Unraveling Segmentation Quality of Remotely Sensed Images on Plastic-Covered Greenhouses: A Rigorous Experimental Analysis from Supervised Evaluation Metrics

Unraveling Segmentation Quality of Remotely Sensed Images on Plastic-Covered Greenhouses: A Rigorous Experimental Analysis from Supervised Evaluation Metrics

Plastic-covered greenhouse (PCG) segmentation represents a significant challenge for object-based PCG mapping studies due to the spectral characteristics of these singular structures. Therefore, the assessment of PCG segmentation quality by employing a multiresolution segmentation algorithm (MRS) wa...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Senel, Gizem, Aguilar Torres, Manuel Ángel, Aguilar Torres, Fernando José, Nemmaoui, Abderrahim, Goksel, Cigdem
Aineistotyyppi: info:eu-repo/semantics/article
Kieli:English
Julkaistu: MDPI 2023
Aiheet:
greenhouse segmentation
multiresolution segmentation (MRS)
object-based image analysis (OBIA)
segmentation quality
supervised evaluation
Linkit:http://hdl.handle.net/10835/14173

Internet

http://hdl.handle.net/10835/14173

Samankaltaisia teoksia