Unmanned aerial vehicle (UAV) can be a flexible, cost-effective, and accurate method to monitor landslides with high resolution aerial images. Images acquired on 05 May 2013 and 13 December 2014 of the Xishan landslide, China, have been used to produce a high-resolution ortho-mosaic of the entire landslide and digital elevation model (DEM). The UAV capability for imaging detection and displacements on the landslide surface has been evaluated, and the subsequent image processing approaches for suitably georectifying the data have been assessed. Objects derived from the segmentation of a multispectral image were used as classifying units for landslide object-oriented analysis. Spectral information together with various morphometric characteristics was applied for recognizing landslides from false positives. Digital image correlation technique was evaluated to quantify and map terrain displacements. The magnitude and direction of the displacement vectors derived from correlating two temporal UAV images corresponded to a visual interpretation of landslide change. Therefore, the UAV can demonstrate its capability for producing valuable landslide mapping data and deformation information.
Based on RS and GIS, the 2003a's aerial image data of Shanghai is taken as data source. According to the urban green
landscape theory, the green landscapes are well classified to park, street green landscape, affiliation green landscape,
inhabited green landscape, production green landscape and defending green landscape, et al. Several spatio-temporal
models including the space expansion models and ecological analyzing models for urban green landscape have been
constructed and calculated. Then, based on the ORDBMS platform PostgreSQL and OGIS MapServer, the urban green
landscape database including the above six types green landscapes spatial data and model system of Shanghai have been
developed. At last, using the powerful statistics analysis function of the model system, this paper discusses and reveals
the impacts of urban space development on green landscape pattern, structure and function. At the same time, the general
distribution characteristics of green landscape pattern have been researched at three levels such as green patch level, type
level and mosaics structure of different green landscapes. The urban green landscapes model system of Shanghai based
on MapServer provides a powerful interactive and perfect platform for governments to make urban planning decisions
and landscape study.
KEYWORDS: 3D modeling, Data modeling, Geographic information systems, Visualization, Data storage, Internet, 3D optical data storage, 3D imaging standards, Photogrammetry, Standards development
Nowadays, the namely 3D GIS technologies become a key factor in establishing and maintaining large-scale 3D geoinformation
services. However, with the rapidly increasing size and complexity of the 3D models being acquired, a
pressing needed for suitable data management solutions has become apparent. This paper outlines that storage and
exchange of geospatial data between databases and different front ends like 3D models, GIS or internet browsers require
a standardized format which is capable to represent instances of 3D GIS models, to minimize loss of information during
data transfer and to reduce interface development efforts. After a review of previous methods for spatial 3D data
management, a universal lightweight XML-based format for quick and easy sharing of 3D GIS data is presented. 3D data
management based on XML is a solution meeting the requirements as stated, which can provide an efficient means for
opening a new standard way to create an arbitrary data structure and share it over the Internet. To manage reality-based
3D models, this paper uses 3DXML produced by Dassault Systemes. 3DXML uses opening XML schemas to
communicate product geometry, structure and graphical display properties. It can be read, written and enriched by
standard tools; and allows users to add extensions based on their own specific requirements. The paper concludes with
the presentation of projects from application areas which will benefit from the functionality presented above.
QuickBird satellite is quickly becoming the best choice for high-resolution mapping using satellite images. Ortho Ready Standard Product as an intermediate product between Basic and Standard enables to be generated to an orthorectified product. And it becomes mainly financial because the users can purchase sub-scenes instead full scenes. In this paper, we will describe the followings: (1) how to correct QuickBird Ortho Ready Standard Imagery using different geometric correction methods, and (2) data fusion using QuickBird panchromatic and multispectral data.
There is two main factor of High-Resolution Satellite Imagery(HRSI) geometry correction. Besides mathematical models, Ground Control Points (GCPs) has played a big role on rectification. As how to determine the effect of GCPs in image geo-correction, the accuracy estimation of the control points is the main form by means of statistics. Yet this existing method shows nothing more than the partial expression in the statistic level. With the development of visualization technology, using the technology of spatial visualization for the accuracy determination affected by the GCPs and the whole expression are discussed in this paper. Taken affine rectification model and conformal rectification model as example, the paper has mainly deduced the relationship between the accuracy of arbitrary point and the control points. The Inverse Distance relationship is the result, therefore interpolation method related to the result is used to interpolate spatial accuracy for the image geo-correction. Based on above, the visualizations of accuracy is put forward to give the detail description for the quality of image geo-correction and the effect of GCPs' precision, quantity and distribution. The case of HRSI is adopted to give the explanation for the spatial visualization of accuracy of GCPs, and also some helpful conclusions are obtained for its availability. From the case, it can be obtained that the precision of control points after conversion in affine model is lower than that in conformal model according to the different scale parameters in x or y direction.
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