...
首页> 外文期刊>Journal of near infrared spectroscopy >Prediction accuracy of local and regional soil total carbon models, calibrated based on visible-near infrared spectra, in the Djerid arid region
【24h】

Prediction accuracy of local and regional soil total carbon models, calibrated based on visible-near infrared spectra, in the Djerid arid region

机译:局域土壤总碳模型的预测准确性,基于近红外光谱校准,在Djerid干旱地区

获取原文
获取原文并翻译 | 示例

摘要

Visible-near infrared diffuse reflectance spectroscopy (vis-NIR DRS) is recognized as a promising tool for predicting various soil physico-chemical and biological properties. However, models' applicability, transferability, and scaling are still questionable. Our objective was to study, for total carbon, these aspects in arid context. QuickBird satellite images enabled us to establish parsimonious soil sampling strategies over three different sites selected in Djerid arid region. For each site, a spectral local database was built and merging them allowed us to obtain a regional database. The principal component analysis enabled us to select independent calibration and validation sets. Local spectral models were performing well for two sites and poorly for the site with high salinity. In cross-transfer, local models showed limited geographic robustness. The regional model was less efficient than one of the local models, yet quite satisfactory (r(2) = 0.67, bias=0.18%, RMSEP =0.93% and REP =1.72). The choice of local or regional model should depend not only on performance of the model but also on the purpose of the intended application and the required precision.
机译:可见的近红外漫反射反射光谱(Vis-NIR DRS)被认为是预测各种土壤物理化学和生物学性质的有希望的工具。但是,模型的适用性,可转换性和缩放仍然是可疑的。我们的目的是为了总碳,在干旱背景下的这些方面。 QuickBird卫星图像使我们能够在Djerid干旱地区选择的三个不同网站上建立典范的土壤采样策略。对于每个站点,构建并合并它们允许我们获取区域数据库的频谱本地数据库。主成分分析使我们能够选择独立的校准和验证集。本地光谱模型对于两个位点表现良好,对于具有高盐度的遗址差。在交叉转移中,本地模型显示出地理稳健性有限。区域模型效率低于本地模型,但令人满意(R(2)= 0.67,偏差= 0.18%,RMSEP = 0.93%和REP = 1.72)。本地或区域模型的选择不仅应依赖模型的性能,而且还取决于预期应用的目的和所需的精度。

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