首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >Improved Crop Residue Cover Estimates from Satelite Images by Coupling Residue and Water Spectral Indices
【24h】

Improved Crop Residue Cover Estimates from Satelite Images by Coupling Residue and Water Spectral Indices

机译:通过耦合残留量和水谱指数从卫星图像中改进的作物残留量估算

获取原文

摘要

Crop residues protect the soil against erosion, improve runoff water quality and determine C sequestration. Thus, the capability to assess crop residue cover can improve predictions of the impact of agricultural practices. Our objective was to develop a method to alleviate the adverse effect of variable moisture conditions on crop residue estimates from satellite imagery. Fields with uneven and with uniform water distribution were identified in satellite images (WorldView-3) from Maryland (USA). The results showed that moisture correction of spectral bands based on a water index reduced the root mean square error of most common residue indices, NDTI (Normalized Difference Tillage Index) and SINDRI (Shortwave Infrared Normalized Difference Residue Index). If bands are available, crop residue estimation should be based on SINDRI. If only Landsat or Sentinel-2 satellites are available, crop residues estimated combining NDTI with a water index could alleviate the adverse effect of variable moisture conditions.
机译:作物残渣可保护土壤免遭侵蚀,改善径流水质并决定固碳。因此,评估农作物残茬覆盖率的能力可以改善对农业实践影响的预测。我们的目标是开发一种方法,以减轻水分条件变化对卫星影像中估计的农作物残留量的不利影响。在来自美国马里兰州的卫星图像(WorldView-3)中识别出水量分布不均匀且均匀的田地。结果表明,基于水分指数的光谱带湿度校正可降低大多数常见残留指数,NDTI(归一化耕种差值指数)和SINDRI(短波红外归一化残留物指数)的均方根误差。如果频段可用,则作物残渣估算应基于SINDRI。如果只有Landsat或Sentinel-2卫星可用,则将NDTI与水指数结合起来估算的农作物残留量将减轻可变湿度条件的不利影响。

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