I am getting the error . I am using sentinelapi to download images from sentinel 2 l2a .The user draws polygons in the frontend from the map. (it is using leaflet). I am getting the error and I don't know how to solve this.
Your request of 5143.88 meters per pixel exceeds the limit 1500.00 meters per pixel of the collection S2L2A. Please revise the resolution (or corresponding width/height) to make sure it is in supported rangehere is the code that is causing the issue
def get_sentinel_images(field_polygon, start_date, end_date, cloud_cover, selected_area): area_in_meters =selected_area # configuration config = get_config() # search for the catalogue geometry = Geometry(geometry=field_polygon, crs=CRS.WGS84) time_interval = start_date, end_date catalog = SentinelHubCatalog(config=config) search_iterator = catalog.search( DataCollection.SENTINEL2_L2A, time=time_interval, filter="eo:cloud_cover < {}".format(cloud_cover), fields={"include": ["id", "properties.datetime", "properties.eo:cloud_cover"], "exclude": []}, geometry=geometry, ) results = list(search_iterator) print("Total number of results:", len(results)) # separating the unique acquisitions time_difference = dt.timedelta(hours=0) all_timestamps = search_iterator.get_timestamps() unique_acquisitions = filter_times(all_timestamps, time_difference) print("Total number of unique acquisitions:", len(unique_acquisitions)) # make a request to process API for these acquisitions true_color_evalscript = """ //VERSION=3 function setup() { return { input: ["B02", "B03", "B04"], output: { bands: 3, sampleType: "AUTO", // default value - scales the output values from [0,1] to [0,255]. }, } } function evaluatePixel(sample) { return [2.5 * sample.B04, 2.5 * sample.B03, 2.5 * sample.B02] }""" nvdi_evalscript = """//VERSION=3function setup() { return { input: [ { bands: ["B04", "B08"], }, ], output: { id: "default", bands: 3, }, }}function evaluatePixel(sample) { let ndvi = (sample.B08 - sample.B04) / (sample.B08 + sample.B04) if (ndvi < -0.5) return [0.05, 0.05, 0.05] else if (ndvi < -0.2) return [0.75, 0.75, 0.75] else if (ndvi < -0.1) return [0.86, 0.86, 0.86] else if (ndvi < 0) return [0.92, 0.92, 0.92] else if (ndvi < 0.025) return [1, 0.98, 0.8] else if (ndvi < 0.05) return [0.93, 0.91, 0.71] else if (ndvi < 0.075) return [0.87, 0.85, 0.61] else if (ndvi < 0.1) return [0.8, 0.78, 0.51] else if (ndvi < 0.125) return [0.74, 0.72, 0.42] else if (ndvi < 0.15) return [0.69, 0.76, 0.38] else if (ndvi < 0.175) return [0.64, 0.8, 0.35] else if (ndvi < 0.2) return [0.57, 0.75, 0.32] else if (ndvi < 0.25) return [0.5, 0.7, 0.28] else if (ndvi < 0.3) return [0.44, 0.64, 0.25] else if (ndvi < 0.35) return [0.38, 0.59, 0.21] else if (ndvi < 0.4) return [0.31, 0.54, 0.18] else if (ndvi < 0.45) return [0.25, 0.49, 0.14] else if (ndvi < 0.5) return [0.19, 0.43, 0.11] else if (ndvi < 0.55) return [0.13, 0.38, 0.07] else if (ndvi < 0.6) return [0.06, 0.33, 0.04] else return [0, 0.27, 0]}""" nvdi_process_requests = [] process_requests = [] for timestamp in unique_acquisitions: request = SentinelHubRequest( evalscript=true_color_evalscript, input_data=[ SentinelHubRequest.input_data( data_collection=DataCollection.SENTINEL2_L2A.define_from("s2l2a", service_url=config.sh_base_url), time_interval=(timestamp - time_difference, timestamp + time_difference), ) ], responses=[SentinelHubRequest.output_response("default", MimeType.PNG)], geometry=geometry, config=config, ) process_requests.append((request,timestamp)) print("requesting nvdi images ...") # repeating the request but for nvdi images for timestamp in unique_acquisitions: request = SentinelHubRequest( data_folder='data_folder', evalscript=nvdi_evalscript, input_data=[ SentinelHubRequest.input_data( data_collection=DataCollection.SENTINEL2_L2A.define_from("s2l2a", service_url=config.sh_base_url), time_interval=(timestamp - time_difference, timestamp + time_difference), ) ], responses=[SentinelHubRequest.output_response("default", MimeType.TIFF)], geometry=geometry, config=config,) nvdi_process_requests.append(request) # download the data client = SentinelHubDownloadClient(config=config) download_requests = [request.download_list[0] for request,_ in process_requests] timestamps = [timestamps for request,timestamps in process_requests] data = client.download(download_requests) images = convert_ndarray_to_base64(data) images_with_timestamps=list(map(list,zip(images,timestamps))) # arranging the list into descending order(from most recent to oldest) images_with_timestamps.reverse() nvdi_process_requests.reverse() return images_with_timestamps, nvdi_process_requestsWhat I have done?
I tried adding the size parameter in request class conditionally . This somehow removes the error but I did not get the image with the resolution of 10m per pixels . Like this
desired_resolution = 10 max_size_in_pixels = 2500 size_in_pixels = int(min(area_in_meters / desired_resolution, max_size_in_pixels))...request = SentinelHubRequest( evalscript=true_color_evalscript, input_data=[ SentinelHubRequest.input_data( data_collection=DataCollection.SENTINEL2_L2A.define_from("s2l2a", service_url=config.sh_base_url), time_interval=(timestamp - time_difference, timestamp + time_difference), ) ], responses=[SentinelHubRequest.output_response("default", MimeType.PNG)], geometry=geometry, size=(size_in_pixels, size_in_pixels), config=config, )I want to get the images with base resolution of 10 m per pixels . It has been many days I have stuck into this problem. Thanks
