i.modis.qc - GRASS GIS manual

NAME

i.modis.qc - Extracts quality control parameters from MODIS QC layers.

KEYWORDS

imagery, imagery quality assessment, reflectance, land surface temperature, vegetation, satellite, MODIS

SYNOPSIS

i.modis.qc

i.modis.qc --help

i.modis.qc input=name output=name productname=string qcname=string [band=string] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

--overwrite: Allow output files to overwrite existing files
--help: Print usage summary
--verbose: Verbose module output
--quiet: Quiet module output
--ui: Force launching GUI dialog

Parameters:

input=name [required]: Name of input surface reflectance QC layer [bit array]
output=name [required]: Name for output QC type classification layer
productname=string [required]: Name of MODIS product type; Options: mod09Q1, mod09A1, mod09A1s, mod09GA, mod09GAs, mod09CMG, mod09CMGs, mod09CMGi, mod11A1, mod11A2, mod13A2, mcd43B2, mcd43B2q, mod13Q1; mod09Q1: surf. refl. 250m 8-days; mod09A1: surf. refl. 500m 8-days; mod09A1s: surf. refl. 500m 8-days, State QA; mod09GA: surf. refl. 500m daily; mod09GAs: surf. refl. 500m daily, State QA; mod09CMG: surf. refl. 5000m daily; mod09CMGs: surf. refl. 5000m daily, State QA; mod09CMGi: surf. refl. 5000m daily, Internal Climatology; mod11A1: LST 1km daily (Day/Night); mod11A2: LST 1km 8-days (Day/Night); mod13A2: VI 1km 16-days; mcd43B2: Brdf-Albedo Quality (Ancillary SDS) 1km 8-days; mcd43B2q: Brdf-Albedo Quality (BRDF SDS) 1km 8-days; mod13Q1: VI 250m 16-days
qcname=string [required]: Name of QC type to extract; Options: adjcorr, atcorr, cloud, data_quality, diff_orbit_from_500m, modland_qa, mandatory_qa_11A1, data_quality_flag_11A1, emis_error_11A1, lst_error_11A1, data_quality_flag_11A2, emis_error_11A2, mandatory_qa_11A2, lst_error_11A2, aerosol_quantity, brdf_correction_performed, cirrus_detected, cloud_shadow, cloud_state, internal_cloud_algorithm, internal_fire_algorithm, internal_snow_mask, land_water, mod35_snow_ice, pixel_adjacent_to_cloud, salt_pan, icm_cloudy, icm_clear, icm_high_clouds, icm_low_clouds, icm_snow, icm_fire, icm_sun_glint, icm_dust, icm_cloud_shadow, icm_pixel_is_adjacent_to_cloud, icm_cirrus, icm_pan_flag, icm_criteria_for_aerosol_retrieval, icm_aot_has_clim_val, modland_qa, vi_usefulness, aerosol_quantity, pixel_adjacent_to_cloud, brdf_correction_performed, mixed_clouds, land_water, possible_snow_ice, possible_shadow, platform, land_water, sun_z_angle_at_local_noon, brdf_correction_performed, modland_qa, vi_usefulness, aerosol_quantity, pixel_adjacent_to_cloud, brdf_correction_performed, mixed_clouds, land_water, possible_snow_ice, possible_shadow; adjcorr: mod09: Adjacency Correction; atcorr: mod09: Atmospheric Correction; cloud: mod09: Cloud State; data_quality: mod09: Band-Wise Data Quality Flag; diff_orbit_from_500m: mod09: 250m Band is at Different Orbit than 500m; modland_qa: mod13Q1: MODIS Land General Quality Assessment; mandatory_qa_11A1: mod11A1: MODIS Land General Quality Assessment; data_quality_flag_11A1: mod11A1: Detailed Quality Indications; emis_error_11A1: mod11A1: Average Emissivity Error Classes; lst_error_11A1: mod11A1: Average LST Error Classes; data_quality_flag_11A2: mod11A2: Detailed Quality Indications; emis_error_11A2: mod11A2: Average Emissivity Error Classes; mandatory_qa_11A2: mod11A2: MODIS Land General Quality Assessment; lst_error_11A2: mod11A2: Average LST Error Classes; aerosol_quantity: mod13Q1: Quantity range of Aerosol; brdf_correction_performed: mod13Q1: if BRDF correction performed; cirrus_detected: mod09*s: StateQA Cirrus Detected; cloud_shadow: mod09*s: StateQA Cloud Shadow; cloud_state: mod09*s: StateQA Cloud State; internal_cloud_algorithm: mod09*s: StateQA Internal Cloud Algorithm; internal_fire_algorithm: mod09*s: StateQA Internal Fire Algorithm; internal_snow_mask: mod09*s: StateQA Internal Snow Mask; land_water: mod13Q1: separate land from various water objects; mod35_snow_ice: mod09*s: StateQA mod35 Snow Ice; pixel_adjacent_to_cloud: mod13Q1: if pixel is a cloud neighbour; salt_pan: mod09*s: StateQA Salt Pan (mod09GAs); icm_cloudy: mod09*i: Internal CM: Cloudy; icm_clear: mod09*i: Internal CM: Clear; icm_high_clouds: mod09*i: Internal CM: High Clouds; icm_low_clouds: mod09*i: Internal CM: Low Clouds; icm_snow: mod09*i: Internal CM: Snow; icm_fire: mod09*i: Internal CM: Fire; icm_sun_glint: mod09*i: Internal CM: Sun Glint; icm_dust: mod09*i: Internal CM: Dust; icm_cloud_shadow: mod09*i: Internal CM: Cloud Shadow; icm_pixel_is_adjacent_to_cloud: mod09*i: Internal CM: Pixel is Adjacent to Cloud; icm_cirrus: mod09*i: Internal CM: Cirrus; icm_pan_flag: mod09*i: Internal CM: Pan Flag; icm_criteria_for_aerosol_retrieval: mod09*i: Internal CM: Criteria for Aerosol Retrieval; icm_aot_has_clim_val: mod09*i: Internal CM: AOT (aerosol optical depth) has clim. val.; vi_usefulness: mod13Q1: Quality estimation of the pixel; mixed_clouds: mod13Q1: if pixel mixed with clouds; possible_snow_ice: mod13Q1: if snow/ice present in pixel; possible_shadow: mod13Q1: if shadow is present in pixel; platform: mcd43B2: Quality of BRDF correction performed; sun_z_angle_at_local_noon: mcd43B2: Quality of BRDF correction performed
band=string: Band number of MODIS product (mod09Q1=[1,2],mod09A1=[1-7],m[o/y]d09GA=[1-7],m[o/y]d09CMG=[1-7], mcd43B2q=[1-7]); Options: 1, 2, 3, 4, 5, 6, 7; 1: Band 1: Red; 2: Band 2: NIR; 3: Band 3: Blue; 4: Band 4: Green; 5: Band 5: SWIR 1; 6: Band 6: SWIR 2; 7: Band 7: SWIR 3

DESCRIPTION
- MOD09A1 and MOD09Q1
- MOD11A1
- MOD11A2
- MOD13A2
- MOD13Q1
- MCD43B2
NOTES
TODO
REFERENCES
SEE ALSO
AUTHOR

DESCRIPTION

i.modis.qc extracts Requested Quality Assessment flags from the following MODIS products: MOD09A1, MOD09Q1, MOD11A1, MOD11A2, MOD13A2, MOD13Q1, MCD43B2. This does include MOD09A1 QA_state_500m layer (see Notes).
Added MOD09GA support in 2016, it follows MOD09A1 and its StateQA, but does not have BRDF State QA, instead has Salt Pan State QA.

MOD09A1 and MOD09Q1

MOD09A1/Q1: MODLAND QA Bits. bits=[0-1]

[00]= class 0: Corrected product produced at ideal quality -- all bands
[01]= class 1: Corrected product produced at less than ideal quality -- some or all bands
[10]= class 2: Corrected product NOT produced due to cloud effect -- all bands
[11]= class 3: Corrected product NOT produced due to other reasons -- some or all bands maybe be fill value (Note that a value of [11] overrides a value of [01])

MOD09Q1: Cloud State. bits=[2-3]

[00]= class 0: Clear -- No clouds
[01]= class 1: Cloudy
[10]= class 2: Mixed
[11]= class 3: Not Set ; Assumed Clear

MOD09Q1: Band-wise Data Quality 250m bits=[4-7][8-11]
MOD09A1: Band-wise Data Quality 500m bits=[2-5][6-9][10-13][14-17][18-21][22-25][26-29]

[0000]= class 0: highest quality
[0111]= class 1: noisy detector
[1000]= class 2: dead detector; data interpolated in L1B
[1001]= class 3: solar zenith ≥ 86 degrees
[1010]= class 4: solar zenith ≥ 85 and < 86 degrees
[1011]= class 5: missing input
[1100]= class 6: internal constant used in place of climatological data for at least one atmospheric constant
[1101]= class 7: correction out of bounds, pixel constrained to extreme allowable value
[1110]= class 8: L1B data faulty
[1111]= class 9: not processed due to deep ocean or cloud
Class 10-15: Combination of bits unused

MOD09A1/Q1: Atmospheric correction bit=[12]/[30]

[0]= class 0: Not Corrected product
[1]= class 1: Corrected product

MOD09A1/Q1: Adjacency correction bit=[13]/[31]

[0]= class 0: Not Corrected product
[1]= class 1: Corrected product

MOD09Q1: Different orbit from 500m product, bit=[14]

[0]= class 0: same orbit as 500m
[1]= class 1: different orbit from 500m

MOD09A1s: Cloud State bits=[0-1]

[00]= class 0: clear
[01]= class 1: cloudy
[10]= class 2: mixed
[11]= class 3: not set, assumed clear

MOD09A1s: Cloud shadow bits=[2]

[0]= class 0: no
[1]= class 1: yes

MOD09A1s: Land/Water Flag bits=[3-5]

[000]= class 0: Shallow ocean
[001]= class 1: Land
[010]= class 2: Ocean coastlines and lake shorelines
[011]= class 3: Shallow inland water
[100]= class 4: Ephemeral water
[101]= class 5: Deep inland water
[110]= class 6: Continental/moderate ocean
[111]= class 7: Deep ocean

MOD09A1s: Aerosol Quantity bits=[6-7]

[00]= class 0: Climatology
[01]= class 1: Low
[10]= class 2: Average
[11]= class 3: High

MOD09A1s: Cirrus detected bits=[8-9]

[00]= class 0: None
[01]= class 1: Small
[10]= class 2: Average
[11]= class 3: High

MOD09A1s: Internal Cloud Algorithm Flag bits=[10]

[0]= class 0: No cloud
[1]= class 1: Cloud

MOD09A1s: Internal Fire Algorithm Flag bits=[11]

[0]= class 0: No fire
[1]= class 1: Fire

MOD09A1s: MOD35 snow/ice flag bits=[12]

[0]= class 0: No
[1]= class 1: Yes

MOD09A1s: Pixel adjacent to cloud bits=[13]

[0]= class 0: No
[1]= class 1: Yes

MOD09A1s: BRDF correction performed bits=[14]

[0]= class 0: No
[1]= class 1: Yes

MOD09A1s: Internal Snow Mask bits=[15]

[0]= class 0: No snow
[1]= class 1: Snow

MOD11A1

MOD11A1: Mandatory QA Flags bits=[0-1]

[00]= class 0: LST produced, good quality, not necessary to examine more detailed QA
[01]= class 1: LST produced, other quality, recommend examination of more detailed QA
[10]= class 2: LST not produced due to cloud effects
[11]= class 3: LST not produced primarily due to reasons other than cloud

MOD11A1: Data Quality Flag bits=[2-3]

[00]= class 0: Good data quality of L1B in bands 31 and 32
[01]= class 1: Other quality data
[10]= class 2: TBD
[11]= class 3: TBD

MOD11A1: Emis Error Flag bits=[4-5]

[00]= class 0: Average emissivity error ≤ 0.01
[01]= class 1: Average emissivity error ≤ 0.02
[10]= class 2: Average emissivity error ≤ 0.04
[11]= class 3: Average emissivity error > 0.04

MOD11A1: LST Error Flag bits=[6-7]

[00]= class 0: Average LST error ≤ 1
[01]= class 1: Average LST error ≤ 2
[10]= class 2: Average LST error ≤ 3
[11]= class 3: Average LST error > 3

MOD11A2

MOD11A2: Mandatory QA Flags bits=[0-1]

[00]= class 0: LST produced, good quality, not necessary to examine more detailed QA
[01]= class 1: LST produced, other quality, recommend examination of more detailed QA
[10]= class 2: LST not produced due to cloud effects
[11]= class 3: LST not produced primarily due to reasons other than cloud

MOD11A2: Data Quality Flag bits=[2-3]

[00]= class 0: Good data quality of L1B in 7 TIR bands
[01]= class 1: Other quality data
[10]= class 2: TBD
[11]= class 3: TBD

MOD11A2: Emis Error Flag bits=[4-5]

[00]= class 0: Average emissivity error ≤ 0.01
[01]= class 1: Average emissivity error ≤ 0.02
[10]= class 2: Average emissivity error ≤ 0.04
[11]= class 3: Average emissivity error > 0.04

MOD11A2: LST Error Flag bits=[6-7]

[00]= class 0: Average LST error ≤ 1
[01]= class 1: Average LST error ≤ 2
[10]= class 2: Average LST error ≤ 3
[11]= class 3: Average LST error > 3

MOD13A2

MOD13A2: Mandatory QA Flags 1km bits[0-1]

[00]= class 0: VI produced, good quality
[01]= class 1: VI produced, but check other QA
[10]= class 2: Pixel produced, but most probably cloud
[11]= class 3: Pixel not produced due to other reasons than clouds

MOD13A2: VI Usefulness Flag bits[2-5]

[0000]= class 0: Highest quality
[0001]= class 1: Lower quality
[0010]= class 2: Decreasing quality
[0100]= class 3: Decreasing quality
[1000]= class 4: Decreasing quality
[1001]= class 5: Decreasing quality
[1010]= class 6: Decreasing quality
[1100]= class 7: Lowest quality
[1101]= class 8: Quality so low that it is not useful
[1110]= class 9: L1B data faulty
[1111]= class 10: Not useful for any other reason/not processed

MOD13A2: Aerosol quantity Flags 1km bits[6-7]

[00]= class 0: Climatology
[01]= class 1: Low
[10]= class 2: Average
[11]= class 3: High

MOD13A2: Adjacent cloud detected 1km bit[8]

[00]= class 0: No
[01]= class 1: Yes

MOD13A2: Atmosphere BRDF correction performed 1km bit[9]

[00]= class 0: No
[01]= class 1: Yes

MOD13A2: Mixed clouds 1km bit[10]

[00]= class 0: No
[01]= class 1: Yes

MOD13A2: Land/Water Flags 1km bits[11-13]

[000]= class 0: Shallow Ocean
[001]= class 1: Land (Nothing else but land)
[010]= class 2: Ocean Coastlines and lake shorelines
[011]= class 3: Shallow inland water
[100]= class 4: Ephemeral water
[101]= class 5: Deep inland water
[110]= class 6: Moderate or continental ocean
[111]= class 7: Deep ocean

MOD13A2: Possible Snow/Ice 1km bits[14]

[0]= class 0: No
[1]= class 1: Yes

MOD13A2: Possible Shadow 1km bits[15]

[0]= class 0: No
[1]= class 1: Yes

MOD13Q1

MOD13Q1: Mandatory QA Flags 250m bits[0-1]

[00]= class 0: VI produced, good quality
[01]= class 1: VI produced, but check other QA
[10]= class 2: Pixel produced, but most probably cloud
[11]= class 3: Pixel not produced due to other reasons than clouds

MOD13Q1: VI Usefulness Flag 250m bits[2-5]

[0000]= class 0: Highest quality
[0001]= class 1: Lower quality
[0010]= class 2: Decreasing quality
[0100]= class 3: Decreasing quality
[1000]= class 4: Decreasing quality
[1001]= class 5: Decreasing quality
[1010]= class 6: Decreasing quality
[1100]= class 7: Lowest quality
[1101]= class 8: Quality so low that it is not useful
[1110]= class 9: L1B data faulty
[1111]= class 10: Not useful for any other reason/not processed

MOD13Q1: Aerosol quantity Flags 250m bits[6-7]

[00]= class 0: Climatology
[01]= class 1: Low
[10]= class 2: Average
[11]= class 3: High

MOD13Q1: Adjacent cloud detected 250m bit[8]

[00]= class 0: No
[01]= class 1: Yes

MOD13Q1: Atmosphere BRDF correction performed 250m bit[9]

[00]= class 0: No
[01]= class 1: Yes

MOD13Q1: Mixed clouds 250m bit[10]

[00]= class 0: No
[01]= class 1: Yes

MOD13Q1: Land/Water Flags 250m bits[11-13]

[000]= class 0: Shallow Ocean
[001]= class 1: Land (Nothing else but land)
[010]= class 2: Ocean Coastlines and lake shorelines
[011]= class 3: Shallow inland water
[100]= class 4: Ephemeral water
[101]= class 5: Deep inland water
[110]= class 6: Moderate or continental ocean
[111]= class 7: Deep ocean

MOD13Q1: Possible Snow/Ice 250m bits[14]

[0]= class 0: No
[1]= class 1: Yes

MOD13Q1: Possible Shadow 250m bits[15]

[0]= class 0: No
[1]= class 1: Yes

MCD43B2

MCD43B2: Albedo Quality Ancillary Platform Data 1km bits[0-3]
SDS: BRDF_Albedo_Ancillary

[0000]= class 0: Satellite Platform: Terra
[0001]= class 1: Satellite Platform: Terrra/Aqua
[0010]= class 2: Satellite Platform: Aqua
[1111]= class 15: Fill Value
Classes 3-14: Not used

MCD43B2: Albedo Quality Ancillary Land/Water Data 1km bits[4-7]
SDS: BRDF_Albedo_Ancillary

[0000] class 0: Shallow Ocean
[0001] class 1: Land (Nothing else but land)
[0010] class 2: Ocean and lake shorelines
[0011] class 3: Shallow inland water
[0100] class 4: Ephemeral water
[0101] class 5: Deep inland water
[0110] class 6: Moderate or continental ocean
[0111] class 7: Deep ocean
[1111] class 15: Fill Value
Classes 8-14: Not used

MCD43B2: Albedo Quality Ancillary Sun Zenith Angle at Local Solar Noon Data 1km bits[8-14]
SDS: BRDF_Albedo_Ancillary

Returns integer value [0-90], 127 is Fill Value

MCD43B2: Band-wise Albedo Quality Data 1km
SDS: BRDF_Albedo_Band_Quality

bits[0-3][4-7][8-11][12-15][16-19][20-23][24-27]

[0000]= class 0: best quality, 75% or more with best full inversions
[0001]= class 1: good quality, 75% or more with full inversions
[0010]= class 2: Mixed, 50% or less full inversions and 25% or less fill values
[0011]= class 3: All magnitude inversions or 50% or less fill values
[0100]= class 4: 75% or more fill values
Classes 5-14: Not Used
[1111]= class 15: Fill Value

NOTES

In MOD09A1: It seems that cloud related info is not filled properly in the standard QC (MOD09A1 in this module) since version 3, State-QA 500m images (MOD09A1s in this module) should be used (see Vermote et al., 2008). MOD11A2 quality control (QC) bands do not have a FillValue (No-data) according to MODIS Land Products site. However, the metadata of the QC bands (i.e.: gdalinfo QC_band) shows No-data=0. This value is then transformed into GRASS NULLs when data is imported through r.in.gdal. Applying i.modis.qc on those QC bands will not give the expected range of values in the different QC bits. Therefore, before using i.modis.qc, the user needs to set the NULL value in QC bands back to zero (i.e.: r.null map=QC_band null=0) or just edit the metadata with GDAL utilities before importing into GRASS GIS. This is a known issue for MOD11A2 (8-day LST product), but other MODIS products might be affected as well.

TODO

Add more daily products.

REFERENCES

MODIS Products
Vermote E.F., Kotchenova S.Y., Ray J.P. MODIS Surface Reflectance User's Guide. Version 1.2. June 2008. MODIS Land Surface Reflectance Science Computing Facility. Homepage

AUTHOR

Yann Chemin

SOURCE CODE

Available at: i.modis.qc source code (history)

Latest change: Thursday Jan 26 14:10:26 2023 in commit: cdd84c130cea04b204479e2efdc75c742efc4843