Export Data

You can find on the Downloads tab on the left menu, all downloadable and exportable items in a Site.

All the files are organized and displayed by category on the left side. You can find the file that have been generated through a platform analytic in section "All Analytics files".

Also you will find other files that have been uploaded in the "All other files" section. You can select the ones you want to see. 

You can also use the Search bar on the right top corner to look for a specific file.


According to the nature of your file, you can Export or Download.

  • Export : You will be able to choose the format of your downloadable file as well as the CRS.
  • Download: You will download the original file without any transformation.

1. Vector files

In order to allow you manage your files and vector files ALL the vectors display on the Map view are available on the Download view. 


For reliability purpose these vectors have to be first “exported” before downloading. However the Download option remains available on the information panel on the MAP VIEW.

In order to customize your file to be download, click on the arrow icon and then on Export to choose specific format and CRS.

For vector files corresponding to your Initial files uploaded in Alteia Platform you can directly download them from the Download view by clicking on the arrow icon and then on Download.

2. Raster files

You can choose between:

  • Download which will download the file as it is or 
  • Export and change the GSD* and resampling method** as well.


JPEG format supports a maximum image size of 65000x65000 pixels.


Note : You can also download vector files from the Layer view by clicking on the wanted vector file.

This will open the info panel. Click on the three dots close to the vector name and click on download

*The displayed GSD is the rounded value of the original data.

** Here are the definition of the resampling methods :

  • Bilinear (default) : Bilinear interpolation is a technique for calculating values of a grid location based on four nearby grid cells.
    It assigns the output cell value by taking the weighted average of the four neighboring cells in an image to generate new values.
    It smooths the output raster grid, but not as much as cubic convolution. It’s useful when working with continuous data sets that don’t have distinct boundaries.
    When should you use bilinear resampling?
    Temperature gradients rasters, digital elevation models and annual precipitation grids are examples of when to use bilinear interpolation
  • Near : The nearest neighbor technique doesn’t change any of the values from the input raster data set. It takes the cell center from the input raster data set to determine the closest cell center of the output raster. For processing speed, it’s generally the fastest because of its simplicity.
    Because nearest neighbor resampling doesn’t alter any values in the output raster data set, it is ideal for categorical, nominal, and ordinal data.
    When should you use nearest neighbor resampling?
    Often, you use the nearest neighbor for discrete data like land cover classification, buildings, and soil types that have distinct boundaries and their limits are discrete.
  • Cubic : Cubic convolution interpolation is similar to bilinear interpolation in that it takes the average of surrounding cells. Instead of using the four nearest cells, the output value is based on averaging the 16 nearest cells. As a result, processing time tends to increase for this method.
    This method is generally used for continuous surfaces where much noise exists. Because it takes more neighboring cells compared to bilinear resampling, it’s good for smoothing data from the input raster grid.
    When should you use cubic convolution interpolation?
    Cubic convolution is ideal for noisy rasters like smoothing out a radar image or surface model.
  • Cubicspline : Cubic spline resampling
  • Lanczos : Lanczos windowed sinc resampling.
  • Average : Average resampling, computes the weighted average of all contributing pixels.
  • Mode : Mode resampling, selects the value which appears most often of all the sampled points.
  • Max : Maximum resampling, selects the maximum value from all contributing pixels.
  • Min : Minimum resampling, selects the minimum value from all contributing pixels.
  • Med : Median resampling, selects the median value of all contributing pixels.
  • q1 : First quartile resampling, selects the first quartile value of all contributing pixels.
  • q3 : Third quartile resampling, selects the third quartile value of all contributing pixels.