In this paper calculation of some physical parameters of the receiver of laser scanning system is presented. Basic physical principles of laser scanning of water objects are considered. Ranging standard deviation for typical parameters of laser scanning system are calculated. Formula for calculation of reflected optical power for specular reflective objects is proposed.

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SummaryBased on the study of literature on the classification of forests using high resolution space images it was established that the separation of classes and classes close to the spectral brightness can not be identified with high accuracy. Classification using maximum likelihood algorithm, which generally gives better results compared with algorithms of spectral distance or Mahalanobis distance, does not lead to the definition of areas with a high probability. Therefore, the article examines a method of forest classification by post-processing. Experimental studies were carried out using an satellite image of the forested area of the Precarpathian region, obtained from QuickBird-2 (June 2010). Data collected during field research were used as verification data to determine areas of different objects. The controlled classification has been performed using the method of the maximum likelihood, size of signatures for 8 classes were selected from 100 to 400 points. For these classes a matrix of classes separation was calculated, and a significant correlation between next classes was found: young conifer plantings and pine and mixed forest, and deciduous young plantings and deciduous forest. Post-processing significantly improves the reliability of determination of area, and the procedure consists in assigning to all pixel of the selected neighbourhood brightness of most points, although reliability of determination of area depends on the size of the area. Accuracy of determination of areas are from 92 to 99%.

Earth remote sensing and using the satellite images play an important role when monitoring the effects of forest fires and assessing damage. Applying different methods of multispectral space images processing, we can determine the risk of fire distribution, define hot spots and determine thermal parameters, mapping the damaged areas and assess the consequences of fire. The purpose of the work is the severity assessment connected with the post-fire period on the example of the forests in the Chornobyl Exclusion Zone. The tasks of the study are to define the area of burned zones using space images of different time which were obtained from the Sentinel-2 satellite applying the method of a normalized burn ratio (NBR) and method of supervised classification. Space images taken from the Sentinel-2 satellite before and after the fire were the input data for the study. Copernicus Open Access Hub service is a source of images and its spatial resolution is 10 m for visible and near infrared bands of images, and 20 m for medium infrared bands of images. We used method of Normalized Burn Ratio (NBR) and automatically calculated the area damaged with fire. Using this index we were able to identify areas of zones after active combustion. This index uses near and middle infrared bands for the calculations. In addition, a supervised classification was performed on the study area, and signature files were created for each class. According to the results of the classification, the areas of the territories damaged by the fire were also calculated. The scientific novelty relies upon the application of a method of using the normalized combustion coefficient (NBR) and supervised classification for space images obtained before and after the fire in the Chernobyl Exclusion Zone. The practical significance lies in the fact that the studied methods of GIS technologies can be used to identify territories and calculate the areas of vegetation damaged by fires. These results can be used by local organizations, local governments and the Ministry of Emergency Situations to monitor the condition and to plan reforestation. The normalized burned ratio (NBR) gives possibility efficiently and operatively to define and calculate the area which were damaged by fires, that gives possibility operatively assess the consequences of such fires and estimate the damage. The normalized burned ratio allows to calculate the area of burned forest almost 2 times more accurately than the supervised classification. The calculation process itself also takes less time and does not require additional procedures (set of signatures). Supervised classification in this case gives worse accuracy, the process itself is longer, but allows to determine the area of several different classes.