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from sentinelsat import SentinelAPI, read_geojson, geojson_to_wkt |
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from datetime import datetime, timedelta,date |
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import zipfile |
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import rasterio |
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from rasterio.plot import show |
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from PIL import Image |
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import matplotlib.pyplot as plt |
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import numpy as np |
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import pandas as pd |
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import os |
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from glob import glob |
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from tqdm import tqdm |
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import xmltodict |
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import json |
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import warnings |
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import shutil |
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from shapely.geometry import Point |
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from shapely.geometry.polygon import Polygon |
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warnings.filterwarnings('ignore') |
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def unzip(): |
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files = glob('*.zip') |
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for file in files: |
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with zipfile.ZipFile(file, 'r') as zip_ref: |
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zip_ref.extractall() |
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def select_best_cloud_coverage_tile(): |
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tile_names = {} |
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cld_prob = [] |
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folders = glob('*.SAFE') |
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for fold in folders: |
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metadata_path = fold+"/MTD_MSIL2A.xml" |
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xml_file=open(metadata_path,"r") |
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xml_string=xml_file.read() |
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python_dict=xmltodict.parse(xml_string) |
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cld = float(python_dict["n1:Level-2A_User_Product"]["n1:Quality_Indicators_Info"]["Cloud_Coverage_Assessment"]) |
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tile_names[cld] = fold |
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cld_prob.append(cld) |
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name = tile_names[min(cld_prob)] |
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dates = name.split('_')[2][:8] |
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acquisition_date = datetime.strptime(dates, "%Y%m%d") |
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today = datetime.now() |
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delta = (today - acquisition_date) |
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days_ago = delta.days |
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return name,min(cld_prob),days_ago |
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def find_good_tile(df, point): |
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for row in tqdm(df.itertuples(),total=len(df)): |
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tile_name = row.tiles |
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coordinate = row.coords |
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x = coordinate.replace(']','') |
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x = x.replace('[','') |
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x = x.replace("'",'') |
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tab = [[float(x.split(",")[i]),float(x.split(",")[i+1])] for i in range(0,len(x.split(",")),2)] |
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polygon = Polygon(tab) |
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result = polygon.contains(point) |
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if result: |
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print(tile_name) |
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return tile_name |
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return 404 |
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def delete_tiles(): |
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files = glob('*.zip') |
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folders1 = glob('*.SAFE') |
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folders2 = glob("*.tmp") |
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for f in files: |
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os.remove(f) |
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for fold in folders1: |
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shutil.rmtree(fold, ignore_errors=True) |
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for fold in folders2: |
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shutil.rmtree(fold, ignore_errors=True) |
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