Browsing by Author "Chen, Liang-Chien"

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DEM-Aided Block Adjustment for Satellite Images With Weak Convergence Geometry
(2010-04-01)
Teo, Tee-Ann
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Chen, Liang-Chien
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Liu, Chien-Liang
;
Tung, Yi-Chung
;
Wu, Wan-Yu
To acquire the largest possible coverage for environmental monitoring, it is important in most situations that the overlapping areas and the convergent angles of respective satellite images be small. The traditional bundle adjustment method used in aerial photogrammetry may not be the most suitable for direct orientation modeling in situations characterized by weak convergence geometry. We propose and compare three block adjustment methods for the processing of satellite images using the digital elevation model (DEM) as the elevation control. The first of these methods is a revised traditional bundle adjustment approach. The second is based on the direct georeferencing approach. The third is a rational function model with sensor-oriented rational polynomial coefficients. A collocation technique is integrated into all three methods to improve the positioning accuracy. Experimental results indicate that using the DEM as an elevation control can significantly improve the geometric accuracy as well as the geometric discrepancies between images. This is the case for all three methods. Moreover, the geometric performance of the three methods is similar. There is a significant improvement in geometric consistency between overlapping SPOT images with respect to single image adjustment for steep areas.
Geometric Integration of Heterogeneous Models for Multisatellite Image Positioning
(2012-07-01)
Chen, Liang-Chien
;
Chang, Wen-Chi
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Teo, Tee-Ann
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土木工程學系
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Department of Civil Engineering
With the wider availability of more and more images acquired from various satellites, the integration of different orientation models for different sensors has become an important task in order to maintain geometrical consistency. This study combines two heterogeneous geometric correction models, namely, direct georeferencing and the rational function model for multi-satellite image positioning. Two types of adjustment models, collocation-based block adjustment (CBBA) and collocation-aided block adjustment (CABA), are proposed to reach the goal. The former is based on the concept that the adjustment is first performed on individual images, and then, all images are integrated. Discrepancies are compensated for by least squares collocation (LSC). The latter method entails simultaneous adjustment of the two heterogeneous models followed by LSC. Experimental results indicate that the proposed method can significantly improve the geometric accuracy as well as reduce geometric discrepancies between images. We also demonstrate that CABA is slightly better than CBBA.
High-resolution depth and coastline over major atolls of South China Sea from satellite altimetry and imagery
(2016-04)
Hsiao, Yu-Shen
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Hwang, Cheinway
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Cheng, Yung-Sheng
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Chen, Liang-Chien
;
Hsu, Hung-Jui
Current bathymetric models for the South China Sea (SCS) are largely based on predicted depths from gravity and sparse single-beam echo-sounder measurements. Such models lack high-resolution coastlines and shallow water bottom features around atolls and islands. This study refines the gravity field of the SCS using sea surface heights from measurements of satellite altimeter Geosat/GM, ERS-1/GM, Jason-1/GM and the original Cryosat-2. A new one-minute gravity anomaly grid is determined. The modeled gravity anomalies show a 6-mgal RMS discrepancy with shipborne measurements in shallow waters. An altimeter-only bathymetric model is derived from the new gravity grid by the gravity-geological method that uses the latest global and regional models of the ocean depth and marine gravity as a priori knowledge. The new model outperforms current SCS bathymetric models and is accurate to 100 m, based on comparison with multi-beam depth measurements. Optical images from IKONOS-2, QuickBird-2, GeoEye-1, WorldView-1-2 and -3, are rectified and digitized to derive the zero (coastline) and 20-m depth contours (reef lines) around 44 atolls, which are integrated with the altimeter-only depths, giving significantly improved accuracies and spatial resolutions in modeled depths. The improvement percentages of coastlines by the satellite imagery range from 50% to 97% at 41 of the 44 atolls. We establish a webpage for free access to the optical and depth images, and the depth and gravity grids. We will continue to update satellite images, altimeter-derived gravity grids and bathymetric models over major atolls of the SCS. (C) 2016 Elsevier Inc. All rights reserved.
Multi-type change detection of building models by integrating spatial and spectral information
(2012)
Chen, Liang-Chien
;
Huang, Chih-Yuan
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Teo, Tee-Ann
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土木工程學系
;
Department of Civil Engineering
Detecting building changes followed by updates is preferable for efficient revisions to building models. Additionally, more change types can be detected with spatial information provided by building models for reducing land surveying work. Therefore, for efficient building of model revision and land surveys, this work applies a new multi-type change detection scheme with new light detection and ranging (LIDAR) point clouds, new aerial images and existing building models. By integrating the spatial information from LIDAR data and image-based spectral information, this work identifies changes to existing buildings and identifies newly built and changed buildings. To provide an initial value for further revisions, new building regions are generated from change detection results. Experimental results demonstrate that the proposed scheme has high accuracy for both change type determination and building region generation. To provide comprehensive observations, experimental results deemed unreliable are scrutinized.