Space monitoring using earth remote sensing technologies and stochastic geometry to analyze emergency situations

M. Kazaryan; M. Shakhramanian; E. Semenishchev

doi:10.1117/12.3024950

17 June 2024 Space monitoring using earth remote sensing technologies and stochastic geometry to analyze emergency situations

M. Kazaryan, M. Shakhramanian, E. Semenishchev

Author Affiliations +

Proceedings Volume 13023, Computational Optics 2024; 130230L (2024) https://doi.org/10.1117/12.3024950
Event: SPIE Optical Systems Design, 2024, Strasbourg, France

Conference Poster

Abstract

The article proposes a technology for operating an automatic space monitoring system for the presence of waste disposal sites. The technology is based on the ideas of stochastic geometry, as well as geometric probability and covariograms. The paper proposes an algorithm based on the trace transform using discrete orthogonal transforms to minimize the feature space. The problem of developing a trace matrix and selecting informative features using the stochastic geometry method for finding waste disposal sites from high-resolution satellite images is studied using the orthogonal transformations apparatus. The proposed methodology is tested using space images depicting waste disposal sites.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

M. Kazaryan, M. Shakhramanian, and E. Semenishchev "Space monitoring using earth remote sensing technologies and stochastic geometry to analyze emergency situations", Proc. SPIE 13023, Computational Optics 2024, 130230L (17 June 2024); https://doi.org/10.1117/12.3024950

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE