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
2016-02-14 09:27:13	ga_ls8c_ard_3-1-0_091086_2016-02-13_final
2019-03-10 09:24:54	ga_ls8c_ard_3-1-0_091081_2019-03-09_final
2019-03-10 09:25:18	ga_ls8c_ard_3-1-0_091082_2019-03-09_final
2019-04-07 09:47:31	ga_ls8c_ard_3-1-0_095076_2019-04-07_final
2019-06-14 09:23:06	ga_ls8c_ard_3-1-0_091076_2019-06-13_final
2019-06-17 09:56:25	ga_ls8c_ard_3-1-0_096082_2019-06-17_final
2019-06-26 09:49:29	ga_ls8c_ard_3-1-0_095080_2019-06-26_final
2019-06-30 09:23:35	ga_ls8c_ard_3-1-0_091077_2019-06-29_final
2019-07-16 09:26:25	ga_ls8c_ard_3-1-0_091084_2019-07-15_final
2019-07-28 09:51:13	ga_ls8c_ard_3-1-0_095084_2019-07-28_final
2019-08-01 09:24:56	ga_ls8c_ard_3-1-0_091080_2019-07-31_final
2019-08-01 09:26:07	ga_ls8c_ard_3-1-0_091083_2019-07-31_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-09-02 09:23:53	ga_ls8c_ard_3-1-0_091077_2019-09-01_final
2019-09-02 09:25:29	ga_ls8c_ard_3-1-0_091081_2019-09-01_final
2019-09-02 09:25:52	ga_ls8c_ard_3-1-0_091082_2019-09-01_final
2019-09-14 09:51:52	ga_ls8c_ard_3-1-0_095085_2019-09-14_final
2019-09-18 09:25:10	ga_ls8c_ard_3-1-0_091080_2019-09-17_final
2019-09-21 09:52:30	ga_ls8c_ard_3-1-0_096071_2019-09-21_final
2019-09-30 09:49:57	ga_ls8c_ard_3-1-0_095080_2019-09-30_final
2019-10-16 09:52:23	ga_ls8c_ard_3-1-0_095086_2019-10-16_final
2019-10-20 09:24:04	ga_ls8c_ard_3-1-0_091077_2019-10-19_final
2019-10-20 09:26:52	ga_ls8c_ard_3-1-0_091084_2019-10-19_final
2019-10-23 09:56:34	ga_ls8c_ard_3-1-0_096081_2019-10-23_final
2019-10-23 09:56:58	ga_ls8c_ard_3-1-0_096082_2019-10-23_final
2019-11-01 09:47:59	ga_ls8c_ard_3-1-0_095075_2019-11-01_final
2019-11-17 09:46:21	ga_ls8c_ard_3-1-0_095071_2019-11-17_final
2019-11-17 09:47:32	ga_ls8c_ard_3-1-0_095074_2019-11-17_final
2019-11-24 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-11-24_final
2020-01-08 09:24:16	ga_ls8c_ard_3-1-0_091078_2020-01-07_final
2020-01-08 09:28:40	ga_ls8c_ard_3-1-0_091089_2020-01-07_final
2020-02-05 09:48:04	ga_ls8c_ard_3-1-0_095076_2020-02-05_final
2020-02-21 09:49:36	ga_ls8c_ard_3-1-0_095080_2020-02-21_final
2020-02-25 09:28:27	ga_ls8c_ard_3-1-0_091089_2020-02-24_final
2020-03-28 09:25:49	ga_ls8c_ard_3-1-0_091083_2020-03-27_final
2020-04-13 09:24:05	ga_ls8c_ard_3-1-0_091079_2020-04-12_final
2020-04-25 09:49:31	ga_ls8c_ard_3-1-0_095081_2020-04-25_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-04-01 09:34:35	ga_ls8c_ard_3-2-1_093074_2022-04-01_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-02 10:17:50	ga_ls8c_ard_3-2-1_100074_2022-04-02_final
2022-04-04 10:07:53	ga_ls8c_ard_3-2-1_098080_2022-04-04_final
2022-04-04 11:45:34	ga_ls8c_ard_3-2-1_114077_2022-04-04_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-11 11:51:25	ga_ls8c_ard_3-2-1_115076_2022-04-11_final
2022-04-12 09:18:07	ga_ls8c_ard_3-2-1_090079_2022-04-11_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-15 11:27:31	ga_ls8c_ard_3-2-1_111078_2022-04-15_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-25 10:26:04	ga_ls8c_ard_3-2-1_101079_2022-04-25_final
2022-04-28 10:56:56	ga_ls8c_ard_3-2-1_106079_2022-04-28_final
2022-04-29 09:58:55	ga_ls8c_ard_3-2-1_097073_2022-04-29_final
2022-04-29 10:01:43	ga_ls8c_ard_3-2-1_097080_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:41:24	ga_ls8c_ard_3-2-1_104071_2022-04-30_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-01 09:49:47	ga_ls8c_ard_3-2-1_095081_2022-05-01_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-04 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-05-04_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-07 09:13:10	ga_ls8c_ard_3-2-1_089082_2022-05-06_final
2022-05-07 09:14:22	ga_ls8c_ard_3-2-1_089085_2022-05-06_final
2022-05-08 11:32:32	ga_ls8c_ard_3-2-1_112075_2022-05-08_final
2022-05-09 10:38:55	ga_ls8c_ard_3-2-1_103080_2022-05-09_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-11 10:26:58	ga_ls8c_ard_3-2-1_101081_2022-05-11_final
2022-05-12 11:05:27	ga_ls8c_ard_3-2-1_108069_2022-05-12_final
2022-05-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-05-17_final
2022-05-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-05-17_final
2022-05-17 11:27:37	ga_ls8c_ard_3-2-1_111078_2022-05-17_final
2022-05-19 09:36:47	ga_ls8c_ard_3-2-1_093079_2022-05-19_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-19 11:15:16	ga_ls8c_ard_3-2-1_109078_2022-05-19_final
2022-05-20 10:18:51	ga_ls8c_ard_3-2-1_100076_2022-05-20_final
2022-05-24 09:54:55	ga_ls8c_ard_3-2-1_096078_2022-05-24_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-25 10:38:58	ga_ls8c_ard_3-2-1_103080_2022-05-25_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-06-02 09:48:00	ga_ls8c_ard_3-2-1_095076_2022-06-02_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 10:20:33	ga_ls8c_ard_3-2-1_100080_2022-06-05_final
2022-06-08 09:13:00	ga_ls8c_ard_3-2-1_089081_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-16 09:59:21	ga_ls8c_ard_3-2-1_097073_2022-06-16_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-16 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-06-16_final
2022-06-18 11:26:41	ga_ls8c_ard_3-2-1_111075_2022-06-18_final
2022-06-19 10:31:04	ga_ls8c_ard_3-2-1_102075_2022-06-19_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_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