Application of CNNs in Feature Learning for Remote Sensing Data: A Case Study on Land Cover Classification and Environmental Change Detection

Zhaoyi Li

2024

Abstract

This study is a review and overview of the current training and feature analysis of convolutional neural networks (CNNs) in remote sensing data, especially in the following areas: Environmental monitoring and land use assessment. The aim of the study was to utilize information like high-resolution satellite imagery from “Planet: Understanding the Amazon from Space” dataset to find ways to raise the accuracy of land cover classification and environmental change detection. According to the materials of the cited articles, the paper proposes an automatic CNN-based feature extraction method, which overcomes the limitations of traditional manual methods. The method includes data preprocessing, multi-scale feature fusion, classification, integration of attention mechanism, and further refinement of the performance of the residual network model. The experimental results highlight that, a significant creep in classification accuracy which achieves at 93.5% on areas of detecting deforested. Emphasizing the great potential of the proposed approach for real-time environmental monitoring and land use planning, these results pave the way for the orientation of further researches. The future work of the project will focus on optimizing CNN models to reduce computational complexity, as well as exploring data fusion to improve the generalization and effectiveness of remote sensing utilization from multiple sources.

Paper Citation

in Harvard Style

Li Z. (2024). Application of CNNs in Feature Learning for Remote Sensing Data: A Case Study on Land Cover Classification and Environmental Change Detection. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 354-358. DOI: 10.5220/0013517600004619

in Bibtex Style

@conference{daml24,
author={Zhaoyi Li},
title={Application of CNNs in Feature Learning for Remote Sensing Data: A Case Study on Land Cover Classification and Environmental Change Detection},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={354-358},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013517600004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Application of CNNs in Feature Learning for Remote Sensing Data: A Case Study on Land Cover Classification and Environmental Change Detection
SN - 978-989-758-754-2
AU - Li Z.
PY - 2024
SP - 354
EP - 358
DO - 10.5220/0013517600004619
PB - SciTePress