Research On Geometric Rectification Of High Resolution Remote Sensing Imagein Forest Areas

With the development of remote sensing technology, high-resolution remote sensingima ge have been widely used in forestry. However, the remote sensing ima ge are affected bydifferent errors and bring the geometric distortion. So the geometric rectifica tion must be usedin order to attain precise geocoding and provide the support for geometrica l measuring,reciproca l comparison,ima ge compound and etc. In conventiona l filed-p hotography, physica lmodel that reaches maturity and has the feature of high resolution is mostly used . physica lmodel is of limitation in applica tion because of its sophisticated ima ging eometry, complicatesensor physica l structure,and self-correlation of model parameters．The universa l geometrymodel is the only way to rectify the high-resolution remote sensing ima ges because of lack ingparameter of physica l model.A scene of QuickBird ima ge in Shenzhen was used in this paper, a variety of universa lgeometric rectifica tion models and the solution method were discussed. The factors affect thegeometric rectifica tion accuracy of high resolution remote sensing ima ge and the ima gedistortion in forest areas were studied. The ma in conclusions are:(1) In all of the common geometric correction models, the rationa l function model of thecalibration accuracy is the highest, but the rationa l function model needs more ground controlpoints, and the accuracy of the model depends on the distribution of control points.(2) The precision of avera ge polynomia l method is worse for uneven terrain, varyinggreatly with different kinds of terrains, and the precision of improved polynomia l methodsvaries with the order of polynomia ls and is nearly irrelative to the types of terrains.(3) Among the three direct linear transformation models, the precision of SDLT is thebest, and it only need a sma ll number GCPs.(4) The bala nce among precision, complexity, requirements for known data should alsobe considered for choosing methods from these approxima te ima ge rectifica tion algorithms .(5) Experimental results also show that the improved polynomia l method is a betterchoice for approxima te rectifica tion of high-resolution remote sensing ima ge in forest area,from the viewpoints of precision, complexity, the number and spatial distribution of control -points and so on.(6) The distortion of high resolution remote sensing ima ge in forest area depends on theterrain, so the factor of terrain must be included in the process of geometric rectifica tion.