首页 | 本学科首页   官方微博 | 高级检索  
     


An Extended Approach of Particle Swarm Optimization for Shoreline Extraction from RASAT Imagery
Authors:Hatice Catal Reis  Bülent Bayram  Salih Bozkurt  Abdulkadir Ince  Nusret Demir  Dursun Zafer Seker
Affiliation:1.Department of Geomatics Engineering,Gumushane University,Gumushane,Turkey;2.Department of Geomatics Engineering,Yildiz Technical University,Esenler, Istanbul,Turkey;3.Department of Space Science and Technologies, Faculty of Science,Remote Sensing Application and Research Centre,Antalya,Turkey;4.Department of Geomatics Engineering,Istanbul Technical University,Maslak, Istanbul,Turkey
Abstract:This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号