Cork oak woodland land-cover types classification: a comparison between UAV sensed imagery and field survey
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Author
Heuschmidt, Florence
Gómez-Candón, David
Soares, Cristina
Cerasoli, Sofia
Silva, Joao M.N.
Publication date
2020-07-29ISSN
0143-1161
Abstract
This work assesses the use of aerial imagery for the vegetation cover characterization in cork oak woodlands. The study was conducted in a cork oak woodland in central Portugal during the summer of 2017. Two supervised classification methods, pixel-based and object-based image analysis (OBIA), were tested using a high spatial resolution image mosaic. Images were captured by an unmanned aerial vehicle (UAV) equipped with a red, green, blue (RGB) camera. Four different vegetation covers were distinguished: cork oak, shrubs, grass and other (bare soil and tree shadow). Results have been compared with field data obtained by the point-intercept (PI) method. Data comparison reveals the reliability of aerial imagery classification methods in cork oak woodlands. Results show that cork oak was accurately classified at a level of 82.7% with pixel-based method and 79.5% with OBIA . 96.7% of shrubs were identified by OBIA, whereas there was an overestimation of 21.7% with pixel approach. Grass presents an overestimation of 22.7% with OBIA and 12.0% with pixel-based method. Limitations rise from using only spectral information in the visible range. Thus, further research with the use of additional bands (vegetation indices or height information) could result in better land-cover type classification.
Document Type
Article
Document version
Accepted version
Language
English
Subject (CDU)
631 - Agriculture in general
Pages
13
Publisher
Taylor and Francis
Is part of
International Journal of Remote Sensing (IJRS)
Citation
Heuschmidta, Florence, David Gómez-Candón, Cristina Soares, Sofia Cerasoli, and João M. N. Silva. 2020. "Cork Oak Woodland Land-Cover Types Classification: A Comparison Between UAV Sensed Imagery And Field Survey". International Journal Of Remote Sensing 41 (19): 7649-7659. doi:10.1080/2150704X.2020.
Program
Ús Eficient de l'Aigua en Agricultura
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- ARTICLES CIENTÍFICS [2831]
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