Tag: spatial resolution

How to download a satellite image from Copernicus Open Access Hub

Personally I don’t find the Copernicus Open Access Hub very intuitive to use, so I wanted to provide an example of how I download data from the website.

For this example I want to download a single Sentinel 2 (A or B) image from the northern part of Jutland in Denmark. I want it to be cloud free and it should be as recent as possible.

Here’s how I would do that:

1. Login to Copernicus Open Access Hub by clicking the confused looking person in the top right corner

2. Click on “Switch to Navigation Mode” in order to select the area that you are interested in

3. Select the area

4. Click on the filter-button left of the search bar, and make the following selections:

  • Select Sort by : Sensing date
  • Select the time period you are interested in (choose Sensing period)
  • Select the Sentinel satellite mission you want data from
    Tip: If e.g. you just want any image from Sentinel 2, you don’t have to select anything in the Satellite platform dropdown, just leave it empty.
  • Select cloud cover % if that is relevant. For Sentinel 2, I usually set the cloud cover very low, e.g. “[0 to 10]”.

5. Click on the search symbol in the top, and you should see a list of available images from your area.
If you don’t see any images, try to change the cloud cover or expand the selected time period.

6. Select the image that suits your needs and download it.
The download might take a while. The most recent image I downloaded took ~3 min to download and the size was ~0.6GB.

How a filter could look like

The image I ended up selecting

Once the download is finished, the next challenge is to find the raster files in the labyrinth of subfolders. I found mine here:

C:\Users\username\Downloads\S2B_MSIL2A_20220618T102559_N0400_R108_T32VNJ_20220618T121737\S2B_MSIL2A_20220618T102559_N0400_R108_T32VNJ_20220618T121737.SAFE\GRANULE\L2A_T32VNJ_A027590_20220618T102602\IMG_DATA

Here you can find three resolutions folders (R10m, R20m, R60m). In my case I chose R10m.

The data is in the JP2-format, which a program like QGIS should not have any problem reading.

That’s it — good luck with downloading data on your own!

If you want to see what I used the sentinel image for, you can read about it in this post.

SMAP soil moisture data now available at 10km resolution [Google Earth Engine]

I realise that I am a bit late to the party, but I just noticed the paper by Mladenova et al (2020) which outlines a new SMAP-based soil moisture dataset, where the resolution is increased from 0.25°x0.25° (roughly 27-28km at the equator) to 10km by “assimilating soil moisture retrievals from the Soil Moisture Active Passive (SMAP) mission into the USDA-FAS Palmer model“.

The researchers tested the new dataset in three areas: California (USA), the Western Cape (South Africa) and New South Wales (Australia), as all three areas experienced a drought since the SMAP satellite has been operational.

Study areas for the Mladenova et al (2020) paper.
Study area for the Mladenova et al (2020) paper

Soil moisture is an often overlooked dataset, especially due to the often terribly low spatial resolution. Perhaps this enhanced dataset will result in an increased usage of the data. The increased spatial resolution is, in my opinion, a big improvement:

0.25°x0.25° SMAP image compared to the 10x10km enhanced SMAP image.
Here I used Lithuania used an example, with data from 2017-2018.

As you can guess from the two images above, the enhanced dataset is available on Google Earth Engine.

If you want to see the (to my knowledge) only high-resolution soil moisture product in existence, check out the Dutch remote sensing company VanderSat. Their product is based on passive microwaves, and has a spatial resolution of just 100m.

The NASA-USDA soil moisture product generated from the SMAP-enhanced Palmer model can be found here: https://gimms.gsfc.nasa.gov/SMOS/SMAP/.