کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5754708 1621207 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle
چکیده انگلیسی


- PROSPECT model was calibrated to include chlorophylls, carotenoids and anthocyanins.
- PROSPECT-Dynamic outperforms previous versions for estimating pigment content.
- Simulating leaf optics is strongly improved, particularly for anthocyanic leaves.
- This new model gives new perspectives for the monitoring of vegetation status.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 193, May 2017, Pages 204-215
نویسندگان
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