scholarly journals ACYOTB Plugin: Tool for Accurate Orthorectification in Open-Source Environments

2019 ◽  
Vol 9 (1) ◽  
pp. 11 ◽  
Author(s):  
Valerio Baiocchi ◽  
Francesca Giannone ◽  
Felicia Monti ◽  
Felicia Vatore
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Open Source Software ◽  
Satellite Images ◽  
Polynomial Function ◽  
Full Potential ◽  
Rational Polynomial ◽  
High Resolution Satellite Images ◽  
Image Position ◽  
Rectification Process

High-resolution satellite images must undergo a geometric rectification process in order to be used for metrical purposes. This operation, called orthorectification, is necessary because of deformations mainly due to camera distortions and acquisition geometry. To correctly orthorectify an image, it is necessary to accurately reconstruct the photogrammetric-acquisition characteristics and the image position with respect to a reference system connected to the ground. This operation, called orientation, can be done using various mathematical models such as rigorous, rational polynomial function (RPF), and rational polynomial coefficient, or, according to some authors, rapid positioning coefficient (RPC) models. Orientation and orthorectification are usually performed within specific commercial software, but in QGIS, these complex operations can be performed using the open libraries of the Orfeo Tool Box (OTB). Unfortunately, instructions given by OTB developers lead to scarce results. In fact, the procedure proposed in OTB does not allow for the full exploitation of the potential of RPC models, on which OTB itself is based. As OTB is open-source software, a plugin was developed to overcome these limitations and exploit its full potential. In fact, OTB interfaces are unfortunately essential, and some necessary functions are missing. Therefore, a new QGIS plugin was developed in order to run the entire process in the most photogrammetrically and statistically correct way, and, at the same time, to simplify the relative procedures.

scholarly journals RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 579-586 ◽  
Author(s):  
K. Gong ◽  
D. Fritsch
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Satellite Image ◽  
Relative Orientation ◽  
Ground Control ◽  
Surface Model ◽  
Control Information ◽  
Rational Polynomial ◽  
High Resolution Satellite Images ◽  
Resampling Method

High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM) generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs) provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM) method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

An Approach for Building Rooftop Border Extraction from Very High-Resolution Satellite Images

2021 ◽  
pp. 1-11
Author(s):  
Yasser Mostafa ◽  
Mahmoud Nokrashy O. Ali ◽  
Faten Mostafa ◽  
Mohamed Yousef
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
High Resolution Satellite Images ◽  
Very High

scholarly journals How can remote sensing techniques help monitoring the vine and maximize the terroir potential?

2018 ◽  
Vol 50 ◽  
pp. 02007
Author(s):  
Cecile Tondriaux ◽  
Anne Costard ◽  
Corinne Bertin ◽  
Sylvie Duthoit ◽  
Jérôme Hourdel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Images ◽  
Sampling Strategy ◽  
Wine Quality ◽  
Wine Production ◽  
Spectral Bands ◽  
High Resolution Satellite Images ◽  
Remote Sensing Techniques ◽  
Set Up

In each winegrowing region, the winegrower tries to value its terroir and the oenologists do their best to produce the best wine. Thanks to new remote sensing techniques, it is possible to implement a segmentation of the vineyard according to the qualitative potential of the vine stocks and make the most of each terroir to improve wine quality. High resolution satellite images are processed in several spectral bands and algorithms set-up specifically for the Oenoview service allow to estimate vine vigour and a heterogeneity index that, used together, directly reflect the vineyard oenological potential. This service is used in different terroirs in France (Burgundy, Languedoc, Bordeaux, Anjou) and in other countries (Chile, Spain, Hungary and China). From this experience, we will show how remote sensing can help managing vine and wine production in all covered terroirs. Depending on the winegrowing region and its specificities, its use and results present some differences and similarities that we will highlight. We will give an overview of the method used, the advantage of implementing field intra-or inter-selection and how to optimize the use of amendment and sampling strategy as well as how to anticipate the whole vineyard management.

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