A dataset of hyperspectral Look-Up Tables for 3.5 million
traits and structural combinations of Central European
temperate broadleaf forests

S 2024

A dataset of hyperspectral Look-Up Tables for 3.5 million traits and structural combinations of Central European temperate broadleaf forests

HANOUSEK, Tomáš; Terézia SLANINÁKOVÁ; Tomáš REBOK a Růžena JANOUTOVÁ

Základní údaje

Originální název

A dataset of hyperspectral Look-Up Tables for 3.5 million traits and structural combinations of Central European temperate broadleaf forests

Autoři

HANOUSEK, Tomáš; Terézia SLANINÁKOVÁ; Tomáš REBOK a Růžena JANOUTOVÁ

Vydání

2024

Další údaje

Typ výsledku

Specializovaná databáze

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

DOI

http://dx.doi.org/10.48700/datst.bcnpf-47q73

Klíčová slova anglicky

en LUT en look-up tableradiative transfer model;DART;synthetic spectral data;leaf traits;hyperspectral data

Příznaky

Mezinárodní význam

Změněno: 16. 11. 2024 16:51, Mgr. Tomáš Hanousek

Anotace

V originále

The dataset comprises 3.5 million unique combinations of leaf biochemical properties and canopy structural characteristics of forest scenes, along with various configurations of solar geometry. It provides spectral data spanning wavelengths from 450 nm to 2300 nm, with a 2 nm resolution. The dataset is divided into two files: one detailing the average reflectance of all scene pixels and another focusing specifically on sunlit leaf pixels. Look-up tables (LUT) were created using version 5.10.0 of the Discrete Anisotropic Radiative Transfer model. The virtual forest scenes are based on 3D models of European beech trees, derived from Terrestrial Lidar Scanning, and adjusted for different leaf area indices and structural configurations to simulate natural forest diversity. Reflectance data were processed using Matlab and Python scripts, resulting in hyperspectral cubes, which were subsequently used to generate the LUT. This dataset is valuable for training machine learning models aimed at retrieving forest functional traits and for calibrating remote sensing algorithms. Its high spectral resolution and diverse trait combinations make it adaptable to different times, locations, and both hyper- and multispectral sensors, supporting future hyperspectral satellite missions.

Návaznosti

LM2023048, projekt VaV

Název: Česká infrastruktura sledování uhlíku

MUNI/A/1469/2023, interní kód MU

Název: Geografický výzkum společenských a přírodních procesů v období změn

Investor: Masarykova univerzita, Geografický výzkum společenských a přírodních procesů v období změn

726/2023, interní kód MU

Název: ENVision: platforma pro analýzu přírodních ekosystémů s využitím leteckých a satelitních dat

Investor: CESNET, ENVision: platforma pro analýzu přírodních ekosystémů s využitím leteckých a satelitních dat

90254, velká výzkumná infrastruktura

Název: e-INFRA CZ II

90255, velká výzkumná infrastruktura

Název: ELIXIR CZ III

Citovat

HANOUSEK, Tomáš; Terézia SLANINÁKOVÁ; Tomáš REBOK a Růžena JANOUTOVÁ. A dataset of hyperspectral Look-Up Tables for 3.5 million traits and structural combinations of Central European temperate broadleaf forests. 2024. Dostupné z: https://dx.doi.org/10.48700/datst.bcnpf-47q73.

@manual{2452297,
   author = {Hanousek, Tomáš and Slanináková, Terézia and Rebok, Tomáš and Janoutová, Růžena},
   doi = {http://dx.doi.org/10.48700/datst.bcnpf-47q73},
   keywords = {en LUT en look-up tableradiative transfer model;DART;synthetic spectral data;leaf traits;hyperspectral data},
   title = {A dataset of hyperspectral Look-Up Tables for 3.5 million traits and structural combinations of Central European temperate broadleaf forests},
   url = {https://data.narodni-repozitar.cz/general/datasets/4y0sy-qh735},
   year = {2024}
}

TY  - COMP
ID  - 2452297
AU  - Hanousek, Tomáš - Slanináková, Terézia - Rebok, Tomáš - Janoutová, Růžena
PY  - 2024
TI  - A dataset of hyperspectral Look-Up Tables for 3.5 million traits and structural combinations of Central European temperate broadleaf forests
KW  - en LUT en look-up tableradiative transfer model;DART;synthetic spectral data;leaf traits;hyperspectral data
UR  - https://data.narodni-repozitar.cz/general/datasets/4y0sy-qh735
N2  - The dataset comprises 3.5 million unique combinations of leaf biochemical properties and canopy structural characteristics of forest scenes, along with various configurations of solar geometry. It provides spectral data spanning wavelengths from 450 nm to 2300 nm, with a 2 nm resolution. The dataset is divided into two files: one detailing the average reflectance of all scene pixels and another focusing specifically on sunlit leaf pixels. Look-up tables (LUT) were created using version 5.10.0 of the Discrete Anisotropic Radiative Transfer model. The virtual forest scenes are based on 3D models of European beech trees, derived from Terrestrial Lidar Scanning, and adjusted for different leaf area indices and structural configurations to simulate natural forest diversity. Reflectance data were processed using Matlab and Python scripts, resulting in hyperspectral cubes, which were subsequently used to generate the LUT. This dataset is valuable for training machine learning models aimed at retrieving forest functional traits and for calibrating remote sensing algorithms. Its high spectral resolution and diverse trait combinations make it adaptable to different times, locations, and both hyper- and multispectral sensors, supporting future hyperspectral satellite missions.
ER  -

HANOUSEK, Tomáš; Terézia SLANINÁKOVÁ; Tomáš REBOK a Růžena JANOUTOVÁ. \textit{A dataset of hyperspectral Look-Up Tables for 3.5 million traits and structural combinations of Central European temperate broadleaf forests}. 2024. Dostupné z: https://dx.doi.org/10.48700/datst.bcnpf-47q73.

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