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MXD13Q1 monthly statistics data, long-term average, max, min and stdev
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# -*- coding: utf-8 -*- | |
""" | |
NAME | |
07_mxd13q1_stats_monthly.py | |
MXD13Q1 monthly statistics data, long-term average, max, min and stdev | |
DESCRIPTION | |
Input data for this script will use MXD13Q1 monthly data generate from modis_8day2monthly.py | |
This script can do annual statistics calculation (AVERAGE, MAXIMUM, MINIMUM and STD) | |
REQUIREMENT | |
ArcGIS must installed before using this script, as it required arcpy module. | |
EXAMPLES | |
C:\\Program Files\\ArcGIS\\Pro\\bin\\Python\\envs\\arcgispro-py3\\python 07_mxd13q1_stats_monthly.py | |
NOTES | |
This script is designed to work with MODIS naming convention | |
If using other data, some adjustment are required: parsing filename and directory | |
CONTACT | |
Benny Istanto | |
Climate Geographer | |
GOST/DECAT/DECDG, The World Bank | |
LICENSE | |
This script is in the public domain, free from copyrights or restrictions. | |
VERSION | |
$Id$ | |
TODO | |
xx | |
""" | |
import calendar | |
import os | |
import arcpy | |
from collections import defaultdict | |
from datetime import datetime, timedelta | |
import uuid | |
# To avoid overwriting outputs, change overwriteOutput option to False. | |
arcpy.env.overwriteOutput = True | |
# Raster environment settings for output consistency and optimization | |
arcpy.env.compression = "LZ77" | |
arcpy.env.pyramid = "PYRAMIDS -1 NEAREST LZ77 NO_SKIP" | |
# ISO3 Country Code | |
iso3 = "idn" # Syria: syr, Myanmar: mmr, Lebanon: lbn | |
# Define the range of years | |
start_year = 2003 | |
end_year = 2022 | |
# Change the data and output folder | |
input_folder = "D:\\temp\\modis\\{}\\gee\\04_fillnullwithstats\\evi_all_monthly".format(iso3) | |
output_folder = "D:\\temp\\modis\\{}\\gee\\03_statistics\\evi_all_monthly".format(iso3) | |
# Global variable to store user's choice | |
user_choice = None | |
def set_user_decision(): | |
"""Prompt user for decision on existing files and store it globally.""" | |
global user_choice | |
# Only ask the user if a choice hasn't been made yet | |
if user_choice is None: | |
decision = input("An output file already exists. Choose an action - Replace (R), Skip (S), Abort (A): ").upper() | |
while decision not in ['R', 'S', 'A']: | |
print("Invalid choice. Please choose again.") | |
decision = input("Choose an action - Replace (R), Skip (S), Abort (A): ").upper() | |
user_choice = decision | |
def process_monthlystats(input_folder, output_folder): | |
global user_choice | |
# Define statistic names | |
# Statistics type. | |
# MEAN — The mean (average) of the inputs will be calculated. | |
# MAJORITY — The majority (value that occurs most often) of the inputs will be determined. | |
# MAXIMUM — The maximum (largest value) of the inputs will be determined. | |
# MEDIAN — The median of the inputs will be calculated. Note: The input must in integers | |
# MINIMUM — The minimum (smallest value) of the inputs will be determined. | |
# MINORITY — The minority (value that occurs least often) of the inputs will be determined. | |
# RANGE — The range (difference between largest and smallest value) of the inputs will be calculated. | |
# STD — The standard deviation of the inputs will be calculated. | |
# SUM — The sum (total of all values) of the inputs will be calculated. | |
# VARIETY — The variety (number of unique values) of the inputs will be calculated. | |
stat_names = {"MAXIMUM": "max", "MINIMUM": "min", "MEAN": "avg", "MEDIAN": "med", "STD": "std"} | |
# Monthlys | |
monthlys = ["01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12"] | |
for monthly in monthlys: | |
monthly_files = [] | |
# Gather all the monthly mean files for each monthly across all years | |
for year in range(start_year, end_year + 1): | |
monthly_mean_name = f"{iso3}_phy_mxd13q1_evi_mean_{year}{monthly}.tif" | |
monthly_mean_path = os.path.join(input_folder, monthly_mean_name) | |
if arcpy.Exists(monthly_mean_path): | |
monthly_files.append(monthly_mean_path) | |
# Calculate the long-term statistics for the monthly | |
for stat_type, suffix in stat_names.items(): | |
out_raster_name = f"{iso3}_phy_mxd13q1_evi_{monthly}_{start_year}_{end_year}_{suffix}.tif" | |
out_raster_path = os.path.join(output_folder, out_raster_name) | |
if arcpy.Exists(out_raster_path): | |
if user_choice is None: | |
set_user_decision() | |
if user_choice == 'S': | |
print(f"Skipping existing file: {out_raster_path}") | |
continue | |
elif user_choice == 'A': | |
print("Aborting process.") | |
exit() | |
elif user_choice == 'R': | |
print(f"Replacing existing file: {out_raster_path}") | |
else: | |
print(f"Processing {out_raster_name}...") | |
# Generate a unique temporary filename for intermediate storage | |
temp_filename = f"temp_{uuid.uuid4().hex}.tif" | |
temp_file_path = os.path.join(arcpy.env.scratchFolder, temp_filename) | |
# Proceed to save the output | |
arcpy.CheckOutExtension("spatial") | |
outCellStatistics = arcpy.sa.CellStatistics(monthly_files, stat_type, "DATA") | |
outCellStatistics.save(temp_file_path) | |
# Use CopyRaster to save the output raster with specific pixel type and LZ77 compression | |
arcpy.management.CopyRaster( | |
in_raster=arcpy.sa.Int(temp_file_path), | |
out_rasterdataset=out_raster_path, | |
config_keyword="", | |
background_value="", | |
nodata_value="", | |
onebit_to_eightbit="NONE", | |
colormap_to_RGB="NONE", | |
pixel_type="16_BIT_SIGNED", | |
scale_pixel_value="NONE", | |
RGB_to_Colormap="NONE", | |
format="TIFF", | |
transform="NONE", | |
process_as_multidimensional="CURRENT_SLICE", | |
build_multidimensional_transpose="NO_TRANSPOSE" | |
) | |
# Attempt to delete the in-memory raster | |
try: | |
arcpy.Delete_management(temp_file_path) | |
print(f"Temporary file {temp_file_path} deleted.") | |
except Exception as e: | |
print(f"Warning: Unable to delete temporary file {temp_file_path}") | |
# Clear any locks or residual files | |
arcpy.ClearWorkspaceCache_management() | |
arcpy.CheckInExtension("spatial") | |
print(f"{out_raster_name} completed with LZ77 compression.") | |
# Main function | |
def main(): | |
# Call the process_files() function for the input folder | |
process_monthlystats(input_folder, output_folder) | |
if __name__ == '__main__': | |
main() | |
print("Script completed.") |
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