VegetationAnalysisToolkit is designed to provide a unified software platform for soil scientists and researchers, facilitating the efficient management and processing of field measurement data. The toolkit currently supports two key vegetation indices: the Normalized Difference Vegetation Index (NDVI) and the Chlorophyll Content Index (CCI), streamlining the handling of raw data from compatible instruments:
- MC-100 Chlorophyll Concentration Meter (Apogee Instruments)
- PlantPen NDVI & PRI (Photon Systems Instruments).
The package offers a suite of functions designed to streamline the analysis and visualization of these indices within an intuitive and user-friendly environment:
process_PlantPen_NDVI_PRI()processes PlantPen NDVI & PRI data.process_MC100_Chlorophyll()processes MC-100 Chlorophyll Concentration Meter data.plot_measurement_data()generates basic visualizations.generate_statistics()computes descriptive statistics.
If you are new to VegetationAnalysisToolkit, the best place to start after installing the package is trying to reproduce the example listed here in the Getting started section or to check out the detailed Documentation of the package.
# If devtools is not installed, install it first:
install.packages("devtools")
# Install VegetationAnalysisToolkit from GitHub
install_github("anonymus06/VegetationAnalysisToolkit")
# Alternatively, install from CRAN
install.packages("VegetationAnalysisToolkit", repos = "https://cloud.r-project.org")To get a bug fix or to use a feature from the development version, you can install the development version of VegetationAnalysisToolkit from GitHub.
# install.packages("pak")
pak::pak("anonymus06/VegetationAnalysisToolkit")The following example demonstrates how to process NDVI data measured by the PlantPen NDVI & PRI instrument. To get a local copy up and running follow these simple example steps!
First, set up your output folder and use the sample data provided within
the package folder by locating it using the system.file() function.
folder_path <- system.file("extdata", "plantpen_ndvi_pri_data", package = "VegetationAnalysisToolkit")
output_path <- "your/path/to/save/your/data"Next, use the process_PlantPen_NDVI_PRI() function to load and process
the NDVI data:
# Load package
library(VegetationAnalysisToolkit)# Process the NDVI data
process_PlantPen_NDVI_PRI(
folder_path,
output_path,
lower_limit = 0.0,
upper_limit = 1.0,
variable = "NDVI",
validate = TRUE,
split_code = TRUE
)
#> ===== Configuration =====
#> Device: PlantPen NDVI & PRI
#> Selected variable: NDVI
#> Lower limit: 0
#> Upper limit: 1
#> Split Code Columns: ON
#> Data validation: ON
#> =========================
#> ===== Activity Log =====
#> * Validation completed without any known issues. Note: Not all potential issues are checked.
#> * Invalid code detected: GERGELY1, GERGELY2, GERGELY3
#> * Invalid code detected: CSRHP, CSUHP, SZCS, SZU
#> * Invalid code detected: T1 , T1, TS1 , TS1, Cc1, T2_new , Ts4_A, T1_A, Cc1_A, T2_new_A, TS1_A
#> * Invalid code detected: SZCS, SZU
#> * Invalid code detected: SZCS, SZ2, SZ3, SZ4, SZU
#> * Data filtering results are available in 'NDVI_feedback.txt' (summary) and 'NDVI_detailed_feedback.txt' (detailed).
#> * Data (filtered and raw) saved to: C:\Users\Levente\AppData\Local\Temp\Rtmpqkqk0H/temp_output/
#> * In filtered data, values outside of bounds: 0 and 1 [NDVI] were discarded!
#> =========================The processed data is stored in an Excel file. Below is a preview of the content:
#> Date Code Position Landuse InterRow NDVI
#> 1 2023-10-18 CSTF F CST S 0.62
#> 2 2023-10-18 CSTF F CST S 0.59
#> 3 2023-10-18 CSTF F CST S 0.58
#> 4 2023-10-18 CSTF F CST S 0.50
#> 5 2023-10-18 CSTF F CST S 0.60
#> 6 2023-10-18 CSTF F CST S 0.61
#> 7 2023-10-18 CSTF F CST S 0.62
#> 8 2023-10-18 CSTF F CST S 0.59
#> 9 2023-10-18 CSTF F CST S 0.56
#> 10 2023-10-18 CSTF F CST S 0.55
During the data processing, a feedback file is generated. This file summarizes the data filtering results, detailing which data points were excluded. Reviewing this feedback can help ensure the quality of your data analysis.
Below is an excerpt from the generated ndvi_feedback.txt file:
#> Summary of Data Filtering, Grouped by Code:
#> Code Total Filtered Removed Percentage Removed (%)
#> ---- ----- -------- ------- ---------------------
#> CSRA 161 161 0 0.00
#> CSRAHP 81 80 1 1.23
#> CSRAHPSK 80 80 0 0.00
#> CSRASK 89 86 3 3.37
#> CSRF 165 158 7 4.24
#> CSRFSK 90 90 0 0.00
#> CSRHP 20 20 0 0.00
In addition, a validation report can be generated. This report helps to identify any potential issues with the dataset. Below is an excerpt from the val_issues.txt file, showing an example of the types of errors and warnings that could be encountered.
#> 2024-07-01 13:35:25 - Non-sequential values detected in column 'index', dataset: 'plantpen_NDVI_231018.txt' . Source file: 'inst/extdata/ndvi/plantpen_NDVI_231018.txt'
#> 2024-07-01 14:21:15 - Duplicate rows found in the data. Source file: 'inst/extdata/ndvi/plantpen_NDVI_231018.txt'
#> 2024-07-01 15:00:03 - The data frame 'plantpen_NDVI_231018.txt' is empty. Source file: 'inst/extdata/ndvi/plantpen_NDVI_231018.txt'
The next step involves generating statistics using
generate_statistics() from the processed data:
generate_statistics(output_path)#> Code Mean_NDVI SD_NDVI Min_NDVI Max_NDVI N
#> ---- --------- ------- ------- ------- -
#> CSRA 0.706 0.093 0.410 0.820 161
#> CSRAHP 0.664 0.078 0.290 0.780 80
#> CSRAHPSK 0.569 0.159 0.010 0.780 80
#> CSRASK 0.616 0.116 0.120 0.730 86
#> CSRF 0.646 0.098 0.420 0.790 158
#> CSRFSK 0.628 0.140 0.010 0.800 90
#> CSRHP 0.689 0.056 0.490 0.770 20
#> CSTA 0.690 0.087 0.310 0.800 177
Finally, the processed data is visualized with plot_measurement_data()
for easier interpretation. The plot below shows the NDVI data over time
for the specified site:
# Plot NDVI data as a time series
plot_measurement_data(output_path,
variable = "NDVI",
code = "CSTA",
tstart = "2023-07-10",
tend = "2023-10-18",
plot_type = "time_series")
For detailed instructions on how to use the VegetationAnalysisToolkit, check out the package vignettes or refer to the official documentation.
A cheat sheet will be available soon to summarize the key functions and workflows for easy reference.
If you encounter a clear bug, please file an issue with a minimal reproducible example on GitHub. For questions or further inquiries, feel free to reach out to me directly via email.
This project is licensed under the MIT License - see the LICENSE.md file for details.