Hi all,
I am relatively new to using the Sentinelhub API and am having issues with receiving S5p NO2 data. I have a list of point coordinates which I iteratively (not so neatly) convert to a rough Bbox with a certain buffer size. Based on this BBox I should receive an image of the NO2 values in that area, but whereever I try to do this I always get only zeros, also in the dataMask. So this tells me the data is not available, but I find that hard to believe given the sheer size of the request and the time_frame which can be up to a year. Is there something wrong with my request? See the code below.
Note that I can choose between S2L1 and S5p. S2L1 works fine.
from sentinelhub import DataCollection
from sentinelhub import SHConfig, BBox, CRS, SentinelHubRequest, MimeType, bbox_to_dimensions
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import h5py
import datetime
# Define parameters
MAIN_FOLDER = os.getcwd()
input_path = os.path.join(MAIN_FOLDER, 'Data')
output_path = os.path.join(MAIN_FOLDER, 'Data')
if not os.path.exists(output_path):
os.makedirs(output_path)
csv_file_name = 'df_weekly_august.csv'
satellite_type = 'S5p' # S5p
if satellite_type == 'S2A':
time_interval = ('2021-08-01', '2021-08-31')
buffer = 1200 # in meters
elif satellite_type == 'S5p': # Need to get data for every day within this time_interval
time_interval = ('2021-08-01', '2021-08-31')
buffer = 20000 # in meters
# !!! Ideally this part would create a 1200 m directly around the point instead of
# using coordinates to do that !!!
crs = CRS.WGS84
# Approximation WGS84
# 1 degree of latitude corresponds to 111km
# 1 degree of longitude corresponds to 73km
long_adj = (buffer/67000)/2
lat_adj = (buffer/112000)/2
resolution = 10 # 10m resolution is used in paper
# Configure login details
config = SHConfig()
config.instance_id='11d91198-MASKED'
config.sh_client_id='be4369f0-MASKED'
config.sh_client_secret='#Vtzd8)-MASKED'
if config.sh_client_id == '' or config.sh_client_secret == '':
print("Warning! To use Sentinel Hub services, please provide the credentials (client ID and client secret).")
#%%
# https://apps.sentinel-hub.com/requests-builder/
if satellite_type == 'S2A':
dataCollectionType = DataCollection.SENTINEL2_L1C
evalscript = """
//VERSION=3
function setup() {
return {
input: [{
bands: ["B01","B02","B03","B04","B05","B06","B07","B08","B8A","B09","B10","B11","B12","CLM"],
units: "DN"
}],
output: {
bands: 14,
sampleType: "FLOAT32"
}
};
}
function evaluatePixel(sample) {
if (sample.CLM == 1) {
return [sample.B01,
sample.B02+1000,
sample.B03,
sample.B04,
sample.B05,
sample.B06,
sample.B07,
sample.B08,
sample.B8A,
sample.B09,
sample.B10,
sample.B1972,
sample.B12,
sample.CLM];
}
return [sample.B01,
sample.B02,
sample.B03,
sample.B04,
sample.B05,
sample.B06,
sample.B07,
sample.B08,
sample.B8A,
sample.B09,
sample.B10,
sample.B1972,
sample.B12,
sample.CLM];
}
"""
elif satellite_type == 'S5p':
dataCollectionType = DataCollection.SENTINEL5P
evalscript = """
//VERSION=3
function setup() {
return {
input: [
{
bands: ["NO2", "dataMask"],
}
],
output: [
{
bands: 2,
sampleType: "FLOAT32",
},
],
};
}
function evaluatePixel(sample) {
if (sample.dataMask == 1) {
return [sample.NO2];
}
}
"""
else:
raise Warning("Only S2A and S5p are currently available")
groundstation_df = pd.read_csv(os.path.join(input_path, csv_file_name), index_col=None, header=0)
sentinel_paths = []
for index, row in groundstation_df.iterrows():
ID = index #row['StationLocalId']
print(ID)
lat, long = row['latitude'], row['longitude'] #row['SamplingPoint_Latitude'], row['SamplingPoint_Longitude']
print(lat, long)
bbox = BBox( ((long-long_adj,lat-lat_adj), (long+long_adj, lat+lat_adj)), crs)
bbox_size = bbox_to_dimensions(bbox, resolution=resolution)
if satellite_type == 'S2A':
request = SentinelHubRequest(
evalscript=evalscript,
input_data=[
SentinelHubRequest.input_data(
data_collection=dataCollectionType,
time_interval=time_interval,
mosaicking_order='leastCC',
other_args={'processing': {'upsampling': 'BILINEAR'}},
)],
responses=[
SentinelHubRequest.output_response('default', MimeType.TIFF)
],
bbox=bbox,
size=bbox_size,
config=config
)
elif satellite_type == 'S5p':
request = SentinelHubRequest(
evalscript=evalscript,
input_data=[
SentinelHubRequest.input_data(
data_collection=dataCollectionType,
time_interval=time_interval,
#mosaicking_order='mostRecent',
other_args={'processing': {'upsampling': 'BILINEAR', \
'minQa':'75', \
'timeliness': 'NRTI'}, }, # minQa 75 is used in paper
)],
responses=[
SentinelHubRequest.output_response('default', MimeType.TIFF)
],
bbox=bbox,
size=bbox_size,
config=config
)
image = request.get_data()[0]
if satellite_type == 'S2A':
plt.figure()
plt.imshow(image[:,:,[1,2,3]]/10000)
elif satellite_type == 'S5p':
plt.figure()
plt.imshow(image[:,:,1])
