userid <- Sys.getenv("WISP_IREA_USERID")
pwd <- Sys.getenv("WISP_IREA_PSW")
In this function if the save_csv parameter is set to TRUE, the function
will save the reflectance data as a .csv file in the ‘output’ folder within
the working directory.
reflect_data <- WISP.data::wisp_get_reflectance_multi_data(
time_from = "2024-09-11T09:00",
time_to = "2024-09-17T14:00",
station = "WISPstation012",
userid = userid,
pwd = pwd,
save_csv = FALSE,
out_dir = tempdir()
)
In this function if the save_csv parameter is set to TRUE, the function
will save the quality checked reflectance data as a .csv file in
the ‘output’ folder within the working directory.
User-configurable Parameters:
TRUE, computes scattering parameters and band ratiosTRUE, computes SPM concentration according to Novoa et al. (2017)TRUE, computes TUR concentration according to Novoa et al. (2017)TRUE, computes SPM concentration according to Jiang et al. (2021)TRUE, computes CHL concentration according to Gons et al. (2002)TRUE, computes CHL concentration according to Gons et al. (2002)TRUE, computes NDCI index according to Mishra et al. (2012)TRUE, computes CHL concentration according to Mishra et al. (2012)TRUE, computes dominant wavelength and Hue AngleTRUE, computes Optical Water Type classificationreflect_data_qc <- WISP.data::wisp_qc_reflectance_data(
data = reflect_data,
maxPeak = 0.05,
maxPeak_blue = 0.02,
qa_threshold = 0.5,
qwip_threshold = 0.2,
calc_scatt = TRUE,
calc_SPM = TRUE,
calc_TUR = TRUE,
calc_TSS = TRUE,
calc_gons = TRUE,
calc_gons740 = TRUE,
calc_NDCI = TRUE,
calc_mishra = TRUE,
calc_dom_wave = TRUE,
calc_OWT = TRUE,
save_csv = FALSE,
out_dir = tempdir()
)
# ----
# 106 spectral signatures were removed during QC:
#
# - 16 spectral signatures were removed thanks to QA+QWIP
# - 2 spectral signatures were removed thanks to QC1+QA+QWIP
# - 4 spectral signatures were removed thanks to QC2+QA+QWIP
# - 1 spectral signatures were removed thanks to QC3+QC4+QA+QWIP
# - 4 spectral signatures were removed thanks to QC4+QA+QWIP
# - 79 spectral signatures were removed thanks to QC6+QA+QWIP
#
# The spectral signature of 2024-09-11 09:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 09:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 09:30:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 09:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 10:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 10:15:05 has been removed thanks to: QA QWIP
# The spectral signature of 2024-09-11 10:30:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 10:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 11:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 11:15:05 has been removed thanks to: QC2 QA QWIP
# The spectral signature of 2024-09-11 11:30:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 11:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 12:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 12:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 12:30:06 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 12:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 13:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 13:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-11 13:30:05 has been removed thanks to: QC6 QA QWIP
# ...
# The spectral signature of 2024-09-17 09:00:05 has been removed thanks to: QC3 QC4 QA QWIP
# The spectral signature of 2024-09-17 09:15:05 has been removed thanks to: QC4 QA QWIP
# The spectral signature of 2024-09-17 09:30:05 has been removed thanks to: QA QWIP
# The spectral signature of 2024-09-17 09:45:05 has been removed thanks to: QA QWIP
# The spectral signature of 2024-09-17 10:00:05 has been removed thanks to: QA QWIP
# The spectral signature of 2024-09-17 10:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 10:30:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 10:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 11:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 11:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 11:30:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 11:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 12:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 12:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 12:30:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 12:45:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 13:00:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 13:15:05 has been removed thanks to: QC6 QA QWIP
# The spectral signature of 2024-09-17 13:30:05 has been removed thanks to: QC4 QA QWIP
# The spectral signature of 2024-09-17 13:45:05 has been removed thanks to: QC6 QA QWIP
#
# QA remove spectral signatures with low quality based on Wei et al. (2016)
# QC1 remove spectral signatures with negative values below 845 nm
# QC2 remove spectral signatures with outliers in the NIR (840 nm > 700 nm)
# QC3 remove spectral signatures with maximum peak greater than maxPeak
# QC4 remove spectral signatures with outliers in the Blue domain
# QC6 remove 'invalid' and 'None' spectral signatures according to level2.quality
# QWIP remove spectral signatures with low quality based on Dierssen et al., 2022
# ----
In this function if the save_csv parameter is set to TRUE, the function
will save the reflectance data with the sunglint removed as a .csv file in
the ‘output’ folder within the working directory.
User-configurable Parameters:
TRUE, computes scattering parameters and band ratiosTRUE, computes SPM concentration according to Novoa et al. (2017)TRUE, computes TUR concentration according to Novoa et al. (2017)TRUE, computes SPM concentration according to Jiang et al. (2021)TRUE, computes CHL concentration according to Gons et al. (2002)TRUE, computes CHL concentration according to Gons et al. (2002)TRUE, computes NDCI index according to Mishra et al. (2012)TRUE, computes CHL concentration according to Mishra et al. (2012)TRUE, computes dominant wavelength and Hue AngleTRUE, computes Optical Water Type classificationreflect_data_sr <- WISP.data::wisp_sr_reflectance_data(
qc_data = reflect_data_qc,
calc_scatt = TRUE,
calc_SPM = TRUE,
calc_TUR = TRUE,
calc_TSS = TRUE,
calc_gons = TRUE,
calc_gons740 = TRUE,
calc_NDCI = TRUE,
calc_mishra = TRUE,
calc_dom_wave = TRUE,
calc_OWT = TRUE,
save_csv = FALSE,
out_dir = tempdir()
)
In this function, you can set to TRUE for the parameters you want to display
in the legend for each of the three plots (raw, QC, SR).
custom_raw <- list(
legend_TSM = TRUE,
legend_Chla = TRUE,
legend_Kd = TRUE,
legend_cpc = TRUE
)
custom_qc <- list(
legend_TSM = TRUE,
legend_Chla = TRUE,
legend_Kd = TRUE,
legend_cpc = TRUE,
legend_scatt = TRUE,
legend_ratio = TRUE,
legend_novoa_SPM = TRUE,
legend_novoa_TUR = TRUE,
legend_jiang_TSS = TRUE,
legend_gons_CHL = TRUE,
legend_gons740_CHL = TRUE,
legend_NDCI = TRUE,
legend_mishra_CHL = TRUE,
legend_hue_angle = TRUE,
legend_dom_wavelength = TRUE,
legend_OWT_class = TRUE,
legend_OWT_score = TRUE,
legend_OWT_z_dist = TRUE
)
custom_sr <- list(
legend_TSM = TRUE,
legend_Chla = TRUE,
legend_Kd = TRUE,
legend_cpc = TRUE,
legend_scatt = TRUE,
legend_ratio = TRUE,
legend_novoa_SPM = TRUE,
legend_novoa_TUR = TRUE,
legend_jiang_TSS = TRUE,
legend_gons_CHL = TRUE,
legend_gons740_CHL = TRUE,
legend_NDCI = TRUE,
legend_mishra_CHL = TRUE,
legend_hue_angle = TRUE,
legend_dom_wavelength = TRUE,
legend_OWT_class = TRUE,
legend_OWT_score = TRUE,
legend_OWT_z_dist = TRUE
)
fig_comparison <- WISP.data::wisp_plot_comparison(
raw_data = reflect_data,
qc_data = reflect_data_qc,
sr_data = reflect_data_sr,
raw_args = custom_raw,
qc_args = custom_qc,
sr_args = custom_sr
)
fig_comparison
In this function, you can modify the following variables:
TRUE, parameters sharing the same unit are overlaid in a single plotfig_trend <- WISP.data::wisp_trend_plot(
data = reflect_data_sr,
params = c("TSM", "Chla", "Novoa_SPM", "Mishra_CHL"),
aggregate = "daily_mean",
merge_plot = TRUE
)
fig_trend