首页    期刊浏览 2025年06月17日 星期二
登录注册

文章基本信息

  • 标题:Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia
  • 本地全文:下载
  • 作者:Nicola Clerici ; Cesar Augusto Valbuena Calderón ; Juan Manuel Posada
  • 期刊名称:Journal of Maps
  • 印刷版ISSN:1744-5647
  • 出版年度:2017
  • 卷号:13
  • 期号:2
  • 页码:718-726
  • DOI:10.1080/17445647.2017.1372316
  • 出版社:Journal of Maps
  • 摘要:Land cover–land use (LCLU) classification tasks can take advantage of the fusion of radar and optical remote sensing data, leading generally to increase mapping accuracy. Here we propose a methodological approach to fuse information from the new European Space Agency Sentinel-1 and Sentinel-2 imagery for accurate land cover mapping of a portion of the Lower Magdalena region, Colombia. Data pre-processing was carried out using the European Space Agency’s Sentinel Application Platform and the SEN2COR toolboxes. LCLU classification was performed following an object-based and spectral classification approach, exploiting also vegetation indices. A comparison of classification performance using three commonly used classification algorithms was performed. The radar and visible-near infrared integrated dataset classified with a Support Vector Machine algorithm produce the most accurate LCLU map, showing an overall classification accuracy of 88.75%, and a Kappa coefficient of 0.86. The proposed mapping approach has the main advantages of combining the all-weather capability of the radar sensor, spectrally rich information in the visible-near infrared spectrum, with the short revisit period of both satellites. The mapping results represent an important step toward future tasks of aboveground biomass and carbon estimation in the region.
  • 关键词:Sentinel;1 ; Sentinel;2 ; land cover mapping ; data fusion ; segmentation ; Colombia
国家哲学社会科学文献中心版权所有