Assessing the utility of visible-to-shortwave infrared reflectance spectroscopy for analysis of soil weathering intensity and paleoclimate reconstruction
Assessing the utility of visible-to-shortwave infrared reflectance spectroscopy for analysis of soil weathering intensity and paleoclimate reconstruction
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评估可见光到短波红外反射光谱在土壤风化强度分析和古气候重建中的效用
DOI：
10.1016/j.palaeo.2017.07.007
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发表时间：
2017-07
期刊：
影响因子：
--
通讯作者：
Algeo Thomas J
中科院分区：
文献类型：
--
作者：
Zhao Lulu;Hong Hanlie;Liu Jiacheng;Fang Qian;Yao Yuzeng;Tan Wei;Yin Ke;Wang Chaowen;Chen Mi;Algeo Thomas J
可见-短波红外光谱技术是一种快速、有效的土壤性质评价方法。为了检验在VSWIR范围内（350-2500 nm）的反射光谱是否可以预测土壤风化强度，并检验这种方法的有效性，以补充或取代传统的矿物学和地球化学技术的古气候重建，我们调查了中国西南四川盆地胜利第四纪土壤序列。VSWIR吸收带可以通过包括位置（P）、深度（D）、宽度（W）、不对称性（AS）和半峰全宽（F）的几何参数来表征。我们的研究结果表明，在可见光到近红外（VNIR; 350-1000 nm）范围内的光谱特征可以解释在个别铁氧化物相的存在和/或浓度。光谱检测的水主要是结合在粘土矿物，这一单一的主要水源有利于短波红外（SWIR; 1000-2500 nm）参数的解释。土壤光谱参数进行了比较，从传统的实验室分析获得的土壤样品的铁氧化物矿物学，主要元素组成，粘土矿物学。VNIR参数和铁氧化物矿物学之间存在较强的相关性，D900是三价铁总浓度的最佳代表。P900和D700/D500与土壤样品的赤铁矿/（赤铁矿+针铁矿）[H/（H + G）]比值具有相似的变化趋势和关系，证实了它们作为季风风化强度指标的价值。较低的P900和D700/D500值表明较温暖和季节性干燥的土壤环境，反映了较强的东亚夏季风。一些SWIR参数用于评估非均质土壤中风化强度下降的实用性（例如，具有蠕虫状结构的那些）。因此，风化强度的光谱评价在相对均匀的土壤中最有效，风化程度与AS 2200，D2200/D1900和AS 1400高度相关。这些光谱代用指标的效用主要取决于土壤的矿物组成和应用类型（即，实验室与现场研究）。VSWIR在现场的应用（例如，成像光谱法（IS）显示出快速、原位绘制风化强度图的前景，从而为偏远和难以到达地区的古气候重建提供了一种方便的方法。
Visible-to-shortwave infrared reflectance (VSWIR) spectroscopy is a fast and efficient approach for estimation of soil properties. In order to test whether soil weathering intensity can be predicted using reflectance spectra in the VSWIR range (350–2500 nm), and to examine the efficacy of this methodology to supplement or substitute for traditional mineralogical and geochemical techniques of paleoclimate reconstruction, we investigated a Quaternary soil sequence at Shengli in the Sichuan Basin of southwestern China. VSWIR absorption bands can be characterized by geometrical parameters including position (P), depth (D), width (W), asymmetry (AS), and full width at half maximum (F). Our results indicate that spectral features in the visible-to-near-infrared (VNIR; 350–1000 nm) range can be interpreted in terms of the presence and/or concentration of individual Fe-oxide phases. Spectrally detected water is mostly bound in clay minerals, and this single dominant water source facilitates interpretation of shortwave infrared (SWIR; 1000–2500 nm) parameters. Soil spectral parameters were compared with the Fe-oxide mineralogy, major element composition, and clay mineralogy of soil samples obtained from conventional laboratory analyses. Strong correlations are found between VNIR parameters and Fe-oxide mineralogy, with D900serving as the best proxy for total ferric iron concentration. P900and D700/D500exhibit similar variation trends and relationships to the hematite/(hematite + goethite) [H/(H + G)] ratio of soil samples, confirming their value as monsoonal weathering intensity proxies. Lower values of P900and D700/D500indicate warmer and seasonally drier pedoenvironments, reflecting a stronger East Asian summer monsoon. The utility of some SWIR parameters for assessment of weathering intensity declines in inhomogeneous soils (e.g., those having vermiform structure). Thus, spectral evaluation of weathering intensity is most effective in soils that are relatively homogeneous, for which weathering degree is highly correlated to AS2200, D2200/D1900, and AS1400. The utility of these spectral proxies depends mainly on the mineral composition of soils and the application type (i.e., laboratory versus field studies). The application of VSWIR in the field (e.g., imaging spectroscopy, or IS) shows promise for rapid, in-situ mapping of weathering intensity, thus providing a convenient approach to paleoclimate reconstruction in remote and inaccessible regions.
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DOI：
--
发表时间：
2002
期刊：
--
影响因子：
--
作者：
Roger;Clark
通讯作者：
Roger;Clark
2.36 Ma以来东亚季风降水与热带太平洋ENSO系统的共同演化：西菲律宾海高分辨率粘土矿物记录的新见解
影响因子：
5.3
作者：
Yu Zhaojie;Wan Shiming;Colin Christophe;Yan Hong;Bonneau Lucile;Liu Zhifei;Song Lina;Sun Hanjie;Xu Zhaokai;Jiang Xuejun;Li Anchun;Li Tiegang
通讯作者：
Li Tiegang
影响因子：
2.2
作者：
A. Varga;G. Újvári;B. Raucsik
通讯作者：
A. Varga;G. Újvári;B. Raucsik
影响因子：
4
作者：
S. Xiong;Z. Ding;Yuanjian Zhu;Rufang Zhou;Haijian Lu
通讯作者：
S. Xiong;Z. Ding;Yuanjian Zhu;Rufang Zhou;Haijian Lu
影响因子：
1.4
作者：
V. Rosolen;M. Lamotte;R. Boulet;J. Trichet;O. Rouer;A. Melfi
通讯作者：
V. Rosolen;M. Lamotte;R. Boulet;J. Trichet;O. Rouer;A. Melfi