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
2023-02-02 10:04:08	ga_ls8c_ard_3-2-1_098069_2023-02-02_final
2023-02-02 10:09:19	ga_ls8c_ard_3-2-1_098082_2023-02-02_final
2023-02-04 11:34:38	ga_ls8c_ard_3-2-1_112079_2023-02-04_final
2023-03-19 09:39:33	ga_ls8c_ard_3-2-1_093086_2023-03-19_final
2023-03-19 11:13:38	ga_ls8c_ard_3-2-1_109074_2023-03-19_final
2023-03-19 11:15:38	ga_ls8c_ard_3-2-1_109079_2023-03-19_final
2023-03-19 11:16:02	ga_ls8c_ard_3-2-1_109080_2023-03-19_final
2023-03-21 09:23:10	ga_ls8c_ard_3-2-1_091076_2023-03-20_final
2023-03-21 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-03-21_final
2023-03-24 09:54:49	ga_ls8c_ard_3-2-1_096078_2023-03-24_final
2023-05-12 10:38:20	ga_ls8c_ard_3-2-1_103080_2023-05-12_final
2023-05-15 09:30:44	ga_ls8c_ard_3-2-1_092081_2023-05-15_final
2023-05-22 11:13:25	ga_ls8c_ard_3-2-1_109075_2023-05-22_final
2023-05-23 10:19:24	ga_ls8c_ard_3-2-1_100079_2023-05-23_final
2023-05-25 11:46:20	ga_ls8c_ard_3-2-1_114080_2023-05-25_final
2023-05-27 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-27_final
2023-05-28 10:38:21	ga_ls8c_ard_3-2-1_103080_2023-05-28_final
2023-05-29 11:20:49	ga_ls8c_ard_3-2-1_110078_2023-05-29_final
2023-05-29 11:21:13	ga_ls8c_ard_3-2-1_110079_2023-05-29_final
2023-05-31 09:29:58	ga_ls8c_ard_3-2-1_092079_2023-05-30_final
2023-06-05 09:47:45	ga_ls8c_ard_3-2-1_095077_2023-06-05_final
2023-06-07 11:14:42	ga_ls8c_ard_3-2-1_109078_2023-06-07_final
2023-06-07 11:15:06	ga_ls8c_ard_3-2-1_109079_2023-06-07_final
2023-06-11 09:13:32	ga_ls8c_ard_3-2-1_089084_2023-06-10_final
2023-06-11 10:49:38	ga_ls8c_ard_3-2-1_105077_2023-06-11_final
2023-06-14 09:44:52	ga_ls8c_ard_3-2-1_094085_2023-06-14_final
2023-06-16 09:30:07	ga_ls8c_ard_3-2-1_092079_2023-06-16_final
2023-06-16 11:09:48	ga_ls8c_ard_3-2-1_108081_2023-06-16_final
2023-06-21 11:25:57	ga_ls8c_ard_3-2-1_111075_2023-06-21_final
2023-06-23 09:36:18	ga_ls8c_ard_3-2-1_093079_2023-06-23_final
2023-06-23 11:17:11	ga_ls8c_ard_3-2-1_109084_2023-06-23_final
2023-06-26 10:08:04	ga_ls8c_ard_3-2-1_098081_2023-06-26_final
2023-07-02 09:33:04	ga_ls8c_ard_3-2-1_092086_2023-07-02_final
2023-07-03 11:50:26	ga_ls8c_ard_3-2-1_115074_2023-07-03_final
2023-07-05 09:59:37	ga_ls8c_ard_3-2-1_097075_2023-07-05_final
2023-07-05 11:41:41	ga_ls8c_ard_3-2-1_113083_2023-07-05_final
2023-07-06 10:45:17	ga_ls8c_ard_3-2-1_104081_2023-07-06_final
2023-07-07 11:27:45	ga_ls8c_ard_3-2-1_111079_2023-07-07_final
2023-07-09 09:36:55	ga_ls8c_ard_3-2-1_093080_2023-07-09_final
2023-07-11 09:22:58	ga_ls8c_ard_3-2-1_091076_2023-07-10_final
2023-07-20 09:20:23	ga_ls8c_ard_3-2-1_090085_2023-07-19_final
2023-07-22 10:45:20	ga_ls8c_ard_3-2-1_104081_2023-07-22_final
2023-07-23 09:48:56	ga_ls8c_ard_3-2-1_095079_2023-07-23_final
2023-07-25 09:36:36	ga_ls8c_ard_3-2-1_093079_2023-07-25_final
2023-07-25 09:38:36	ga_ls8c_ard_3-2-1_093084_2023-07-25_final
2023-07-25 11:15:29	ga_ls8c_ard_3-2-1_109079_2023-07-25_final
2023-07-29 10:46:49	ga_ls8c_ard_3-2-1_105069_2023-07-29_final
2023-07-29 10:50:25	ga_ls8c_ard_3-2-1_105078_2023-07-29_final
2023-07-30 11:34:29	ga_ls8c_ard_3-2-1_112080_2023-07-30_final
2023-08-01 11:20:57	ga_ls8c_ard_3-2-1_110077_2023-08-01_final
2023-08-03 09:34:30	ga_ls8c_ard_3-2-1_092089_2023-08-03_final
2023-08-03 11:09:00	ga_ls8c_ard_3-2-1_108078_2023-08-03_final
2023-08-08 11:27:32	ga_ls8c_ard_3-2-1_111078_2023-08-08_final
2023-08-10 11:14:46	ga_ls8c_ard_3-2-1_109077_2023-08-10_final
2023-08-14 10:51:18	ga_ls8c_ard_3-2-1_105080_2023-08-14_final
2023-08-15 09:54:53	ga_ls8c_ard_3-2-1_096078_2023-08-15_final
2023-08-21 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-08-21_final
2023-08-23 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-08-23_final
2023-08-27 10:20:30	ga_ls8c_ard_3-2-1_100080_2023-08-27_final
2023-08-29 10:06:56	ga_ls8c_ard_3-2-1_098077_2023-08-29_final
2023-08-30 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-08-30_final
2023-08-31 09:54:59	ga_ls8c_ard_3-2-1_096078_2023-08-31_final
2023-08-31 11:34:39	ga_ls8c_ard_3-2-1_112080_2023-08-31_final
2023-09-02 11:21:06	ga_ls8c_ard_3-2-1_110077_2023-09-02_final
2023-09-02 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-09-02_final
2023-09-02 11:23:05	ga_ls8c_ard_3-2-1_110082_2023-09-02_final
2023-09-07 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-09-07_final
2023-09-10 10:32:52	ga_ls8c_ard_3-2-1_102080_2023-09-10_final
2023-09-11 11:15:44	ga_ls8c_ard_3-2-1_109079_2023-09-11_final
2023-09-13 11:03:00	ga_ls8c_ard_3-2-1_107078_2023-09-13_final
2023-09-16 09:55:02	ga_ls8c_ard_3-2-1_096078_2023-09-16_final
2023-09-16 11:34:19	ga_ls8c_ard_3-2-1_112079_2023-09-16_final
2023-09-18 11:21:34	ga_ls8c_ard_3-2-1_110078_2023-09-18_final
2023-09-18 11:21:58	ga_ls8c_ard_3-2-1_110079_2023-09-18_final
2023-09-20 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-09-20_final
2023-09-21 10:16:23	ga_ls8c_ard_3-2-1_099085_2023-09-21_final
2023-09-25 11:25:47	ga_ls8c_ard_3-2-1_111073_2023-09-25_final
2023-10-02 09:55:06	ga_ls8c_ard_3-2-1_096078_2023-10-02_final
2023-10-02 09:55:54	ga_ls8c_ard_3-2-1_096080_2023-10-02_final
2023-10-06 09:30:46	ga_ls8c_ard_3-2-1_092079_2023-10-06_final
2023-10-11 09:48:58	ga_ls8c_ard_3-2-1_095078_2023-10-11_final
2023-10-11 11:25:03	ga_ls8c_ard_3-2-1_111071_2023-10-11_final
2023-10-11 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-10-11_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_final
2023-10-19 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-10-19_final
2023-10-24 10:58:10	ga_ls8c_ard_3-2-1_106081_2023-10-24_final
2023-10-27 09:49:00	ga_ls8c_ard_3-2-1_095078_2023-10-27_final
2023-10-29 09:39:27	ga_ls8c_ard_3-2-1_093085_2023-10-29_final
2023-10-29 11:15:08	ga_ls8c_ard_3-2-1_109077_2023-10-29_final
2023-10-29 11:15:56	ga_ls8c_ard_3-2-1_109079_2023-10-29_final
2023-11-03 09:57:59	ga_ls8c_ard_3-2-1_096085_2023-11-03_final
2023-11-05 11:19:18	ga_ls8c_ard_3-2-1_110072_2023-11-05_final
2023-11-05 11:22:06	ga_ls8c_ard_3-2-1_110079_2023-11-05_final
2023-11-06 10:23:16	ga_ls8c_ard_3-2-1_101071_2023-11-06_final
2023-11-07 11:07:19	ga_ls8c_ard_3-2-1_108073_2023-11-07_final
2023-11-07 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-11-07_final
2023-11-10 11:38:58	ga_ls8c_ard_3-2-1_113075_2023-11-10_final
2023-11-12 11:28:14	ga_ls8c_ard_3-2-1_111079_2023-11-12_final
2023-11-12 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-11-12_final
2023-11-14 09:35:25	ga_ls8c_ard_3-2-1_093075_2023-11-14_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