Importing Copernicus Global Land Service Leaf Area Index (netcdf) files

Gillian

Hi. Trying to import Leaf Area Index (netcdf) from Copernicus Global Land Service. I understand that GM is able to regognise these files from this provider, and I am able to load a single layer (if I define the file). However there should be more layers (the satellite returns every 10 days) and the the values as shown in GM seem to be a sum of all the layers. If I import the file into ArcGIS again I get only one layer - but the values look more reasonable.

Is there something further I should be doing in GM, or is this a problem with the import filter?

Thanks

Gillian

bmg_mike

Hi Gillian,

I was able to update the importer in Global Mapper so that the LAI data loads automatically so you don't have to set up a custom data set. The no-data pixels in the ocean are also now properly recognized and made transparent.

Note that to get the proper value from the raw data, you needed to use a scale factor of 0.0333333 (1 / 30) [see https://land.copernicus.eu/global/products/lai]. This is likely why the values looked too large for you. The new automatic reader sets that correctly.

Tomorrow's v23.1 daily build at https://www.bluemarblegeo.com/products/global-mapper-daily-builds.php will have this update.

Thanks,

Mike

Global Mapper Guru

bmg_mike

HI Gillian,

The NetCDF format is a generic scientific format that supports a large variety of methods for storing data. I would expect a prompt in GM to select the layer(s) to load if there are multiple recognized layers.

If you can provide a sample file (or point to one online) we can take a look at what is there.

Thanks,

Mike

Global Mapper Guru

Gillian

Hi Mike

The smallest files are approx. 400 Mb (!) so here is a link to a 1Km tile. https://land.copernicus.vgt.vito.be/PDF/free?productID=59933309&collectionID=1000083&fileIndex=1 . I can put it up on a share service if you cant access it.

Would love to use the 300m tiles but they are too large for my PC (16GB RAM)

thanks

Gillian

Gillian

Brilliant! Thank you so much for sorting this.

Gillian