Application of Machine Learning Methods for Classification of Agricultural Crops
DOI:
https://doi.org/10.52171/2076-0515_2022_14_02_106_116Ключевые слова:
satellite image, training sample, machine learning, classification, assessment, agricultural cropАннотация
The article demonstrates the significant role of the impact of training samples on the processing of satellite images for the accurate classification of crops. To achieve the goal of the study, three machine learning methods are tested by classifying various satellite data with high spatial resolution. As a result of the application of machine learning methods, the results are compared and a method with a high classification accuracy is selected. Based on the obtained data, crop maps have been developed and an assessment of the vegetation state for the research period is carried out.
Загрузки
Опубликован
2022-06-30
Как цитировать
Badalova, A., & Guliyeva, S. (2022). Application of Machine Learning Methods for Classification of Agricultural Crops. Вестник Азербайджанской инженерной академии, 14(2), 106–116. https://doi.org/10.52171/2076-0515_2022_14_02_106_116
Выпуск
Раздел
Articles
Лицензия
Это произведение доступно по лицензии Creative Commons «Attribution-NonCommercial» («Атрибуция — Некоммерческое использование») 4.0 Всемирная.
