of 
the 
sets 
tral 
and 
and 
find 
and 
n of 
late 
ired 
nal 
rite, 
itor 
J.S. 
lon, 
129, 
| of 
Petrosyan, Arakel 
  
THE NEW PHOTOGRAMMETRIC METHOD FOR CLOUD REMOTE STUDIES 
S. Pavlov, A. Petrosyan 
Space Research Institute of the Russian Academy of Sciences, Russia 
apetrosy@iki.rssi.ru 
KEY WORDS: Clouds, Entrainment, Image Matching, Photogrammetry , Remote Sensing 
ABSTRACT 
The main objective of the suggested work is to improve predictions of cloud top entrainment phenomena with 
photogrammetric methods based on satellite data analyses. The new analysis methodology for the cloud top 2D-flow 
reconstruction from remote sensing data is developed and suggestions for further satellite missions and data sets is 
discussed. Validation examples based on available data is provided. Method uses a set of images of the cloud layer with 
known temporal and spatial resolution in order to obtain flow pattern. We consider visual movement and deformation of the 
picture as an atmospheric flow perturbation and in the simplest situation imply it to be identical. The identity of two points 
is determined by their neighboring vicinity. Thus the method, analyzing some vicinity of point at the first image, is to find 
an identical vicinity at the second one. Algorithm analyses the couple of consecutive In that way we build an auxiliary 
space in which small displacement of original image point will be in correspondence with that of auxiliary space point. 
Also two points with equal in the above sense vicinities have the same image point in the space. The solution is developed 
by use of iterative method. 
1 INTRODUCTION 
The main objective of the suggested work is to improve predictions of cloud top entrinment phenomena with 
photogrammetric methods based on satellite data analyses. The new analysis methodology for the cloud top 2D-flow 
reconstruction from remote sensing data is developed and suggestions for further satellite missions and data sets is 
discussed. Method uses a set of images of the cloud layer with known temporal and spatial resolution in order to obtain flow 
pattern. We consider visual movement and deformation of the picture as an atmospheric flow perturbation and in the 
simplest situation in order to obtain flow pattern. We consider visual movement and deformation of the picture as an 
atmospheric flow perturbation and in the simplest situation imply it to be identical. The identity of two points is determined 
by their neighboring vicinity. Thus the method, analyzing some vicinity of point at the first image, is to find an identical 
vicinity at the second one. It is natural that we can not find the exact transformation because of liquid particle deformation. 
However, assuming that the above deformation is small enough we can disregard such a problem. Algorithm analyses the 
couple of consecutive monochromic images in some spectral range and releases the field of deformation which translate the 
first image into the second one. The field of deformation in hand is developed as a solution of a variation problem. In that 
way we build an auxiliary space in which small displacement of original image point will be in correspondence with that of 
auxiliary space point. Also two points with equal in the above sense vicinities have the same image point in the space. The 
solution is developed by use of iterative method. A tangent hyperplane is considered and found is the optimum directions of 
movement toward the solution. Further the iterative process is repeated, and as we can control both the movement of image 
point and displacement itself, the error of iteration is not accumulated. Therefore the solution can be obtained with adequate 
accuracy. Then it extracts regions free of clouds and calculates the velocity field. Numerical experiments show major 
parameters affecting the solution to be the size of point vicinity and how thoroughly it is described, that can be determined 
by number of reference points, and therefore by dimension of auxiliary space. It is interesting that both parameters have 
their optimum values depending on image character. This technique is subjected to time resolution of input data, so there 
are some restrictions for experiments methods. In analysis of cyclones in Earth atmosphere with the scale about thousand 
kilometers it requires temporal resolution about some minutes while at the present time such resolution is about hour 
depending on satellite orbit. The further possible development of the method may follow several directions, such as to take 
into consideration the vertical movement of the cloud layer using stereoimages, to improve trajectory search algorithm in 
case when exact coincidence is impossible, to automate evaluation of optimum algorithm parameters in accordance with 
statistical properties of images being aligned. 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000. 1149