Articles | Volume 4
06 Jun 2023
 | 06 Jun 2023

Detection of small-scale landscape elements with remote sensing

Nikita Murin, Alexander Kmoch, and Evelyn Uuemaa

Keywords: landscape elements, GEOBIA, openness index, machine learning

Abstract. Landscape elements located on agricultural fields or on their edges play a crucial role in the biodiversity of agricultural land. The landscape elements’ database in Estonia is updated in accordance with the applications of the field owners, and usually it does not represent a real situation of the landscape elements on the field. Hence, the analysis and control over landscape elements are limited. The main aim of this study is to create a methodology to map landscape elements in Estonia with remote sensing data. The first method was created considering the importance of computational efficiency and therefore fast and non-complex map algebra solution was developed. The second, more precise but more computationally expensive way to map landscape elements, was the object-based image analysis method utilizing machine learning classification. Both methods displayed high overall accuracies, but users’ and producers’ accuracies were lower. Taking into account the computational time and accuracy, it was concluded that the map algebra method is better suitable for fast landscape elements’ detection. However, the object-based image analysis method is more suitable for identifying more exact classes of landscape elements.