Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations
<p>Recently, remotely sensed measurements of the near-infrared reflectance (NIRv) of vegetation, the fluorescence correction vegetation index (FCVI), and radiance (NIRvrad) of vegetation have emerged as indicators of vegetation structure and function with potential to enhance or improve upon c...
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| Autores principales: | , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/5bf07e4cca8c496d9e0a7c652712c525 |
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| Sumario: | <p>Recently, remotely sensed measurements of the
near-infrared reflectance (NIRv) of vegetation, the fluorescence correction
vegetation index (FCVI), and radiance (NIRvrad) of vegetation have emerged
as indicators of vegetation structure and function with potential to enhance
or improve upon commonly used indicators, such as the normalized difference
vegetation index (NDVI) and the enhanced vegetation index (EVI). The
applicability of these remotely sensed indices to tropical forests, key
ecosystems for global carbon cycling and biodiversity, has been limited. In
particular, fine-scale spatial and temporal heterogeneity of structure and
physiology may contribute to variation in these indices and the properties
that are presumed to be tracked by them, such as gross primary productivity
(GPP) and absorbed photosynthetically active radiation (APAR). In this
study, fine-scale (approx. 15 cm) tropical forest heterogeneity represented by
NIRv, FCVI, and NIRvrad and by lidar-derived height is investigated and
compared to NIRv and EVI using unoccupied aerial system (UAS)-based
hyperspectral and lidar sensors. By exploiting near-infrared signals, NIRv,
FCVI, and NIRvrad captured the greatest spatiotemporal variability, followed
by the enhanced vegetation index (EVI) and then the normalized difference
vegetation index (NDVI). Wavelet analyses showed the dominant spatial scale
of variability of all indicators was driven by tree clusters and
larger-than-tree-crown size gaps rather than individual tree crowns. NIRv,
FCVI, NIRvrad, and EVI captured variability at smaller spatial scales
(<span class="inline-formula">∼</span> 50 m) than NDVI (<span class="inline-formula">∼</span> 90 m) and the lidar-based
surface model (<span class="inline-formula">∼</span> 70 m). We show that spatial and temporal
patterns of NIRv and FCVI were virtually identical for a dense green canopy,
confirming predictions in earlier studies. Furthermore, we show that
NIRvrad, which does not require separate irradiance measurements, correlated
more strongly with GPP and PAR than did other indicators. NIRv, FCVI, and
NIRvrad, which are related to canopy structure and the radiation regime of
vegetation canopies, are promising tools to improve understanding of
tropical forest canopy structure and function.</p> |
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