Junjie Zhu

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain. Coastal digital elevation model (DEM) data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise. The Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are currently the most accurate and freely available DEM data. However, an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking. The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System (ICESat/GLAS) and Real Time Kinematic (RTK) Global Positioning System (GPS) field survey data. The findings show that DEM accuracy is much better than the mission specifications over coastal plains. In addition, optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas. This study provides a systematic approach to assess the accuracy of DEMs in coastal zones, and the results highlight the limitations and potential of these DEMs in coastal applications.

Fusion of high-resolution remote sensing images based on a/spl acute/ trous wavelet algorithm

There are some problems not to be resolved very well, when we merge images by the wavelet transform method. One problem is how many levels the original images should be decomposed to, in order to make fusion images obtain more information. Other problem is how to reduce the spectral distortions of the fusion images more efficiently, when we enhance the spatial resolution of the low-resolution images. We rightly select the number of wavelet decomposition levels by computing entropy of the fusion images. When performing wavelet reconstruction, we introduce the local correlation coefficient and set up the different thresholds at different levels of wavelet decomposition, in order to reduce the spectral distortions of the fusion images. In our experiment we merge three multispectral images with a panchromatic image of Quickbird data by our method. The results demonstrate that our method is a good fusion method to increase information and reduce spectral distortions.

Flood modeling and inundation risk evaluation using remote sensing imagery in coastal zone of China

Global climate change has caused sea level rise, and one of the most extremely consequences are the increased frequency and hazards of the storm surge disasters, therefore, how to effectively assess the risk of storm surge disaster is of importance to hazard reduction and mitigation. However, the storm surge forecast models have complex parameters, which computational inefficiency. Traditional large-scale assessment usually takes elevation-area method based on GIS software, which result in large errors. The present study is attempted to: (1) Select proper two-dimensional hydraulic storm surge inundation model. This model not only has the physical realism but simple and efficient. (2)The present study will focus on the method to extract the required surface parameters based on the remote sensing data to integrate remote sensing data into the model. This project aims to provide the theoretical basis and methodologies for flood risk assessment in coastal zone of China.

Three-dimensional visualization simulation assessment system based on multi-source data fusion for the Wenchuan earthquake

We have developed a visual three-dimensional simulation and assessment system of the Wenchuan earthquake zone using the Digital Earth concept and highly efficient spatial information visualization technology. Our goal is to provide a foundation for earthquake disaster relief and reconstruction. A number of major collapses, landslides, mud-rock flows and other geological disasters are analysed in the system, and the system can be used to monitor and analyse earthquake relief, rescue and insurance to provide first-hand source material for disaster situation assessment. Multi-sensor, multi-temporal, multi-resolution remote sensing data and multi-scale DEM data are integrated into this system, and produce a sequence of comprehensive resolution datasets. We present management methods for a dynamic multi-resolution terrain model and multi-level scene. These methods are based on the model division, delaminating algorithm, and make use of high-speed buffering mechanisms to achieve a multi-level large-scale real-time rendering of scenes in the disaster areas, which also effectively reduces the rendering delay, and achieves smooth, seamless roaming at different model levels.

Information extraction from high-resolution SAR image with object-oriented method

This paper points out that many countries are developing high-resolution SAR technique, and it also introduces the development process of object-oriented image analysis, its merits and shortcomings. After analyzing the overall process of the object-oriented remote sensing image analysis, this paper uses this method to analyze high-resolution SAR images. In the same time, it also used the traditional method of pixel-based remote sensing image analysis to analyze the images, to compare with the object-oriented method. By comparison, we can find that object-oriented remote sensing image analysis method is better. Finally, this paper forecasts the application of object-oriented remote sensing image analysis to high-resolution images.

Research on SAR data integrated processing methodology oriented on earth environment factor inversions

ABSTRACT As an important advanced technique in the field of Earth observations, Synthetic Aperture Radar (SAR) plays a key role in the study of global environmental change, resources exploration, disaster mitigation, urban environments, and even lunar exploration. However, studies on imaging, image processing, and Earth factor inversions have often been conducted independently for a long time, which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing. Focusing on this SAR application issue, this paper proposes and describes a new SAR data processing methodology – SAR data integrated processing (DIP) oriented on Earth environment factor inversions. The simple definition, typical integrated modes and overall implementation ideas are introduced. Finally, focusing on building information extraction (man-made targets) and sea ice classification (natural targets) applications, three SAR DIP methods and experiments are conducted. Improved results are obtained under the guidance of the SAR DIP framework. Therefore, the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies.

SAR information integrated processing and its application method study

Summary form only given. Although Synthetic Aperture Radar (SAR) can capture rich land cover information as a most important advanced technique in the field of international earth observation, the application effects still limited significantly. The reason is that the study of SAR imaging processing, SAR image processing and SAR applications are conducted respectively, the integrated study are lacked for parameter selection of SAR imaging processing and SAR image processing and targets identification of SAR application. Focusing on above science problems, the study for phase high fidelity model of high precision interferometric SAR, SAR non-stationary backscattering characteristics and cognition, SAR three-dimensional electromagnetic scattering modeling and its scattering mechanism and SAR multi-parameters optimization information extraction has been conducted. The typical natural distributed targets and man-made targets such as surface deformation, sea ice, building complex and collapsed building are selected, the method and application study oriented to SAR environmental parameters inversion are conduced, the main result and conclusion are as follows: (1) The overall theoretical frames of SAR information integrated processing was proposed; The simulation and ground validation system used to assess the effects of SAR information integrated processing was created; furthermore, the spaceborne SAR imaging algorithm with three steps focusing processing was proposed and realized the multi-modal integrated imaging processing and improved the imaging processing precision. (2) In terms of SAR information integrated processing of natural targets, focusing on phase high fidelity imaging processing of interferometric SAR surface deformation monitoring, an novel spaceborne SAR high fidelity simulation method based on stationary RCS and improved Goldstein SAR interferogram filter based on empirical mode decomposition were proposed. Focusing on multi-parameters optimization processing of sea ice types classification, the multi-channel spaceborne SAR sparse imaging method based on compressive sensing, Kalman filter for removal of scalloping and inter-scan banding in ScanSAR images and SVM sea ice classification method combined with sea ice concentration were proposed. (3) In terms of SAR information integrated processing of man-made targets, focusing on non-stationary backscattering from building complex, mitigation of azimuth ambiguities in spaceborne stripmap SAR iamges using selective restoration, SAR image despeckling by selective 3D filtering of multiple compressive reconstructed images and man-made target detection in urban areas based on a new azimuth stationary extraction method were proposed. Focusing on three-dimensional modeling and fast extraction of collapsed building, H-a-p method used for collapsed building extraction was proposed.

3D visualization computing in fast design and construction

This paper describes a 3D visualization computing methodology to aid the design of tremendous civil engineering in exploiting DEM and RS images. The methodology has been applied to the design and construction of astronomical telescope project, the FAST. Attempting to meet scientific and technological challenges in the process of the project, this paper has developed an innovational 3D computing platform. To simulate the virtual environment of the spot, 3D terrain model has been created based on QuickBird images and DEM, meanwhile, subtle model of massive main active reflector is loaded on the terrain. The algorithm of optimizing telescope antenna location in depressions is presented. In the virtual environment, considering the slope of the terrain, the distribution of feed supporting towers on the telescope has been optimized. It has been proved that the proposed methodology is of high efficiency in the practice of the application.

Study on Web-based Spatial Decision Support System

Based on OGC Web Service (OWS) code, the article describes that a gross structure of Web-based Spatial Decision Support System (WebSDSS) is designed, and model service and data service are both encapsulated into Web Service program and registered through UDDI to form virtual model library and database respectively. Model service management system is used for searching for and managing model service; data service management system is used for searching for and managing data service; flow-type interface is used for building framework flow for decision process; and service workflow controlling technology is used for ensuring trouble-free operation of decision process to provide operating environment for sharing of network model and data. Based on WebSDSS requirements, technologies such as model standardization, data description of model cell, model releasing, model searching and calling, integration of model and disparate data and generation and operation of decision support flow are studied and a WebSDSS prototype system is developed so as to realize broad sharing and calling of model and data reresources on network and support web-based spatial decision.

Study on 3D visualization application for the Grand Canal heritage site research

This study focuses on two problems in 3D visualization application for heritage site research. Firstly, methods for large scale terrain modeling and rendering were presented. Complex virtual environments were constructed with sequences of remote sensing images and DEM data. The algorithm of precise 3D scenes modeling was optimized. At the same time, the spatial index of quadtree and the images cache management strategies were introduced for improving the performance of interactive 3D visualization system. A novel method creating a mapping between 3D models and the image textures were put forward, so that the models and the textures can be managed respectively. As a result, the capacity of massive 3D terrain surface models management was enhanced as well as the real-time rendering was accelerated. Secondly, methods for 3D culture relics modeling were presented. The culture relics and ancient buildings of the Canal were simulated, which will contribute to its reconstruction and protection. Some ancient water facilities such as ship-lock and docks models and animated navigation scenes were created based on the construction principle and architecture of the Canal transport hub.