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
2022-03-27 09:22:52	ga_ls8c_ard_3-2-1_090091_2022-03-26_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2023-01-02 10:48:37	ga_ls8c_ard_3-2-1_105072_2023-01-02_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-08 10:15:07	ga_ls8c_ard_3-2-1_099081_2023-01-08_final
2023-01-16 11:01:40	ga_ls8c_ard_3-2-1_107074_2023-01-16_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-01-18 10:48:29	ga_ls8c_ard_3-2-1_105072_2023-01-18_final
2023-01-30 09:35:37	ga_ls8c_ard_3-2-1_093075_2023-01-30_final
2023-02-03 09:13:42	ga_ls8c_ard_3-2-1_089082_2023-02-02_final
2023-02-04 09:53:46	ga_ls8c_ard_3-2-1_096074_2023-02-04_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-11 11:42:21	ga_ls8c_ard_3-2-1_113083_2023-02-11_final
2023-02-18 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-02-18_final
2023-02-26 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-02-25_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-19 11:17:14	ga_ls8c_ard_3-2-1_109083_2023-03-19_final
2023-03-21 11:04:50	ga_ls8c_ard_3-2-1_107083_2023-03-21_final
2023-03-27 10:25:18	ga_ls8c_ard_3-2-1_101077_2023-03-27_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-04-06 09:27:21	ga_ls8c_ard_3-2-1_091087_2023-04-05_final
2023-04-08 10:49:02	ga_ls8c_ard_3-2-1_105075_2023-04-08_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-14 10:15:52	ga_ls8c_ard_3-2-1_099085_2023-04-14_final
2023-04-17 09:06:16	ga_ls8c_ard_3-2-1_088081_2023-04-16_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-13 11:18:24	ga_ls8c_ard_3-2-1_110072_2023-05-13_final
2023-05-15 09:32:20	ga_ls8c_ard_3-2-1_092085_2023-05-15_final
2023-05-15 09:32:44	ga_ls8c_ard_3-2-1_092086_2023-05-15_final
2023-05-16 10:10:23	ga_ls8c_ard_3-2-1_099072_2023-05-16_final
2023-05-16 10:15:11	ga_ls8c_ard_3-2-1_099084_2023-05-16_final
2023-06-17 10:13:47	ga_ls8c_ard_3-2-1_099080_2023-06-17_final
2023-06-25 09:25:59	ga_ls8c_ard_3-2-1_091084_2023-06-24_final
2023-06-26 10:06:28	ga_ls8c_ard_3-2-1_098077_2023-06-26_final
2023-07-03 10:09:57	ga_ls8c_ard_3-2-1_099070_2023-07-03_final
2023-07-10 11:57:05	ga_ls8c_ard_3-2-1_116075_2023-07-10_final
2023-07-10 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-07-10_final
2023-07-16 11:20:01	ga_ls8c_ard_3-2-1_110075_2023-07-16_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-07-28 10:07:32	ga_ls8c_ard_3-2-1_098079_2023-07-28_final
2023-08-06 11:42:18	ga_ls8c_ard_3-2-1_113084_2023-08-06_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-19 11:07:06	ga_ls8c_ard_3-2-1_108073_2023-08-19_final
2023-08-21 10:53:10	ga_ls8c_ard_3-2-1_106069_2023-08-21_final
2023-08-21 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-08-21_final
2023-08-27 10:17:18	ga_ls8c_ard_3-2-1_100072_2023-08-27_final
2023-09-02 11:18:18	ga_ls8c_ard_3-2-1_110070_2023-09-02_final
2023-09-02 11:19:54	ga_ls8c_ard_3-2-1_110074_2023-09-02_final
2023-09-22 10:54:27	ga_ls8c_ard_3-2-1_106072_2023-09-22_final
2023-10-08 09:18:02	ga_ls8c_ard_3-2-1_090078_2023-10-07_final
2023-10-09 11:42:11	ga_ls8c_ard_3-2-1_113083_2023-10-09_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_final
2023-10-16 10:10:18	ga_ls8c_ard_3-2-1_098085_2023-10-16_final
2023-10-20 09:40:45	ga_ls8c_ard_3-2-1_094073_2023-10-20_final
2023-10-20 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-10-20_final
2023-10-22 11:07:18	ga_ls8c_ard_3-2-1_108073_2023-10-22_final
2023-10-29 09:40:15	ga_ls8c_ard_3-2-1_093087_2023-10-29_final
2023-10-30 10:19:07	ga_ls8c_ard_3-2-1_100076_2023-10-30_final
2023-10-31 09:27:53	ga_ls8c_ard_3-2-1_091087_2023-10-30_final
2023-10-31 11:00:23	ga_ls8c_ard_3-2-1_107071_2023-10-31_final
2023-11-02 09:13:32	ga_ls8c_ard_3-2-1_089082_2023-11-01_final
2023-11-03 09:57:35	ga_ls8c_ard_3-2-1_096084_2023-11-03_final
2023-11-07 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-11-07_final
2023-11-12 09:52:09	ga_ls8c_ard_3-2-1_095086_2023-11-12_final
2023-11-16 09:28:40	ga_ls8c_ard_3-2-1_091089_2023-11-15_final
2023-11-18 09:13:08	ga_ls8c_ard_3-2-1_089081_2023-11-17_final
2023-11-19 11:36:05	ga_ls8c_ard_3-2-1_112083_2023-11-19_final
2023-11-21 11:20:57	ga_ls8c_ard_3-2-1_110076_2023-11-21_final
2023-11-26 09:58:13	ga_ls8c_ard_3-2-1_097070_2023-11-26_final
2023-11-26 10:04:12	ga_ls8c_ard_3-2-1_097085_2023-11-26_final
2023-12-03 10:03:55	ga_ls8c_ard_3-2-1_098069_2023-12-03_final
2023-12-08 10:23:35	ga_ls8c_ard_3-2-1_101072_2023-12-08_final
2023-12-11 10:55:20	ga_ls8c_ard_3-2-1_106074_2023-12-11_final
2023-12-12 09:57:43	ga_ls8c_ard_3-2-1_097069_2023-12-12_final
2023-12-21 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-12-21_final
2023-12-28 09:57:45	ga_ls8c_ard_3-2-1_097069_2023-12-28_final
2023-12-28 11:38:38	ga_ls8c_ard_3-2-1_113074_2023-12-28_final
2024-01-02 10:19:01	ga_ls8c_ard_3-2-1_100076_2024-01-02_final
2024-01-28 09:22:42	ga_ls8c_ard_3-2-1_090090_2024-01-27_final
2024-01-30 10:41:16	ga_ls8c_ard_3-2-1_104070_2024-01-30_final
2024-02-06 09:12:13	ga_ls8c_ard_3-2-1_089079_2024-02-05_final
2024-02-10 10:25:35	ga_ls8c_ard_3-2-1_101077_2024-02-10_final
2024-02-20 10:59:50	ga_ls8c_ard_3-2-1_107070_2024-02-20_final
2024-02-22 09:12:58	ga_ls8c_ard_3-2-1_089081_2024-02-21_final
2024-02-26 10:27:54	ga_ls8c_ard_3-2-1_101083_2024-02-26_final
2024-02-29 09:22:16	ga_ls8c_ard_3-2-1_090089_2024-02-28_final
2024-03-02 10:41:35	ga_ls8c_ard_3-2-1_104071_2024-03-02_final
2024-03-05 11:12:02	ga_ls8c_ard_3-2-1_109070_2024-03-05_final
2024-03-19 11:25:04	ga_ls8c_ard_3-2-1_111072_2024-03-19_nrt
2024-03-19 11:25:52	ga_ls8c_ard_3-2-1_111074_2024-03-19_nrt
2024-04-02 09:57:35	ga_ls8c_ard_3-2-1_097070_2024-04-02_nrt

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