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
2022-08-21 09:49:20	ga_ls8c_ard_3-2-1_095078_2022-08-21_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-30 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-08-30_final
2022-08-30 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-08-30_final
2022-08-30 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-08-30_final
2022-09-03 10:56:54	ga_ls8c_ard_3-2-1_106077_2022-09-03_final
2022-09-06 09:46:34	ga_ls8c_ard_3-2-1_095071_2022-09-06_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-07 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-09-07_final
2022-09-12 10:51:13	ga_ls8c_ard_3-2-1_105078_2022-09-12_final
2022-09-12 10:51:37	ga_ls8c_ard_3-2-1_105079_2022-09-12_final
2022-09-14 10:39:40	ga_ls8c_ard_3-2-1_103080_2022-09-14_final
2022-09-17 11:09:23	ga_ls8c_ard_3-2-1_108077_2022-09-17_final
2022-09-17 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-09-17_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_final
2022-09-24 09:40:17	ga_ls8c_ard_3-2-1_093086_2022-09-24_final
2022-09-24 11:15:34	ga_ls8c_ard_3-2-1_109077_2022-09-24_final
2022-09-28 10:52:27	ga_ls8c_ard_3-2-1_105081_2022-09-28_final
2022-09-30 10:35:17	ga_ls8c_ard_3-2-1_103069_2022-09-30_final
2022-10-04 10:11:20	ga_ls8c_ard_3-2-1_099071_2022-10-04_final
2022-10-05 10:53:24	ga_ls8c_ard_3-2-1_106068_2022-10-05_final
2022-10-10 09:40:59	ga_ls8c_ard_3-2-1_093088_2022-10-10_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-14 09:13:24	ga_ls8c_ard_3-2-1_089081_2022-10-13_final
2022-10-16 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-10-16_final
2022-10-17 09:41:09	ga_ls8c_ard_3-2-1_094073_2022-10-17_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-21 10:56:10	ga_ls8c_ard_3-2-1_106075_2022-10-21_final
2022-10-24 11:26:42	ga_ls8c_ard_3-2-1_111074_2022-10-24_final
2022-10-26 11:15:33	ga_ls8c_ard_3-2-1_109077_2022-10-26_final
2022-10-30 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-10-30_final
2022-11-02 09:42:52	ga_ls8c_ard_3-2-1_094077_2022-11-02_final
2022-11-02 11:22:33	ga_ls8c_ard_3-2-1_110079_2022-11-02_final
2022-11-04 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-11-04_final
2022-11-04 11:09:23	ga_ls8c_ard_3-2-1_108077_2022-11-04_final
2022-11-05 10:14:33	ga_ls8c_ard_3-2-1_099079_2022-11-05_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-18 11:18:49	ga_ls8c_ard_3-2-1_110070_2022-11-18_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-01 10:51:10	ga_ls8c_ard_3-2-1_105078_2022-12-01_final
2022-12-12 10:28:59	ga_ls8c_ard_3-2-1_102069_2022-12-12_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-17 10:50:40	ga_ls8c_ard_3-2-1_105077_2022-12-17_final
2022-12-19 10:35:05	ga_ls8c_ard_3-2-1_103069_2022-12-19_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-20 09:44:14	ga_ls8c_ard_3-2-1_094081_2022-12-20_final
2022-12-20 11:22:19	ga_ls8c_ard_3-2-1_110079_2022-12-20_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-22 09:31:02	ga_ls8c_ard_3-2-1_092079_2022-12-22_final
2022-12-22 11:07:08	ga_ls8c_ard_3-2-1_108072_2022-12-22_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-24 10:58:22	ga_ls8c_ard_3-2-1_106081_2022-12-24_final
2022-12-27 11:26:05	ga_ls8c_ard_3-2-1_111073_2022-12-27_final
2022-12-28 10:28:53	ga_ls8c_ard_3-2-1_102069_2022-12-28_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-02 10:49:49	ga_ls8c_ard_3-2-1_105075_2023-01-02_final
2023-01-03 09:55:24	ga_ls8c_ard_3-2-1_096078_2023-01-03_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-07 09:31:51	ga_ls8c_ard_3-2-1_092081_2023-01-07_final
2023-01-07 11:09:09	ga_ls8c_ard_3-2-1_108077_2023-01-07_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-16 11:03:16	ga_ls8c_ard_3-2-1_107078_2023-01-16_final
2023-01-18 10:49:41	ga_ls8c_ard_3-2-1_105075_2023-01-18_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-21 09:44:32	ga_ls8c_ard_3-2-1_094082_2023-01-21_final
2023-01-21 11:24:13	ga_ls8c_ard_3-2-1_110084_2023-01-21_final
2023-01-22 10:24:37	ga_ls8c_ard_3-2-1_101074_2023-01-22_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-23 11:08:17	ga_ls8c_ard_3-2-1_108075_2023-01-23_final
2023-01-23 11:11:53	ga_ls8c_ard_3-2-1_108084_2023-01-23_final
2023-01-25 10:58:20	ga_ls8c_ard_3-2-1_106081_2023-01-25_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-15 09:37:54	ga_ls8c_ard_3-2-1_093081_2023-02-15_final
2023-02-19 10:49:36	ga_ls8c_ard_3-2-1_105075_2023-02-19_final
2023-02-21 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-02-21_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-02-22 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-02-22_final
2023-02-24 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-02-24_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-02-26 10:56:02	ga_ls8c_ard_3-2-1_106076_2023-02-26_final
2023-03-01 11:24:33	ga_ls8c_ard_3-2-1_111070_2023-03-01_final
2023-03-04 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-03-04_final
2023-03-05 11:05:23	ga_ls8c_ard_3-2-1_107084_2023-03-05_final
2023-03-08 11:35:50	ga_ls8c_ard_3-2-1_112083_2023-03-08_final
2023-03-10 11:20:41	ga_ls8c_ard_3-2-1_110076_2023-03-10_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