Year: 2024
Type: article
Abstract: Monitoring natural vegetation and detecting planes in satellite imagery are critical tasks in remote sensing, with applications ranging from environmental conservation to security and surveillance. This project aims to develop an effective method for analyzing natural vegetation and detecting planes by utilizing satellite imagery and applying advanced image processing and machine learning techniques. By leveraging various features such as vegetation indices, texture, shape, and spectral signatures, we aim to build predictive models that accurately classify vegetation types and identify planes. This paper discusses the methodology, including data collection, preprocessing, feature extraction, model training, and evaluation, ultimately highlighting the models' performance and potential applications in real-world scenarios. Keywords— Vegetation Analysis,Deep learning ,Plane Detection.
DOI: 10.55041/ijsrem37257
Authors: Sweatha J, Neena Murali, Gayathri N
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
SDG: Life on land
Open Access status: bronze
OpenAlex ID: W4402132354