What does the band's value signify of Landsat-8 L1C, Sentinel-2 L1C and MODIS MCD43A4

I was doing some processing on the Landsat-8 L1C bands downloaded from sentinel-hub. All the pixel values were between 0-1. Where as when i downloaded the same Landsat-8 LIC (level 1) scene from USGS EarthExplorer. Values of all the bands were between 0-65535. So, I know scenes downloaded from USGC gives you the DN values in level-1 product. So, what does the pixel values denote when downloaded from sentinel-hub for different sensors i.e. Landsat-8 L1C, Sentinel-2 L1C and MODIS MCD43A4

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This FAQ will hopefully answer your question:
https://www.sentinel-hub.com/faq/how-are-values-calculated-within-sentinel-hub-and-how-are-they-returned-output

We do suggest you check our latest API, which gives you control over what you are getting - reflectance or DN
https://docs.sentinel-hub.com/api/latest/#/data/Landsat-8

@gmilcinski I wanted to compute Land surface temperature (LST) as mentioned here from DN. So, how do i get the MLT.txt or MTL.json to convert the DN to radiance also for further calculation. I don’t see any documentation in the above link.

You are probably referring to MTL, right? You can get these directly on AWS, e.g. this link

So what you can do is:

-use WFS service to get relevant information about the landsat path

-use DN data from Sentinel Hub API

-compile a path to MTL file

-calculate

@gmilcinski Can you please elaborate how do i get landsat path and row for a date range for my area of interest as you mentioned using WFS service?

I have a suggestion. Isn’t it defying the purpose of eo-learn. If i have to iterate over all the landsat-tiles(path and row) to get their respective MTL file. Where as the purpose of eo-learn it to save from this hussle. Can we add the MTL in the existing platform itself the way QA band has been added?

By using WFS request, you can actually get information about the AWS location, e.g.
https://services-uswest2.sentinel-hub.com/ogc/wfs/INSTANCE_ID?REQUEST=GetFeature&SERVICE=WFS&VERSION=1.1.1&SRS=EPSG:4326&BBOX=-102.86243167867883,32.12394382391051,-103.3169910048507,31.899492878755403&TYPENAMES=DSS6&TIME=2019-03-31/2019-06-30/P1D&MAXCC=30&OUTPUTFORMAT=application/json

you will find:
http://landsat-pds.s3.amazonaws.com/c1/L8/031/038/LC08_L1TP_031038_20190625_20190625_01_RT/LC08_L1TP_031038_20190625_20190625_01_RT

For your suggestion - you are most welcome to add this functionality to the eo-learn. eo-learn is an open-source package and community contributions are more than welcome.

Adding MTL to the core Sentinel Hub service would be probably possible, but currently not high on our priority list.

https://docs.sentinel-hub.com/api/latest/#/data/Landsat-8 does this gives you surface reflectance or TOA reflectance? Reason being i am asking this because on USGS you have to first request for surface reflectance product of landsat-8.

These are Top of the atmospher data (more info here https://registry.opendata.aws/landsat-8/)

Collection 2 data are being prepared by the USGS at this moment and should become available on AWS in a couple of months. Once they are, we will integrate them as well.