A Detailed Study about Digital Surface Model Generation Using High Resolution Satellite Stereo Imagery

نویسنده

  • K. Gong
چکیده

Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coefficients (RPCs) Bundle Block Adjustment is applied to image orientation and the rectification of stereo scenes is realized based on the Project-Trajectory-Based Epipolarity (PTE) Model. Very dense DSMs are generated from WorldView-2 satellite stereo imagery using the dense image matching module of the C/C++ library LibTsgm. We carry out various tests to evaluate the quality of generated DSMs regarding robustness and precision. The results have verified that the presented pipeline of DSM generation from high resolution satellite imagery is applicable, reliable and very promising.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Refinement of Urban Digital Elevation Models from Very High Resolution Stereo Satellite Images

Digital elevation models (DEM) of high resolution and high quality are required for many applications like urban modeling, readiness for catastrophes or disaster assessment. A good source for the derivation of such DEMs from any place in the world are very high resolution (VHR) satellite stereo images as provided e.g. by Ikonos, QuickBird or WorldView. In this paper a method for the generation ...

متن کامل

Satellite Stereo Based Digital Surface Model Generation Using Semi Global Matching in Object and Image Space

This paper presents methodology and evaluation of Digital Surface Models (DSM) generated from satellite stereo imagery using Semi Global Matching (SGM) applied in image space and georeferenced voxel space. SGM is a well known algorithm, used widely for DSM generation from airborne and satellite imagery. SGM is typically applied in the image space to compute disparity map corresponding to a ster...

متن کامل

Generation of Coarse 3d Models of Urban Areas from High Resolution Stereo Satellite Images

With the emergence of more and more satellites delivering very high resolution (VHR) imagery with ground sampling distances in the range of one meter or below the generation of three dimensional urban models directly from space may become possible. Such models are required for many applications in areas where no up-to-date detailed urban mapping exists like in developing countries. Besides the ...

متن کامل

3D modeling of large urban areas with stereo VHR satellite imagery: lessons learned

This paper discusses the potentials of very high-resolution (VHR) stereo imagery for automatic generation of digital surface models (DSM) and 3D information extraction on large metropolitan cities. Stereo images acquired by GeoEye-1 on Dakar (Senegal) and Guatemala City (Guatemala) and by WorldView-2 on Panama City (Panama), Constitucion (Chile), Kabul (Afghanistan), Teheran (Iran), Kathmandu (...

متن کامل

Application of high-resolution stereo satellite images to detailed landslide hazard assessment

This study investigates and demonstrates the state of the art in remote sensing techniques for detailed landslide hazard assessment applicable to large areas. Since the most common methods of landslide hazard assessment using simple inventories and weighted overlays are heavily dependent on three-dimensional terrain visualization and analysis, stereo satellite images from the IKONOS Very High R...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016