The underground surface analysis of waste disposal objects based on the neural network image processing methods

M. Kazaryan; E. Semenishchev; V. Voronin

doi:10.1117/12.2620807

31 May 2022 The underground surface analysis of waste disposal objects based on the neural network image processing methods

M. Kazaryan, E. Semenishchev, V. Voronin

Author Affiliations +

Proceedings Volume 12094, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII; 1209410 (2022) https://doi.org/10.1117/12.2620807
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Conference Poster

Abstract

Remote sensing of the Earth allows to receive medium information, a high spatial resolution from space vehicles, and to conduct hyperspectral measurements. This study presents a remote sensing application using time-series Landsat satellite images to monitor the solid waste disposal site (WDS). In this work, neural network image processing methods are used as part of the proposed algorithm for computer modeling of the fractal-percolation process of the underlying surface filtrate in remote sensing imaging. Investigations related to the analysis of the filtrate and decryption of space images are carried out using the apparatus of discrete orthogonal transformations and two convolutional neural networks. The first neural network detects a waste disposal facility, the second works to localize the area of the leachate identified based on the first network. The results obtained can serve as a basis for developing a methodology for assessing the effectiveness of measures to neutralize the underlying surface of waste disposal sites from leachate and its seepage into the soil using remote sensing technologies. This technique can become the object of further research on developing a medical-prophylactic expert system at the territorial level for the detection and neutralization of unauthorized waste disposal sites based on medium and high-resolution space images. As a result, the proposed method demonstrates good accuracy in detection the solid waste disposal site on real satellite images.

Citation Download Citation

M. Kazaryan, E. Semenishchev, and V. Voronin "The underground surface analysis of waste disposal objects based on the neural network image processing methods", Proc. SPIE 12094, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII, 1209410 (31 May 2022); https://doi.org/10.1117/12.2620807

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