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Малопараметрический метод оконтуривания сельскохозяйственных полей на спутниковых снимках с помощью исторических данных MSAVI2
М.А. Павлова 1, В.А. Тимофеев 1, Д.А. Бочаров 1, Д.С. Сидорчук 1, А.Л. Нурмухаметов 1, А.В. Никоноров 2,3, М.С. Ярыкина 1, И.А. Кунина 1, А.А. Смагина 1, М.А. Загарев 1

1 Институт проблем передачи информации им. А.А. Харкевича РАН,
127051, Москва, Большой Каретный пер., д. 19;
2 ИСОИ РАН – филиал ФНИЦ «Кристаллография и фотоника» РАН,
443001, Россия, г. Самара, ул. Молодогвардейская, д. 151;
3 Самарский национальный исследовательский университет имени академика С.П. Королёва,
443086, Россия, г. Самара, Московское шоссе, д. 34

 PDF, 4771 kB

DOI: 10.18287/-6179-CO-1235

Страницы: 451-463.

Аннотация:
В данной работе рассматривается проблема оконтуривания сельскохозяйственных полей на спутниковых снимках. Для решения этой задачи применяется подход, основанный на анализе исторических данных. В работе показано, что на таких данных можно добиться высокого качества с помощью простого малопараметрического метода. Метод состоит из детектора полей и детектора границ. Детекция полей основана на определении порога Оцу, а для определения границ используется детектор краев Кэнни. В связи с нехваткой доступных наборов данных нами был подготовлен и опубликован собственный набор данных, состоящий из 18859 экспертно аннотированных полей на снимках Sentinel-2. Для сравнения оконтуривания на мгновенных и исторических данных был реализован один из наиболее современных методов, основанный на глубоком обучении. Эксперимент показал, что использование исторических данных позволяет получить более высокое качество с более низкими затратами. Предлагаемый малопараметрический метод требует значительно меньше обучающих данных по сравнению с методом на мгновенных данных. Подготовленный набор данных и реализация алгоритма на языке Python были выложены в открытый доступ.

Ключевые слова:
оконтуривание сельскохозяйственных полей, малопараметрический алгоритм, компьютерное зрение, дистанционное зондирование Земли, исторические данные, открытый набор данных.

Благодарности
Исследование выполнено при поддержке Российского научного фонда (проект № 20-61-47089).

Цитирование:
Павлова, М.А. Малопараметрический метод оконтуривания сельскохозяйственных полей на спутниковых снимках с помощью исторических данных MSAVI2 / М.А. Павлова, В.А. Тимофеев, Д.А. Бочаров, Д.С. Сидорчук, А.Л. Нурмухаметов, А.В. Никоноров, М.С. Ярыкина, И.А. Кунина, А.А. Смагина, М.А. Загарев // Компьютерная оптика. – 2023. – Т. 47, № 3. – С. 451-463. – DOI: 10.18287/2412-6179-CO-1235.

Citation:
Pavlova MA, Timofeev VA, Bocharov DA, Sidorchuk DS, Nurmukhametov AL, Nikonorov AV, Yarykina MS, Kunina IA, Smagina AA, Zagarev MA. Low-parameter method for delineation of agricultural fields in satellite images based on multi-temporal MSAVI2 data. Computer Optics 2023; 47(3): 451-463. DOI: 10.18287/-6179-CO-1235.

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