion awareness subsystem, and a coastal structures permit subsystem. The system is designed and developed for applications in the Lake Erie area and has the potential to be adapted and applied in other coastal areas.

An Improved Approach to Automatic Recognition of Civil Infrastructure Objects

Abstract Civil infrastructure objects are important elements in GIS applications. Due to the wide variety of object types, automatic recognition of infrastructure objects from imagery has been a challenging issue for the last two decades. Different approaches have been developed for recognition of buildings, one kind of infrastructure object most frequently dealt with in GIS. by defining and employing individual criteria. A Hopfield neural network can effectively combine different criteria in an overall network structure for a global optimization in finding object. In this paper we develop a holistic feature extraction approach including edge extraction, noise edge elimination by Gabor filters, contour extraction based on morphological operations, polygon simplification by local Hough transform, and building roof candidate selection using central contour sequence moment. In addition, shadows associated with buildings are extracted. This improved feature extraction approach greatly enhances the quality of recognition of objects, such as peaked-roofed and flat-roofed buildings, by a Hopfield neural network that accommodates similarity measures using the extracted features in a structured way. The achieved results demonstrate a promising approach for building recognition and can be extended to other infrastructure objects.