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Sentinel 2 giving better resolution than PlanetScope

  • April 26, 2024
  • 14 replies
  • 140 views
S

Hello,

I’ve added sentinel 2 basemap to my map but wanted to retrieve a higher resolution image for specific area. So, I ordered PlanetScope high resolution image and after comparing both, it looks like sentinel 2 is giving a higher resolution or a clearer image.
Please advise if there are specific configuration that would make PlanetScope image looks clearer.
Also, a comparison of both outputs can be found in the link below:

[Album] imgur.com 7406dc3c2de793e962d04644779d68f5b1ecdd7a.jpg

Left image is from sentinel 2 while the right one is from PlanetScope.

14 replies

S

Hi,

Please can you share the request body so that we can help you solve the issue that you are having. My assumption is that the resolution of the Planetscope isn’t taking full advantage of the sensor’s spatial resolution capabilities but I’m guessing without seeing your request body.

S

Yes, sure.

  • Order payload:
{
    "name": "some name",
    "collectionId": "",
    "input": {
        "provider": "PLANET",
        "planetApiKey": {{PLANET_API_KEY}},
        "bounds": {
            "geometry": {
        "type": "Polygon",
        "coordinates": [
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            ],
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            ],
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              28.239784981256882
            ],
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            ],
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            ],
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            ],
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            ],
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            ],
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      }
        },
        "data": [
            {
                "harmonizeTo": "NONE",
                "itemType": "PSScene",
                "productBundle": "analytic_8b_sr_udm2",
                "dataFilter": {
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                        "to": "2023-11-21T00:00:00.000Z"
                    },
                    "maxCloudCoverage": 20,
                    "nativeFilter": {
                        "type": "StringInFilter",
                        "field_name": "quality_category",
                        "config": [
                            "standard"
                        ]
                    }
                }
            }
        ]
    }
}

  • Process api request:
{
"input": {
"bounds": {
"geometry": {
        "coordinates": [
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              28.239834825108545
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        ],
        "type": "Polygon"
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      },
"data": [
{
"type": "byoc-{{collection_id}}",
"dataFilter": {
"timeRange": {
"from": "2023-11-18T00:00:00Z",
"to": "2023-11-21T00:00:00Z"
}
}
}
]
},
"output": {
"width": 512,
"height": 512
}
}
  • process api evalscript:
//VERSION=3
//True Color
function setup() {
  return {
    input: ["Red", "Green", "Blue", "dataMask"],
    output: { bands: 4 }
  };
}
function evaluatePixel(sample) {
  return [sample.Red/3000, 
          sample.Green/3000, 
          sample.Blue/3000,
          sample.dataMask];
}

Thank you very much for your assistancePreformatted text

S

Try looking at this example. Note how instead of width and height are used as parameters, resx and resy are used as input parameters instead explicitly setting the resolution of the image.

S

I’ve tried following the example you’ve mentioned but I get the error below

{
    "error": {
        "status": 400,
        "reason": "Bad Request",
        "message": "Your request of 577.04 meters per pixel exceeds the limit 500.00 meters per pixel of the collection {{collection-id}}. Please revise the resolution (or corresponding width/height) to make sure it is in supported range.",
        "code": "RENDERER_EXCEPTION"
    }
}```
S

Reading the error message your pixel are 577m across. Did you change the parameters from height and width to resx and resy?

S

Yes, I did change them to resx and resy and assigned them value 3 as in the example.
However, I don’t fully understand how do I pick a suitable value for resx and resy?
You can find below the updated process api request I’m using now

{
"input": {
"bounds": {
"geometry": {
        "coordinates": [
          [
            [
              28.920228033247895,
              28.239834825108545
            ],
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            ],
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            ]
          ]
        ],
        "type": "Polygon"
      }
      
      },
"data": [
{
"type": "byoc-{{collection_id}}",
"dataFilter": {
"timeRange": {
"from": "2023-11-18T00:00:00Z",
"to": "2023-11-21T00:00:00Z"
}
}
}
]
},
"output": {
"resx": 3,
"resy": 3
}
}
S

The resolution should be in the same resolution as the projection of your output. Therefore, if using UTM then the units you are using are in metres. If it is WGS84, then that will be in degrees.

S

I did convert the 3m to degrees and assigned the value in degrees to resx and resy.
I got the following image:

[Album] imgur.com 9ada2edaf429076c3b983fa153a210cd79231781.jpg

I still don’t see a difference in the image resolution.

S

Please can you share the request again please. It is difficult to help with only screenshots.

S
{
"input": {
"bounds": {
"geometry": {
        "coordinates": [
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            ],
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              28.917340220099973,
              28.23774687294491
            ],
            [
              28.917297829448245,
              28.23749506588791
            ],
            [
              28.91728365846194,
              28.23724081081276
            ],
            [
              28.9172978434143,
              28.236986556343528
            ],
            [
              28.91734024749538,
              28.23673475108101
            ],
            [
              28.91741046213733,
              28.23648782002169
            ],
            [
              28.91750781095657,
              28.236248141204687
            ],
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              28.917631356274576,
              28.23601802281155
            ],
            [
              28.91777990815421,
              28.2357996809394
            ],
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              28.917952035864438,
              28.23559521826131
            ],
            [
              28.918146081662684,
              28.235406603779467
            ],
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              28.918360176762036,
              28.235235653865857
            ],
            [
              28.91859225932948,
              28.235084014773026
            ],
            [
              28.91884009434169,
              28.23495314678315
            ],
            [
              28.919101295107275,
              28.23484431014802
            ],
            [
              28.91937334624827,
              28.234758552955135
            ],
            [
              28.919653627919654,
              28.234696701036672
            ],
            [
              28.919939441033925,
              28.234659350018468
            ],
            [
              28.920228033247895,
              28.23464685958541
            ],
            [
              28.920516625461868,
              28.234659350018468
            ],
            [
              28.920802438576136,
              28.234696701036672
            ],
            [
              28.921082720247522,
              28.234758552955135
            ],
            [
              28.92135477138852,
              28.23484431014802
            ],
            [
              28.9216159721541,
              28.23495314678315
            ],
            [
              28.921863807166314,
              28.235084014773026
            ],
            [
              28.922095889733757,
              28.235235653865857
            ],
            [
              28.92230998483311,
              28.235406603779467
            ],
            [
              28.92250403063135,
              28.23559521826131
            ],
            [
              28.922676158341584,
              28.2357996809394
            ],
            [
              28.922824710221217,
              28.23601802281155
            ],
            [
              28.92294825553922,
              28.236248141204687
            ],
            [
              28.923045604358457,
              28.23648782002169
            ],
            [
              28.923115819000415,
              28.23673475108101
            ],
            [
              28.923158223081494,
              28.236986556343528
            ],
            [
              28.923172408033853,
              28.23724081081276
            ],
            [
              28.92315823704755,
              28.23749506588791
            ],
            [
              28.92311584639582,
              28.23774687294491
            ],
            [
              28.923045644130426,
              28.237993806918304
            ],
            [
              28.922948306159327,
              28.23823348965699
            ],
            [
              28.922824769744167,
              28.238463612828713
            ],
            [
              28.922676224479943,
              28.238681960152714
            ],
            [
              28.922504100843458,
              28.238886428746408
            ],
            [
              28.922310056420756,
              28.23907504938027
            ],
            [
              28.92209595994586,
              28.2392460054459
            ],
            [
              28.921863873304673,
              28.239397650454336
            ],
            [
              28.921616031677047,
              28.23952852389606
            ],
            [
              28.921354822008624,
              28.239637365309775
            ],
            [
              28.921082760019488,
              28.239723126424344
            ],
            [
              28.920802465971537,
              28.239784981256882
            ],
            [
              28.920516639427923,
              28.23982233406956
            ],
            [
              28.920228033247895,
              28.239834825108545
            ]
          ]
        ],
        "type": "Polygon"
      }
      
      },
"data": [
{
"type": "byoc-{{collection_id}}",
"dataFilter": {
"timeRange": {
"from": "2023-11-18T00:00:00Z",
"to": "2023-11-21T00:00:00Z"
}
}
}
]
},
"output": {
"resx": 0.00002699322,
"resy": 0.00002699322
}
}```

This is the last request I've done after converting the resx and resy to degrees.
S

Hi, there doesn’t appear to be anything wrong with your requests. Depending on how zoomed in you are, you may see very little difference between a 10m resolution and a 3m resolution image. Are you viewing the Planetscope at its full resolution?

S

How do I ensure I’m viewing PlanetScope in its full resolution?
Isn’t it through the resx and resy value set to 3m or its equivalent in degrees?
I’ve followed the example in the following link :

8d4f7f154c57e214a4c8da9b606204b4423c9845.pngdocs.sentinel-hub.com
57b10d77cdf19cda03dbe73c52e6d5854ef7620d.png

Examples for PlanetScope

Use these CURL and Postman examples to access PlanetScope data with Sentinel Hub Processing API.

And I’ve converted the 3m to degrees as you can see in my request in my last reply.

S

This depends what software you are using. For example, I use QGIS which has the function to zoom to the raster resolution of your layer.

Try downloading your Planetscope image at 10m resolution and 3m resolution and compare them in the software and you should see the difference.

S

This topic was automatically closed 60 days after the last reply. New replies are no longer allowed.

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