Summary
In this notebook we will open a NetCDF4 file from the Earth Surface Minteral Dust Source Investigation (EMIT), specifically the Level 2A (L2A) Reflectance product. We will inspect the structure and plot the spectra of individual pixels and spatial coverage of a single scene. After that we will take advantage of the holoviews streams
to build an interactive plot.
Background
The EMIT instrument is an imaging spectrometer that measures light in visible and infrared wavelengths. These measurements display unique spectral signatures that correspond to the composition on the Earth's surface. The EMIT mission focuses specifically on mapping the composition of minerals to better understand the effects of mineral dust throughout the Earth system and human populations now and in the future. More details about EMIT and its associated products can be found in the README.md and on the EMIT website.
The L2A Reflectance Product contains estimated surface reflectance. Surface reflectance is the fraction of incoming solar radiation reflected Earth's surface. Different materials reflect different proportions of radiation based opon their chemical composition, meaning that this information can be used to determine the composition of a target. In this guide you will learn how to plot a layer from the L2A reflectance spatially and look at the spectral curve associated with individual pixels, which can be used to identify targets.
File Structure
Inside the .netcdf
file there are 3 groups, the root group containing reflectance values accross the downtrack, crosstrack, and bands dimensions, the sensor_band_parameters
group containing the wavelength of each band center, and the full-width half maximum (FWHM) or bandwidth at half of the maximum amplitude, and the location
group containing latitude and longitude values of each pixel as well as a geometric lookup table (GLT). The GLT is an orthorectified image that provides relative downtrack and crosstrack reference locations from the raw scene to facilitate fast projection of the dataset.
Requirements
Learning Objectives
.nc
file as an xarray.Dataset
import numpy as np
import math
import xarray as xr
import geoviews as gv
import holoviews as hv
import hvplot.xarray
import netCDF4 as nc
gv.extension('bokeh')