How to download image for L8 satellite using /v1/process API?

The URL works but it doesn’t give pansharpened response using the following evalscript:

"evalScript": "//VERSION=3\nlet minVal = 0.0;\nlet maxVal = 0.4;\n\nlet viz = new HighlightCompressVisualizer(minVal, maxVal);\n\nfunction evaluatePixel(samples) {\n let sudoPanW = (samples.B04 + samples.B03 + samples.B02 * 0.4) / 2.4;\n let ratioW = samples.B08 / sudoPanW;\n let val = [samples.B04 * ratioW, samples.B03 * ratioW, samples.B02 * ratioW];\n val = viz.processList(val);\n val.push(samples.dataMask);\n return val;\n}\n\nfunction setup() {\n return {\n input: [{\n bands: [\n "B02",\n "B03",\n "B04",\n "B08",\n "dataMask"\n ]\n }],\n output: {\n bands: 4\n }\n }\n}\n\n"

You need to use different end-point for Landsat-8, see:

Landsat 8-9 Level 1

Use Sentinel Hub Processing API to access Landsat 8-9 Level 1 data with 8 optical, 2 thermal, and a 15 m resolution panchromatic band.

With b8 it sharpens the RGB image. So we have to use b8 as an overlay. This is what the code says.

Hm, the evalscript looks good.
What do you mean that “it doesn’t give pansharpened response”?

I have no idea, why the evalscript fails. If I put exactly the same evalscript to EO Browser, it works just fine. So I am guessing you are doing something else wrong.

Sentinel-hub EO-Browser3

Landsat 8 (USGS archive) imagery taken on November 28, 2020

Basically, I am trying to obtain the pansharpened image of L8 using B08 but the evalscript fails. If i use just use B02, B03, B04 the RGB image quality is terrible. I have tried to debug my script but it wont return the pansharpened image.

Sorry, but I do not understand, what is the problem.

The same evalscript works for me as well, the problem is I want to find out the date of the image through metadata.

evalscript = """

//VERSION=3




let minVal = 0.0;
let maxVal = 0.4;
let viz = new HighlightCompressVisualizer(minVal, maxVal);
function evaluatePixel(samples) {
     let sudoPanW = (samples.B04 + samples.B03 + samples.B02 * 0.4) / 2.4;
     let ratioW = samples.B08 / sudoPanW;
     let val = [samples.B04 * ratioW, samples.B03 * ratioW, samples.B02 * ratioW];
     val = viz.processList(val);
     val.push(samples.dataMask); 
     return val;
}
function setup() {
     return {
          input: [{
               bands: ["B02","B03","B04","B08","dataMask" ]
          }], 
          output: { 
               bands: 4
          }
     }
}

function updateOutputMetadata(scenes, inputMetadata, outputMetadata) {
  outputMetadata.userData = { "metadata":  JSON.stringify(scenes) }
  return [0]
}


"""

 payload = {
            "input":{
                "bounds":{
                "geometry":{  
                    "type": "Polygon",  
                    "coordinates": COORDINATES
                    },
                    "properties":{
                    "crs":"http://www.opengis.net/def/crs/EPSG/0/32719"}},
                    # "crs": "http://www.opengis.net/def/crs/OGC/1.3/CRS84"}},
                    "data":[{
                        "dataFilter":{
                        "timeRange":{
                            "from":strt_dt,
                            "to":end_dt
                            },
                            "maxCloudCoverage":100,
                            "previewMode":"EXTENDED_PREVIEW"},
                            "processing":{"upsampling":"BICUBIC"},
                            "type":TYPE}]},
                        "output":{"resx":10,"resy":10,
                        "responses": [
                                {
                                    "identifier": "userdata",
                                    "format": {
                                        "type": resp_type
                                    }
                                }
                            ]
                        }, "evalscript": evalscript 

            }