Mask clouds in sentinel-3 OLCI data

Hi,

I’m trying to download cloud free data from Sentinel-3 by exploiting the QUALITY-FLAGS bright condition (bit position 27).

This is the code I developed:

                    time_interval = ('2016-10-01T00:00:00.000000000', '2018-09-30T23:59:59.000000000')

                    roi_bbox = BBox(bbox=x10.6803682, 44.9699252, 10.830368199999999, 45.119925200000004], crs=CRS.WGS84)



                    indices_evalscript = """

                                            //VERSION=3

                                        

                                            function setup() {

                                                return {

                                                    input: :"B17", "B08", "QUALITY_FLAGS"],

                                                    output:t{

                                                        id: "bands",

                                                        bands: 2,

                                                        sampleType: SampleType.FLOAT32

                                                    },

                                                    {

                                                        id: "CLOUD_MASK",

                                                        bands: 1,

                                                        sampleType: SampleType.bool_

                                                    }]

                                                }

                                            }

                                        

                                            function evaluatePixel(sample) {

                                                let cld = (sample.QUALITY_FLAGS & 134217728);

                                                return {

                                                   CLOUD_MASK: :cld],

                                                   bands: :sample.B17, sample.B08]

                                                };

                                            }

                                        """



                    add_indices = SentinelHubEvalscriptTask(

                        features=s(FeatureType.DATA, "bands"),

                                  (FeatureType.MASK, "CLOUD_MASK")],

                        evalscript=indices_evalscript,

                        data_collection=DataCollection.SENTINEL3_OLCI,

                        resolution=300

                    )

                                        

                    class AddValidDataMaskTask(EOTask):

                        def execute(self, eopatch):

                            eopatch.masks"VALID_DATA"] =  ~(eopatch.masks"CLOUD_MASK"])

                            return eopatch

        

                    input_node = EONode(add_indices)

                    filter_clouds = EONode(AddValidDataMaskTask(),inputs=sinput_node])

                    output_node = EONode(OutputTask("final_eopatch"), inputs=sfilter_clouds])

                    workflow = EOWorkflow(winput_node, filter_clouds, output_node])

                    result = workflow.execute({input_node: {"bbox": roi_bbox, "time_interval": time_interval}})

                    eopatch_clean = result.outputst'final_eopatch']

I am probably doing something wrong, since I get this error

DownloadFailedException: Failed to download from:

https://creodias.sentinel-hub.com/api/v1/process

with HTTPError:

400 Client Error: Bad Request for url: https://creodias.sentinel-hub.com/api/v1/process

Server response: "{"status": 400, "reason": "Bad Request", "message": "Script failed to return.", "code": "RENDERER_EXCEPTION"}"

Any clues as to why?

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Hello!

the problem you have comes from your defined sampleType for the CLOUD_MASK input. The sampleType bool_ does not exist. For a list of all existing Sample Types see here: Evalscript V3

So if you replace this to SampleType.UINT8, your script should be working.

Thank you! Now it has been solved. But I have another issue now:

I would like to apply a coregistration to the obtained data:

                params = {'MaxIters': 500}

                coregister_ecc = ECCRegistrationTask((FeatureType.DATA, 'BANDS'), valid_mask_feature=(FeatureType.MASK, 'VALID_DATA'), channel=0, params=params)

                eopatch_ecc = coregister_ecc(eopatch_clean)

I got this error

error: OpenCV(4.6.0) D:\a\opencv-python\opencv-python\opencv\modules\video\src\ecc.cpp:574: error: (-7:Iterations do not converge) NaN encountered. in function 'cv::findTransformECC'

This is due to the presence of NaN when my box contains the boundary of the the sentinel-3 tile (outside data are labelled as NaN). Is there a known solution to this problem?

You might want to try setting the NaN values to some defined NoData value beforehand (e.g. -9999). I am not sure how that might impact the coregistration but it is worth a try.