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    Zhang Surong, Wang Daming, Yang Junquan, Zhang Jing, Wang Jianhua, Zhang Donghui, Tong Yunxiao, Jin Zhibin, Chen Donglei. 2024. Quantitative remote sensing inversion of elements in soils: Advances in research and future prospects[J]. Geology in China, 51(5): 1664−1675. DOI: 10.12029/gc20231011002
    Citation: Zhang Surong, Wang Daming, Yang Junquan, Zhang Jing, Wang Jianhua, Zhang Donghui, Tong Yunxiao, Jin Zhibin, Chen Donglei. 2024. Quantitative remote sensing inversion of elements in soils: Advances in research and future prospects[J]. Geology in China, 51(5): 1664−1675. DOI: 10.12029/gc20231011002

    Quantitative remote sensing inversion of elements in soils: Advances in research and future prospects

    • This paper is the result of agricultural geological survey engineering.
      Objective Soil quality is closely related to human activities. Given that traditional methods fall short in achieving the large−scale dynamic monitoring of soil quality, the quantitative inversion of elements in soils using hyperspectral remote sensing, which proves macroscopic, real−time, in−situ, and fast, has emerged as a hot topic and challenge in the field of remote sensing application.
      Methods This paper explores three methods for quantitative remote sensing inversion of elements in soils: direct quantitative inversion, indirect quantitative inversion using correlations among the elements, and quantitative inversion based on plant spectra. Specifically, this paper systematically summarizes the primary principles, advantages, and current research status of these methods and proposes future trends in relevant fields from the perspective of interdisciplinary integration.
      Results The commonly used methods for the quantitative inversion of elements in soils face challenges when applied on a large scale. Among these, the indirect inversion based on the spectra of plant leaves or canopies is considered the most reliable. Achievements in ecological geochemistry enable the identification of the unique spectral effects of target elements in different plants, which assists in determining the principle of the plant spectrum−based quantitative inversion of elements in soils.
      Conclusions More in−depth research based on big data mining and the physicochemical properties of soils while promoting interdisciplinary integration represents a favorable direction for achieving breakthroughs in wide−area monitoring technology for elements in soils.
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