Unraveling Segmentation Quality of Remotely Sensed Images on Plastic-Covered Greenhouses: A Rigorous Experimental Analysis from Supervised Evaluation Metrics
MetadataShow full item record
Author/sSenel, Gizem; Aguilar Torres, Manuel Angel; Aguilar Torres, Fernando José; Nemmaoui, Abderrahim; Goksel, Cigdem
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) was addressed in this study. The structure of this work is composed of two differentiated phases. The first phase aimed at testing the performance of eight widely applied supervised segmentation metrics in order to find out which was the best metric for evaluating image segmentation quality over PCG land cover. The second phase focused on examining the effect of several factors (reflectance storage scale, image spatial resolution, shape parameter of MRS, study area, and image acquisition season) and their interactions on PCG segmentation quality through a full factorial analysis of variance (ANOVA) design. The analysis considered two different study areas (Almeria (Spain) and Antalya (Turkey))...
multiresolution segmentation (MRS)
object-based image analysis (OBIA)