Hi Sonam,

I think it's a matter of your scale. You have a lot of zero values and then your data spans of many orders of magnitude.

I find the tidync package in R very useful. I used this to load your netcdf file and did a quick plot by filtering out all zero values and I see something that makes sense:

library(tidync)

library(tidyverse)

library(viridis)

#Load netcdf file, extract data into tibble dataframe and filter out zero values:

nc_143 %

tidync::hyper_tibble() %>%

dplyr::filter(emi_co2 > 0)

#plot the emi_co2 values:

ggplot(data = nc_143, aes(x = lon, y = lat)) +

geom_tile(aes(fill = emi_co2)) +

scale_fill_viridis(trans = "log")

Sonam Sahu

You seem to have no data of emission on your NC file, each geolocation shows a 0 value of emission, I quickly checked it on panoply and then in R.Attaching you the Screenshot of your data when I extracted in R.

This is the reason you're getting a flat plot.

this may be helpful https://www.youtube.com/watch?v=roMf6xzB9NI

however, I would prefer ggplot2 for this.