Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-07-26 09:27:35	ga_ls8c_ard_3-1-0_091087_2017-07-25_final
2019-03-13 09:51:47	ga_ls8c_ard_3-1-0_096071_2019-03-13_final
2019-03-13 09:52:11	ga_ls8c_ard_3-1-0_096072_2019-03-13_final
2019-03-13 09:56:59	ga_ls8c_ard_3-1-0_096084_2019-03-13_final
2019-03-17 11:07:32	ga_ls8c_ard_3-1-0_108075_2019-03-17_final
2019-04-02 11:09:52	ga_ls8c_ard_3-1-0_108081_2019-04-02_final
2019-04-07 09:50:18	ga_ls8c_ard_3-1-0_095083_2019-04-07_final
2019-06-17 09:56:01	ga_ls8c_ard_3-1-0_096081_2019-06-17_final
2019-06-26 09:51:52	ga_ls8c_ard_3-1-0_095086_2019-06-26_final
2019-07-12 09:49:56	ga_ls8c_ard_3-1-0_095081_2019-07-12_final
2019-07-12 09:50:44	ga_ls8c_ard_3-1-0_095083_2019-07-12_final
2019-07-16 09:26:25	ga_ls8c_ard_3-1-0_091084_2019-07-15_final
2019-07-19 09:56:08	ga_ls8c_ard_3-1-0_096081_2019-07-19_final
2019-07-19 09:57:20	ga_ls8c_ard_3-1-0_096084_2019-07-19_final
2019-08-13 09:48:55	ga_ls8c_ard_3-1-0_095078_2019-08-13_final
2019-08-13 09:49:43	ga_ls8c_ard_3-1-0_095080_2019-08-13_final
2019-08-13 09:50:07	ga_ls8c_ard_3-1-0_095081_2019-08-13_final
2019-08-13 09:50:55	ga_ls8c_ard_3-1-0_095083_2019-08-13_final
2019-08-20 09:57:56	ga_ls8c_ard_3-1-0_096085_2019-08-20_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-09-02 09:26:40	ga_ls8c_ard_3-1-0_091084_2019-09-01_final
2019-09-04 10:46:25	ga_ls8c_ard_3-1-0_105067_2019-09-04_final
2019-09-05 09:57:59	ga_ls8c_ard_3-1-0_096085_2019-09-05_final
2019-09-14 09:51:04	ga_ls8c_ard_3-1-0_095083_2019-09-14_final
2019-09-30 09:46:45	ga_ls8c_ard_3-1-0_095072_2019-09-30_final
2019-10-16 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-10-16_final
2019-11-01 09:51:11	ga_ls8c_ard_3-1-0_095083_2019-11-01_final
2019-11-05 09:26:27	ga_ls8c_ard_3-1-0_091083_2019-11-04_final
2019-11-24 09:52:06	ga_ls8c_ard_3-1-0_096070_2019-11-24_final
2020-01-04 09:51:00	ga_ls8c_ard_3-1-0_095083_2020-01-04_final
2020-01-10 10:49:12	ga_ls8c_ard_3-1-0_105074_2020-01-10_final
2020-01-11 09:55:58	ga_ls8c_ard_3-1-0_096080_2020-01-11_final
2020-01-15 11:10:55	ga_ls8c_ard_3-1-0_108082_2020-01-15_final
2020-01-27 09:58:17	ga_ls8c_ard_3-1-0_096086_2020-01-27_final
2020-02-21 09:50:00	ga_ls8c_ard_3-1-0_095081_2020-02-21_final
2020-02-25 09:25:16	ga_ls8c_ard_3-1-0_091081_2020-02-24_final
2020-02-25 09:25:40	ga_ls8c_ard_3-1-0_091082_2020-02-24_final
2020-03-31 09:53:29	ga_ls8c_ard_3-1-0_096075_2020-03-31_final
2020-04-09 09:46:27	ga_ls8c_ard_3-1-0_095073_2020-04-09_final
2020-04-09 09:48:50	ga_ls8c_ard_3-1-0_095079_2020-04-09_final
2020-04-16 09:53:22	ga_ls8c_ard_3-1-0_096075_2020-04-16_final
2020-04-16 09:56:58	ga_ls8c_ard_3-1-0_096084_2020-04-16_final
2020-04-25 09:45:55	ga_ls8c_ard_3-1-0_095072_2020-04-25_final
2020-04-25 09:50:43	ga_ls8c_ard_3-1-0_095084_2020-04-25_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-05 10:50:22	ga_ls8c_ard_3-2-1_105078_2022-04-05_final
2022-04-06 09:55:33	ga_ls8c_ard_3-2-1_096080_2022-04-06_final
2022-04-07 10:38:49	ga_ls8c_ard_3-2-1_103080_2022-04-07_final
2022-04-10 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-04-10_final
2022-04-10 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-04-10_final
2022-04-11 10:14:08	ga_ls8c_ard_3-2-1_099080_2022-04-11_final
2022-04-12 09:17:19	ga_ls8c_ard_3-2-1_090077_2022-04-11_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-15 11:25:56	ga_ls8c_ard_3-2-1_111074_2022-04-15_final
2022-04-15 11:26:19	ga_ls8c_ard_3-2-1_111075_2022-04-15_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-19 11:03:35	ga_ls8c_ard_3-2-1_107080_2022-04-19_final
2022-04-19 11:04:23	ga_ls8c_ard_3-2-1_107082_2022-04-19_final
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-22 09:55:35	ga_ls8c_ard_3-2-1_096080_2022-04-22_final
2022-04-22 11:34:04	ga_ls8c_ard_3-2-1_112079_2022-04-22_final
2022-04-23 10:38:03	ga_ls8c_ard_3-2-1_103078_2022-04-23_final
2022-04-26 09:33:38	ga_ls8c_ard_3-2-1_092087_2022-04-26_final
2022-04-27 10:12:05	ga_ls8c_ard_3-2-1_099075_2022-04-27_final
2022-05-01 09:48:11	ga_ls8c_ard_3-2-1_095077_2022-05-01_final
2022-05-03 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-03 11:15:32	ga_ls8c_ard_3-2-1_109079_2022-05-03_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-05 10:59:36	ga_ls8c_ard_3-2-1_107070_2022-05-05_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-07 10:51:15	ga_ls8c_ard_3-2-1_105080_2022-05-07_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-11 10:24:11	ga_ls8c_ard_3-2-1_101074_2022-05-11_final
2022-05-24 09:55:19	ga_ls8c_ard_3-2-1_096079_2022-05-24_final
2022-05-24 11:34:12	ga_ls8c_ard_3-2-1_112079_2022-05-24_final
2022-05-25 10:36:35	ga_ls8c_ard_3-2-1_103074_2022-05-25_final
2022-05-26 09:42:09	ga_ls8c_ard_3-2-1_094077_2022-05-26_final
2022-06-02 11:27:17	ga_ls8c_ard_3-2-1_111077_2022-06-02_final
2022-06-03 10:30:53	ga_ls8c_ard_3-2-1_102075_2022-06-03_final
2022-06-04 11:14:34	ga_ls8c_ard_3-2-1_109076_2022-06-04_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-13 11:10:29	ga_ls8c_ard_3-2-1_108081_2022-06-13_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-18 09:49:00	ga_ls8c_ard_3-2-1_095078_2022-06-18_final
2022-06-18 09:52:11	ga_ls8c_ard_3-2-1_095086_2022-06-18_final
2022-06-18 11:25:53	ga_ls8c_ard_3-2-1_111073_2022-06-18_final
2022-06-20 09:36:39	ga_ls8c_ard_3-2-1_093078_2022-06-20_final
2022-06-20 11:13:08	ga_ls8c_ard_3-2-1_109072_2022-06-20_final
2022-06-20 11:14:44	ga_ls8c_ard_3-2-1_109076_2022-06-20_final
2022-06-21 10:20:19	ga_ls8c_ard_3-2-1_100079_2022-06-21_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years