...
首页> 外文期刊>Advances in Meteorology >Combining of the H/A/Alpha and Freeman-Durden Polarization Decomposition Methods for Soil Moisture Retrieval from Full-Polarization Radarsat-2 Data
【24h】

Combining of the H/A/Alpha and Freeman-Durden Polarization Decomposition Methods for Soil Moisture Retrieval from Full-Polarization Radarsat-2 Data

机译:H / A / Alpha和Freeman-Durden偏振分解分解方法的结合从全极化雷达拉特 - 2数据中的土壤水分检索

获取原文
获取原文并翻译 | 示例
           

摘要

Soil moisture (SM) plays important roles in surface energy conversion, crop growth, environmental protection, and drought monitoring. As crops grow, the associated vegetation seriously affects the ability of satellites to retrieve SM data. Here, we collected such data at different growth stages of maize using Bragg and X-Bragg scattering models based on the Freeman-Durden polarization decomposition method. We used the H/A/Alpha polarization decomposition approach to extract accurate threshold values of decomposed scattering components. The results showed that the H and Alpha values of bare soil areas were lower and those of vegetated areas were higher. The threshold values of the three scattering components were 0.2-0.4 H and 7-24° Alpha for the surface scattering component, 0.6-0.9 H and 22-50° Alpha for the volume scattering component, and other values for the dihedral scattering component. The SM data retrieved (using the X-Bragg model) on June 27, 2014, were better than those retrieved at other maize growth stages and were thus associated with the minimum root-mean-square error value (0.028). The satellite-evaluated SM contents were in broad agreement with data measured in situ. Our algorithm thus improves the accuracy of SM data retrieval from synthetic-aperture radar (SAR) images.
机译:土壤水分(SM)在表面能转化,作物生长,环保和干旱监测中起重要作用。随着作物的增长,相关的植被严重影响卫星检索SM数据的能力。在这里,我们使用基于Freeman-Durden偏振分解方法的布拉格和X-Bragg散射模型在玉米的不同增长阶段收集了这些数据。我们使用了H / A / alpha偏振分解方法来提取分解散射组件的精确阈值。结果表明,裸土壤区域的H和α值较低,植被地区的含量较高。三个散射组分的阈值为0.2-0.4小时,对于表面散射组分,0.6-0.9小时和22-50°α的7-24°α为体积散射组分,以及二对面散射组分的其他值。从2014年6月27日检索的SM数据(使用X-Bragg Models)优于其他玉米生长阶段的那些,因此与最小根平均误差值(0.028)相关联。卫星评估的SM内容与原位测量的数据相吻合。因此,我们的算法提高了来自合成孔径雷达(SAR)图像的SM数据检索的准确性。

著录项

  • 来源
    《Advances in Meteorology》 |2018年第3期|共17页
  • 作者单位

    Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100101 China;

    Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100101 China;

    Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100101 China;

    Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100101 China;

    Satellite Environment Center Ministry of Environmental Protection Beijing 100094 China;

    Satellite Environment Center Ministry of Environmental Protection Beijing 100094 China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学(气象学);
  • 关键词

    Combining; H/A/Alpha; Freeman-Durden;

    机译:结合;h / a / alpha;freeman-durden;

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