基于Sentinel-2影像SAR融合的高分辨率土地覆盖制图

Yuhendra, E. Yulianti, Jupriadi Na'am
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引用次数: 1

摘要

哨兵-2是欧洲空间局(欧空局)的一个非常新的方案,旨在进行精细的空间分辨率全球监测。土地覆盖-土地利用(LCLU)分类任务可以利用雷达和光学遥感数据的融合,从而提高制图精度。在这里,我们提出了一种方法方法,将新的欧洲航天局Sentinel-1和Sentinel-2图像的信息融合在一起,对西苏门答腊南索洛克地区的一部分进行精确的土地覆盖测绘。数据预处理使用欧洲航天局的哨兵应用平台和SEN2COR工具箱进行。本研究的两个主要目标是评估ESA Sentinel-1A c波段SAR和Sentinel-2A光学数据在LCLU分类和制图中的潜在用途和协同效应。通过研究,得出了两个主要优点。首先,由ESA开发的传感器专用工具箱支持的预处理链代表了准备准备处理图像的可靠和快速方法。其次,建立并测试了基于雷达和光学影像整合Sentinel-1和Sentinel-2影像进行土地覆盖制图的方法框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optical SAR Fusion of Sentinel-2 Images for Mapping High Resolution Land Cover
Sentinel-2 is a very new programme of the European Space Agency (ESA) that is designed for fine spatial resolution global monitoring. 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 South Solok region, West Sumatera. Data pre-processing was carried out using the European Space Agency's Sentinel Application Platform and the SEN2COR toolboxes. The two main objectives of this study are to evaluate the potential use and synergetic effects of ESA Sentinel-1A C-band SAR and Sentinel-2A Optical data for classification and mapping of LCLU. As a result of the research, two main advantages. First, the pre-processing chain supported by sensor-specific toolboxes developed by ESA represents a reliable and fast approach for the preparation of ready-to-process imagery. Second, investigation to derive a methodological framework to integrate Sentinel-1 and Sentinel-2 imagery for land cover mapping by integrating of radar and optical imagery have been set up and tested.
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