Abstract
High resolution data have high relief displacement in hilly terrains. Development of Digital Elevation model helps to assess bio resources more accurately in such terrains. While estimating bio resources in the Himalayan hilly terrain using multispectral LISS-III data of 23 m spatial resolution, the need for orthorectifcation of satellite data was necessary to correct for spatial distances due to high undulating slopes. Therefore, Cartosat stereo pair based Digital Elevation Model (DEM) was generated using the Rational Polynomial Coefficients (RPC) supplied along with the data products. By using the DEM orthorectification of LISS-III was created. In order to evaluate the positional accuracy of ortho rectified LISS-III Ground control points were selected using the Global Positioning System in differential GPS mode. As there is variation in the spatial distances and height over few points, the GCP corrected DEM was used for ortho rectifcation of Cartosat PAN and LISS-III data. This paper presents the procedure followed for ortho rectification and digital elevation model generation using Cartosat stereo pair data. The result of the study indicated high spatial resolution stereo images helped generation of three dimensional mountainous regions more accurately which helps in estimating the bio resources using multispectral LISS III data.
Highlights
Stereo imaging from space-borne platforms offers information about terrain elevation besides supplying spectral reflectance of the scene
While estimating bio resources in the Himalayan hilly terrain using multispectral LISS-III data of 23 m spatial resolution, the need for orthorectifcation of satellite data was necessary to correct for spatial distances due to high undulating slopes
This paper presents the procedure followed for ortho rectification and digital elevation model generation using Cartosat stereo pair data
Summary
Stereo imaging from space-borne platforms offers information about terrain elevation besides supplying spectral reflectance of the scene. Rational functions models (RFMs) have gained popularity, with the recent advent of high resolution data supplying Rational Polynomial Coefficients (RPCs) along with stereo/mono data Providing these coefficients along with stereo data, instead of delivering the interior and exterior orientation parameters and other properties related to physical Sensor, one can proceed to satellite photogram metric processes which approximate the sensor model itself. Poon [5] focuses on Digital Surface Model (DSM) generation from high resolution satellite imagery (HRSI) using different commercial of the shelf (COTS) packages. They validated the stereo DEM with InSAR DEM for different land forms. Similar attempts to evaluate the accuracy of the DEM using different number of GCPs have been made by Michalis and Dowman [11] and Rao [12]
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