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
2017-05-14 11:06:58	ga_ls8c_ard_3-1-0_108074_2017-05-14_final
2019-03-13 09:52:35	ga_ls8c_ard_3-1-0_096073_2019-03-13_final
2019-03-16 10:23:29	ga_ls8c_ard_3-1-0_101073_2019-03-16_final
2019-03-22 09:50:22	ga_ls8c_ard_3-1-0_095083_2019-03-22_final
2019-03-22 11:26:04	ga_ls8c_ard_3-1-0_111075_2019-03-22_final
2019-03-22 11:27:39	ga_ls8c_ard_3-1-0_111079_2019-03-22_final
2019-03-29 09:55:44	ga_ls8c_ard_3-1-0_096081_2019-03-29_final
2019-04-02 11:05:29	ga_ls8c_ard_3-1-0_108070_2019-04-02_final
2019-04-14 09:52:51	ga_ls8c_ard_3-1-0_096074_2019-04-14_final
2019-04-18 11:09:47	ga_ls8c_ard_3-1-0_108081_2019-04-18_final
2019-04-18 11:10:11	ga_ls8c_ard_3-1-0_108082_2019-04-18_final
2019-06-13 11:57:36	ga_ls8c_ard_3-1-0_116076_2019-06-13_final
2019-06-16 10:46:02	ga_ls8c_ard_3-1-0_105067_2019-06-16_final
2019-07-03 09:51:42	ga_ls8c_ard_3-1-0_096070_2019-07-03_final
2019-07-12 11:29:13	ga_ls8c_ard_3-1-0_111082_2019-07-12_final
2019-07-16 09:24:49	ga_ls8c_ard_3-1-0_091080_2019-07-15_final
2019-08-24 11:10:31	ga_ls8c_ard_3-1-0_108081_2019-08-24_final
2019-09-04 10:48:01	ga_ls8c_ard_3-1-0_105071_2019-09-04_final
2019-09-14 11:29:33	ga_ls8c_ard_3-1-0_111082_2019-09-14_final
2019-09-17 11:58:04	ga_ls8c_ard_3-1-0_116076_2019-09-17_final
2019-09-20 10:50:30	ga_ls8c_ard_3-1-0_105077_2019-09-20_final
2019-09-21 09:52:30	ga_ls8c_ard_3-1-0_096071_2019-09-21_final
2019-09-30 11:30:26	ga_ls8c_ard_3-1-0_111084_2019-09-30_final
2019-10-16 11:26:53	ga_ls8c_ard_3-1-0_111075_2019-10-16_final
2019-10-17 10:29:40	ga_ls8c_ard_3-1-0_102071_2019-10-17_final
2019-10-22 10:48:12	ga_ls8c_ard_3-1-0_105071_2019-10-22_final
2019-10-22 10:50:36	ga_ls8c_ard_3-1-0_105077_2019-10-22_final
2019-10-23 09:52:59	ga_ls8c_ard_3-1-0_096072_2019-10-23_final
2019-10-23 09:53:47	ga_ls8c_ard_3-1-0_096074_2019-10-23_final
2019-10-27 11:11:32	ga_ls8c_ard_3-1-0_108083_2019-10-27_final
2019-11-05 09:25:39	ga_ls8c_ard_3-1-0_091081_2019-11-04_final
2019-11-18 10:29:36	ga_ls8c_ard_3-1-0_102071_2019-11-18_final
2019-11-18 10:30:48	ga_ls8c_ard_3-1-0_102074_2019-11-18_final
2019-11-18 10:31:36	ga_ls8c_ard_3-1-0_102076_2019-11-18_final
2019-11-23 10:51:43	ga_ls8c_ard_3-1-0_105080_2019-11-23_final
2019-11-24 09:57:17	ga_ls8c_ard_3-1-0_096083_2019-11-24_final
2019-11-24 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-11-24_final
2019-11-24 11:33:23	ga_ls8c_ard_3-1-0_112076_2019-11-24_final
2019-11-28 11:11:03	ga_ls8c_ard_3-1-0_108082_2019-11-28_final
2019-12-03 09:47:55	ga_ls8c_ard_3-1-0_095075_2019-12-03_final
2019-12-26 09:53:14	ga_ls8c_ard_3-1-0_096073_2019-12-26_final
2020-01-08 09:28:40	ga_ls8c_ard_3-1-0_091089_2020-01-07_final
2020-01-20 09:47:45	ga_ls8c_ard_3-1-0_095075_2020-01-20_final
2020-01-20 09:50:09	ga_ls8c_ard_3-1-0_095081_2020-01-20_final
2020-01-21 10:28:37	ga_ls8c_ard_3-1-0_102069_2020-01-21_final
2020-01-31 11:10:50	ga_ls8c_ard_3-1-0_108082_2020-01-31_final
2020-02-05 09:48:27	ga_ls8c_ard_3-1-0_095077_2020-02-05_final
2020-02-05 09:51:39	ga_ls8c_ard_3-1-0_095085_2020-02-05_final
2020-02-16 11:09:58	ga_ls8c_ard_3-1-0_108080_2020-02-16_final
2020-02-22 10:31:40	ga_ls8c_ard_3-1-0_102077_2020-02-22_final
2020-02-25 09:26:28	ga_ls8c_ard_3-1-0_091084_2020-02-24_final
2020-02-25 09:28:51	ga_ls8c_ard_3-1-0_091090_2020-02-24_final
2020-03-08 11:28:48	ga_ls8c_ard_3-1-0_111081_2020-03-08_final
2020-03-11 11:57:41	ga_ls8c_ard_3-1-0_116076_2020-03-11_final
2020-03-11 11:58:28	ga_ls8c_ard_3-1-0_116078_2020-03-11_final
2020-03-14 10:50:04	ga_ls8c_ard_3-1-0_105077_2020-03-14_final
2020-03-19 11:07:22	ga_ls8c_ard_3-1-0_108074_2020-03-19_final
2020-03-31 09:55:29	ga_ls8c_ard_3-1-0_096080_2020-03-31_final
2020-03-31 11:31:34	ga_ls8c_ard_3-1-0_112073_2020-03-31_final
2020-04-09 09:49:38	ga_ls8c_ard_3-1-0_095081_2020-04-09_final
2020-04-09 09:51:14	ga_ls8c_ard_3-1-0_095085_2020-04-09_final
2020-04-09 11:25:43	ga_ls8c_ard_3-1-0_111074_2020-04-09_final
2020-04-15 10:50:12	ga_ls8c_ard_3-1-0_105078_2020-04-15_final
2020-04-20 11:05:55	ga_ls8c_ard_3-1-0_108071_2020-04-20_final
2020-04-28 11:56:53	ga_ls8c_ard_3-1-0_116075_2020-04-28_final
2020-04-28 11:57:17	ga_ls8c_ard_3-1-0_116076_2020-04-28_final
2020-05-02 11:34:55	ga_ls8c_ard_3-1-0_112082_2020-05-02_final
2020-05-05 10:27:18	ga_ls8c_ard_3-1-0_101083_2020-05-05_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-11 10:14:56	ga_ls8c_ard_3-2-1_099082_2022-04-11_final
2022-04-11 10:15:20	ga_ls8c_ard_3-2-1_099083_2022-04-11_final
2022-04-12 10:58:12	ga_ls8c_ard_3-2-1_106082_2022-04-12_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-14 10:41:04	ga_ls8c_ard_3-2-1_104070_2022-04-14_final
2022-04-15 11:29:07	ga_ls8c_ard_3-2-1_111082_2022-04-15_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-17 11:13:10	ga_ls8c_ard_3-2-1_109073_2022-04-17_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-24 09:43:13	ga_ls8c_ard_3-2-1_094080_2022-04-24_final
2022-04-28 10:54:09	ga_ls8c_ard_3-2-1_106072_2022-04-28_final
2022-04-28 10:57:20	ga_ls8c_ard_3-2-1_106080_2022-04-28_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-03 11:13:08	ga_ls8c_ard_3-2-1_109073_2022-05-03_final
2022-05-04 10:20:19	ga_ls8c_ard_3-2-1_100080_2022-05-04_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-08 11:35:20	ga_ls8c_ard_3-2-1_112082_2022-05-08_final
2022-05-15 10:01:29	ga_ls8c_ard_3-2-1_097079_2022-05-15_final
2022-05-17 09:47:32	ga_ls8c_ard_3-2-1_095075_2022-05-17_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-31 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-05-31_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-13 09:31:12	ga_ls8c_ard_3-2-1_092080_2022-06-13_final
2022-06-15 10:54:33	ga_ls8c_ard_3-2-1_106072_2022-06-15_final
2022-06-16 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-06-16_final
2022-06-20 09:35:51	ga_ls8c_ard_3-2-1_093076_2022-06-20_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