This package provides tools to process spectral data from plant samples recorded with the ScanCorder using CICADA, and to calculate a wide range of vegetation indices.
You can install the source package from GitLab.
options(repos = c(
gitlab = "https://gitlab.com/api/v4/projects/70774833/packages/generic/scancorder.indices/1.3.2/",
CRAN = "https://cloud.r-project.org"
))
install.packages("scancorder.indices")You can install the development version of scancorder.indices from
GitHub with (available soon):
# install.packages("pak")
pak::pak("compolytics/scancorder.indices")For private repository, valid GitHub colaborator credentials are required.
Install from CRAN package manager (available soon):
install.packages("scancorder.indices")This basic example demonstrates how to calculate a table of spectral indices from a CICADA json file containing ScanCorder sensor data.
# include scancorder.indices package
library(scancorder.indices)
# First rule of programming: clean it
rm(list = ls())
# Step 0: What data file to process
# ------------------------------------------------------------------------------
# Please change this to the path and file name of your CICADA json data file.
# ------------------------------------------------------------------------------
# Change this name to the actual file you exported from the CICADA measurement app
# This file is also available from the Compolytics website (https://compolytics.com/vi-ppda)
cicada_file_name = "Compolytics_R-Package_VI_Test_File.json"
# Get current directory
current_dir <- getwd()
# Build full path + file name to the data file, change this location to the
# location of your actual file
sensor_file_path <- file.path(current_dir, "example", "data", cicada_file_name)
# Step 1: Load the json file and extract data
# ------------------------------------------------------------------------------
# Setup a decoder that will average the reflectance per LED across sensor channels
decoder <- DecodeCompolyticsRegularScanner$new(average_sensor_values = TRUE)
# Decode the sensor data file reflectance values
data <- decoder$score(sensor_file_path)
# Step 2: Run multi calibration for improved reflectance
# ------------------------------------------------------------------------------
# Setup multi-calibration tool
calibrator <- CalibrationReflectanceMultipoint$new()
# Run multi-calibration with sensor provided factors
calibReflectance <- calibrator$score(data$reflectance, sensor_file_path)
# Step 3: Calculate Indices table from all available data
# ------------------------------------------------------------------------------
index_table <- calculate_indices_table(data$wavelength, calibReflectance, data$fwhm, data$meta_table, data$sensor_info)
# Step 4: Save spectral indices in CSV file
# ------------------------------------------------------------------------------
# Generate an output file name based on the input file name
# ------------------------------------------------------------------------------
# Change this file and path to the location where you want to save the indices table
# ------------------------------------------------------------------------------
table_file_path <- file.path(current_dir, "example", "data", "Compolytics_R-Package_VI_Test_File_Indices.csv")
write_indices_csv(index_table, table_file_path, row.names = FALSE)
# ------------------------------------------------------------------------------
# The End| uuid | filename | sample_id | sample | ARI | ARI2 | BGI1 | BGI2 | BRI1 | BRI2 | CAR | CARgreen | CARrededge | CCI | CI | CRI1 | CRI2 | Ctr2 | Ctr3 | Ctr4 | Datt2 | Datt3 | Datt4 | Datt5 | Datt6 | DI | DRIpri | DVI | DWSI4 | EVI | EVI2 | FR | FR2 | GCIa | GCIb | GI | GLI | GM1 | GM2 | GNDVI.800.550. | GR | GRVI | LCI | Lic1 | Lic2 | Lic3 | MCARI.OSAVI750 | MCARI1 | MCARI2 | MCARI705 | MCARI710 | MGRVI | mNDI | MSAVI | MSAVI1 | mSRI1 | mSRI2 | MSRNir.Red | MTCI | MTVI.MSAVI | MTVI | MTVI2 | NBNDVI | NDI | NDRE | NDVI | NDVI1.760.708. | NDVI2.800.600. | NDVI3.780.550. | NDVI4.800.700. | NDVIg | NGRDI | NVI1 | OSAVI | PMI | PRI | PRI570 | PRIm2 | PRIm3 | PRIm4 | PSND.800.635. | PSNDa1 | PSNDc1 | PSRI | PSSRa | PSSRa1 | PSSRb | PSSRc1 | R.M | RARS | RDVI | reNDVI | RGI | RGR1 | RVI | RVI1 | RVI2 | SAVI | SBRI | SIPI1 | SIPI2 | SR.520.670. | SR.520.760. | SR.542.750. | SR.550.670. | SR.550.760. | SR.550.800. | SR.556.750. | SR.560.658. | SR.570.670. | SR.605.670. | SR.672.550.708. | SR.672.708. | SR.674.553. | SR.675.555. | SR.675.700. | SR.675.705. | SR.678.750. | SR.683.510. | SR.685.735. | SR.694.840. | SR.695.800. | SR.700. | SR.706.750. | SR.750.705. | SR.752.690. | SR.760.695. | SR.774.677. | SR.800.550. | SR.800.600. | SR.801.550. | SR.810.560. | SR.833.658. | SR.860.550. | SR.860.708. | TGI1 | TGI2 | TVI2 | TVI1 | VARI | VARIgreen | VIopt1 | VIopt2 | WDRVIa | WDRVIb | WDRVIc |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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| 845567d7-4573-4557-ac81-d0b64903598e | 20250911_133329_Lime_7094830a-7194-4cae-9aa8-0c26f0b7ad50.json | Lime | 8 | 2.276122 | 1.1041719 | 0.4843794 | 0.7348054 | 0.4394557 | 0.6666561 | 1.1304546 | -0.5150876 | 0.5503960 | 0.0612332 | 3.301597 | -1.1003474 | 1.1757745 | 0.2942899 | 0.2240397 | 0.2942899 | 3.384622 | 3.301597 | 8.000993 | 1.1022256 | 32.27260 | 0.3802350 | -0.0173889 | 0.3695140 | 0.9072553 | 0.2860760 | 0.4570496 | 0.8391126 | 0.2541536 | 2.932850 | 2.384622 | 0.9072553 | 0.0493221 | 4.336849 | 3.301597 | 0.6444802 | 0.8606030 | 3.932850 | 0.9367956 | 1.5000238 | 0.6666561 | 0.1694330 | 1.669193 | 0.4488833 | 0.3678349 | 0.8157564 | 0.8157564 | -0.1490043 | 0.7231363 | 0.4599979 | 0.4402846 | 1.758495 | 1.185781 | 1.138816 | 14.305634 | 0.9758377 | 0.4488833 | 0.3678349 | 0.6026680 | 0.6151307 | 0.5438604 | 0.6339339 | 0.5452489 | 0.6444802 | 0.6339339 | 0.5576585 | 0.6252470 | -0.0749203 | 7.984157 | 0.5146766 | 0.1989943 | 0.0612332 | -0.0612332 | -0.0612332 | 0.0749203 | -0.4192825 | 0.6444802 | 0.6151307 | 0.7176961 | 0.0788619 | 4.196569 | 4.196569 | 4.625566 | 6.084563 | 2.301597 | 5.871371 | 0.4401166 | 0.5350564 | 1.1022256 | 0.8606030 | 3.521394 | 3.521394 | 0.6897075 | 0.4640109 | 0.0076473 | 1.174745 | 1.1042818 | 0.8606030 | 0.2532668 | 0.2305822 | 0.7612893 | 0.2240397 | 0.2161898 | 0.2305822 | 0.7612893 | 0.7612893 | 0.7612893 | 8.000993 | 0.8391126 | 1.1022256 | 1.1022256 | 0.8391126 | 0.8391126 | 0.2541536 | 0.9750287 | 0.8391126 | 0.2954539 | 0.2839785 | 7.258943 | 0.3028838 | 3.301597 | 3.934629 | 3.398010 | 4.049528 | 4.625566 | 4.625566 | 4.625566 | 4.625566 | 3.384622 | 4.445908 | 3.384622 | 1.8175252 | 0.0178221 | 17.70883 | 1.021695 | -0.0761734 | -0.1071293 | 3.398010 | 122.3190 | -0.7105258 | -0.4942521 | -0.1926595 |
| 41f49fff-47ea-470d-bad6-176dc2129b72 | 20250911_133329_Lime_7094830a-7194-4cae-9aa8-0c26f0b7ad50.json | Lime | 9 | 1.268001 | 0.6024811 | 0.4953303 | 0.7129260 | 0.5019172 | 0.7224065 | 1.0517892 | -0.1953673 | 0.3793058 | 0.0252410 | 3.322933 | -0.4310728 | 0.8369281 | 0.2947199 | 0.2520335 | 0.2947199 | 3.541495 | 3.322933 | 7.388429 | 0.9868765 | 31.00466 | 0.3609179 | -0.0070957 | 0.3624169 | 1.0132980 | 0.2941452 | 0.4731647 | 0.8439404 | 0.2539745 | 2.937395 | 2.541495 | 1.0132980 | 0.0555173 | 3.885730 | 3.322933 | 0.6123821 | 0.8994513 | 3.937395 | 0.9421477 | 1.3842622 | 0.7224065 | 0.1834728 | 1.663579 | 0.4616840 | 0.3821869 | 0.8119627 | 0.8119627 | -0.1055755 | 0.7484648 | 0.4576882 | 0.4554798 | 1.685606 | 1.197900 | 1.192586 | 14.884909 | 1.0087304 | 0.4616840 | 0.3821869 | 0.6151167 | 0.6164936 | 0.5596164 | 0.5974013 | 0.5447357 | 0.6123821 | 0.5974013 | 0.5611379 | 0.5906446 | -0.0529357 | 7.957891 | 0.5154374 | 0.1588115 | 0.0252410 | -0.0252410 | -0.0252410 | 0.0529357 | -0.3791050 | 0.6123821 | 0.6164936 | 0.6984906 | 0.0639414 | 4.215037 | 4.215037 | 4.159721 | 5.633292 | 2.322933 | 5.373283 | 0.4378001 | 0.5373512 | 0.9868765 | 0.8994513 | 3.557240 | 3.557240 | 0.7482370 | 0.4621195 | 0.0415443 | 1.152638 | 1.0863422 | 0.8994513 | 0.2650862 | 0.2573519 | 0.8551631 | 0.2520335 | 0.2404007 | 0.2573519 | 0.8551631 | 0.8551631 | 0.8551631 | 7.388429 | 0.8439404 | 0.9868765 | 0.9868765 | 0.8439404 | 0.8439404 | 0.2539745 | 0.9382836 | 0.8439404 | 0.2823666 | 0.2811168 | 7.486680 | 0.3009389 | 3.322933 | 3.937403 | 3.393053 | 4.020488 | 4.159721 | 4.159721 | 4.159721 | 4.159721 | 3.541495 | 4.141310 | 3.541495 | 1.8523286 | 0.0183731 | 17.84269 | 1.029377 | 0.0105117 | -0.0779578 | 3.393053 | 122.1730 | -0.6991274 | -0.4769418 | -0.1707552 |
| cf4660c5-5e96-47f3-ad3d-9aa078a533de | 20250911_133200_Lime_4bb7735b-aeb4-45d1-b33f-a34b9965fac0.json | Lime | 10 | 1.509658 | 0.7135385 | 0.5454734 | 0.7429258 | 0.5289901 | 0.7204758 | 1.1469078 | -0.5491374 | 0.1450528 | 0.0684276 | 3.454804 | -1.1942108 | 0.3154468 | 0.2783252 | 0.2332574 | 0.2783252 | 3.586723 | 3.454804 | 8.057001 | 1.0311600 | 33.43970 | 0.3653898 | -0.0185287 | 0.3620476 | 0.9697816 | 0.2930140 | 0.4686006 | 0.8641894 | 0.2501414 | 2.731526 | 2.586723 | 0.9697816 | 0.0845587 | 4.122309 | 3.454804 | 0.6300816 | 0.9611948 | 3.731526 | 0.9501161 | 1.3879716 | 0.7204758 | 0.1802208 | 1.710960 | 0.4639903 | 0.3877781 | 0.8540066 | 0.8540066 | -0.0395576 | 0.7648439 | 0.4659795 | 0.4514536 | 1.745426 | 1.243134 | 1.207810 | 18.075195 | 0.9957313 | 0.4639903 | 0.3877781 | 0.6116799 | 0.6207408 | 0.5639589 | 0.6217215 | 0.5645471 | 0.6300816 | 0.6217215 | 0.5738388 | 0.6095510 | -0.0197865 | 8.155299 | 0.5256320 | 0.1964107 | 0.0684276 | -0.0684276 | -0.0684276 | 0.0197865 | -0.4012188 | 0.6300816 | 0.6207408 | 0.6984000 | 0.0603160 | 4.273438 | 4.273438 | 4.406598 | 5.631301 | 2.454804 | 5.478603 | 0.4447278 | 0.5510464 | 1.0311600 | 0.9611948 | 3.693060 | 3.693060 | 0.7588724 | 0.4697293 | -0.0044361 | 1.140128 | 1.0853916 | 0.9611948 | 0.2675247 | 0.2425825 | 0.8380750 | 0.2332574 | 0.2269324 | 0.2425825 | 0.8380750 | 0.8380750 | 0.8380750 | 8.057001 | 0.8641894 | 1.0311600 | 1.0311600 | 0.8641894 | 0.8641894 | 0.2501414 | 0.8990783 | 0.8641894 | 0.2788060 | 0.2707782 | 7.813532 | 0.2894520 | 3.454804 | 3.997739 | 3.592919 | 4.157560 | 4.406598 | 4.406598 | 4.406598 | 4.406598 | 3.586723 | 4.279716 | 3.586723 | 2.4260284 | 0.0244949 | 18.02146 | 1.031484 | -0.0249551 | -0.0289901 | 3.592919 | 127.8965 | -0.6958693 | -0.4720253 | -0.1645886 |
Spectral indices calculated from CICADA data.