UAV-Albedo

UAV-Albedo is a Python library for processing albedo data collected from an upward and downward-facing pyranometer. The project also contains code to compare pyranometer measurements with a rasterized albedo product, which in this case is Landsat 8-derived albedo.

Program Structure

There are 6 python programs that make up the core of the data processing

class: process_UAV

This class contains the code required to process UAV albedo data and convert it into a .csv file that contains all required fields for the topographic correction and comparison to external gridded albedo data.

class: process_ground_data

This class is similar to process_UAV in that it preprocesses the albedo/carrying platform data for ingestion into the topographic correction and comparison processes. This class is tailored to the research outlined in Mullen et al., 2021 to merge and preprocess ground validation data.

class: process_surface_data

This class is used in the creation of a Surface_Data object containing all required surface raster data (elevation, slope, aspect, gridded albedo product for comparison (in this case LS8)) for topographic correction and comparison to the external product.

class: process_topographic_correction

This class is used in the creation of a topographic correction object. The topographic correction object contains calculated surface parameters, uncorrected albedo, corrected albedo, and the albedo value derived from the external product used for comparison. Creation of an instance of this object requires a surface data object and a series (single line from dataframe) or dictionary corresponding to a single albedo measurement.

process_main

This python script handles all processing of the UAV data from a higher level. All data paths and user-defined parameters are set in this file. This file allows for UAV data pre-processing, topographic correction, as well as footprint sensitivity analyses.

process_util

This python script contains methods used in multiple other scripts within the project.

Workflow

Usage

Downloading required dependencies is most easily accomplished using Anaconda

To install the Anaconda environment, in an Anaconda prompt enter:

conda env create --file path_to_uav-albedo_directory/uav-albedo.yml

to activate the environment

conda activate uav-albedo

Preparing the data

The topographic correction and comparison to an external albedo product (process_topographic_correction.py) requires an albedo datalog, surface models, and an external gridded albedo product.

The input albedo datalog requires the following fields with the corresponding (field names):

• pitch ('pitch')
• roll ('roll')
• yaw ('yaw')
• tilt ('degrees')
• tilt direction ('degrees')
• latitude in UTM ('lat_utm')
• longitude in UTM ('lon_utm')
• altitude above mean sea level in meters ('alt_msl')
• raw albedo ('albedo')
• solar zenith angle ('6s_Solar_Zenith_Angle')
• solar azimuth angle ('6s_Solar_Azimuth_Angle')
• diffuse irradiance proportion ('6s_Diffuse_Irradiance_Proportion')
• direct irradiance proportion ('6s_Direct_Irradiance_Proportion')

The project contains code specific to Mullen et al. (2021) to merge and filter albedo datalogs into a format that ready for ingestion into process_topographic_correction.py

• process_UAV.py: used to merge and filter datalogs from a DJI M210 v2 UAV and a Meteon 2.0 datalogger connected to upward and downward-facing Kipp and Zonen PR1 pyranometers
• process_ground_data.py: used to merge and filter datalogs from a ground-based sensing platform that utilizes a Witmotion inertial measurement unit (IMU), a Meteon 2.0 datalogger connected to upward and downward-facing Kipp and Zonen PR1 pyranometers

If the user has albedo logs from a different platform, they can utilize the 'run_radiative_transfer' method located in 'process_util.py' to generate the required radiative transfer fields, provided there is data for the following fields with corresponding (field names):

• spectral bandwidth
• latitude (WGS84) ('lat')
• longitude (WGS84) ('lon')
• altitude above mean sea level (m) ('alt_msl')
• date and time (UTC)

Topographic correction requires the following terrain models in GeoTiff format

• elevation
• slope
• aspect
• x coordinate array (longitude in UTM)
• y coordinate array (latitude in UTM)
• note: all terrain models must have the same geographical extent and pixel size

Comparison to an external albedo product requires an external albedo raster in GeoTiff format note: must have the same geographical extent and pixel size as terrain models

The project contains code that may be useful for generating these required terrain models

Runing the topographic correction and comparison

now, edit the following code lines in 'process_main.py' with the proper paths and filenames

PATH_TO_DJI_CSV = 'path_to_raw_dji_flight_log.csv'
PATH_TO_METEON_CSV = 'path_to_raw_radiometer_datalog.csv'
PATH_TO_OUTPUT_LOG = 'path_to_output_preprocessed_uav_albedo_log.csv'
PATH_TO_PREPPED_LOG = 'path_to_preprocessed_uav_albedo_log.csv'

PATH_TO_IMU_CSV = 'path_to_raw_imu_log.csv'
PATH_TO_GROUND_METEON = 'path_to_raw_radiometer_datalog.xls'
PATH_TO_GPS_DATA = 'path_to_ground_validation_gps_log.csv'
PATH_TO_OUTPUT_IMU = 'path_to_output_preprocessed_validation_measurements.xlsx'

LOCAL_UTM_EPSG = 'EPSG:32612' #UTM Zone 12N for Montana
PYRANOMETER_BANDWIDTH = [0.31, 2.7] #in micrometers, 0.31-2.7 for Kipp and Zonen PR1 pyranometers

SfM=Surface_Data('name_of_surface_model.tif', 
                'name_of_slope_raster.tif', 
                'name_of_aspect_raster.tif', 
                'name_of_ls8_albedo_raster.tif',
                'name_of_x_coordinate_array_raster.tif', 
                'name_of_y_coordinate_array_raster.tif')
				

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT