首页> 外文会议>Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing >Clay contents predicted from hyperspectral VNIR/SWIR imagery, under different atmospheric conditions and spatial resolutions
【24h】

Clay contents predicted from hyperspectral VNIR/SWIR imagery, under different atmospheric conditions and spatial resolutions

机译:从高光谱VNIR / SWIR图像预测的粘土含量,在不同的大气条件和空间分辨率下

获取原文

摘要

Visible, Near-Infrared and Short Wave Infrared hyperspectral satellite imaging is one of the most promising tools for soil property mapping. The objective of this study was to test the sensitivity of soil property prediction results to atmospheric effects and to degradation in image spatial resolutions, to offer a first analysis of the potential of future hyperspectral satellite sensors for Soil applications (HYPXIM, PRISMA, Shalom, ENMAP and HyspIRI). Our results showed that (i) regression methods have robust performances from images from 5 to 30m and are inaccurate from images at 60 and 90m; (ii) when a correct compensation of the atmosphere effects is done, no differences are detected between the soil property maps retrieved from airborne imagery and the ones from spaceborne imagery; (iii) the spatial aggregation of the images induces a loss of the variance of the soil property prediction from 15 m of spatial resolution and a loss of information on soil spatial structures from 30 m of spatial resolution.
机译:可见,近红外和短波红外高光谱卫星成像是用于土壤特性制图的最有前途的工具之一。这项研究的目的是测试土壤性质预测结果对大气影响和图像空间分辨率退化的敏感性,以提供对未来土壤应用的高光谱卫星传感器(HYPXIM,PRISMA,Shalom,ENMAP)的潜力的初步分析。和HyspIRI)。我们的结果表明:(i)回归方法在5至30m的图像上具有鲁棒的性能,而在60和90m的图像上则不准确; (ii)在对大气影响进行了正确的补偿后,从机载图像获取的土壤特性图与从机载图像获取的土壤特性图之间没有发现差异; (iii)图像的空间聚集会导致15 m空间分辨率的土壤性质预测方差的损失,以及30 m空间分辨率的土壤空间结构信息的损失。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号