期刊文献+

基于新组合光谱指数的马铃薯植株氮含量遥感估测 被引量:3

Remotely Estimation of Plant Nitrogen Concentration in Potato Using New Combined Spectral Index
下载PDF
导出
摘要 如何利用卫星搭载的常规通道蓝光(B)、绿光(G)、红光(R)和近红外(NIR)实现作物氮素营养诊断对于区域氮素优化管理及氮素循环估测具有重要意义。本研究以2014—2016年在内蒙古阴山北麓武川县和四子王旗布置的多年多点不同氮水平的田间试验为基础,通过冠层高光谱仪tec5采集马铃薯关键生育期块茎形成期、块茎膨大期和淀粉积累期植株冠层光谱数据,利用卫星通道的波段响应函数模拟GF-2(GF)和Sentinel 2A(S)卫星光谱反射率,通过波段优化和指数组合计算波段优化归一化及其组合多光谱指数,构建基于多光谱指数的马铃薯植株氮素含量估测模型,并用田块数据进行验证。研究结果表明,敏感波段的提取对卫星通道的准确筛选具有指导意义,基于中心敏感波段筛选的绿光(G)和蓝光(B)通道计算的优化多光谱指数GF-GBNDSI和S-GBNDSI与马铃薯植株氮素含量的线性拟合决定系数(R^(2))最高,分别为0.41和0.38。GBNDSI分别与NDVI和GNDVI组合得到的多光谱指数GBNDSI/NDVI和GBNDSI/GNDVI能够显著提高对马铃薯植株氮素含量的解释能力,其中GF-GBNDSI/NDVI和GF-GBNDSI/GNDVI与马铃薯植株氮素含量的线性拟合R^(2)分别为0.57和0.56;S-GBNDSI/NDVI和S-GBNDSI/GNDVI与马铃薯植株氮素含量的线性拟合R^(2)分别为0.54和0.55。与红边(red edge,RE)多光谱指数相比,GBNDSI/NDVI和GBNDSI/GNDVI不仅克服了大部分高分辨率卫星缺乏红边通道的缺点,而且能够达到与红边多光谱指数REBNDSI/NDVI(R^(2)=0.53)和REBNDSI/GNDVI(R^(2)=0.59)基本相当的估测建模能力,并在模拟的田块数据中到了良好的验证。S-GBNDSI/NDVI估测模型的均方根误差和平均相对误差分别为0.40%、10.48%;GF-GBNDSI/NDVI估测模型的均方根误差和平均相对误差分别为0.39%、10.06%。鉴于目前大多数高分辨率卫星,尤其是国产系列卫星缺乏红边通道,基于常规通道构建的优化光谱指数GBNDSI/NDVI和GBNDSI/GNDVI在作物植株氮素含量监测上更具备推广应用的价值。 Optimally using satellite carrying channels of blue(B),green(G),red(R)and near-infrared(NIR)to estimate crop N status play a crucial role in the management and estimation of regional N cycling.The current study was aimed to assess the performance of optimized normalized and integrated spectral indices,derived from simulated broadband GF-2(GF)and Sentinel 2A(S)satellites data,to remotely sense plant N concentration in potato(Solanum tuberosum L.).Different field experiments were conducted with different N levels for two potato cultivars in Wuchuan County and Siziwangqi County at the northern Yinshan in Inner Mongolia from 2014 to 2016.The canopy reflectance data of potato at the growth stages of tuber formation,tuber bulking and starch accumulation were collected by a canopy hyper-spectrometer tec5.The estimation models of potato plant nitrogen concentration based on different spectral indices were constructed and validated by independent field data.The results showed that the extractive sensitive bands were able to guide the selection of satellite carrying channels.The optimal multi-spectral indices GF-GBNDSI and S-GBNDSI calculated based on the green(G)and blue(B)channels selected from the sensitive central bands had the highest coefficient of determination(R^(2))with plant N concentration of potato,and the R^(2) was 0.41 and 0.38,respectively.The multi-spectral indices GBNDSI/NDVI and GBNDSI/GNDVI constructed by combining NDVI and GNDVI with GBNDSI,respectively,could significantly improve the explanation ability of plant N concentration of potato.The R^(2) of GBNDSI/NDVI and GBNDSI/GNDVI based on GF-2 and Sentinel 2A channel ranged from 0.54 to 0.57.Compared with the red edge multi-spectral index,GBNDSI/NDVI and GBNDSI/GNDVI not only overcame the lacking the red edge channel with most high-resolution satellites,but also reached a better estimating ability like red edge based REBNDSI/NDVI(R^(2)=0.53)and REBNDSI/GNDVI(R^(2)=0.59).The validated results showed that the root mean square error and mean relative error of the S-GBNDSI/NDVI and GF-GBNDSI/NDVI models were about 0.40%and 10.27%,respectively.Since most high-resolution satellites,especially most of the domestic satellites lacking the red edge channel,the optimized GBNDSI/NDVI and GBNDSI/GNDVI involving conventional channels can be used to monitor plant N concentration in crop.
作者 杨海波 李渊 尹航 李斐 YANG Haibo;LI Yuan;YIN Hang;LI Fei(Inner Mongolia Key Laboratory of Soil Quality and Nutrient Resource,College of Grassland,Resources and Environment,Inner Mongolia Agricultural University,Key Laboratory of Agricultural Ecological Security and Green Development at Universities of Inner Mongolia Autonomous Region,Hohhot 010011,China)
出处 《土壤》 CAS CSCD 北大核心 2022年第2期385-395,共11页 Soils
基金 内蒙古自治区关键技术攻关计划项目(2019GG248,2020GG0038)资助。
关键词 马铃薯 氮素含量 光谱指数 卫星遥感 Potato Nitrogen concentration Spectral index Satellite based remote sensing
  • 相关文献

参考文献11

二级参考文献137

共引文献824

同被引文献43

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部