【24h】

Study on methods of cloud identification and data recover for MODIS data

机译:MODIS数据云识别与数据恢复方法研究

获取原文
获取原文并翻译 | 示例

摘要

MODIS data have great potential in rice growth monitoring and yield estimation due to the low cost and high time resolution. Unfortunately, MODIS, which is a kind of visible-infrared sensor, cannot detect land surface through cloud, and cloud-free image is quite rare during rice growth period due to cloudy weather. Therefore, cloud contamination is one of the main obstacles in rice growth monitoring and yield estimation using MODIS data. Based on spectral characteristics of cloud and MODIS channels, taking it into account that MODIS data includes thirty-six bands, especially the infrared channels subdivided, it has realized cloud detection in MODIS images by multi-spectral synthesis method, infrared difference algorithm, index methods and cloud detection index in this paper. The result shows that infrared difference algorithm, index methods analysis are the simple and effective methods to detect cloud. After geometric correction, the cloud-free images are obtained through interpolating using time series MODIS data and ratio value using same date data of different year.
机译:由于低成本和高时间分辨率,MODIS数据在水稻生长监测和产量估算中具有巨大潜力。不幸的是,MODIS是一种可见红外传感器,无法通过云来检测土地表面,并且由于多云的天气,水稻生长期间无云的图像非常罕见。因此,云污染是使用MODIS数据进行水稻生长监测和产量估算的主要障碍之一。基于云和MODIS通道的光谱特征,考虑到MODIS数据包括36个波段,尤其是细分的红外通道,它通过多光谱合成方法,红外差分算法,索引方法实现了MODIS图像中的云检测。和本文的云检测指标。结果表明,红外差分算法,指标法分析是检测云的简单有效的方法。经过几何校正后,通过使用时间序列MODIS数据和使用不同年份的相同日期数据的比率值进行插值获得无云图像。

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