NOAA Center for Satellite Applications and Research banner
National Oceanic & Atmospheric Administration website NOAA Center for Satellite Applications and Research website

STAR - Global Vegetation Health Products : NPP VIIRS Daily map

"VIIRS GVI daily map" was GVI-x like product with 500m resolution, in NETCDF format.

It was composed from VIIRS SDR dataset of image bands: I1 (0.600-0.680um), I2 (0.846-0.885um) and I5 (10.50-12.40um) and Moderate Band M3(0.478-0.498um). The resolution of these input images is 375m at nadir. There are 14 or 15 orbits per day, saving as about 1000 (up to 1014) granules. Geo-location information, reflectance (of image band 1 and 2), brightness temperature (of image band 5) and could mask are saved in separate files respectively. For Image bands, each granule has 6400 x 1536 pixels.

File Type resolutiondatasets used for GVI
GITCO 375m "/All_Data/VIIRS-IMG-GEO_All/Latitude"
SVI01 375m "/All_Data/VIIRS-I1-SDR_All/Reflectance"
SVI02 375m "/All_Data/VIIRS-I2-SDR_All/Reflectance"
SVM03 750m "/All_Data/VIIRS-M3-SDR_All/Reflectance"
SVI05 375m "/All_Data/VIIRS-I5-SDR_All/BrightnessTemperature"

Procedure to create VIIRS GVI daily map

First, the "Orbit-Map" is created to map each granule pixel to GVI grid by slecting the pixel closest to the center of grid cell. It may have some holes on orbit-map if the output GVI grid is finer than the resolution of input VIIRS data (at nadir, it is 375m for image bands and 750m for MOD band). The holes are filled by nearest pixels. The figure below shows an example of VIIRS orbit map observed on April 19, 2012. It also shows the rate of missing pixels varies with latitide as well as sensor zenith angle if the holes are not filled.

Second, orbit maps of a day are merged into daily map by selecting the most nadir one form available pixels on orbit maps. This ensure the best data will be used, especially for high latitude area. Below figure shows The daily map of April 19 2012 (top), percentage of gaps on 500m daily map without gap-filling (bottom left) and the maimum sensor zenith angle if gaps are filled (bottom right).

For making VIIRS GVI daily map, the challenge is huge data volume because of the high resolution.
There are at least 6000 to 21000 input files (with size 700GB to 1TB, depending on the variables to be output) are rquired to process; If 500m VIIRS GVI daily map is genereated, the output array for thw whole GVI area will be 80000x 28928. We have to save it by multiple files,each file covers a small region (a tile). For example, 8x8 tiles, then, we have 220MB/file, 14GB/daily map.

Data flow chart for making VIIRS daily map are described below in detail

VIIRS GVI daily map product files
"VIIRS GVI daily map" covers the same spatial range as the GVI-x product, i.e. latitude range: [-55.152S to 75.024N], longitude range:[-180W, 180E]. The output array size is huge, [80000 x 28928]. Thus, GVI area is divided into 8 x 8 sub-regions with the same size: [10000 x 3616]. Each sub-region covers 45 degrees in longitude and 16.274 degrees in latitude.

File name example:

VGVI prefix of file
Gxx (or Gxxxm) resoution in KM (or in meters)
C01 fixed, indicate this is daily map
npp satellite ID
Pyyyyddd year and day of year
rxx row number of GVI sub-region
cxx column number of GVI sub-region

In each output file of "VIIRS GVI daily map", the following datasets are included:

variable SDS name unit typerange scaled scale_factor
reflectance of image band 1 reflectance_I1 NONE int16[0,1] yes 0.001
reflectance of image band 2 reflectance_I2 NONE int16[0,1] yes 0.001
reflectance of MOD band 3 reflectance_M3 NONE int16[0,1] yes 0.001
brightness temperature of image band 5 temperature_I5K int16 [0,400] yes 0.1
solar zenith solar_zenith degree int16[0,180]yes0.01
sensor zenith sensor_zenith degree int16[0,180]yes0.01
solar azimuth solar_azimuth degree int16[0,360]yes0.1
sensor azimuth sensor_azimuth degree int16[0,360]yes0.1
packed cloud mask packed_cloud_maskNONEint8
1. int16: 16 bits integer
2. int8: 8 bits integer
3. scaling formular: value= scale_facor * (scaled_value) +offset (normarlly,offset=0)

"packed cloud mask" dataset contains the following information:

bit from the least
significant bit(LSB)
0 invalid(1) / valid(0)
1 day(1) / night(0)
2 land(1) / water(0)
3 coast(1)/ no-coast(0)
4 glint(1)/ no-glint(0)
5 snow(1) / no-snow(0) (reserved bit, not set)
6~7 cloud mask(0~3): clear(0),partial-clear(1),partial-cloudy(2),cloudy(3)

Quick processing technique:
The range of geo-location and solar zenith angle of each granule is quickly extracted from "GITCO" file by reading the 4 corner pixels only. By using such granule information, we can skip granules which are out of GVI spatial range or observed in night.