The purpose of treespectra code is to take ground or image-based tree reflectance spectra, build a classifier or regression ,and apply that model to an imaging spectrometer data cube (aka hyperspectral image).
1) First, install dependencies /Scripts/install_dependencies.R 2) Then source the package of lecospectR /Functions/lecospectR.R
The functions in lecospectR are divided into sections, all of which are loaded by sourcing /Functions/lecospectR.R
/Functions/dataframe_operations.R
/Functions/model_support.R
/Functions/pfts.R
/Functions/pipeline.R
/Functions/raster_operations.R
/Functions/spectral_operations.R
/Functions/training_utilities.R
/Functions/type_conversion.R
/Functions/utilities.R
/Functions/validation.R
1) Ground spectra were collected around Maine.
2) Locations where ground spectra were collected
1) Our workflow assumes a list of tree species from a table. This table is used for several steps, including aggregating validation to the same taxonomic level as training data. 2) Build a spectral library from a range of field scans collected with Tungsten halogen illumination using a leaf clip or contact probe. These scripts delete bad scans and standardize the associated information into a single metadata format. Around 90 vegetation indices are also calculated and the narrow band reflectance is resampled and smoothed to 5 nm bands.
/Scripts/2_DataMunging.R
/Scripts/2B_DataMunging_missing_spectra.R
/Scripts/3_Create_SpecLibPSR.R
The output of running these scripts are two spectral libraries, one of reflectance and one of vegetation indices along with the metadata for these reflectance measurements.
/Output/C_001_SC3_Cleaned_SpectralLib.csv
/Data/D_002_SpecLib_Derivs.csv
3) Collect spectra from pixels in UAV-captured images of tree canopies that are visible in imagery. Stem maps of known tree locations are overlaid on UAV flight path extents to identify canopy sources of spectra (1_MSGC_extent, 2_MSGC_get_trees). Reflectance spectra are extracted from hand-digitized tree canopies provided as a shapefile to the script (3_crop_image_canopy_ROI). Each canopy is associated with three hand-digitized shapefiles: 1) full canopy, 2) illuminated-only branches, and 3) shaded-only branches. Cropping each image by the shapefile creates a set of images with 326 bands from 400-1000nm, with each image representing the spectral profile of one tree canopy. Script (4_Parse_ROI_canopy_spectra) adds metadata to each pixel by tree species and outputs a spectral library in wide format. Scripts (5_Clean_image_spectra) and (6_Preprocess_viz_image) clean and process data to facilitate the visualization of reflectance data by species.
/Scripts/2_Image_processing/Headwall/1_MSGC_extent.R
/Scripts/2_Image_processing/Headwall/2_MSGC_get_trees.R
/Scripts/2_Image_processing/Headwall/3_Crop_image_canopy_ROI.R
/Scripts/2_Image_processing/Headwall/4_Parse_ROI_canopy_spectra.R
/Scripts/2_Image_processing/Headwall/5_Clean_image_spectra.R
/Scripts/2_Image_processing/Headwall6_Preprocess_viz_image.R
After running these scripts, the outputs include the relectance for each pixel from the canopies digitized from images. These data can be found in the MSGC_DATA directory (PEF example is shown here).
M:/MSGC_DATA/PEF-Demerit/Spectral_libraries/
After cleaning and pre-processing, the reflectance data can be summarized and visualized in various ways. Below is a summary of the median (purple) and interquartile ranges (75% dark grey & 95% light grey) of reflectance for a number of forest tree species in Maine. Median reflectance of fully-illuminated branches (orange) and fully-shaded branches (blue) are also shown. Sample size in number of individuals and number of spectral pixels is displayed for each species.
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Example UAS-based VNIR images showing RGB
## Study Area and Data locations
All UAV flights for Maine are shown in the map in the first image below (top left). Flight extents are generated from /Scripts/2_Image_processing/Headwall/1_MSGC_extent. These locations are then collected and summarized using /Scripts/2_Image_processing/Headwall/7_Visualize_spectra_locations, which produces the flight locations plotted on the map. The second image below (top right) shows all flight extents at the Penobscot Experimental Forest. Each overlapping rectangle polygon represents a single hyperspectral image (aka imaging spectrometer data cube). The third image below (bottom left) shows a screen capture of one data cube. The fourth image below (bottom right) shows a portion of the same data cube enlarged, with hand-digitized shapefiles of tree canopies overlaid.
Currently in development