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Wang W.,Key Laboratory of Disaster Reduction and Emergency Response Engineering | Zhao L.,Satellite Surveying and Mapping Application Center
2011 International Symposium on Image and Data Fusion, ISIDF 2011 | Year: 2011

In this paper, 5 schemes of compensation models for Rational Function Model (RFM) is proposed to improve stereo geolocation accuracy of GeoEye-1. And experimentation is carried out using stereo pair of Hobart, Australia. The results show that the accuracy of 5 schemes is similar, and with high accurate and well-distributed Ground Control Points (GCPs) the planimetry and elevation accuracy of GeoEye-1 stereo imagery pairs are both better than 0.5-meter and meet the specification for 1:5,000 topographic map of China. © 2011 IEEE.

Zhao L.,Satellite Surveying and Mapping Application Center | Wang W.,Key Laboratory of Disaster Reduction and Emergency Response Engineering | Liu F.,Chinese Academy of Surveying and Mapping | Xia X.,Information Institute of Photogrammetry and Remote Sensing of Yunnan Province | And 2 more authors.
2011 International Symposium on Image and Data Fusion, ISIDF 2011 | Year: 2011

In this paper, the specifications of WorldView-1 and its payloads are introduced, and seven polynomial adjustment models used to improve the vendor-provided Rational Function Model (RFM) accuracy are discussed in detail. WorldView-1 images of mountainous area of Yunnan Province are used to test the correction accuracy of these adjustment models. Results show that the accuracy of seven modes is similar when using well-distributed GCPs with high accuracy and the planimetry RMS errors are better than 1.6 pixels (0.9 meter). The correction accuracy of different polynomial RFM adjustment models using sparse, badly-distributed GCPs is analyzed in this paper. Results show that with the degradation of GCPs accuracy, the accuracy of independent check points(ICPs) using zero order polynomial adjustment model remains stable, while that of one order and two order polynomial adjustment models degrade distinctly. Experiments show that zero-order polynomial RFM adjustment is the simplest, most adaptive and has highest accuracy for WorldView-1 image, and it is recommended to be used in difficult area mapping with sparse or badly-distributed GCPs. © 2011 IEEE.

Ye J.,Key Laboratory of Disaster Reduction and Emergency Response Engineering | Ye J.,Fujian Normal University | Ye J.,Center for Monitoring Research | Ye J.,Space Star Technology | And 5 more authors.
Intelligent Systems and Decision Making for Risk Analysis and Crisis Response - Proceedings of the 4th International Conference on Risk Analysis and Crisis Response, RACR 2013 | Year: 2013

Due to the special geographical location and topography features, the flood disasters of the coastal cities in southeast China often share the common characteristics of flood, waterlogging and tide meeting together. The paper takes Putian city as an example, analyzes the reasons, and proposes measures to reduce the risk of flood disasters, which will provide a scientific basis for urban flood control and mitigation. © 2013 Taylor & Francis Group.

Li C.,Central China Normal University | Li C.,Key Laboratory of Disaster Reduction and Emergency Response Engineering | Shi W.,Hong Kong Polytechnic University | Shi W.,Wuhan University
IEEE Geoscience and Remote Sensing Letters | Year: 2014

Imagery registration and rectification is a process of transforming different sets of data into one coordinate system. A new model, i.e., the generalized-line-based iterative transformation model (GLBITM), is proposed by integrating the line-based transformation model (LBTM) and generalized point photogrammetry (GPP). First, the initial value of an affine transformation is acquired by LBTM. Then, on the basis of ground control lines (GCLs), not ground control points, the linear feature adjustment model with GPP is extended to a quadratic polynomial model and utilized to iteratively solve transformation coefficients. This process eliminates the translation amount and recalculates the scale and rotation coefficients. The authors suggest an iterative method with variable weights that is based on posterior variance estimation to improve quality control. A significant characteristic of the GLBITM is that the two endpoints of the corresponding GCLs are not necessarily conjugate points. The GLBITM integrates the advantages of the LBTM and GPP and avoids their respective shortfalls. Finally, this experiment verifies that the GLBITM gives correct, robust, and effective results that can be applied in high-resolution satellite imagery processing of multiple sensors, angles, and resolutions. © 2004-2012 IEEE.

Wen Q.,Key Laboratory of Disaster Reduction and Emergency Response Engineering | Li L.,Key Laboratory of Disaster Reduction and Emergency Response Engineering | Liu Q.,Beihang University | Fan W.,Satellite Surveying and Mapping Application Center | And 2 more authors.
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | Year: 2013

Object detection and extraction are very important research topic in remote sensing processing and analysis. An object-oriented based accurate object extraction method was proposed by combining saliency detection and image segmentation. Firstly, a new saliency detection method which is adequate for high resolution remote sensing image analysis is presented by fusing graph-based visual saliency detection and line density visual saliency detection. By introducing line density, the proposed method can detect building regions under very complex background remote sensing images in an unsupervised manner. Then, graph-cut based segmentation is used to obtain image regions. Pixels in each region have similar saliency scores and features. Accurate boundaries of objects can be extracted by analyzing saliency of these regions. Compared with pixel based salient objects detection methods, our method has high true detection rate as well as low false detection rate by using object-oriented idea. Experimental results also demonstrate that our method can detect human buildings accurate target boundary.

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