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
2022-06-29 09:32:06	ga_ls8c_ard_3-2-1_092082_2022-06-29_final
2022-07-15 09:31:16	ga_ls8c_ard_3-2-1_092080_2022-07-15_final
2022-07-15 11:07:22	ga_ls8c_ard_3-2-1_108073_2022-07-15_final
2022-07-20 11:29:10	ga_ls8c_ard_3-2-1_111081_2022-07-20_final
2022-07-25 10:03:42	ga_ls8c_ard_3-2-1_098068_2022-07-25_final
2022-07-25 10:05:17	ga_ls8c_ard_3-2-1_098072_2022-07-25_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-08-09 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-08-09_final
2022-08-14 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-14_final
2022-08-17 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-08-17_final
2022-08-21 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-08-21_final
2022-08-25 11:05:06	ga_ls8c_ard_3-2-1_107082_2022-08-25_final
2022-09-01 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-09-01_final
2022-09-05 09:07:41	ga_ls8c_ard_3-2-1_088082_2022-09-04_final
2022-09-10 09:23:53	ga_ls8c_ard_3-2-1_091076_2022-09-09_final
2022-09-10 11:00:22	ga_ls8c_ard_3-2-1_107070_2022-09-10_final
2022-09-10 11:04:45	ga_ls8c_ard_3-2-1_107081_2022-09-10_final
2022-09-10 11:05:33	ga_ls8c_ard_3-2-1_107083_2022-09-10_final
2022-09-18 10:10:34	ga_ls8c_ard_3-2-1_099069_2022-09-18_final
2022-09-23 10:31:07	ga_ls8c_ard_3-2-1_102074_2022-09-23_final
2022-09-24 09:37:53	ga_ls8c_ard_3-2-1_093080_2022-09-24_final
2022-09-27 10:05:12	ga_ls8c_ard_3-2-1_098071_2022-09-27_final
2022-09-29 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-09-29_final
2022-09-29 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-09-29_final
2022-10-11 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-10-11_final
2022-10-15 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-10-15_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-17 11:18:51	ga_ls8c_ard_3-2-1_110070_2022-10-17_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-10-30 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-10-30_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-09 09:51:25	ga_ls8c_ard_3-2-1_095083_2022-11-09_final
2022-11-15 09:10:40	ga_ls8c_ard_3-2-1_089074_2022-11-14_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-19 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-11-19_final
2022-11-20 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-11-20_final
2022-11-21 10:16:03	ga_ls8c_ard_3-2-1_099083_2022-11-21_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-29 11:00:20	ga_ls8c_ard_3-2-1_107070_2022-11-29_final
2022-12-06 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-12-06_final
2022-12-09 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-12-09_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-17 09:12:11	ga_ls8c_ard_3-2-1_089078_2022-12-16_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-10 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-10_final
2023-01-11 10:42:24	ga_ls8c_ard_3-2-1_104072_2023-01-11_final
2023-01-16 09:27:10	ga_ls8c_ard_3-2-1_091085_2023-01-15_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-24 10:16:16	ga_ls8c_ard_3-2-1_099084_2023-01-24_final
2023-01-26 11:40:49	ga_ls8c_ard_3-2-1_113079_2023-01-26_final
2023-01-29 10:30:03	ga_ls8c_ard_3-2-1_102072_2023-01-29_final
2023-01-30 09:40:01	ga_ls8c_ard_3-2-1_093086_2023-01-30_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-04 11:36:38	ga_ls8c_ard_3-2-1_112084_2023-02-04_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-15 09:40:18	ga_ls8c_ard_3-2-1_093087_2023-02-15_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-20 11:32:02	ga_ls8c_ard_3-2-1_112073_2023-02-20_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-03 11:13:22	ga_ls8c_ard_3-2-1_109073_2023-03-03_final
2023-03-08 09:51:46	ga_ls8c_ard_3-2-1_096070_2023-03-08_final
2023-03-09 10:34:13	ga_ls8c_ard_3-2-1_103068_2023-03-09_final
2023-03-10 11:18:17	ga_ls8c_ard_3-2-1_110070_2023-03-10_final
2023-03-18 10:28:00	ga_ls8c_ard_3-2-1_102068_2023-03-18_final
2023-03-18 10:28:24	ga_ls8c_ard_3-2-1_102069_2023-03-18_final
2023-03-21 09:28:45	ga_ls8c_ard_3-2-1_091090_2023-03-20_final
2023-04-06 09:21:46	ga_ls8c_ard_3-2-1_091073_2023-04-05_final
2023-05-03 10:41:53	ga_ls8c_ard_3-2-1_104073_2023-05-03_final
2023-05-06 09:33:03	ga_ls8c_ard_3-2-1_093071_2023-05-06_final
2023-05-06 11:17:08	ga_ls8c_ard_3-2-1_109084_2023-05-06_final
2023-05-14 10:27:09	ga_ls8c_ard_3-2-1_101083_2023-05-14_final
2023-05-20 11:24:10	ga_ls8c_ard_3-2-1_111071_2023-05-20_final
2023-05-29 11:17:37	ga_ls8c_ard_3-2-1_110070_2023-05-29_final
2023-06-02 09:20:48	ga_ls8c_ard_3-2-1_090087_2023-06-01_final
2023-06-30 09:43:48	ga_ls8c_ard_3-2-1_094082_2023-06-30_final
2023-07-11 09:26:34	ga_ls8c_ard_3-2-1_091085_2023-07-10_final
2023-07-15 10:37:09	ga_ls8c_ard_3-2-1_103076_2023-07-15_final
2023-07-23 09:46:32	ga_ls8c_ard_3-2-1_095073_2023-07-23_final
2023-07-23 09:47:20	ga_ls8c_ard_3-2-1_095075_2023-07-23_final
2023-07-27 11:01:09	ga_ls8c_ard_3-2-1_107074_2023-07-27_final
2023-08-03 09:34:54	ga_ls8c_ard_3-2-1_092090_2023-08-03_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-10 11:13:11	ga_ls8c_ard_3-2-1_109073_2023-08-10_final
2023-08-14 09:16:00	ga_ls8c_ard_3-2-1_089089_2023-08-13_final
2023-08-14 10:48:54	ga_ls8c_ard_3-2-1_105074_2023-08-14_final
2023-08-17 11:18:15	ga_ls8c_ard_3-2-1_110070_2023-08-17_final
2023-08-22 09:58:21	ga_ls8c_ard_3-2-1_097071_2023-08-22_final
2023-08-22 11:38:26	ga_ls8c_ard_3-2-1_113074_2023-08-22_final
2023-09-05 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-09-05_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-13 09:23:19	ga_ls8c_ard_3-2-1_091076_2023-09-12_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