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
2022-03-03 10:03:46	ga_ls8c_ard_3-2-1_098069_2022-03-03_final
2022-03-12 09:59:31	ga_ls8c_ard_3-2-1_097074_2022-03-12_final
2022-03-18 11:02:04	ga_ls8c_ard_3-2-1_107076_2022-03-18_final
2022-03-20 09:14:47	ga_ls8c_ard_3-2-1_089086_2022-03-19_final
2022-03-22 10:34:30	ga_ls8c_ard_3-2-1_103069_2022-03-22_final
2022-03-24 10:25:18	ga_ls8c_ard_3-2-1_101077_2022-03-24_final
2022-03-26 10:14:07	ga_ls8c_ard_3-2-1_099080_2022-03-26_final
2022-03-30 09:46:08	ga_ls8c_ard_3-2-1_095072_2022-03-30_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-08 11:23:41	ga_ls8c_ard_3-2-1_110084_2022-04-08_final
2022-04-22 09:52:24	ga_ls8c_ard_3-2-1_096072_2022-04-22_final
2022-05-16 10:40:22	ga_ls8c_ard_3-2-1_104068_2022-05-16_final
2022-05-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2022-05-17_final
2022-05-18 10:28:01	ga_ls8c_ard_3-2-1_102068_2022-05-18_final
2022-05-22 10:09:17	ga_ls8c_ard_3-2-1_098083_2022-05-22_final
2022-05-27 10:25:48	ga_ls8c_ard_3-2-1_101078_2022-05-27_final
2022-06-08 10:52:17	ga_ls8c_ard_3-2-1_105082_2022-06-08_final
2022-06-16 09:58:33	ga_ls8c_ard_3-2-1_097071_2022-06-16_final
2022-06-16 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-06-16_final
2022-06-24 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-06-24_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-11-27 11:18:16	ga_ls8c_ard_3-2-1_109084_2022-11-27_final
2022-12-07 11:53:45	ga_ls8c_ard_3-2-1_115080_2022-12-07_final
2022-12-09 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-12-09_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-15 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-12-15_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2022-12-20 11:19:55	ga_ls8c_ard_3-2-1_110073_2022-12-20_final
2022-12-23 11:53:35	ga_ls8c_ard_3-2-1_115080_2022-12-23_final
2022-12-30 11:58:12	ga_ls8c_ard_3-2-1_116076_2022-12-30_final
2023-01-02 10:47:26	ga_ls8c_ard_3-2-1_105069_2023-01-02_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-12 09:46:46	ga_ls8c_ard_3-2-1_095072_2023-01-12_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-30 11:12:55	ga_ls8c_ard_3-2-1_109071_2023-01-30_final
2023-02-01 09:24:52	ga_ls8c_ard_3-2-1_091079_2023-01-31_final
2023-02-01 09:28:27	ga_ls8c_ard_3-2-1_091088_2023-01-31_final
2023-02-02 11:46:36	ga_ls8c_ard_3-2-1_114078_2023-02-02_final
2023-02-02 11:46:36	ga_ls8c_ard_3-2-1_114078_2023-02-02_nrt
2023-02-03 10:50:11	ga_ls8c_ard_3-2-1_105076_2023-02-03_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-15 11:17:59	ga_ls8c_ard_3-2-1_109084_2023-02-15_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-28 10:40:29	ga_ls8c_ard_3-2-1_104068_2023-02-28_final
2023-03-03 11:13:22	ga_ls8c_ard_3-2-1_109073_2023-03-03_final
2023-03-07 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-03-07_final
2023-03-17 11:25:14	ga_ls8c_ard_3-2-1_111072_2023-03-17_final
2023-03-26 11:18:32	ga_ls8c_ard_3-2-1_110071_2023-03-26_final
2023-03-28 11:10:57	ga_ls8c_ard_3-2-1_108083_2023-03-28_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-06 09:26:33	ga_ls8c_ard_3-2-1_091085_2023-04-05_final
2023-04-06 09:28:09	ga_ls8c_ard_3-2-1_091089_2023-04-05_final
2023-04-07 10:06:36	ga_ls8c_ard_3-2-1_098077_2023-04-07_final
2023-04-08 09:11:21	ga_ls8c_ard_3-2-1_089078_2023-04-07_final
2023-04-11 11:23:27	ga_ls8c_ard_3-2-1_110084_2023-04-11_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-04-28 10:22:35	ga_ls8c_ard_3-2-1_101071_2023-04-28_final
2023-05-09 10:03:30	ga_ls8c_ard_3-2-1_098070_2023-05-09_final
2023-05-13 11:22:23	ga_ls8c_ard_3-2-1_110082_2023-05-13_final
2023-05-16 11:52:04	ga_ls8c_ard_3-2-1_115079_2023-05-16_final
2023-05-18 09:58:01	ga_ls8c_ard_3-2-1_097072_2023-05-18_final
2023-05-24 09:27:46	ga_ls8c_ard_3-2-1_091089_2023-05-23_final
2023-05-31 11:05:39	ga_ls8c_ard_3-2-1_108071_2023-05-31_final
2023-05-31 11:06:27	ga_ls8c_ard_3-2-1_108073_2023-05-31_final
2023-06-02 09:20:00	ga_ls8c_ard_3-2-1_090085_2023-06-01_final
2023-06-07 11:16:42	ga_ls8c_ard_3-2-1_109083_2023-06-07_final
2023-06-10 10:03:58	ga_ls8c_ard_3-2-1_098071_2023-06-10_final
2023-06-11 10:45:38	ga_ls8c_ard_3-2-1_105067_2023-06-11_final
2023-06-12 09:57:13	ga_ls8c_ard_3-2-1_096085_2023-06-12_final
2023-06-12 11:34:54	ga_ls8c_ard_3-2-1_112082_2023-06-12_final
2023-06-12 11:35:42	ga_ls8c_ard_3-2-1_112084_2023-06-12_final
2023-06-14 11:22:57	ga_ls8c_ard_3-2-1_110083_2023-06-14_final
2023-06-21 11:29:09	ga_ls8c_ard_3-2-1_111083_2023-06-21_final
2023-06-24 10:21:11	ga_ls8c_ard_3-2-1_100083_2023-06-24_final
2023-06-25 09:22:47	ga_ls8c_ard_3-2-1_091076_2023-06-24_final
2023-06-27 09:16:03	ga_ls8c_ard_3-2-1_089090_2023-06-26_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-06-29 10:35:25	ga_ls8c_ard_3-2-1_103072_2023-06-29_final
2023-07-01 10:22:42	ga_ls8c_ard_3-2-1_101071_2023-07-01_final
2023-07-05 11:41:17	ga_ls8c_ard_3-2-1_113082_2023-07-05_final
2023-07-06 09:06:24	ga_ls8c_ard_3-2-1_088081_2023-07-05_final
2023-07-13 09:14:37	ga_ls8c_ard_3-2-1_089086_2023-07-12_final
2023-07-19 10:15:37	ga_ls8c_ard_3-2-1_099084_2023-07-19_final
2023-07-25 09:39:24	ga_ls8c_ard_3-2-1_093086_2023-07-25_final
2023-07-26 11:57:34	ga_ls8c_ard_3-2-1_116076_2023-07-26_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-08-03 11:05:24	ga_ls8c_ard_3-2-1_108069_2023-08-03_final
2023-08-03 11:06:12	ga_ls8c_ard_3-2-1_108071_2023-08-03_final
2023-08-05 10:52:39	ga_ls8c_ard_3-2-1_106068_2023-08-05_final
2023-08-22 10:03:56	ga_ls8c_ard_3-2-1_097085_2023-08-22_final
2023-08-27 10:21:42	ga_ls8c_ard_3-2-1_100083_2023-08-27_nrt
2023-09-04 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-09-04_final
2023-09-04 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-09-04_nrt
2023-09-12 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-09-12_final
2023-09-13 09:26:31	ga_ls8c_ard_3-2-1_091084_2023-09-12_final
2023-09-14 10:03:48	ga_ls8c_ard_3-2-1_098069_2023-09-14_final
2023-09-14 10:06:59	ga_ls8c_ard_3-2-1_098077_2023-09-14_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