This study looks into the integration of Sentinel-2 and Landsat 8 satellite imagery with machine learning algorithms for enhanced crop yield prediction and agricultural monitoring. The use of remote sensing technologies has transformed precision agriculture through real-time assessment of vegetation health, soil conditions, and environmental changes. A good complement to this long-term history and thermal imagery from Landsat 8, Sentinel-2 has high spatial resolution and high revisit cycles to enable a robust dataset for accurate yield estimation. Machine learning models, which include decision trees, random forests, and neural networks, have started processing vast datasets in agriculture that offer predictive insights into crop growth patterns, resource optimization, and risk management. Data pre-processing techniques such as atmospheric correction and cloud removal are very essential in making the satellite imagery reliable, improving the accuracy of vegetation indices and predictive models. Even though data quality, model interpretability, and high implementation costs are still issues, advances in artificial intelligence and deep learning have been refining remote sensing applications. The study highlights the transformative potential of integrating satellite technology and machine learning to enhance food security, optimize resource utilization, and promote sustainable farming practices and pave the way for more precise and data-driven agricultural decision-making.
| Mualliflar | Hassan , Wassan A., Abed , Ayat Farhan, Ismail , Rafah R., Kouder , Noor Zubair, Haider , Dina H. |
|---|---|
| Jurnal | Innovative Multidisciplinary Journal of Applied Technology |
| Nashr sanasi | 2025-06-02 |
| Jild | 3 |
| Son | 5 |
| Betlar | 24-45 |
| Til | Ingliz |
Sentinel-2, Landsat 8, satellite imagery, machine learning, crop yield prediction
The objective of the paper is to compare the SLRM with the WM and highlights the practical applications of both models in the spatial data analysis. Spatial linear regression is an important statistical method for…
Machining processes, including turning, milling, and grinding, are vital to modern manufacturing, ensuring precision and adaptability in producing high-quality components. However, traditional teaching methods often…
This article explores the impact of sodium carboxymethyl cellulose (Na-CMC) and sericin on the rheological, physical, and mechanical properties of thickening polymer compositions used in cotton fabric printing…
The increased use of e-health systems requires better methods for keeping patients’ sensitive information private, complete, and available.In this study, we propose the use of a dual encryption model which encompasses…
Building collapse has become a recurrent and alarming issue in many urban centers across Nigeria, with Nsukka urban in Enugu State witnessing a noticeable rise in such incidents. The objective of this research work is…
The article discusses the main methods of innovative technology and their effective use in teaching students computer science at school.
The design and modeling of skirts from waist garments play a significant role in light industry, particularly in women’s fashion. This study explores various methods of skirt modeling from the standpoint of…
In the modern era, characterized by rapid socio-economic, cultural, and technological changes, the socio-psychological development of the younger generation has become one of the most pressing priorities. This article…
This article discusses ways to improve the efficiency of parking lot operations and enhance driver convenience in using parking facilities. It examines existing challenges in increasing the effectiveness of parking…
In this article, a new ovoid-shaped side inlet for a centrifugal fan in a cotton picker is proposed and its aerodynamic efficiency is theoretically substantiated. In order to maximize the efficiency of the fan, aspects…
Innovative Multidisciplinary Journal of Applied Technology — barcha maqolalar