I obtained the Sentinel-2 images of interest from SentinelHub using the following code. However, I noticed that all the ROIs obtained had pixel values 1000 less than the original Sentinel-2 pixel values. Is the 1000 reduction an implicit setting of SentinelHub? If so, how can it be disabled? Thanks.
My environment is: Windows 10, sentinelhub==3.10.2, python==3.9.5.
def save_tiff_to_drive(index, resolution, OUTPUT_DIR):
try:
file_name = data_manifest[data_manifest['index'] == index]['imagery_sample_id'][index-1]
dest_folder = os.path.join(OUTPUT_DIR, file_name)
if os.path.isdir(dest_folder):
print("Product already downloaded!")
return "Product already downloaded!"
if len(shape_coord_lists[index-1]) == 0:
print("Instance does not have a shape extent")
return "Instance does not have a shape extent"
# retrieving datetime from manifest and converting it to the right format
capture_datetime = data_manifest[data_manifest['index'] == index]['capture_datetime'][index-1]
# capture_datetime = datetime.strptime(capture_datetime, '%d-%m-%Y %H:%M')
capture_datetime = datetime.strptime(capture_datetime, '%Y-%m-%d %H:%M:%S')
capture_date = capture_datetime.strftime("%Y-%m-%d")
# in case you want to broaden date range to include 1 day prior and 1 day after capture day --> possible edge cases?
#capture_datetime_prior = capture_datetime.replace(day=capture_datetime.day - 1)
#capture_datetime_post = capture_datetime.replace(day=capture_datetime.day + 1)
#capture_date_prior = capture_datetime_prior.strftime("%Y-%m-%d")
#capture_date_post = capture_datetime_post.strftime("%Y-%m-%d")
print("shape_coord_lists_1 = ", shape_coord_lists[index-1])
shape_coord_list = create_extended_bbox(shape_coord_lists[index-1], 10)
print("shape_coord_lists_2 = ", shape_coord_list)
capture_bbox = BBox(bbox=shape_coord_lists[index-1], crs=CRS.WGS84)
capture_size = bbox_to_dimensions(capture_bbox, resolution=resolution)
print(f"Image shape at {resolution} m resolution: {capture_size} pixels")
print("Box: ", capture_bbox)
# API query
evalscript_all_bands = """
//VERSION=3
function setup() {
return {
input: [{
bands: ["B01","B02","B03","B04","B05","B06","B07","B08","B8A","B09","B10","B11","B12"],
units: "DN"
}],
output: {
bands: 13,
sampleType: "INT16"
}
};
}
function evaluatePixel(sample) {
return [sample.B01,
sample.B02,
sample.B03,
sample.B04,
sample.B05,
sample.B06,
sample.B07,
sample.B08,
sample.B8A,
sample.B09,
sample.B10,
sample.B11,
sample.B12];
}
"""
# requesting from Process API
request_all_bands = SentinelHubRequest(
data_folder=dest_folder,
evalscript=evalscript_all_bands,
input_data=[SentinelHubRequest.input_data(data_collection=DataCollection.SENTINEL2_L1C,
time_interval=(capture_date, capture_date),
mosaicking_order=MosaickingOrder.LEAST_CC,
)
],
responses=[SentinelHubRequest.output_response("default", MimeType.TIFF)],
bbox=capture_bbox,
size=capture_size,
config=config,
)
print("Saving all bands to device...")
try:
request_all_bands.save_data()
except Exception as e:
print(f"An error occurred in request_all_bands: {e}")
return None
tiff_path = ''
for dirpath, _, files in os.walk(dest_folder, topdown=False):
for file in files:
if os.path.abspath(os.path.join(dirpath, file))[-5:] == '.tiff':
tiff_path = os.path.join(dirpath, file)
if tiff_path == '':
raise TypeError("No .tiff file detected")
with rasterio.open(tiff_path) as src:
out_images = src.read()
#out_image_masked, out_transform = rasterio.mask.mask(src, data.geometry, crop=True)
out_meta = src.meta
print()
print("done!")
print()
size = os.path.getsize(tiff_path)
print(f'The .tiff size is: ', convert_bytes(size))
except Exception as e:
print(f"An error occurred: {e}")
return None
return out_meta, out_images
