A Synthetic Bio-Optical Dataset for Danjiangkou Reservoir: Hyperspectral Reflectance and Inherent Optical Properties
Authors/Creators
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1.
Nanjing Institute of Geography and Limnology
- 2. Changjiang Basin Ecology and Environment Monitoring and Scientific Research Center, Changjiang Basin Ecology and Environment Administration, Ministry of Ecology and Environment
- 3. Hubei Key Laboratory of Intelligent Monitoring, Early Warning and Protection for Watershed Aquatic Ecology
Description
Summary
This dataset contains 10,000 samples of synthetic bio-optical data generated specifically for the optical characteristics of Danjiangkou Reservoir (China). It was created using the Danjiangkou Bio-Optical Model (DBOM) forward simulation framework.
The dataset links biogeochemical concentrations (Chlorophyll-a, Inorganic Suspended Matter, CDOM) and phytoplankton community structure (Cyanobacteria, Green algae, Brown algae) to Inherent Optical Properties (IOPs) and hyperspectral Remote Sensing Reflectance ($R_{rs}$). The dataset contains the stochastic perturbation of bio-optical parametrization coefficients (e.g., spectral slopes, specific absorption coefficients), which were randomized by $\pm 30\%$ around their local default values to simulate natural variability and support algorithm uncertainty analysis.
Data Generation Methodology
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Concentration Generation: Input concentrations were generated using a multivariate log-normal distribution to mimic natural covariance. Phytoplankton community fractions were generated using a Dirichlet distribution.
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Forward Modeling:
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IOP Model: Localized bio-optical models for Danjiangkou Reservoir were used to compute absorption ($a$) and backscattering ($b_b$) coefficients.
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Parameter Perturbation: Key bio-optical parameters (including $S_{cdom}$, $S_{nap}$, $a^*_{ph}$, etc.) were independently perturbed using a uniform distribution $U(0.7, 1.3)$ for each sample to introduce realistic optical complexity.
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Radiative Transfer: Remote sensing reflectance ($R_{rs}$) was derived from IOPs using the semi-analytical model by Lee et al. (2011).
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Spectral Resolution: Hyperspectral data covering 350 nm to 900 nm with a 2 nm interval.
File Structure
The data is stored in a single NetCDF file (.nc) compatible with Xarray and other multidimensional array libraries.
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Dimensions:
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sample_id: 10,000 (Number of samples) -
wavelen: 276 (Spectral bands from 350 to 900 nm)
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Data Variables (Outputs):
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Rrs: Remote Sensing Reflectance [$sr^{-1}$] -
aph: Absorption coefficient of phytoplankton [$m^{-1}$] -
ad: Absorption coefficient of detritus/non-algal particles [$m^{-1}$] -
acdom: Absorption coefficient of CDOM [$m^{-1}$] -
bbp: Particulate backscattering coefficient [$m^{-1}$] -
bp: Particulate total scattering coefficient [$m^{-1}$]
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Coordinates (Inputs & Truth Data):
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Chla: Chlorophyll-a concentration [$mg/m^3$] -
ISM: Inorganic Suspended Matter concentration [$g/m^3$] -
ag440: CDOM absorption at 440 nm [$m^{-1}$] -
frac_cyano,frac_green,frac_brown: Fractional composition of phytoplankton groups (0-1). -
Perturbed Parameters: The file also records the specific randomized parameters used for each sample (e.g.,
S_cdom,A_ph,gamma_nap) to allow for sensitivity analysis.
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Potential Applications
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Development and validation of semi-analytical algorithms for inland waters.
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Training machine learning models for water quality retrieval.
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Phytoplankton functional type (PFT) discrimination studies.
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Sensitivity analysis of bio-optical inversion algorithms.
Technical Info
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Format: NetCDF4
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Compression: zlib (level 9)
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Code Author: Shun Bi (bishun@niglas.ac.cn)
Files
Files
(39.0 MB)
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Additional details
Funding
- National Natural Science Foundation of China
- 42501484
- National Natural Science Foundation of China
- U25A20753
- National Natural Science Foundation of China
- 42425102
- National Natural Science Foundation of China
- 42501511