20 February 2023 Mapping overwintering grain stubbles using machine-learning methods and image compositions for common agriculture policy-control and water framework directive connected activities
Sebastian Goihl
Author Affiliations +
Abstract

By leaving grain stubble on the field over the winter, farmers can actively contribute to nature conservation. Animals receive food and living space in these areas, endangered herbs too, but at the same time, it is reducing the input of substances into water and function as covered ground to protect the fertile soil from erosion. Remote sensing can deliver information on this type of land cover, which is also important for the agricultural administration. The farmer can be compensated by the government to let stubbles on the fields. The results of this study show that there is a high potential to detect overwintering stubbles fields area for common agriculture policy (CAP)-control to verify agricultural funding with Support Vector Machine (96.5%) by combining remote sensing classification methods with geodata analysis techniques using geoinformation systems (GIS), negative buffering (-20 m), and using threshold settings for correct classified pixel per field. These results give occasion for optimism for the further processing of this land cover by using it as an application for the government to support CAP- and water framework directive-activities.

© 2023 Society of Photo-Optical Instrumentation Engineers (SPIE)
Sebastian Goihl "Mapping overwintering grain stubbles using machine-learning methods and image compositions for common agriculture policy-control and water framework directive connected activities," Journal of Applied Remote Sensing 17(1), 014515 (20 February 2023). https://doi.org/10.1117/1.JRS.17.014515
Received: 3 August 2022; Accepted: 25 January 2023; Published: 20 February 2023
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KEYWORDS
Agriculture

Land cover

Education and training

Remote sensing

Image classification

Vegetation

Soil science

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