8 Table 1. Description of the leaf datasets used in this study. * The ANGER dataset is available online http://opticleaf.ipgp.fr/index.php?page=database.181 Database Reference Spectral range (nm) Number of leaves Optical properties Chlorophyll content 𝑪𝒂𝒃 (g cm2 ) Carotenoid content 𝑪𝒙𝒄 (g cm2 ) Anthocyanin content 𝑪𝒂𝒏𝒕𝒉 (g cm2 ) Mean SD Min Max Mean SD Min Max Mean SD Min Max ANGERS* 1, 2 400-2500 308 R & T 34.41 21.85 0.78 106.70 8.84 5.14 0.00 25.28 N/A N/A N/A V
Open resource ↗opticleaf.ipgp.fr · ANGERS · pdf-raw-page:9 lines:1-28Paper record
PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle
Remote Sensing of Environment · 1 Jan 2017 · 10.1016/j.rse.2017.03.004
Abstract
Leaf pigments provide valuable information about plant physiology. High resolution monitoring of their dynamics will give access to better understanding of processes occurring at different scales, and will be particularly important for ecologists, farmers, and decision makers to assess the influence of climate change on plant functions, and the adaptation of forest, crop, and other plant canopies. In this article, we present a new version of the widely-used PROSPECT model, hereafter named PROSPECT-D for dynamic, which adds anthocyanins to chlorophylls and carotenoids, the two plant pigments in the current version. We describe the evolution and improvements of PROSPECT-D compared to the previous versions, and perform a validation on various experimental datasets. Our results show that PROSPECT-D outperforms all the previous versions. Model prediction uncertainty is decreased and photosynthetic pigments are better retrieved. This is particularly the case for leaf carotenoids, the estimation of which is particularly challenging. PROSPECT-D is also able to simulate realistic leaf optical properties with minimal error in the visible domain, and similar performances to other versions in the near infrared and shortwave infrared domains.
Code and data availability