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
2022-03-04 09:14:07	ga_ls8c_ard_3-2-1_089084_2022-03-03_final
2022-03-08 10:27:28	ga_ls8c_ard_3-2-1_101082_2022-03-08_final
2022-03-31 10:33:00	ga_ls8c_ard_3-2-1_102081_2022-03-31_final
2022-04-08 11:19:42	ga_ls8c_ard_3-2-1_110074_2022-04-08_final
2022-04-14 10:45:27	ga_ls8c_ard_3-2-1_104081_2022-04-14_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-15 11:25:56	ga_ls8c_ard_3-2-1_111074_2022-04-15_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-04-24 11:19:42	ga_ls8c_ard_3-2-1_110074_2022-04-24_final
2022-04-26 09:33:38	ga_ls8c_ard_3-2-1_092087_2022-04-26_final
2022-05-03 11:13:32	ga_ls8c_ard_3-2-1_109074_2022-05-03_final
2022-05-07 10:49:40	ga_ls8c_ard_3-2-1_105076_2022-05-07_final
2022-05-17 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-05-17_final
2022-05-17 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-05-17_final
2022-05-28 09:33:46	ga_ls8c_ard_3-2-1_092087_2022-05-28_final
2022-05-31 10:03:32	ga_ls8c_ard_3-2-1_097084_2022-05-31_final
2022-06-02 09:47:12	ga_ls8c_ard_3-2-1_095074_2022-06-02_final
2022-06-16 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-06-16_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-27 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-06-27_final
2022-07-02 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-02_final
2022-07-06 11:14:22	ga_ls8c_ard_3-2-1_109075_2022-07-06_final
2022-07-13 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-07-13_final
2022-07-15 11:08:57	ga_ls8c_ard_3-2-1_108077_2022-07-15_final
2022-07-22 11:14:02	ga_ls8c_ard_3-2-1_109074_2022-07-22_final
2022-07-26 10:51:45	ga_ls8c_ard_3-2-1_105080_2022-07-26_final
2022-07-30 10:25:53	ga_ls8c_ard_3-2-1_101077_2022-07-30_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-02 10:58:25	ga_ls8c_ard_3-2-1_106081_2022-08-02_final
2022-08-06 10:28:32	ga_ls8c_ard_3-2-1_102068_2022-08-06_final
2022-08-07 09:38:07	ga_ls8c_ard_3-2-1_093081_2022-08-07_final
2022-08-11 10:47:07	ga_ls8c_ard_3-2-1_105068_2022-08-11_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-17 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-08-17_final
2022-08-18 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-08-18_final
2022-08-18 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-08-18_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-21 11:24:38	ga_ls8c_ard_3-2-1_111069_2022-08-21_final
2022-08-23 09:37:22	ga_ls8c_ard_3-2-1_093079_2022-08-23_final
2022-08-28 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-08-28_final
2022-09-07 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-09-07_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-10 11:03:33	ga_ls8c_ard_3-2-1_107078_2022-09-10_final
2022-09-14 10:39:16	ga_ls8c_ard_3-2-1_103079_2022-09-14_final
2022-09-15 09:43:39	ga_ls8c_ard_3-2-1_094079_2022-09-15_final
2022-09-19 10:56:38	ga_ls8c_ard_3-2-1_106076_2022-09-19_final
2022-09-26 09:27:31	ga_ls8c_ard_3-2-1_091085_2022-09-25_final
2022-10-01 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-10-01_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-12 09:27:23	ga_ls8c_ard_3-2-1_091085_2022-10-11_final
2022-10-15 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-10-15_final
2022-10-17 09:45:57	ga_ls8c_ard_3-2-1_094085_2022-10-17_final
2022-10-21 09:22:04	ga_ls8c_ard_3-2-1_090087_2022-10-20_final
2022-11-04 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-11-04_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:42:40	ga_ls8c_ard_3-2-1_113083_2022-11-07_final
2022-11-09 11:29:54	ga_ls8c_ard_3-2-1_111082_2022-11-09_final
2022-11-20 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-11-19_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-12-01 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-12-01_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-08 09:22:50	ga_ls8c_ard_3-2-1_090089_2022-12-07_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-08 10:56:08	ga_ls8c_ard_3-2-1_106075_2022-12-08_final
2022-12-13 09:34:57	ga_ls8c_ard_3-2-1_093073_2022-12-13_final
2022-12-24 10:53:10	ga_ls8c_ard_3-2-1_106068_2022-12-24_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-16 11:03:16	ga_ls8c_ard_3-2-1_107078_2023-01-16_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-24 10:11:29	ga_ls8c_ard_3-2-1_099072_2023-01-24_final
2023-01-30 09:40:49	ga_ls8c_ard_3-2-1_093088_2023-01-30_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-05 09:26:54	ga_ls8c_ard_3-2-1_091085_2023-03-04_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-06 11:47:02	ga_ls8c_ard_3-2-1_114080_2023-03-06_final
2023-03-07 09:10:31	ga_ls8c_ard_3-2-1_089075_2023-03-06_final
2023-03-07 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-03-07_final
2023-03-09 10:39:01	ga_ls8c_ard_3-2-1_103080_2023-03-09_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-04-01 10:45:23	ga_ls8c_ard_3-2-1_104081_2023-04-01_final
2023-04-02 09:50:09	ga_ls8c_ard_3-2-1_095082_2023-04-02_final
2023-04-02 11:26:39	ga_ls8c_ard_3-2-1_111076_2023-04-02_final
2023-04-29 09:32:33	ga_ls8c_ard_3-2-1_092085_2023-04-29_final
2023-04-29 11:07:26	ga_ls8c_ard_3-2-1_108075_2023-04-29_final
2023-05-03 10:44:16	ga_ls8c_ard_3-2-1_104079_2023-05-03_final
2023-05-04 09:45:27	ga_ls8c_ard_3-2-1_095071_2023-05-04_final
2023-05-08 11:02:20	ga_ls8c_ard_3-2-1_107078_2023-05-08_final
2023-05-15 11:07:13	ga_ls8c_ard_3-2-1_108075_2023-05-15_final
2023-05-15 11:08:49	ga_ls8c_ard_3-2-1_108079_2023-05-15_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