@misc{10481/66810,
year = {2021},
month = {1},
url = {http://hdl.handle.net/10481/66810},
abstract = {Vegetation generally appears scattered in drylands. Its structure, composition and spatial patterns are key controls of biotic interactions, water, and nutrient cycles. Applying segmentation methods to very high-resolution images for monitoring changes in vegetation cover can provide relevant information for dryland conservation ecology. For this reason, improving segmentation methods and understanding the effect of spatial resolution on segmentation results is key to improve dryland vegetation monitoring. We explored and analyzed the accuracy of Object-Based Image Analysis (OBIA) and Mask Region-based Convolutional Neural Networks (Mask R-CNN) and the fusion of both methods in the segmentation of scattered vegetation in a dryland ecosystem. As a case study, we mapped Ziziphus lotus, the dominant shrub of a habitat of conservation priority in one of the driest areas of Europe. Our results show for the first time that the fusion of the results from OBIA and Mask R-CNN increases the accuracy of the segmentation of scattered shrubs up to 25% compared to both methods separately. Hence, by fusing OBIA and Mask R-CNNs on very high-resolution images, the improved segmentation accuracy of vegetation mapping would lead to more precise and sensitive monitoring of changes in biodiversity and ecosystem services in drylands.},
organization = {European Research Council (ERC)
	
647038},
organization = {European LIFE Project 
	
ADAPTAMED LIFE14 CCA/ES/000612},
organization = {Junta de Andalucia
	
P18-RT-1927
P18-RT-5130},
organization = {DETECTOR 
	
A-RNM-256-UGR18},
organization = {European Union Funds for Regional Development},
organization = {HIPATIA-UAL fellowship},
organization = {Spanish Government
	
RYC-201518136},
organization = {A-TIC-458-UGR18},
publisher = {MDPI},
keywords = {Deep learning},
keywords = {Fusion},
keywords = {Mask R-CNN},
keywords = {Object-Based Image Analysis (OBIA)},
keywords = {Optical sensor},
keywords = {Scattered vegetation},
keywords = {Very high-resolution},
title = {Mask R-CNN and OBIA Fusion Improves the Segmentation of Scattered Vegetation in Very High-Resolution Optical Sensors},
doi = {10.3390/s21010320},
author = {Guirado, Emilio and Blanco Sacristán, Javier and Rodríguez-Caballero, Emilio and Tabik, Siham and Alcaraz Segura, Domingo and Martínez-Valderrama, Jaime and Cabello, Javier},
}