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
2017-12-30 10:28:38	ga_ls8c_ard_3-1-0_102069_2017-12-30_final
2019-03-07 10:28:07	ga_ls8c_ard_3-1-0_102069_2019-03-07_final
2019-03-17 11:09:08	ga_ls8c_ard_3-1-0_108079_2019-03-17_final
2019-03-22 09:49:10	ga_ls8c_ard_3-1-0_095080_2019-03-22_final
2019-03-23 10:30:02	ga_ls8c_ard_3-1-0_102074_2019-03-23_final
2019-03-29 09:57:20	ga_ls8c_ard_3-1-0_096085_2019-03-29_final
2019-04-07 11:22:48	ga_ls8c_ard_3-1-0_111067_2019-04-07_final
2019-04-07 11:26:24	ga_ls8c_ard_3-1-0_111076_2019-04-07_final
2019-04-11 09:22:22	ga_ls8c_ard_3-1-0_091075_2019-04-10_final
2019-04-11 09:27:57	ga_ls8c_ard_3-1-0_091089_2019-04-10_final
2019-04-14 09:52:03	ga_ls8c_ard_3-1-0_096072_2019-04-14_final
2019-06-14 09:24:42	ga_ls8c_ard_3-1-0_091080_2019-06-13_final
2019-07-02 10:46:07	ga_ls8c_ard_3-1-0_105067_2019-07-02_final
2019-07-23 11:08:20	ga_ls8c_ard_3-1-0_108076_2019-07-23_final
2019-07-28 11:23:19	ga_ls8c_ard_3-1-0_111067_2019-07-28_final
2019-08-03 10:47:04	ga_ls8c_ard_3-1-0_105069_2019-08-03_final
2019-08-17 09:23:25	ga_ls8c_ard_3-1-0_091076_2019-08-16_final
2019-08-20 09:52:44	ga_ls8c_ard_3-1-0_096072_2019-08-20_final
2019-09-04 10:48:25	ga_ls8c_ard_3-1-0_105072_2019-09-04_final
2019-09-05 09:52:48	ga_ls8c_ard_3-1-0_096072_2019-09-05_final
2019-09-09 11:09:46	ga_ls8c_ard_3-1-0_108079_2019-09-09_final
2019-09-14 09:46:40	ga_ls8c_ard_3-1-0_095072_2019-09-14_final
2019-09-14 11:25:09	ga_ls8c_ard_3-1-0_111071_2019-09-14_final
2019-09-20 10:48:30	ga_ls8c_ard_3-1-0_105072_2019-09-20_final
2019-10-06 10:48:35	ga_ls8c_ard_3-1-0_105072_2019-10-06_final
2019-10-07 09:52:57	ga_ls8c_ard_3-1-0_096072_2019-10-07_final
2019-10-11 11:05:56	ga_ls8c_ard_3-1-0_108069_2019-10-11_final
2019-10-17 10:32:03	ga_ls8c_ard_3-1-0_102077_2019-10-17_final
2019-10-20 09:22:29	ga_ls8c_ard_3-1-0_091073_2019-10-19_final
2019-10-20 09:25:40	ga_ls8c_ard_3-1-0_091081_2019-10-19_final
2019-10-20 09:26:04	ga_ls8c_ard_3-1-0_091082_2019-10-19_final
2019-10-23 09:56:58	ga_ls8c_ard_3-1-0_096082_2019-10-23_final
2019-11-05 09:28:03	ga_ls8c_ard_3-1-0_091087_2019-11-04_final
2019-11-07 10:49:23	ga_ls8c_ard_3-1-0_105074_2019-11-07_final
2019-11-12 11:05:55	ga_ls8c_ard_3-1-0_108069_2019-11-12_final
2019-11-12 11:10:18	ga_ls8c_ard_3-1-0_108080_2019-11-12_final
2019-11-17 11:30:25	ga_ls8c_ard_3-1-0_111084_2019-11-17_final
2019-11-23 10:51:19	ga_ls8c_ard_3-1-0_105079_2019-11-23_final
2019-11-28 11:11:03	ga_ls8c_ard_3-1-0_108082_2019-11-28_final
2019-12-09 10:47:19	ga_ls8c_ard_3-1-0_105069_2019-12-09_final
2019-12-09 10:51:18	ga_ls8c_ard_3-1-0_105079_2019-12-09_final
2019-12-25 10:49:16	ga_ls8c_ard_3-1-0_105074_2019-12-25_final
2019-12-25 10:51:39	ga_ls8c_ard_3-1-0_105080_2019-12-25_final
2019-12-26 09:56:50	ga_ls8c_ard_3-1-0_096082_2019-12-26_final
2020-01-15 11:09:19	ga_ls8c_ard_3-1-0_108078_2020-01-15_final
2020-01-20 11:27:50	ga_ls8c_ard_3-1-0_111078_2020-01-20_final
2020-01-20 11:28:38	ga_ls8c_ard_3-1-0_111080_2020-01-20_final
2020-01-21 10:31:49	ga_ls8c_ard_3-1-0_102077_2020-01-21_final
2020-01-26 10:51:31	ga_ls8c_ard_3-1-0_105080_2020-01-26_final
2020-02-05 11:26:33	ga_ls8c_ard_3-1-0_111075_2020-02-05_final
2020-02-06 10:32:55	ga_ls8c_ard_3-1-0_102080_2020-02-06_final
2020-02-12 09:52:38	ga_ls8c_ard_3-1-0_096072_2020-02-12_final
2020-02-28 09:56:33	ga_ls8c_ard_3-1-0_096082_2020-02-28_final
2020-03-08 09:49:31	ga_ls8c_ard_3-1-0_095080_2020-03-08_final
2020-03-08 11:24:48	ga_ls8c_ard_3-1-0_111071_2020-03-08_final
2020-03-19 11:11:22	ga_ls8c_ard_3-1-0_108084_2020-03-19_final
2020-03-24 09:46:35	ga_ls8c_ard_3-1-0_095073_2020-03-24_final
2020-03-25 10:32:37	ga_ls8c_ard_3-1-0_102080_2020-03-25_final
2020-03-28 09:28:36	ga_ls8c_ard_3-1-0_091090_2020-03-27_final
2020-03-30 10:51:31	ga_ls8c_ard_3-1-0_105081_2020-03-30_final
2020-04-15 10:47:00	ga_ls8c_ard_3-1-0_105070_2020-04-15_final
2020-04-15 10:48:12	ga_ls8c_ard_3-1-0_105073_2020-04-15_final
2020-04-16 09:56:10	ga_ls8c_ard_3-1-0_096082_2020-04-16_final
2020-04-20 11:05:07	ga_ls8c_ard_3-1-0_108069_2020-04-20_final
2020-04-25 09:47:07	ga_ls8c_ard_3-1-0_095075_2020-04-25_final
2020-05-01 10:48:52	ga_ls8c_ard_3-1-0_105075_2020-05-01_final
2022-03-31 10:33:00	ga_ls8c_ard_3-2-1_102081_2022-03-31_final
2022-04-02 10:21:50	ga_ls8c_ard_3-2-1_100084_2022-04-02_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-09 10:22:29	ga_ls8c_ard_3-2-1_101070_2022-04-09_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-10 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-04-10_final
2022-04-12 10:54:37	ga_ls8c_ard_3-2-1_106073_2022-04-12_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-17 09:40:16	ga_ls8c_ard_3-2-1_093088_2022-04-17_final
2022-04-19 09:23:06	ga_ls8c_ard_3-2-1_091076_2022-04-18_final
2022-04-19 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-04-18_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-26 09:34:26	ga_ls8c_ard_3-2-1_092089_2022-04-26_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-28 10:54:09	ga_ls8c_ard_3-2-1_106072_2022-04-28_final
2022-04-28 10:54:33	ga_ls8c_ard_3-2-1_106073_2022-04-28_final
2022-04-29 09:58:31	ga_ls8c_ard_3-2-1_097072_2022-04-29_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-05 09:23:07	ga_ls8c_ard_3-2-1_091076_2022-05-04_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-21 09:26:49	ga_ls8c_ard_3-2-1_091085_2022-05-20_final
2022-05-24 09:56:31	ga_ls8c_ard_3-2-1_096082_2022-05-24_final
2022-05-30 10:54:21	ga_ls8c_ard_3-2-1_106072_2022-05-30_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-04 09:38:04	ga_ls8c_ard_3-2-1_093082_2022-06-04_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-15 10:54:33	ga_ls8c_ard_3-2-1_106072_2022-06-15_final
2022-06-16 09:56:57	ga_ls8c_ard_3-2-1_097067_2022-06-16_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-16 10:01:44	ga_ls8c_ard_3-2-1_097079_2022-06-16_final
2022-06-17 10:42:13	ga_ls8c_ard_3-2-1_104072_2022-06-17_final
2022-06-20 09:36:39	ga_ls8c_ard_3-2-1_093078_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