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
2022-08-25 11:00:42	ga_ls8c_ard_3-2-1_107071_2022-08-25_final
2022-08-26 11:47:33	ga_ls8c_ard_3-2-1_114080_2022-08-26_final
2022-09-15 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-09-15_final
2022-09-23 10:29:07	ga_ls8c_ard_3-2-1_102069_2022-09-23_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-09-26 09:23:08	ga_ls8c_ard_3-2-1_091074_2022-09-25_final
2022-09-26 11:00:49	ga_ls8c_ard_3-2-1_107071_2022-09-26_final
2022-09-29 09:57:37	ga_ls8c_ard_3-2-1_096083_2022-09-29_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-17 11:23:14	ga_ls8c_ard_3-2-1_110081_2022-10-17_final
2022-10-24 09:50:36	ga_ls8c_ard_3-2-1_095081_2022-10-24_final
2022-10-26 09:37:27	ga_ls8c_ard_3-2-1_093079_2022-10-26_final
2022-11-01 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-11-01_final
2022-11-11 11:17:07	ga_ls8c_ard_3-2-1_109081_2022-11-11_final
2022-11-19 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-11-19_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-11-21 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-11-21_final
2022-11-21 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-11-21_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-31 09:29:17	ga_ls8c_ard_3-2-1_091090_2022-12-30_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-11 10:42:00	ga_ls8c_ard_3-2-1_104071_2023-01-11_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-14 11:17:39	ga_ls8c_ard_3-2-1_109083_2023-01-14_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-24 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-01-24_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-19 10:52:23	ga_ls8c_ard_3-2-1_105082_2023-02-19_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-03-05 11:05:23	ga_ls8c_ard_3-2-1_107084_2023-03-05_final
2023-03-11 10:25:51	ga_ls8c_ard_3-2-1_101078_2023-03-11_final
2023-03-28 09:30:28	ga_ls8c_ard_3-2-1_092079_2023-03-28_final
2023-04-01 09:07:18	ga_ls8c_ard_3-2-1_088083_2023-03-31_final
2023-04-11 11:19:52	ga_ls8c_ard_3-2-1_110075_2023-04-11_final
2023-04-18 09:49:55	ga_ls8c_ard_3-2-1_095082_2023-04-18_final
2023-04-21 10:16:49	ga_ls8c_ard_3-2-1_100072_2023-04-21_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-05-01 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-05-01_final
2023-05-08 09:25:51	ga_ls8c_ard_3-2-1_091084_2023-05-07_final
2023-05-17 09:20:21	ga_ls8c_ard_3-2-1_090086_2023-05-16_final
2023-05-17 10:52:51	ga_ls8c_ard_3-2-1_106070_2023-05-17_final
2023-05-25 10:09:26	ga_ls8c_ard_3-2-1_098085_2023-05-25_final
2023-05-26 09:13:01	ga_ls8c_ard_3-2-1_089083_2023-05-25_final
2023-06-01 10:08:50	ga_ls8c_ard_3-2-1_099068_2023-06-01_final
2023-06-02 10:54:29	ga_ls8c_ard_3-2-1_106074_2023-06-02_final
2023-06-09 09:21:05	ga_ls8c_ard_3-2-1_091072_2023-06-08_final
2023-06-11 09:13:32	ga_ls8c_ard_3-2-1_089084_2023-06-10_final
2023-06-11 10:51:14	ga_ls8c_ard_3-2-1_105081_2023-06-11_final
2023-06-18 10:53:03	ga_ls8c_ard_3-2-1_106070_2023-06-18_final
2023-06-24 10:16:48	ga_ls8c_ard_3-2-1_100072_2023-06-24_final
2023-06-26 10:04:04	ga_ls8c_ard_3-2-1_098071_2023-06-26_final
2023-07-02 09:31:28	ga_ls8c_ard_3-2-1_092082_2023-07-02_final
2023-07-12 10:04:39	ga_ls8c_ard_3-2-1_098072_2023-07-12_final
2023-07-13 10:46:43	ga_ls8c_ard_3-2-1_105069_2023-07-13_final
2023-07-14 11:31:34	ga_ls8c_ard_3-2-1_112073_2023-07-14_final
2023-07-16 11:18:25	ga_ls8c_ard_3-2-1_110071_2023-07-16_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-07-20 10:54:53	ga_ls8c_ard_3-2-1_106074_2023-07-20_final
2023-07-27 09:23:28	ga_ls8c_ard_3-2-1_091077_2023-07-26_final
2023-07-27 09:26:40	ga_ls8c_ard_3-2-1_091085_2023-07-26_final
2023-07-27 10:59:58	ga_ls8c_ard_3-2-1_107071_2023-07-27_final
2023-07-29 09:12:44	ga_ls8c_ard_3-2-1_089081_2023-07-28_final
2023-08-01 09:46:03	ga_ls8c_ard_3-2-1_094087_2023-08-01_final
2023-08-13 11:46:30	ga_ls8c_ard_3-2-1_114079_2023-08-13_final
2023-08-20 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-08-20_final
2023-08-24 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-08-24_final
2023-08-29 10:07:44	ga_ls8c_ard_3-2-1_098079_2023-08-29_final
2023-09-02 09:45:00	ga_ls8c_ard_3-2-1_094084_2023-09-02_final
2023-09-04 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-09-04_final
2023-09-11 11:11:45	ga_ls8c_ard_3-2-1_109069_2023-09-11_final
2023-09-14 10:04:12	ga_ls8c_ard_3-2-1_098070_2023-09-14_final
2023-09-18 11:23:58	ga_ls8c_ard_3-2-1_110084_2023-09-18_final
2023-09-25 09:51:41	ga_ls8c_ard_3-2-1_095085_2023-09-25_final
2023-09-28 11:57:54	ga_ls8c_ard_3-2-1_116076_2023-09-28_final
2023-09-29 09:23:48	ga_ls8c_ard_3-2-1_091077_2023-09-28_final
2023-09-30 10:05:04	ga_ls8c_ard_3-2-1_098072_2023-09-30_final
2023-10-05 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-10-05_final
2023-10-11 09:47:22	ga_ls8c_ard_3-2-1_095074_2023-10-11_final
2023-10-23 11:52:59	ga_ls8c_ard_3-2-1_115079_2023-10-23_final
2023-10-24 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-10-23_final
2023-10-25 09:58:33	ga_ls8c_ard_3-2-1_097071_2023-10-25_final
2023-11-02 10:52:01	ga_ls8c_ard_3-2-1_105081_2023-11-02_final
2023-11-07 09:33:13	ga_ls8c_ard_3-2-1_092085_2023-11-07_final
2023-11-08 10:16:28	ga_ls8c_ard_3-2-1_099085_2023-11-08_final
2023-11-13 10:28:14	ga_ls8c_ard_3-2-1_102068_2023-11-13_final
2023-11-17 10:05:09	ga_ls8c_ard_3-2-1_098072_2023-11-17_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_final
2023-11-19 09:52:49	ga_ls8c_ard_3-2-1_096072_2023-11-19_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