Development of a spectral vegetation index for simultaneous characterization of flowering and foliage development

IF 0.3 Q4 AGRONOMY Terra Latinoamericana Pub Date : 2018-04-16 DOI:10.28940/terra.v36i2.249
Marcos Casiano Dominguez, F. P. Pellat
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引用次数: 1

Abstract

It is important to characterize the phenological patterns of flowering and foliage development in vegetation that has some degree of deciduous behavior due to its relation to the carbon cycle and water. Field techniques and use of digital photograph observation towers have limited geographical scope, so that remote sensing technology is a cost-effective option. In this work a flowering-foliage phenology model was revised and a new model that includes the use of vegetation index of flowering and foliage (VIFF) to characterize and differentiate the patterns is presented. To correlate the VIFF coverage flowering (CF) in vegetation, we conducted a validation experiment that included a low-growing shrub, in which different coverages (<15%) of white flowers were placed. The results showed that the VIFF correlates linearly with the coverage of flowers and the relationship depends on the coverage of the foliage where they are placed. The proposed development allowed establishing clear correlations between VIFF and floral vegetation cover of different coverage area, which was signif icantly effective, even with low percentages of flowering, undetectable with other techniques. Because it uses only red and near infrared bands, the proposed tool is accessible for most applications of remote sensing.
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同时表征花叶发育的光谱植被指数的建立
在具有一定落叶行为的植被中,花叶发育的物候特征与碳循环和水分的关系具有重要意义。实地技术和数字摄影观测塔的使用具有有限的地理范围,因此遥感技术是一种具有成本效益的选择。本文对花叶物候模型进行了修正,提出了利用花叶植被指数(VIFF)表征和区分花叶物候模式的新模型。为了关联植被的VIFF覆盖度开花(CF),我们在低矮灌木中进行了验证实验,在不同覆盖度(<15%)的白花中放置了不同的白花。结果表明,植被覆盖度与花的覆盖度呈线性相关关系,这种关系取决于花所处的叶的覆盖度。所建议的发展使VIFF与不同覆盖区域的花卉植被覆盖之间建立了明确的相关性,即使在开花百分比低的情况下也非常有效,这是其他技术无法检测到的。由于它只使用红色和近红外波段,因此所提出的工具可用于大多数遥感应用。
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来源期刊
Terra Latinoamericana
Terra Latinoamericana Environmental Science-Ecology
CiteScore
1.10
自引率
0.00%
发文量
49
审稿时长
16 weeks
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