Large amount of spatial data is indexed and delivered through files in Hierarchical Data Format (HDF). These files are compatible with desktop GIS software as QGIS but they are not so easy to open/read/process with standard Python libraries as Rasterio, or with dedicated libraries. On our research we found the spatial functionality on the powerful GDAL binaries and library for Python. 

We have done an applied case for the download, reproject (to WGS84) and clip to the area of interest of several MYD16A2 actual evapotranspiration images. We have also create an interactive visualization of the clipped images that allow us to examine the precipitation trends and the challenges in the use of these data products. 

Input data:
https://hatarilabs.com/ihen/howtor...