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
2019-03-12 10:48:37	ga_ls8c_ard_3-1-0_105074_2019-03-12_final
2019-03-12 10:51:25	ga_ls8c_ard_3-1-0_105081_2019-03-12_final
2019-03-13 09:56:11	ga_ls8c_ard_3-1-0_096082_2019-03-13_final
2019-03-22 09:50:22	ga_ls8c_ard_3-1-0_095083_2019-03-22_final
2019-04-13 10:48:05	ga_ls8c_ard_3-1-0_105073_2019-04-13_final
2019-04-14 09:56:03	ga_ls8c_ard_3-1-0_096082_2019-04-14_final
2019-06-14 09:25:05	ga_ls8c_ard_3-1-0_091081_2019-06-13_final
2019-07-02 10:46:07	ga_ls8c_ard_3-1-0_105067_2019-07-02_final
2019-07-02 10:48:31	ga_ls8c_ard_3-1-0_105073_2019-07-02_final
2019-07-16 09:23:13	ga_ls8c_ard_3-1-0_091076_2019-07-15_final
2019-07-29 10:30:30	ga_ls8c_ard_3-1-0_102074_2019-07-29_final
2019-08-01 09:25:43	ga_ls8c_ard_3-1-0_091082_2019-07-31_final
2019-08-04 09:57:27	ga_ls8c_ard_3-1-0_096084_2019-08-04_final
2019-08-17 09:23:25	ga_ls8c_ard_3-1-0_091076_2019-08-16_final
2019-08-19 10:52:21	ga_ls8c_ard_3-1-0_105082_2019-08-19_final
2019-08-24 11:07:19	ga_ls8c_ard_3-1-0_108073_2019-08-24_final
2019-09-04 10:48:49	ga_ls8c_ard_3-1-0_105073_2019-09-04_final
2019-09-09 11:05:47	ga_ls8c_ard_3-1-0_108069_2019-09-09_final
2019-09-14 09:47:04	ga_ls8c_ard_3-1-0_095073_2019-09-14_final
2019-09-14 11:26:21	ga_ls8c_ard_3-1-0_111074_2019-09-14_final
2019-09-15 10:33:08	ga_ls8c_ard_3-1-0_102080_2019-09-15_final
2019-09-20 10:52:30	ga_ls8c_ard_3-1-0_105082_2019-09-20_final
2019-09-21 09:52:53	ga_ls8c_ard_3-1-0_096072_2019-09-21_final
2019-10-06 10:48:35	ga_ls8c_ard_3-1-0_105072_2019-10-06_final
2019-10-06 10:52:34	ga_ls8c_ard_3-1-0_105082_2019-10-06_final
2019-10-07 09:52:57	ga_ls8c_ard_3-1-0_096072_2019-10-07_final
2019-10-17 10:33:15	ga_ls8c_ard_3-1-0_102080_2019-10-17_final
2019-10-20 09:22:53	ga_ls8c_ard_3-1-0_091074_2019-10-19_final
2019-10-22 10:49:24	ga_ls8c_ard_3-1-0_105074_2019-10-22_final
2019-11-01 09:52:47	ga_ls8c_ard_3-1-0_095087_2019-11-01_final
2019-11-02 10:30:27	ga_ls8c_ard_3-1-0_102073_2019-11-02_final
2019-11-02 10:33:15	ga_ls8c_ard_3-1-0_102080_2019-11-02_final
2019-11-05 09:28:51	ga_ls8c_ard_3-1-0_091089_2019-11-04_final
2019-11-07 10:47:23	ga_ls8c_ard_3-1-0_105069_2019-11-07_final
2019-11-07 10:52:10	ga_ls8c_ard_3-1-0_105081_2019-11-07_final
2019-11-23 10:47:20	ga_ls8c_ard_3-1-0_105069_2019-11-23_final
2019-12-03 09:46:43	ga_ls8c_ard_3-1-0_095072_2019-12-03_final
2019-12-04 10:33:10	ga_ls8c_ard_3-1-0_102080_2019-12-04_final
2019-12-09 10:51:18	ga_ls8c_ard_3-1-0_105079_2019-12-09_final
2019-12-23 09:27:08	ga_ls8c_ard_3-1-0_091085_2019-12-22_final
2019-12-25 10:47:16	ga_ls8c_ard_3-1-0_105069_2019-12-25_final
2020-01-04 11:26:41	ga_ls8c_ard_3-1-0_111075_2020-01-04_final
2020-01-08 09:27:04	ga_ls8c_ard_3-1-0_091085_2020-01-07_final
2020-01-11 09:51:59	ga_ls8c_ard_3-1-0_096070_2020-01-11_final
2020-01-11 09:58:22	ga_ls8c_ard_3-1-0_096086_2020-01-11_final
2020-01-15 11:07:19	ga_ls8c_ard_3-1-0_108073_2020-01-15_final
2020-01-15 11:09:19	ga_ls8c_ard_3-1-0_108078_2020-01-15_final
2020-01-27 09:56:41	ga_ls8c_ard_3-1-0_096082_2020-01-27_final
2020-01-31 11:06:50	ga_ls8c_ard_3-1-0_108072_2020-01-31_final
2020-02-05 09:52:27	ga_ls8c_ard_3-1-0_095087_2020-02-05_final
2020-02-11 10:47:51	ga_ls8c_ard_3-1-0_105071_2020-02-11_final
2020-02-11 10:49:27	ga_ls8c_ard_3-1-0_105075_2020-02-11_final
2020-02-22 10:32:52	ga_ls8c_ard_3-1-0_102080_2020-02-22_final
2020-03-03 11:05:54	ga_ls8c_ard_3-1-0_108070_2020-03-03_final
2020-03-03 11:07:29	ga_ls8c_ard_3-1-0_108074_2020-03-03_final
2020-03-19 11:05:22	ga_ls8c_ard_3-1-0_108069_2020-03-19_final
2020-03-25 10:28:14	ga_ls8c_ard_3-1-0_102069_2020-03-25_final
2020-03-25 10:28:38	ga_ls8c_ard_3-1-0_102070_2020-03-25_final
2020-03-28 09:28:36	ga_ls8c_ard_3-1-0_091090_2020-03-27_final
2020-04-15 10:50:12	ga_ls8c_ard_3-1-0_105078_2020-04-15_final
2020-04-25 09:51:07	ga_ls8c_ard_3-1-0_095085_2020-04-25_final
2020-04-26 10:29:35	ga_ls8c_ard_3-1-0_102073_2020-04-26_final
2020-05-06 11:06:34	ga_ls8c_ard_3-1-0_108073_2020-05-06_final
2020-05-06 11:10:09	ga_ls8c_ard_3-1-0_108082_2020-05-06_final
2022-03-29 10:41:46	ga_ls8c_ard_3-2-1_104072_2022-03-29_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-04-03 09:28:36	ga_ls8c_ard_3-2-1_091090_2022-04-02_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-07 10:34:02	ga_ls8c_ard_3-2-1_103068_2022-04-07_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-10 09:34:04	ga_ls8c_ard_3-2-1_092088_2022-04-10_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-20 10:04:46	ga_ls8c_ard_3-2-1_098072_2022-04-20_final
2022-04-23 10:34:03	ga_ls8c_ard_3-2-1_103068_2022-04-23_final
2022-04-24 09:40:49	ga_ls8c_ard_3-2-1_094074_2022-04-24_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:35:03	ga_ls8c_ard_3-2-1_093075_2022-05-03_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-06 10:09:59	ga_ls8c_ard_3-2-1_098085_2022-05-06_final
2022-05-08 09:52:51	ga_ls8c_ard_3-2-1_096073_2022-05-08_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-15 09:59:29	ga_ls8c_ard_3-2-1_097074_2022-05-15_final
2022-05-15 10:03:29	ga_ls8c_ard_3-2-1_097084_2022-05-15_final
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-24 11:31:24	ga_ls8c_ard_3-2-1_112072_2022-05-24_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-03 10:28:53	ga_ls8c_ard_3-2-1_102070_2022-06-03_final
2022-06-05 10:21:21	ga_ls8c_ard_3-2-1_100082_2022-06-05_final
2022-06-06 09:28:32	ga_ls8c_ard_3-2-1_091089_2022-06-05_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-17 10:41:25	ga_ls8c_ard_3-2-1_104070_2022-06-17_final
2022-06-19 10:33:51	ga_ls8c_ard_3-2-1_102082_2022-06-19_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