Table of Contents

1. Rrs simulation with given IOPs [MATLAB]
2. QAA6 [python]

Intro

Open Water&Light: this repository implements some water-and-light interaction algorithms in ocean optics and remote sensing.

1A. Rrs simulation with given IOPs [Python]

Simulate water-leaving radiance (Rrs) as used in:

• Zeng C, Binding C. The effect of mineral sediments on satellite chlorophyll-a retrievals from line-height algorithms using red and near-infrared bands. Remote Sensing. 2019;11(19). doi:10.3390/rs11192306

The purpose of this package is for fast computation and analysis with changing IOPs (e.g., chl concentration); for a stricter simulation, please consider HydroLight/Ecolight by Mobley, et al. To simulate Rrs, use OpenWL_simu_Rrs_from_IOP.py, examples:

>> python OpenLW_simu_Rrs_from_IOP.py --chl 1:3:31 --mspm '[1,5,10,20,30]' --cdom '[0.05]' 
==== input argument inspection:...
===== successfully finish the Rrs simulation ===========
===== written simulation result to: ./[_Rrs , _rrs_].csv ===========

>> python OpenLW_simu_Rrs_from_IOP.py --chl '[1]' --mspm '[1,5,10,20,30]' --cdom '[0.005 0.993]' --wavelength 400:5:901

>> python OpenLW_simu_Rrs_from_IOP.py -h  

1B. Rrs simulation with given IOPs [Matlab]

It uses a simplified water and light interaction empirical model: Rrs = f/PI * bb/(a + bb) according to: Albert, A. and C. D. Mobley (2003)Optics Express. It does not count the impact of wind speed, temperature, etc. It was implemented in Matlab 2017b licensed to ECCC. should be compatible to versions>=2015b.

To simulate Rrs, use OpenWL_simu_Rrs_from_IOP.m, examples:

>> Rrs=OpenWL_simu_Rrs_from_IOP(0.1:5:20.1,1:10);
====finish Rrs simulation, result written to:OpenWL_simu_Rrs_from_IOP_LELW_chl20_mspm10_cdom0.994.csv====
>> Rrs=OpenWL_simu_Rrs_from_IOP(0.1:5:20.1,1:10,[0.494,0.994],'bAB',false,'bSave',true,'waterIOP','waterIOP_SmithandBaker.txt','IOPname','LakeErie','wavelength',400:100:800);
====finish Rrs simulation, result written to:OpenWL_simu_Rrs_from_IOP_LakeErie_chl20_mspm10_cdom0.994.csv====
>> help OpenWL_simu_Rrs_from_IOP   %show the help info

a comparison of Rrs derived from OpenWL and Ecolight on some test data as follows,

Rrs_HE_Ecolight	Rrs_OpenWL	Rrs_OpenWL_vs_Ecolight_scatter	WaterIdx_insitu_vs_simulation

To simulate line-height water indexes for a specific sensor ['HYPER','OLCI','MSI','MERIS','OCI','VIIRS','OLI','MODIS_Aqua','MODIS_Terra'], use OpenWL_simu_water_index.m, examples:

>> OpenWL_simu_water_index    %use all default arguments as MCI index, over OCLI sensor
====finish sensor water index simulation, result written to:./TestData/OpenWL_simu_waterIDX_MCI_of_sensor_OLCI.csv====
>> OpenWL_simu_water_index('sensor','MERIS','waterIDX','CI')  %same as CI model
====finish sensor water index simulation, result written to:./TestData/OpenWL_simu_waterIDX_CI_of_sensor_MERIS.csv====
>> OpenWL_simu_water_index('sensor','HYPER','waterIDX','user','designed_bands',[665, 674, 753])  %same as FLH model
====finish sensor water index simulation, result written to:./TestData/OpenWL_simu_waterIDX_user_of_sensor_HYPER.csv====
>> help OpenWL_simu_water_index      %show the help info
--------------------------------------------------------------------------------------------------------------------------

and simulation result of the above 3 examples are:

Water index: MCI	CI	FLH (user-defined)

---

2. QAA

implemented in python, files in ./QAA. It relies on python packages: numpy

to run QAA, use ./QAA/OpenWL_QAA6.py, examples:

• work within ./QAA folder , then enter a python environment with numpy package.

• example1: use default parameters to run a csv file and save the result.

>>python .\OpenWL_QAA6.py --file 'Rrs_QAA_test.csv' -S  
===QAA completed,the absorption of phytoplankton is written to file: aph_Rrs_QAA_test.csv ===

• example2: run a single spectra with customized parameters.

>>python .\OpenWL_QAA6.py --wavelength '412,443,489,510,555,670' --Rrs '0.0012,0.00169,0.00329,0.00404,0.00748,0.00346' '--eta' 2.0 1.2 -0.6 '--waterIOP' '../IOPfiles/waterIOP_SmithandBaker.txt'
===input params:h55x :[-1.1459, -1.36583, -0.46927],A:5,h66x:[0.39, 1.14],
 eta:[2.0, 1.2, -0.6],zeta:[0.74, 0.2, 0.8],xi :[0.015, 0.002, 0.6]
===QAA completed,the absorption of phytoplankton at input bands [N*1,set 0 for failed values; unit: (1/m)]:
 [0.27205821 0.4042206  0.26982815 0.25434736 0.12065384 0.23782884] ===

• more details:

>>> python .\OpenWL_QAA6.py -h
usage: OpenWL_QAA6.py [-h] [-N] [-U] [-R] [-F] [-W] [--h55x  ] [--A] [--h66x ] [--eta  ] [--zeta  ] [--xi  ] [-S]
Implementation of QAA version 6
optional arguments:
  -h, --help          show this help message and exit
  -N , --wavelength   the wavelength of the input Rrs or rrs bands. default:[412,443,489,510,555,670]
  -U , --rrs          an sample of under water remote sensing reflectance, dimensions:N*1
  -R , --Rrs          an sample of above water remote sensing reflectance, dimensions:N*1; if rrs is given, then Rrs is ignored
  -F , --file         a csv file of *above* water remote sensing reflectance, if --file given, --rrs/--Rrs are ignored ; dimenion:N*M; where there is N samples, with M bands,
                      each row is a sample; example data: Rrs_QAA_test.csv
  -W , --waterIOP     water absorption curve, dimensions: N*3: 1st column as wavelength, 2nd column abs value (1/m), 3rd for scatter, consistent with Hydrolight; if not provided,
                      use water abs and bb from ../IOPfiles/waterIOP_sea_water.txt
  --h55x              parameters in QAA; step 2 left IF, h0,h1,h2
  --A                 parameters in QAA; step 2 left IF, coeff in the log(...)
  --h66x              parameters in QAA; step 2 right
  --eta               parameters in QAA; step 4
  --zeta              parameters in QAA; step 7A
  --xi                parameters in QAA; step 7B
  -S, --save          flag to save the a_ph as .csv file, default is False