首页> 外文期刊>Geoderma: An International Journal of Soil Science >Sensing landscape level change in soil fertility following deforestation and conversion in the highlands of Madagascar using Vis-NIR spectroscopy.
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Sensing landscape level change in soil fertility following deforestation and conversion in the highlands of Madagascar using Vis-NIR spectroscopy.

机译:使用Vis-NIR光谱仪感知马达加斯加高地的森林砍伐和转换后土壤肥力的景观水平变化。

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Research data on soil quality are scarce in Madagascar, despite the island's widely recognized problems of soil and environmental degradation. One of the major constraints to properly assessing current status, trends and processes of soil degradation is the high level of costs involved when using conventional soil analytical methods. Previous studies have demonstrated that visible-near-infrared (Vis-NIR) reflectance spectroscopy may permit rapid and cost effective analysis of tropical soils that could provide new opportunities for farmers, land managers, local authorities and researchers in assessing and managing soil quality. This study tested the potential of Vis-NIR soil spectral libraries for predicting and mapping soil properties in the eastern highlands of Madagascar. Stable calibration models were developed for several key soil properties. Cross-validated r2 values were soil organic carbon (SOC), 0.94; total nitrogen (TN), 0.96; and cation exchange capacity (CEC), 0.80. A spectral soil fertility index (SFI) was developed based on ten commonly used agronomic indicators of soil fertility. SFI varied significantly with current and historic land use. The index was successfully calibrated to both soil reflectance measured in the laboratory (p=0.003) and Landsat TM reflectance (p=0.003), which permitted mapping of the index..
机译:尽管该岛已广为人知的土壤和环境退化问题,但马达加斯加缺乏有关土壤质量的研究数据。正确评估土壤退化的现状,趋势和过程的主要限制之一是使用常规土壤分析方法时所涉及的高昂费用。先前的研究表明,可见-近红外(Vis-NIR)反射光谱法可以对热带土壤进行快速且经济高效的分析,这可以为农民,土地管理者,地方当局和研究人员提供评估和管理土壤质量的新机会。这项研究测试了Vis-NIR土壤谱库在预测和绘制马达加斯加东部高地土壤特性方面的潜力。针对几种关键土壤特性开发了稳定的校准模型。交叉验证的r2值为土壤有机碳(SOC)为0.94;总氮(TN)为0.96;阳离子交换容量(CEC)为0.80。根据十个常用的土壤肥力农学指标,开发了光谱土壤肥力指数(SFI)。 SFI随当前和历史土地用途而有很大差异。该指数已成功地校准为在实验室测量的土壤反射率(p = 0.003)和Landsat TM反射率(p = 0.003),这允许对该指数进行映射。

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