Challenges of crop classification from satellite imagery with Eurocrops dataset
[ 1 ] Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ 2 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doctoral school student | [ P ] employee
[2.2] Automation, electronics, electrical engineering and space technology
2023
chapter in monograph / paper
english
- computer vision
- multispectral imaging
- remote sensing
- crop classification
EN Crops monitoring and classification on a nationwide level provide important information for sustainable agricultural management, food security, and policy-making. Recent technological advancements, followed by Earth observation programmes like Copernicus, have provided plenty of publicly available multispectral data. Combining these data with field annotations allows for continuous crop monitoring from publicly available data. In this paper, we present a solution for crop classification to determine crop type from Sentinel-2 multispectral data, utilizing machine learning techniques. Apart from presenting initial results, we discuss the challenges of crop classification on a Eurocrops dataset and further research directions.
25 - 30
dla wszystkich w zakresie dozwolonego użytku
open repository
final published version
at the time of publication
20