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
2019-03-13 09:52:35	ga_ls8c_ard_3-1-0_096073_2019-03-13_final
2019-03-22 09:50:46	ga_ls8c_ard_3-1-0_095084_2019-03-22_final
2019-06-17 09:53:13	ga_ls8c_ard_3-1-0_096074_2019-06-17_final
2019-06-17 09:53:37	ga_ls8c_ard_3-1-0_096075_2019-06-17_final
2019-06-17 09:58:00	ga_ls8c_ard_3-1-0_096086_2019-06-17_final
2019-07-03 09:53:41	ga_ls8c_ard_3-1-0_096075_2019-07-03_final
2019-07-03 09:56:05	ga_ls8c_ard_3-1-0_096081_2019-07-03_final
2019-07-07 11:10:16	ga_ls8c_ard_3-1-0_108081_2019-07-07_final
2019-07-16 09:25:13	ga_ls8c_ard_3-1-0_091081_2019-07-15_final
2019-07-28 09:51:13	ga_ls8c_ard_3-1-0_095084_2019-07-28_final
2019-08-13 09:50:55	ga_ls8c_ard_3-1-0_095083_2019-08-13_final
2019-08-20 09:51:57	ga_ls8c_ard_3-1-0_096070_2019-08-20_final
2019-08-20 09:57:32	ga_ls8c_ard_3-1-0_096084_2019-08-20_final
2019-09-05 09:58:23	ga_ls8c_ard_3-1-0_096086_2019-09-05_final
2019-10-23 09:52:11	ga_ls8c_ard_3-1-0_096070_2019-10-23_final
2019-11-01 09:48:47	ga_ls8c_ard_3-1-0_095077_2019-11-01_final
2019-11-08 09:52:10	ga_ls8c_ard_3-1-0_096070_2019-11-08_final
2019-11-12 11:07:06	ga_ls8c_ard_3-1-0_108072_2019-11-12_final
2019-11-21 09:28:47	ga_ls8c_ard_3-1-0_091089_2019-11-20_final
2020-01-08 09:28:40	ga_ls8c_ard_3-1-0_091089_2020-01-07_final
2020-02-05 09:49:15	ga_ls8c_ard_3-1-0_095079_2020-02-05_final
2020-02-25 09:24:28	ga_ls8c_ard_3-1-0_091079_2020-02-24_final
2020-03-08 09:50:18	ga_ls8c_ard_3-1-0_095082_2020-03-08_final
2020-03-12 09:24:22	ga_ls8c_ard_3-1-0_091079_2020-03-11_final
2020-03-15 09:52:27	ga_ls8c_ard_3-1-0_096072_2020-03-15_final
2020-03-31 09:53:29	ga_ls8c_ard_3-1-0_096075_2020-03-31_final
2020-04-16 09:53:22	ga_ls8c_ard_3-1-0_096075_2020-04-16_final
2020-04-25 09:51:55	ga_ls8c_ard_3-1-0_095087_2020-04-25_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-03-30 11:26:37	ga_ls8c_ard_3-2-1_111076_2022-03-30_final
2022-03-31 10:29:00	ga_ls8c_ard_3-2-1_102071_2022-03-31_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-03-31 10:32:12	ga_ls8c_ard_3-2-1_102079_2022-03-31_final
2022-04-01 09:35:22	ga_ls8c_ard_3-2-1_093076_2022-04-01_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-08 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-08_final
2022-04-08 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-08_final
2022-04-08 11:22:53	ga_ls8c_ard_3-2-1_110082_2022-04-08_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-11 10:12:56	ga_ls8c_ard_3-2-1_099077_2022-04-11_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-12 09:21:43	ga_ls8c_ard_3-2-1_090088_2022-04-11_final
2022-04-12 10:53:25	ga_ls8c_ard_3-2-1_106070_2022-04-12_final
2022-04-12 10:57:00	ga_ls8c_ard_3-2-1_106079_2022-04-12_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-15 11:26:19	ga_ls8c_ard_3-2-1_111075_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-16 10:29:54	ga_ls8c_ard_3-2-1_102073_2022-04-16_final
2022-04-17 09:37:04	ga_ls8c_ard_3-2-1_093080_2022-04-17_final
2022-04-19 09:25:06	ga_ls8c_ard_3-2-1_091081_2022-04-18_final
2022-04-19 09:26:18	ga_ls8c_ard_3-2-1_091084_2022-04-18_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-20 11:45:15	ga_ls8c_ard_3-2-1_114076_2022-04-20_final
2022-04-22 11:32:29	ga_ls8c_ard_3-2-1_112075_2022-04-22_final
2022-04-22 11:34:28	ga_ls8c_ard_3-2-1_112080_2022-04-22_final
2022-04-24 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-24_final
2022-04-26 11:08:55	ga_ls8c_ard_3-2-1_108078_2022-04-26_final
2022-04-26 11:09:43	ga_ls8c_ard_3-2-1_108080_2022-04-26_final
2022-04-27 10:10:54	ga_ls8c_ard_3-2-1_099072_2022-04-27_final
2022-04-27 10:12:29	ga_ls8c_ard_3-2-1_099076_2022-04-27_final
2022-04-28 09:21:39	ga_ls8c_ard_3-2-1_090088_2022-04-27_final
2022-04-28 10:56:32	ga_ls8c_ard_3-2-1_106078_2022-04-28_final
2022-04-28 10:56:56	ga_ls8c_ard_3-2-1_106079_2022-04-28_final
2022-04-30 10:41:00	ga_ls8c_ard_3-2-1_104070_2022-04-30_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-04 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-05-04_final
2022-05-05 09:23:55	ga_ls8c_ard_3-2-1_091078_2022-05-04_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-06 11:45:16	ga_ls8c_ard_3-2-1_114076_2022-05-06_final
2022-05-10 11:21:47	ga_ls8c_ard_3-2-1_110079_2022-05-10_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-15 09:57:30	ga_ls8c_ard_3-2-1_097069_2022-05-15_final
2022-05-16 10:43:57	ga_ls8c_ard_3-2-1_104077_2022-05-16_final
2022-05-20 10:20:26	ga_ls8c_ard_3-2-1_100080_2022-05-20_final
2022-05-24 09:54:31	ga_ls8c_ard_3-2-1_096077_2022-05-24_final
2022-05-25 10:37:22	ga_ls8c_ard_3-2-1_103076_2022-05-25_final
2022-05-26 09:42:09	ga_ls8c_ard_3-2-1_094077_2022-05-26_final
2022-05-31 10:02:20	ga_ls8c_ard_3-2-1_097081_2022-05-31_final
2022-06-01 09:06:20	ga_ls8c_ard_3-2-1_088080_2022-05-31_final
2022-06-02 11:28:05	ga_ls8c_ard_3-2-1_111079_2022-06-02_final
2022-06-04 09:39:40	ga_ls8c_ard_3-2-1_093086_2022-06-04_final
2022-06-04 11:12:34	ga_ls8c_ard_3-2-1_109071_2022-06-04_final
2022-06-07 10:08:13	ga_ls8c_ard_3-2-1_098080_2022-06-07_final
2022-06-07 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-06-07_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-06-13 11:08:54	ga_ls8c_ard_3-2-1_108077_2022-06-13_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-17 10:45:24	ga_ls8c_ard_3-2-1_104080_2022-06-17_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-18 11:24:17	ga_ls8c_ard_3-2-1_111069_2022-06-18_final
2022-06-18 11:25:29	ga_ls8c_ard_3-2-1_111072_2022-06-18_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