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
2021-05-03 10:02:04	ga_ls8c_ard_3-2-1_098066_2021-05-03_final
2022-02-19 11:24:20	ga_ls8c_ard_3-2-1_110085_2022-02-19_final
2022-02-22 10:13:33	ga_ls8c_ard_3-2-1_099078_2022-02-22_final
2022-02-26 09:50:01	ga_ls8c_ard_3-2-1_095081_2022-02-26_final
2022-03-11 09:22:16	ga_ls8c_ard_3-2-1_090089_2022-03-10_final
2022-03-16 11:14:27	ga_ls8c_ard_3-2-1_109076_2022-03-16_final
2022-03-22 10:37:42	ga_ls8c_ard_3-2-1_103077_2022-03-22_final
2022-03-30 08:10:27	ga_ls8c_ard_3-2-1_079080_2022-03-29_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-06 11:32:02	ga_ls8c_ard_3-2-1_112074_2022-04-06_final
2022-05-26 09:40:09	ga_ls8c_ard_3-2-1_094072_2022-05-26_final
2022-05-30 09:22:39	ga_ls8c_ard_3-2-1_090090_2022-05-29_final
2022-06-11 09:39:57	ga_ls8c_ard_3-2-1_094071_2022-06-11_final
2022-06-17 10:46:12	ga_ls8c_ard_3-2-1_104082_2022-06-17_final
2022-06-24 09:14:20	ga_ls8c_ard_3-2-1_089084_2022-06-23_final
2022-06-29 09:33:18	ga_ls8c_ard_3-2-1_092085_2022-06-29_final
2022-07-08 11:05:36	ga_ls8c_ard_3-2-1_107084_2022-07-08_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-07-18 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-18_final
2022-07-18 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-18_final
2022-07-20 09:46:17	ga_ls8c_ard_3-2-1_095071_2022-07-20_final
2022-07-22 11:14:02	ga_ls8c_ard_3-2-1_109074_2022-07-22_final
2022-07-23 10:20:49	ga_ls8c_ard_3-2-1_100080_2022-07-23_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-08-03 09:58:24	ga_ls8c_ard_3-2-1_097070_2022-08-03_final
2022-08-03 11:40:29	ga_ls8c_ard_3-2-1_113078_2022-08-03_final
2022-08-05 11:24:09	ga_ls8c_ard_3-2-1_111068_2022-08-05_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-12 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-08-12_final
2022-08-17 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-08-17_final
2022-08-26 10:05:29	ga_ls8c_ard_3-2-1_098072_2022-08-26_final
2022-08-31 10:26:01	ga_ls8c_ard_3-2-1_101077_2022-08-31_final
2022-09-26 09:23:32	ga_ls8c_ard_3-2-1_091075_2022-09-25_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-10-09 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-10-09_final
2022-10-15 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-10-15_final
2022-10-20 10:16:05	ga_ls8c_ard_3-2-1_099083_2022-10-20_final
2022-10-26 11:15:09	ga_ls8c_ard_3-2-1_109076_2022-10-26_final
2022-11-05 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-11-05_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-11 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-12-11_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-13 11:15:50	ga_ls8c_ard_3-2-1_109078_2022-12-13_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-25 11:40:02	ga_ls8c_ard_3-2-1_113077_2022-12-25_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-25 10:55:57	ga_ls8c_ard_3-2-1_106075_2023-01-25_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-13 11:27:58	ga_ls8c_ard_3-2-1_111078_2023-02-13_final
2023-02-17 09:21:55	ga_ls8c_ard_3-2-1_091072_2023-02-16_final
2023-03-01 09:46:28	ga_ls8c_ard_3-2-1_095072_2023-03-01_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_final
2023-03-12 09:30:38	ga_ls8c_ard_3-2-1_092079_2023-03-12_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-15 09:57:56	ga_ls8c_ard_3-2-1_097070_2023-03-15_final
2023-03-17 09:45:57	ga_ls8c_ard_3-2-1_095071_2023-03-17_final
2023-03-25 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-03-25_final
2023-04-01 09:06:54	ga_ls8c_ard_3-2-1_088082_2023-03-31_final
2023-04-02 11:25:51	ga_ls8c_ard_3-2-1_111074_2023-04-02_final
2023-04-02 11:26:15	ga_ls8c_ard_3-2-1_111075_2023-04-02_final
2023-04-06 09:24:57	ga_ls8c_ard_3-2-1_091081_2023-04-05_final
2023-04-10 10:39:01	ga_ls8c_ard_3-2-1_103081_2023-04-10_final
2023-04-24 09:13:14	ga_ls8c_ard_3-2-1_089083_2023-04-23_final
2023-04-28 10:24:35	ga_ls8c_ard_3-2-1_101076_2023-04-28_final
2023-05-09 10:07:06	ga_ls8c_ard_3-2-1_098079_2023-05-09_final
2023-05-09 11:45:59	ga_ls8c_ard_3-2-1_114079_2023-05-09_final
2023-05-14 10:21:58	ga_ls8c_ard_3-2-1_101070_2023-05-14_final
2023-05-18 10:01:13	ga_ls8c_ard_3-2-1_097080_2023-05-18_final
2023-05-25 10:03:03	ga_ls8c_ard_3-2-1_098069_2023-05-25_final
2023-06-02 09:20:24	ga_ls8c_ard_3-2-1_090086_2023-06-01_final
2023-06-03 11:40:10	ga_ls8c_ard_3-2-1_113080_2023-06-03_final
2023-06-21 09:49:28	ga_ls8c_ard_3-2-1_095081_2023-06-21_final
2023-07-13 10:45:55	ga_ls8c_ard_3-2-1_105067_2023-07-13_final
2023-07-18 09:33:33	ga_ls8c_ard_3-2-1_092087_2023-07-18_final
2023-07-18 11:08:03	ga_ls8c_ard_3-2-1_108076_2023-07-18_final
2023-08-19 11:05:31	ga_ls8c_ard_3-2-1_108069_2023-08-19_final
2023-08-28 11:01:46	ga_ls8c_ard_3-2-1_107075_2023-08-28_final
2023-09-19 10:25:57	ga_ls8c_ard_3-2-1_101078_2023-09-19_final
2023-09-21 10:09:36	ga_ls8c_ard_3-2-1_099068_2023-09-21_final
2023-10-04 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-04_final
2023-10-08 09:16:50	ga_ls8c_ard_3-2-1_090075_2023-10-07_final
2023-10-08 09:18:02	ga_ls8c_ard_3-2-1_090078_2023-10-07_final
2023-10-16 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-10-16_final
2023-10-31 09:27:29	ga_ls8c_ard_3-2-1_091086_2023-10-30_final
2023-11-02 10:46:49	ga_ls8c_ard_3-2-1_105068_2023-11-02_final
2023-11-05 09:41:13	ga_ls8c_ard_3-2-1_094074_2023-11-05_final
2023-11-07 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-11-07_final
2023-11-11 10:42:58	ga_ls8c_ard_3-2-1_104074_2023-11-11_final
2023-12-01 10:19:06	ga_ls8c_ard_3-2-1_100076_2023-12-01_final
2023-12-02 11:05:08	ga_ls8c_ard_3-2-1_107083_2023-12-02_final
2023-12-17 11:58:47	ga_ls8c_ard_3-2-1_116078_2023-12-17_final
2023-12-19 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-12-19_final
2023-12-20 09:15:56	ga_ls8c_ard_3-2-1_089088_2023-12-19_final
2024-01-03 09:26:34	ga_ls8c_ard_3-2-1_091084_2024-01-02_final
2024-01-05 10:50:16	ga_ls8c_ard_3-2-1_105077_2024-01-05_final
2024-01-15 11:25:01	ga_ls8c_ard_3-2-1_111071_2024-01-15_final
2024-01-31 11:26:56	ga_ls8c_ard_3-2-1_111076_2024-01-31_final
2024-02-04 09:28:33	ga_ls8c_ard_3-2-1_091089_2024-02-03_final
2024-02-09 11:19:37	ga_ls8c_ard_3-2-1_110073_2024-02-09_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