Satellite Image Classification Using Convolutional Neural Network

Guntuku Vamshi , S. Hemanth Kumar , P. Harsha Vardhan Reddy , Gurram Chandra Sekhar , J. Lethisia Nithiya

Land Cover, Convolutional Neural Network, Crop classification, deep learning, Sentinel-2, Machine learning.

For agronomists and agricultural organizations in charge of land management, it is essential to comprehend how the current land cover is used and to track changes over time. Researchers now have more opportunities to use publicly available multi-spectral optical images with decametric spatial resolution and more frequent revisits for remote sensing applications like land cover and crop classification (LC&CC), agricultural monitoring and management, and environment monitoring. This is due to the increasing spatial and temporal resolution of globally available satellite images, such as those provided by Sentinel-2. Cropland mapping systems now in use can be divided into two categories: object-based and per-pixel. When more agricultural crop classes are taken into account on a large basis, it is still difficult. This research develops an innovative and ideal Pixel-based LC&CC using a deep learning model. This work develops and applies a novel and optimal deep learning model for pixel-based LC&CC utilizing multi-

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"Satellite Image Classification Using Convolutional Neural Network", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 4, page no.883 - 889, April-2024, Available :https://ijsdr.org/papers/IJSDR2404126.pdf

Volume 9 Issue 4, April-2024

Pages : 883 - 889

Paper Reg. ID: IJSDR_210908

Published Paper Id: IJSDR2404126

Downloads: 000347142

Research Area: Computer Engineering 

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2404126

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2404126

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition