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
2013-11-07 09:55:32	ga_ls8c_ard_3-1-0_096075_2013-11-07_final
2018-05-10 09:27:32	ga_ls8c_ard_3-1-0_091089_2018-05-09_final
2019-03-10 09:26:06	ga_ls8c_ard_3-1-0_091084_2019-03-09_final
2019-03-26 09:22:51	ga_ls8c_ard_3-1-0_091076_2019-03-25_final
2019-04-07 09:48:19	ga_ls8c_ard_3-1-0_095078_2019-04-07_final
2019-04-07 09:50:18	ga_ls8c_ard_3-1-0_095083_2019-04-07_final
2019-04-11 09:23:34	ga_ls8c_ard_3-1-0_091078_2019-04-10_final
2019-04-14 09:51:39	ga_ls8c_ard_3-1-0_096071_2019-04-14_final
2019-06-17 09:53:37	ga_ls8c_ard_3-1-0_096075_2019-06-17_final
2019-06-26 09:48:41	ga_ls8c_ard_3-1-0_095078_2019-06-26_final
2019-07-03 09:54:53	ga_ls8c_ard_3-1-0_096078_2019-07-03_final
2019-07-19 09:52:08	ga_ls8c_ard_3-1-0_096071_2019-07-19_final
2019-07-19 09:56:08	ga_ls8c_ard_3-1-0_096081_2019-07-19_final
2019-08-01 09:24:56	ga_ls8c_ard_3-1-0_091080_2019-07-31_final
2019-08-01 09:25:43	ga_ls8c_ard_3-1-0_091082_2019-07-31_final
2019-08-13 09:46:55	ga_ls8c_ard_3-1-0_095073_2019-08-13_final
2019-08-20 09:52:44	ga_ls8c_ard_3-1-0_096072_2019-08-20_final
2019-09-14 09:49:04	ga_ls8c_ard_3-1-0_095078_2019-09-14_final
2019-09-14 09:49:28	ga_ls8c_ard_3-1-0_095079_2019-09-14_final
2019-09-14 09:49:52	ga_ls8c_ard_3-1-0_095080_2019-09-14_final
2019-09-18 09:23:34	ga_ls8c_ard_3-1-0_091076_2019-09-17_final
2019-09-18 09:25:58	ga_ls8c_ard_3-1-0_091082_2019-09-17_final
2019-09-21 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-09-21_final
2019-09-21 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-09-21_final
2019-09-30 09:49:09	ga_ls8c_ard_3-1-0_095078_2019-09-30_final
2019-09-30 09:49:57	ga_ls8c_ard_3-1-0_095080_2019-09-30_final
2019-09-30 09:51:33	ga_ls8c_ard_3-1-0_095084_2019-09-30_final
2019-10-07 09:55:45	ga_ls8c_ard_3-1-0_096079_2019-10-07_final
2019-10-20 09:26:52	ga_ls8c_ard_3-1-0_091084_2019-10-19_final
2019-10-23 09:56:58	ga_ls8c_ard_3-1-0_096082_2019-10-23_final
2019-11-05 09:24:27	ga_ls8c_ard_3-1-0_091078_2019-11-04_final
2019-11-08 09:55:45	ga_ls8c_ard_3-1-0_096079_2019-11-08_final
2019-11-17 09:49:08	ga_ls8c_ard_3-1-0_095078_2019-11-17_final
2019-11-21 09:23:36	ga_ls8c_ard_3-1-0_091076_2019-11-20_final
2019-11-21 09:24:24	ga_ls8c_ard_3-1-0_091078_2019-11-20_final
2019-11-21 09:25:36	ga_ls8c_ard_3-1-0_091081_2019-11-20_final
2019-11-21 09:26:47	ga_ls8c_ard_3-1-0_091084_2019-11-20_final
2019-11-21 09:27:11	ga_ls8c_ard_3-1-0_091085_2019-11-20_final
2019-11-24 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-11-24_final
2019-12-03 09:49:31	ga_ls8c_ard_3-1-0_095079_2019-12-03_final
2019-12-03 09:50:43	ga_ls8c_ard_3-1-0_095082_2019-12-03_final
2019-12-07 09:23:59	ga_ls8c_ard_3-1-0_091077_2019-12-06_final
2019-12-07 09:24:47	ga_ls8c_ard_3-1-0_091079_2019-12-06_final
2019-12-07 09:26:47	ga_ls8c_ard_3-1-0_091084_2019-12-06_final
2019-12-10 09:54:29	ga_ls8c_ard_3-1-0_096076_2019-12-10_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-08 09:24:16	ga_ls8c_ard_3-1-0_091078_2020-01-07_final
2020-01-11 09:53:58	ga_ls8c_ard_3-1-0_096075_2020-01-11_final
2020-01-20 09:50:33	ga_ls8c_ard_3-1-0_095082_2020-01-20_final
2020-02-05 09:46:28	ga_ls8c_ard_3-1-0_095072_2020-02-05_final
2020-02-12 09:52:14	ga_ls8c_ard_3-1-0_096071_2020-02-12_final
2020-02-21 09:49:36	ga_ls8c_ard_3-1-0_095080_2020-02-21_final
2020-02-25 09:22:04	ga_ls8c_ard_3-1-0_091073_2020-02-24_final
2020-03-15 09:53:14	ga_ls8c_ard_3-1-0_096074_2020-03-15_final
2020-04-09 09:50:02	ga_ls8c_ard_3-1-0_095082_2020-04-09_final
2020-04-16 09:54:34	ga_ls8c_ard_3-1-0_096078_2020-04-16_final
2020-04-25 09:48:43	ga_ls8c_ard_3-1-0_095079_2020-04-25_final
2020-04-25 09:51:07	ga_ls8c_ard_3-1-0_095085_2020-04-25_final
2020-05-02 09:53:38	ga_ls8c_ard_3-1-0_096076_2020-05-02_final
2020-05-02 09:56:02	ga_ls8c_ard_3-1-0_096082_2020-05-02_final
2020-05-02 09:57:14	ga_ls8c_ard_3-1-0_096085_2020-05-02_final
2022-03-29 10:42:34	ga_ls8c_ard_3-2-1_104074_2022-03-29_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-09 10:25:17	ga_ls8c_ard_3-2-1_101077_2022-04-09_final
2022-04-11 10:14:56	ga_ls8c_ard_3-2-1_099082_2022-04-11_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-20 10:07:10	ga_ls8c_ard_3-2-1_098078_2022-04-20_final
2022-04-22 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-22 11:34:04	ga_ls8c_ard_3-2-1_112079_2022-04-22_final
2022-04-23 10:37:39	ga_ls8c_ard_3-2-1_103077_2022-04-23_final
2022-04-27 10:13:41	ga_ls8c_ard_3-2-1_099079_2022-04-27_final
2022-04-27 11:50:58	ga_ls8c_ard_3-2-1_115075_2022-04-27_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 11:15:32	ga_ls8c_ard_3-2-1_109079_2022-05-03_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 09:55:39	ga_ls8c_ard_3-2-1_096080_2022-05-08_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-17 09:47:08	ga_ls8c_ard_3-2-1_095074_2022-05-17_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-05-26 09:42:33	ga_ls8c_ard_3-2-1_094078_2022-05-26_final
2022-05-31 09:57:33	ga_ls8c_ard_3-2-1_097069_2022-05-31_final
2022-05-31 10:00:20	ga_ls8c_ard_3-2-1_097076_2022-05-31_final
2022-06-02 11:27:41	ga_ls8c_ard_3-2-1_111078_2022-06-02_final
2022-06-06 09:28:32	ga_ls8c_ard_3-2-1_091089_2022-06-05_final
2022-06-07 10:09:01	ga_ls8c_ard_3-2-1_098082_2022-06-07_final
2022-06-08 10:52:17	ga_ls8c_ard_3-2-1_105082_2022-06-08_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-13 11:10:29	ga_ls8c_ard_3-2-1_108081_2022-06-13_final
2022-06-13 11:10:53	ga_ls8c_ard_3-2-1_108082_2022-06-13_final
2022-06-15 10:56:33	ga_ls8c_ard_3-2-1_106077_2022-06-15_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-16 09:56:57	ga_ls8c_ard_3-2-1_097067_2022-06-16_final
2022-06-20 11:15:56	ga_ls8c_ard_3-2-1_109079_2022-06-20_final
2022-06-22 11:00:47	ga_ls8c_ard_3-2-1_107072_2022-06-22_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