pantierra/efast-phenocam-validation
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

Foo

Browse source
This commit is contained in:
Felix Delattre 2026-03-04 18:50:29 +01:00
parent 915dfd8510
commit a037e6b4fd
12 changed files with 1237 additions and 96 deletions
Download patch file Download diff file Expand all files Collapse all files

53
run.py
View file

@ -1,16 +1,12 @@
from fusion import run_all_efast_scenarios
# from postprocessing import process_all_scenarios
# from metrics_indices import (
# create_ndvi_timeseries_post_process,
# create_gcc_timeseries_post_process,
# create_s2_bands_timeseries_post_process,
# )
from postprocessing import post_process_all_scenarios, post_process_timeseries
from acquisition_s2 import download_s2
from acquisition_s3 import download_s3
from acquisition_phenocam import download_phenocam
from preselection import create_timeseries
from preparation import prepare_s2, prepare_s3
# from metrics_stats import calculate_all_metrics
from metrics_indices import create_prepared_fusion_timeseries
from metrics_stats import calculate_all_metrics
def run_pipeline(season, site_position, site_name):
@ -21,27 +17,26 @@ def run_pipeline(season, site_position, site_name):
#download_s3(season, site_position, site_name)
#download_phenocam(season, site_position, site_name)
#print(f"Creating preselection timeseries: {site_name}, {season}")
#create_timeseries(season, site_position, site_name)
print(f"Creating preselection timeseries: {site_name}, {season}")
create_timeseries(season, site_position, site_name)
#print(f"Preparing S2 and S3 for fusion: {site_name}, {season}")
#for strategy in ["aggressive", "nonaggressive"]:
# prepare_s2(season, site_position, site_name, cleaning_strategy=strategy)
# prepare_s3(season, site_position, site_name, cleaning_strategy=strategy)
print(f"Preparing S2 and S3 for fusion: {site_name}, {season}")
for strategy in ["aggressive", "nonaggressive"]:
prepare_s2(season, site_position, site_name, cleaning_strategy=strategy)
prepare_s3(season, site_position, site_name, cleaning_strategy=strategy)
print(f"Running EFAST fusion for all scenarios: {site_name}, {season}")
run_all_efast_scenarios(season, site_position, site_name)
print(f"Creating prepared/fusion timeseries: {site_name}, {season}")
create_prepared_fusion_timeseries(season, site_position, site_name)
print(f"Post-processing: {site_name}, {season}")
post_process_all_scenarios(season, site_position, site_name)
post_process_timeseries(season, site_position, site_name)
# print(f"Post-processing data: {site_name}, {season}")
# process_all_scenarios(season, site_position, site_name)
# print(f"Generating NDVI for final outputs: {site_name}, {season}")
# create_ndvi_timeseries_post_process(season, site_position, site_name)
# print(f"Generating GCC for final outputs: {site_name}, {season}")
# create_gcc_timeseries_post_process(season, site_position, site_name)
# print(f"Generating S2 band timeseries: {site_name}, {season}")
# create_s2_bands_timeseries_post_process(season, site_position, site_name)
# print(f"Calculating metrics: {site_name}, {season}")
# calculate_all_metrics(season, site_name, site_position)
print(f"Calculating metrics: {site_name}, {season}")
calculate_all_metrics(season, site_name, site_position)
except Exception as e:
print(f"Error: {e}")
@ -50,10 +45,10 @@ def run_pipeline(season, site_position, site_name):
if __name__ == "__main__":
run_pipeline(2024, (47.116171, 11.320308), "innsbruck")
# run_pipeline(2024, (35.3045, 25.0743), "forthgr")
# run_pipeline(2020, (47.116171, 11.320308), "innsbruck")
# run_pipeline(2024, (58.5633, 24.3688), "pitsalu")
# run_pipeline(2023, (64.2437, 19.7673), "vindeln2")
# run_pipeline(2024, (36.7455, -6.0033), "sunflowerjerez1")
# run_pipeline(2024, (42.6558, 26.9837), "institutekarnobat")
run_pipeline(2024, (35.3045, 25.0743), "forthgr")
run_pipeline(2020, (47.116171, 11.320308), "innsbruck")
run_pipeline(2024, (58.5633, 24.3688), "pitsalu")
run_pipeline(2023, (64.2437, 19.7673), "vindeln2")
run_pipeline(2024, (36.7455, -6.0033), "sunflowerjerez1")
run_pipeline(2024, (42.6558, 26.9837), "institutekarnobat")