Leveraging Deep Learning in Remote Sensing: A Novel Approach for Agricultural Greenhouse Detection and Innovation Management

Year 2025, Volume: 10 Issue: 2, 221 - 230

Vilma Tomco , Erika Grabocka , Miranda Harizaj

https://doi.org/10.26833/ijeg.1587264

Abstract

Innovation management plays a pivotal role in harnessing advanced technologies to drive progress across diverse fields. In this context, integrating deep learning models within remote sensing technologies presents transformative potential for monitoring, change detection, analysis, and decision-making in fields such as agriculture, urban planning, and environmental studies. This study examines the role of sophisticated deep learning approaches in analyzing high-resolution satellite imagery to improve the detection of agricultural greenhouses. Using MMSegmentation (DeepLabv3Plus) with multispectral data at 0.7-meter resolution, the research addresses the limitations of traditional methods by substantially enhancing detection accuracy and efficiency. To address data scarcity and increase model robustness, advanced data augmentation techniques—such as rotations, scaling, and flipping - expand dataset diversity, fostering adaptability and performance under diverse conditions. The study also assesses the impact of environmental factors, including seasonal variations and weather, on model performance. Suggested improvements include expanding the dataset to encompass a wider variety of greenhouse types and conditions, incorporating high-resolution or hyperspectral imagery for finer details, and building multi-temporal datasets to capture dynamic environmental changes. The findings underscore the importance of advanced innovation management in enhancing remote sensing applications, offering actionable insights for agricultural management in Albania and similar regions. This research contributes to the broader field of innovation management by showcasing how deep learning can revolutionize practical applications in agriculture

Keywords

Deep Learning Models, Innovation Management, Object Detection – Greenhouses, Remote Sensing

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