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
2022-03-09 11:07:08	ga_ls8c_ard_3-2-1_108073_2022-03-09_final
2022-03-11 09:19:04	ga_ls8c_ard_3-2-1_090081_2022-03-10_final
2022-03-13 10:40:23	ga_ls8c_ard_3-2-1_104068_2022-03-13_final
2022-03-18 09:24:23	ga_ls8c_ard_3-2-1_091079_2022-03-17_final
2022-03-18 11:01:16	ga_ls8c_ard_3-2-1_107074_2022-03-18_final
2022-03-19 10:03:38	ga_ls8c_ard_3-2-1_098069_2022-03-19_final
2022-03-23 11:19:21	ga_ls8c_ard_3-2-1_110073_2022-03-23_final
2022-03-23 11:19:45	ga_ls8c_ard_3-2-1_110074_2022-03-23_final
2022-03-26 10:13:43	ga_ls8c_ard_3-2-1_099079_2022-03-26_final
2022-04-02 10:17:02	ga_ls8c_ard_3-2-1_100072_2022-04-02_final
2022-04-03 09:28:36	ga_ls8c_ard_3-2-1_091090_2022-04-02_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-08 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-08_final
2022-04-26 11:06:55	ga_ls8c_ard_3-2-1_108073_2022-04-26_final
2022-04-27 11:52:34	ga_ls8c_ard_3-2-1_115079_2022-04-27_final
2022-04-28 09:20:03	ga_ls8c_ard_3-2-1_090084_2022-04-27_final
2022-04-28 10:57:20	ga_ls8c_ard_3-2-1_106080_2022-04-28_final
2022-05-05 09:25:31	ga_ls8c_ard_3-2-1_091082_2022-05-04_final
2022-05-07 10:46:04	ga_ls8c_ard_3-2-1_105067_2022-05-07_final
2022-05-08 09:53:15	ga_ls8c_ard_3-2-1_096074_2022-05-08_final
2022-05-10 11:19:24	ga_ls8c_ard_3-2-1_110073_2022-05-10_final
2022-05-22 10:04:05	ga_ls8c_ard_3-2-1_098070_2022-05-22_final
2022-05-28 09:28:59	ga_ls8c_ard_3-2-1_092075_2022-05-27_final
2022-06-01 09:06:43	ga_ls8c_ard_3-2-1_088081_2022-05-31_final
2022-06-03 10:30:53	ga_ls8c_ard_3-2-1_102075_2022-06-03_final
2022-06-11 11:19:38	ga_ls8c_ard_3-2-1_110073_2022-06-11_final
2022-06-27 11:19:45	ga_ls8c_ard_3-2-1_110073_2022-06-27_final
2022-06-29 11:11:47	ga_ls8c_ard_3-2-1_108084_2022-06-29_final
2022-07-15 11:07:22	ga_ls8c_ard_3-2-1_108073_2022-07-15_final
2022-07-17 09:17:44	ga_ls8c_ard_3-2-1_090077_2022-07-16_final
2022-07-18 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-18_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-08-05 11:30:08	ga_ls8c_ard_3-2-1_111083_2022-08-05_final
2022-08-18 09:18:02	ga_ls8c_ard_3-2-1_090077_2022-08-17_final
2022-08-24 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-08-24_final
2022-08-25 11:02:42	ga_ls8c_ard_3-2-1_107076_2022-08-25_final
2022-09-01 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-31_final
2022-09-01 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-09-01_final
2022-09-05 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-09-05_final
2022-09-12 09:14:19	ga_ls8c_ard_3-2-1_089083_2022-09-11_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-09-15_final
2022-09-26 09:23:08	ga_ls8c_ard_3-2-1_091074_2022-09-25_final
2022-10-04 11:53:49	ga_ls8c_ard_3-2-1_115080_2022-10-04_final
2022-10-08 09:48:11	ga_ls8c_ard_3-2-1_095075_2022-10-08_final
2022-10-16 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-10-16_final
2022-10-21 10:53:46	ga_ls8c_ard_3-2-1_106069_2022-10-21_final
2022-10-22 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-22_final
2022-10-28 11:02:00	ga_ls8c_ard_3-2-1_107074_2022-10-28_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-10 10:29:52	ga_ls8c_ard_3-2-1_102071_2022-11-10_final
2022-11-14 10:04:43	ga_ls8c_ard_3-2-1_098070_2022-11-14_final
2022-11-19 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-11-19_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-12-02 09:52:45	ga_ls8c_ard_3-2-1_096071_2022-12-02_final
2022-12-08 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-12-07_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-23 10:14:41	ga_ls8c_ard_3-2-1_099080_2022-12-23_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2023-01-08 11:53:36	ga_ls8c_ard_3-2-1_115080_2023-01-08_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-08 11:07:30	ga_ls8c_ard_3-2-1_108073_2023-02-08_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-15 09:35:30	ga_ls8c_ard_3-2-1_093075_2023-02-15_final
2023-02-23 10:23:35	ga_ls8c_ard_3-2-1_101072_2023-02-23_final
2023-02-26 09:17:57	ga_ls8c_ard_3-2-1_090078_2023-02-25_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-07 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-03-07_final
2023-03-23 09:12:45	ga_ls8c_ard_3-2-1_089081_2023-03-22_final
2023-03-31 09:58:57	ga_ls8c_ard_3-2-1_097073_2023-03-31_final
2023-04-09 09:57:23	ga_ls8c_ard_3-2-1_096085_2023-04-09_final
2023-05-03 09:06:11	ga_ls8c_ard_3-2-1_088081_2023-05-02_final
2023-05-05 10:29:29	ga_ls8c_ard_3-2-1_102073_2023-05-05_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-13 11:21:59	ga_ls8c_ard_3-2-1_110081_2023-05-13_final
2023-05-16 10:13:35	ga_ls8c_ard_3-2-1_099080_2023-05-16_final
2023-05-21 10:29:21	ga_ls8c_ard_3-2-1_102073_2023-05-21_final
2023-05-22 09:38:55	ga_ls8c_ard_3-2-1_093086_2023-05-22_final
2023-05-25 10:03:51	ga_ls8c_ard_3-2-1_098071_2023-05-25_final
2023-05-26 09:15:25	ga_ls8c_ard_3-2-1_089089_2023-05-25_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-20 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-08-20_final
2023-08-23 09:07:31	ga_ls8c_ard_3-2-1_088083_2023-08-22_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-11-15 10:19:05	ga_ls8c_ard_3-2-1_100076_2023-11-15_final
2023-11-18 10:48:49	ga_ls8c_ard_3-2-1_105073_2023-11-18_final
2024-01-19 09:24:35	ga_ls8c_ard_3-2-1_091079_2024-01-18_final
2024-02-21 10:08:12	ga_ls8c_ard_3-2-1_098080_2024-02-21_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