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
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-08 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-08_final
2022-04-08 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-08_final
2022-04-12 10:56:36	ga_ls8c_ard_3-2-1_106078_2022-04-12_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-29 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-04-29_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-06 11:45:16	ga_ls8c_ard_3-2-1_114076_2022-05-06_final
2022-05-08 11:33:20	ga_ls8c_ard_3-2-1_112077_2022-05-08_final
2022-05-09 10:36:31	ga_ls8c_ard_3-2-1_103074_2022-05-09_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-05-11 10:24:35	ga_ls8c_ard_3-2-1_101075_2022-05-11_final
2022-05-13 10:12:14	ga_ls8c_ard_3-2-1_099075_2022-05-13_final
2022-05-14 10:57:06	ga_ls8c_ard_3-2-1_106079_2022-05-14_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-22 10:05:41	ga_ls8c_ard_3-2-1_098074_2022-05-22_final
2022-05-24 09:56:31	ga_ls8c_ard_3-2-1_096082_2022-05-24_final
2022-05-27 10:23:24	ga_ls8c_ard_3-2-1_101072_2022-05-27_final
2022-06-11 09:42:21	ga_ls8c_ard_3-2-1_094077_2022-06-11_final
2022-06-15 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-06-15_final
2022-06-16 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-06-16_final
2022-06-20 09:35:27	ga_ls8c_ard_3-2-1_093075_2022-06-20_final
2022-06-27 11:18:33	ga_ls8c_ard_3-2-1_110070_2022-06-27_final
2022-07-02 11:39:05	ga_ls8c_ard_3-2-1_113075_2022-07-02_final
2022-07-04 09:48:39	ga_ls8c_ard_3-2-1_095077_2022-07-04_final
2022-07-11 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-07-11_final
2022-07-12 10:37:16	ga_ls8c_ard_3-2-1_103075_2022-07-12_final
2022-07-12 10:37:40	ga_ls8c_ard_3-2-1_103076_2022-07-12_final
2022-07-13 09:42:03	ga_ls8c_ard_3-2-1_094076_2022-07-13_final
2022-07-19 10:45:53	ga_ls8c_ard_3-2-1_104081_2022-07-19_final
2022-07-20 09:49:53	ga_ls8c_ard_3-2-1_095080_2022-07-20_final
2022-07-24 11:03:42	ga_ls8c_ard_3-2-1_107079_2022-07-24_final
2022-07-25 10:05:41	ga_ls8c_ard_3-2-1_098073_2022-07-25_final
2022-07-25 10:09:17	ga_ls8c_ard_3-2-1_098082_2022-07-25_final
2022-07-27 09:53:21	ga_ls8c_ard_3-2-1_096073_2022-07-27_final
2022-07-27 09:56:33	ga_ls8c_ard_3-2-1_096081_2022-07-27_final
2022-07-30 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-07-30_final
2022-08-01 10:11:57	ga_ls8c_ard_3-2-1_099073_2022-08-01_final
2022-08-05 11:26:57	ga_ls8c_ard_3-2-1_111075_2022-08-05_final
2022-08-09 09:26:34	ga_ls8c_ard_3-2-1_091083_2022-08-08_final
2022-08-10 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-08-10_final
2022-08-11 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-08-11_final
2022-08-11 10:51:30	ga_ls8c_ard_3-2-1_105079_2022-08-11_final
2022-08-12 11:33:10	ga_ls8c_ard_3-2-1_112075_2022-08-12_final
2022-08-13 10:37:57	ga_ls8c_ard_3-2-1_103076_2022-08-13_final
2022-08-18 09:20:01	ga_ls8c_ard_3-2-1_090082_2022-08-17_final
2022-08-19 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-08-19_final
2022-08-21 09:50:32	ga_ls8c_ard_3-2-1_095081_2022-08-21_final
2022-08-21 11:29:01	ga_ls8c_ard_3-2-1_111080_2022-08-21_final
2022-08-23 09:36:58	ga_ls8c_ard_3-2-1_093078_2022-08-23_final
2022-08-23 11:16:15	ga_ls8c_ard_3-2-1_109079_2022-08-23_final
2022-08-28 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-08-28_final
2022-09-01 11:06:05	ga_ls8c_ard_3-2-1_108069_2022-09-01_final
2022-09-05 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-09-05_final
2022-09-06 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-09-06_final
2022-09-07 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-09-07_final
2022-09-10 11:05:09	ga_ls8c_ard_3-2-1_107082_2022-09-10_final
2022-09-11 10:05:57	ga_ls8c_ard_3-2-1_098073_2022-09-11_final
2022-09-11 10:09:08	ga_ls8c_ard_3-2-1_098081_2022-09-11_final
2022-09-12 10:51:37	ga_ls8c_ard_3-2-1_105079_2022-09-12_final
2022-09-13 09:56:00	ga_ls8c_ard_3-2-1_096079_2022-09-13_final
2022-09-15 09:42:27	ga_ls8c_ard_3-2-1_094076_2022-09-15_final
2022-09-18 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-09-18_final
2022-09-19 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-09-19_final
2022-09-21 10:45:52	ga_ls8c_ard_3-2-1_104080_2022-09-21_final
2022-09-24 09:36:41	ga_ls8c_ard_3-2-1_093077_2022-09-24_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-10-01 09:45:15	ga_ls8c_ard_3-2-1_094083_2022-10-01_final
2022-10-07 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-07_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-08 11:29:27	ga_ls8c_ard_3-2-1_111081_2022-10-08_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-14 10:51:53	ga_ls8c_ard_3-2-1_105080_2022-10-14_final
2022-10-16 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-10-16_final
2022-10-17 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-10-17_final
2022-10-17 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-10-17_final
2022-10-20 10:12:53	ga_ls8c_ard_3-2-1_099075_2022-10-20_final
2022-10-24 11:28:17	ga_ls8c_ard_3-2-1_111078_2022-10-24_final
2022-10-31 11:35:42	ga_ls8c_ard_3-2-1_112081_2022-10-31_final
2022-11-04 09:34:54	ga_ls8c_ard_3-2-1_092088_2022-11-04_final
2022-11-11 09:38:38	ga_ls8c_ard_3-2-1_093082_2022-11-11_final
2022-11-16 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-11-16_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-28 11:58:45	ga_ls8c_ard_3-2-1_116077_2022-11-28_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-15 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-12-15_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-19 10:37:04	ga_ls8c_ard_3-2-1_103074_2022-12-19_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-27 09:48:00	ga_ls8c_ard_3-2-1_095075_2022-12-27_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-18 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-02-18_final
2023-02-20 09:55:33	ga_ls8c_ard_3-2-1_096079_2023-02-20_final
2023-02-20 11:33:14	ga_ls8c_ard_3-2-1_112076_2023-02-20_final
2023-02-20 11:35:14	ga_ls8c_ard_3-2-1_112081_2023-02-20_final
2023-02-22 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-02-22_final
2023-03-05 09:25:42	ga_ls8c_ard_3-2-1_091082_2023-03-04_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