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
2022-03-05 11:35:28	ga_ls8c_ard_3-2-1_112082_2022-03-05_final
2022-03-13 10:40:47	ga_ls8c_ard_3-2-1_104069_2022-03-13_final
2022-03-24 10:27:42	ga_ls8c_ard_3-2-1_101083_2022-03-24_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-17 09:36:16	ga_ls8c_ard_3-2-1_093078_2022-04-17_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-02 10:32:39	ga_ls8c_ard_3-2-1_102080_2022-05-02_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-31 11:41:13	ga_ls8c_ard_3-2-1_113081_2022-05-31_final
2022-06-02 11:27:41	ga_ls8c_ard_3-2-1_111078_2022-06-02_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-21 10:21:31	ga_ls8c_ard_3-2-1_100082_2022-06-21_final
2022-06-22 09:23:54	ga_ls8c_ard_3-2-1_091077_2022-06-21_final
2022-06-25 11:35:17	ga_ls8c_ard_3-2-1_112081_2022-06-25_final
2022-06-27 11:23:44	ga_ls8c_ard_3-2-1_110083_2022-06-27_final
2022-07-12 10:38:52	ga_ls8c_ard_3-2-1_103079_2022-07-12_final
2022-07-15 09:30:52	ga_ls8c_ard_3-2-1_092079_2022-07-15_final
2022-07-18 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-18_final
2022-07-18 11:40:42	ga_ls8c_ard_3-2-1_113079_2022-07-18_final
2022-07-26 09:16:28	ga_ls8c_ard_3-2-1_089089_2022-07-25_final
2022-07-28 10:38:37	ga_ls8c_ard_3-2-1_103078_2022-07-28_final
2022-07-31 11:10:45	ga_ls8c_ard_3-2-1_108081_2022-07-31_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-08-01 10:13:09	ga_ls8c_ard_3-2-1_099076_2022-08-01_final
2022-08-11 10:52:18	ga_ls8c_ard_3-2-1_105081_2022-08-11_final
2022-08-23 11:16:39	ga_ls8c_ard_3-2-1_109080_2022-08-23_final
2022-08-26 10:08:40	ga_ls8c_ard_3-2-1_098080_2022-08-26_final
2022-08-28 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-08-28_final
2022-09-18 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-09-18_final
2022-09-27 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-09-27_final
2022-09-27 11:47:40	ga_ls8c_ard_3-2-1_114080_2022-09-27_final
2022-10-03 09:31:41	ga_ls8c_ard_3-2-1_092080_2022-10-03_final
2022-10-20 10:12:30	ga_ls8c_ard_3-2-1_099074_2022-10-20_final
2022-10-23 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-23_final
2022-10-24 11:29:53	ga_ls8c_ard_3-2-1_111082_2022-10-24_final
2022-10-26 11:13:09	ga_ls8c_ard_3-2-1_109071_2022-10-26_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-12-05 10:24:26	ga_ls8c_ard_3-2-1_101073_2022-12-05_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-01-21 11:21:25	ga_ls8c_ard_3-2-1_110077_2023-01-21_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-02-08 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-02-08_final
2023-02-10 10:56:19	ga_ls8c_ard_3-2-1_106076_2023-02-10_final
2023-02-24 09:31:56	ga_ls8c_ard_3-2-1_092082_2023-02-24_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-24 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-03-24_final
2023-04-14 10:12:17	ga_ls8c_ard_3-2-1_099076_2023-04-14_final
2023-04-15 10:57:08	ga_ls8c_ard_3-2-1_106080_2023-04-15_final
2023-04-18 11:26:25	ga_ls8c_ard_3-2-1_111076_2023-04-18_final
2023-04-27 11:18:13	ga_ls8c_ard_3-2-1_110071_2023-04-27_final
2023-05-07 11:57:11	ga_ls8c_ard_3-2-1_116076_2023-05-07_final
2023-05-10 10:51:08	ga_ls8c_ard_3-2-1_105081_2023-05-10_final
2023-05-13 11:20:24	ga_ls8c_ard_3-2-1_110077_2023-05-13_final
2023-05-14 10:23:10	ga_ls8c_ard_3-2-1_101073_2023-05-14_final
2023-06-04 10:40:34	ga_ls8c_ard_3-2-1_104070_2023-06-04_final
2023-06-11 09:12:21	ga_ls8c_ard_3-2-1_089081_2023-06-10_final
2023-07-08 10:28:57	ga_ls8c_ard_3-2-1_102071_2023-07-08_final
2023-07-12 11:45:55	ga_ls8c_ard_3-2-1_114078_2023-07-12_final
2023-07-25 09:37:24	ga_ls8c_ard_3-2-1_093081_2023-07-25_final
2023-07-25 11:11:54	ga_ls8c_ard_3-2-1_109070_2023-07-25_final
2023-07-25 11:17:05	ga_ls8c_ard_3-2-1_109083_2023-07-25_final
2023-09-01 10:38:14	ga_ls8c_ard_3-2-1_103078_2023-09-01_final
2023-09-15 09:16:34	ga_ls8c_ard_3-2-1_089090_2023-09-14_final
2023-09-17 10:34:19	ga_ls8c_ard_3-2-1_103068_2023-09-17_final
2023-09-27 11:15:02	ga_ls8c_ard_3-2-1_109077_2023-09-27_final
2023-10-13 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-10-13_final
2023-10-27 09:46:13	ga_ls8c_ard_3-2-1_095071_2023-10-27_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-11-02 10:48:25	ga_ls8c_ard_3-2-1_105072_2023-11-02_final
2023-11-20 10:36:53	ga_ls8c_ard_3-2-1_103074_2023-11-20_final
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_final
2023-11-24 11:51:03	ga_ls8c_ard_3-2-1_115074_2023-11-24_final
2023-11-26 11:41:53	ga_ls8c_ard_3-2-1_113082_2023-11-26_final
2023-11-29 10:29:53	ga_ls8c_ard_3-2-1_102072_2023-11-29_final
2023-11-30 09:35:03	ga_ls8c_ard_3-2-1_093074_2023-11-30_final
2023-12-03 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-12-03_final
2023-12-21 11:32:53	ga_ls8c_ard_3-2-1_112075_2023-12-21_final
2023-12-31 10:31:24	ga_ls8c_ard_3-2-1_102076_2023-12-31_final
2024-01-04 11:47:06	ga_ls8c_ard_3-2-1_114080_2024-01-04_final
2024-01-06 09:54:39	ga_ls8c_ard_3-2-1_096077_2024-01-06_final
2024-01-06 11:35:08	ga_ls8c_ard_3-2-1_112081_2024-01-06_final
2024-01-07 10:36:44	ga_ls8c_ard_3-2-1_103074_2024-01-07_final
2024-01-28 10:58:47	ga_ls8c_ard_3-2-1_106083_2024-01-28_final
2024-02-04 11:01:03	ga_ls8c_ard_3-2-1_107073_2024-02-04_final
2024-02-08 10:37:33	ga_ls8c_ard_3-2-1_103076_2024-02-08_final
2024-02-11 11:10:50	ga_ls8c_ard_3-2-1_108082_2024-02-11_final
2024-02-28 10:10:44	ga_ls8c_ard_3-2-1_099071_2024-02-28_final
2024-02-29 10:57:34	ga_ls8c_ard_3-2-1_106080_2024-02-29_final
2024-03-09 10:51:15	ga_ls8c_ard_3-2-1_105080_2024-03-09_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