MODIS SIN Grid data(MOD16A2) visualization.

[kmmrao]

I am trying to extract MODIS ET SIN Grid data(MOD16A2) for some time period. I am able to extract the data rasters but trying to create one-dimensional longitude and latitude arrays from longitude-minimum/maximum and latitude-minimum/maximum. When I am trying to do this the plot is shifting to the left of the plot. The Python code is attached.

[LP DAACx - dgolon]

Hi @kmmrao We'll take a look at your code and get back to you. Thanks - Danielle

[ogsahin]

hdf and netcdf files are stored latitude maximum to minimum (left to right). I think the problem is line 19 in your code. Latitude values need to decrease, not increase, in numpy array.

[kmmrao]

Ok, understood, but the map shifting to left in the high latitudes. How to fix it?

[ogsahin]

lats= np.linspace(lat.min(),lat.max(),2400) this one is wrong. It should be

lats= np.linspace(lat.max(),lat.min(),2400)

[kmmrao]

Hi,
Thanks for your response,
Let me explain, if you are into Python, no matter what
lats= np.linspace(lat.max(),lat.min(),2400) (or)
lats= np.linspace(lat.max(),lat.min(),2400)

My point is simple and straight. When I change the coordinate system from
Sinusoidal to Mercator projection. Still, the map is bending towards the left with an increase in latitude from the equator.
Should I need to use any offset to lats= np.linspace(lat.max(),lat.min(),2400) ??
or to lons ?

[ogsahin]

1) You used (lon, lat) and (lons, lats) coordinates, both of them wgs84, and asked why this map is shifting. It is impossible to understand "simple and straight" point when we follow jupyter notebook you shared.

2) Of course, maps will shift if you are projecting them and there is no solution. How do you expect to get the exact map representation (visualization) after projecting it?

3) If you want to extract ET products for a specific ___location, just use the AρρEEARS software. Otherwise, you must handle and merge more than one "hdf" file.

[LP DAAC - afriesz]

@kmmrao ,

Have you been able to explore NASA's AppEEARS (https://appeears.earthdatacloud.nasa.gov/) as @ogsahin mentioned? I think it would help. Another option outside of Python is to use the GDAL Warp (https://gdal.org/programs/gdalwarp.html) utility.