Anna Lilian Gardossi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Anna Lilian Gardossi has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Abdul Mueed Choudhury
Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131 Ancona, Italy
1 shared publication - Antonio Tomao
Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
1 shared publication - Ernesto Marcheggiani
Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131 Ancona, Italy
1 shared publication - Maurizia Sigura
Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
1 shared publication
Latest Publications
- Open Access
- 24 April 2025
- Published by MDPI AG in Remote Sensing
- Vol. 17 (9) , 1506
Semi-Automatic Extraction of Hedgerows from High-Resolution Satellite Imagery
Small landscape elements are critical in ecological systems, encompassing vegetated and non-vegetated features. As vegetated elements, hedgerows contribute significantly to biodiversity conservation, erosion protection, and wind speed reduction within agroecosystems. This study focuses on the semi-automatic extraction of hedgerows by applying the Object-Based Image Analysis (OBIA) approach to two multispectral satellite datasets. Multitemporal image data from PlanetScope and Copernicus Sentinel-2 have been used to test the applicability of the proposed approach for detailed land cover mapping, with an emphasis on extracting Small Woody Elements. This study demonstrates significant results in classifying and extracting hedgerows, a smaller landscape element, from both Sentinel-2 and PlanetScope images. A good overall accuracy (OA) was obtained using PlanetScope data (OA = 95%) and Sentinel-2 data (OA = 85%), despite the coarser resolution of the latter. This will undoubtedly demonstrate the effectiveness of the OBIA approach in leveraging freely available image data for detailed land cover mapping, particularly in identifying and classifying hedgerows, thus supporting biodiversity conservation and ecological infrastructure enhancement.
- 24 April 2025
- Published by MDPI AG in Remote Sensing
- Vol. 17 (9) , 1506
Open AccessSemi-Automatic Extraction of Hedgerows from High-Resolution Satellite Imagery
Small landscape elements are critical in ecological systems, encompassing vegetated and non-vegetated features. As vegetated elements, hedgerows contribute significantly to biodiversity conservation, erosion protection, and wind speed reduction within agroecosystems. This study focuses on the semi-automatic extraction of hedgerows by applying the Object-Based Image Analysis (OBIA) approach to two multispectral satellite datasets. Multitemporal image data from PlanetScope and Copernicus Sentinel-2 have been used to test the applicability of the proposed approach for detailed land cover mapping, with an emphasis on extracting Small Woody Elements. This study demonstrates significant results in classifying and extracting hedgerows, a smaller landscape element, from both Sentinel-2 and PlanetScope images. A good overall accuracy (OA) was obtained using PlanetScope data (OA = 95%) and Sentinel-2 data (OA = 85%), despite the coarser resolution of the latter. This will undoubtedly demonstrate the effectiveness of the OBIA approach in leveraging freely available image data for detailed land cover mapping, particularly in identifying and classifying hedgerows, thus supporting biodiversity conservation and ecological infrastructure enhancement.