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
2021-06-17 09:35:29	ga_ls8c_ard_3-2-0_093076_2021-06-17_final
2021-07-22 10:09:18	ga_ls8c_ard_3-2-0_098083_2021-07-22_final
2021-07-26 11:19:55	ga_ls8c_ard_3-2-0_110074_2021-07-26_final
2021-07-28 09:27:53	ga_ls8c_ard_3-2-0_092072_2021-07-27_final
2021-07-31 10:02:24	ga_ls8c_ard_3-2-0_097081_2021-07-31_final
2021-09-06 10:17:33	ga_ls8c_ard_3-2-0_100072_2021-09-06_final
2021-09-14 11:08:13	ga_ls8c_ard_3-2-0_108075_2021-09-14_final
2021-09-17 09:58:39	ga_ls8c_ard_3-2-0_097071_2021-09-17_final
2021-10-05 11:30:27	ga_ls8c_ard_3-2-0_111084_2021-10-05_final
2021-10-07 09:34:26	ga_ls8c_ard_3-2-0_093072_2021-10-07_final
2021-10-14 11:20:43	ga_ls8c_ard_3-2-0_110075_2021-10-14_final
2021-10-16 09:35:04	ga_ls8c_ard_3-2-0_092089_2021-10-16_final
2021-10-19 10:04:23	ga_ls8c_ard_3-2-0_097085_2021-10-19_final
2021-10-21 11:26:55	ga_ls8c_ard_3-2-0_111075_2021-10-21_final
2021-10-30 09:38:39	ga_ls8c_ard_3-2-0_094067_2021-10-30_final
2021-10-31 10:24:43	ga_ls8c_ard_3-2-0_101074_2021-10-31_final
2021-11-23 10:29:37	ga_ls8c_ard_3-2-0_102071_2021-11-23_final
2021-11-24 11:14:04	ga_ls8c_ard_3-2-0_109074_2021-11-24_final
2021-12-10 11:14:05	ga_ls8c_ard_3-2-1_109074_2021-12-10_final
2021-12-28 09:29:08	ga_ls8c_ard_3-2-1_091090_2021-12-27_final
2022-01-06 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-01-05_final
2022-01-06 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-01-06_final
2022-01-09 09:50:38	ga_ls8c_ard_3-2-1_095082_2022-01-09_final
2022-01-09 09:51:02	ga_ls8c_ard_3-2-1_095083_2022-01-09_final
2022-02-08 11:38:58	ga_ls8c_ard_3-2-1_113075_2022-02-08_final
2022-02-09 10:44:32	ga_ls8c_ard_3-2-1_104078_2022-02-09_final
2022-02-14 09:21:46	ga_ls8c_ard_3-2-1_091072_2022-02-13_final
2022-02-19 09:45:51	ga_ls8c_ard_3-2-1_094086_2022-02-19_final
2022-02-24 09:59:35	ga_ls8c_ard_3-2-1_097074_2022-02-24_final
2022-03-07 11:20:42	ga_ls8c_ard_3-2-1_110076_2022-03-07_final
2022-03-14 11:26:02	ga_ls8c_ard_3-2-1_111074_2022-03-14_final
2022-03-16 09:33:34	ga_ls8c_ard_3-2-1_093071_2022-03-16_final
2022-03-27 09:21:16	ga_ls8c_ard_3-2-1_090087_2022-03-26_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-27 11:50:34	ga_ls8c_ard_3-2-1_115074_2022-04-27_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-07 09:13:10	ga_ls8c_ard_3-2-1_089082_2022-05-06_final
2022-06-02 11:30:05	ga_ls8c_ard_3-2-1_111084_2022-06-02_final
2022-06-04 09:34:53	ga_ls8c_ard_3-2-1_093074_2022-06-04_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-09 09:52:17	ga_ls8c_ard_3-2-1_096071_2022-06-09_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-19 10:30:40	ga_ls8c_ard_3-2-1_102074_2022-06-19_final
2022-07-06 09:39:05	ga_ls8c_ard_3-2-1_093084_2022-07-06_final
2022-07-06 11:16:46	ga_ls8c_ard_3-2-1_109081_2022-07-06_final
2022-07-22 09:39:56	ga_ls8c_ard_3-2-1_093086_2022-07-22_final
2022-07-26 09:10:29	ga_ls8c_ard_3-2-1_089074_2022-07-25_final
2022-08-12 09:52:18	ga_ls8c_ard_3-2-1_096070_2022-08-12_final
2022-08-26 11:47:10	ga_ls8c_ard_3-2-1_114079_2022-08-26_final
2022-09-23 10:32:19	ga_ls8c_ard_3-2-1_102077_2022-09-23_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-25 10:31:05	ga_ls8c_ard_3-2-1_102074_2022-10-25_final
2022-11-08 10:43:51	ga_ls8c_ard_3-2-1_104075_2022-11-08_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-11-27 11:14:41	ga_ls8c_ard_3-2-1_109075_2022-11-27_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-14 10:19:48	ga_ls8c_ard_3-2-1_100077_2022-12-14_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-18 09:55:02	ga_ls8c_ard_3-2-1_096077_2022-12-18_final
2022-12-23 11:52:23	ga_ls8c_ard_3-2-1_115077_2022-12-23_final
2022-12-31 11:03:23	ga_ls8c_ard_3-2-1_107078_2022-12-31_final
2023-01-15 11:58:06	ga_ls8c_ard_3-2-1_116076_2023-01-15_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-22 10:25:25	ga_ls8c_ard_3-2-1_101076_2023-01-22_final
2023-01-31 10:21:17	ga_ls8c_ard_3-2-1_100081_2023-01-31_final
2023-02-02 11:46:12	ga_ls8c_ard_3-2-1_114077_2023-02-02_final
2023-03-15 10:03:31	ga_ls8c_ard_3-2-1_097084_2023-03-15_final
2023-03-15 11:41:12	ga_ls8c_ard_3-2-1_113081_2023-03-15_final
2023-03-26 11:20:32	ga_ls8c_ard_3-2-1_110076_2023-03-26_final
2023-03-30 09:20:05	ga_ls8c_ard_3-2-1_090084_2023-03-29_final
2023-04-08 09:12:09	ga_ls8c_ard_3-2-1_089080_2023-04-07_final
2023-04-25 09:57:41	ga_ls8c_ard_3-2-1_096086_2023-04-25_final
2023-04-29 11:09:02	ga_ls8c_ard_3-2-1_108079_2023-04-29_final
2023-05-04 09:47:02	ga_ls8c_ard_3-2-1_095075_2023-05-04_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-18 11:40:54	ga_ls8c_ard_3-2-1_113082_2023-05-18_final
2023-06-03 09:57:17	ga_ls8c_ard_3-2-1_097070_2023-06-03_final
2023-06-03 11:40:34	ga_ls8c_ard_3-2-1_113081_2023-06-03_final
2023-06-07 11:15:06	ga_ls8c_ard_3-2-1_109079_2023-06-07_final
2023-06-10 10:08:45	ga_ls8c_ard_3-2-1_098083_2023-06-10_final
2023-06-25 11:00:29	ga_ls8c_ard_3-2-1_107073_2023-06-25_final
2023-07-08 10:31:20	ga_ls8c_ard_3-2-1_102077_2023-07-08_final
2023-07-16 09:43:07	ga_ls8c_ard_3-2-1_094080_2023-07-16_final
2023-07-21 11:40:56	ga_ls8c_ard_3-2-1_113081_2023-07-21_final
2023-07-25 11:12:42	ga_ls8c_ard_3-2-1_109072_2023-07-25_final
2023-08-02 10:24:08	ga_ls8c_ard_3-2-1_101074_2023-08-02_final
2023-08-06 11:40:42	ga_ls8c_ard_3-2-1_113080_2023-08-06_final
2023-08-12 09:22:45	ga_ls8c_ard_3-2-1_091075_2023-08-11_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-17 11:19:27	ga_ls8c_ard_3-2-1_110073_2023-08-17_final
2023-08-20 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-08-20_final
2023-09-05 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-09-05_final
2023-09-27 11:14:38	ga_ls8c_ard_3-2-1_109076_2023-09-27_final
2023-10-06 11:11:15	ga_ls8c_ard_3-2-1_108083_2023-10-06_final
2023-10-15 11:02:20	ga_ls8c_ard_3-2-1_107076_2023-10-15_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