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
2019-03-22 09:49:34	ga_ls8c_ard_3-1-0_095081_2019-03-22_final
2019-03-26 09:28:02	ga_ls8c_ard_3-1-0_091089_2019-03-25_final
2019-06-14 09:26:17	ga_ls8c_ard_3-1-0_091084_2019-06-13_final
2019-06-26 09:50:17	ga_ls8c_ard_3-1-0_095082_2019-06-26_final
2019-07-28 09:50:01	ga_ls8c_ard_3-1-0_095081_2019-07-28_final
2019-08-13 09:48:55	ga_ls8c_ard_3-1-0_095078_2019-08-13_final
2019-08-17 09:26:13	ga_ls8c_ard_3-1-0_091083_2019-08-16_final
2019-08-29 09:46:12	ga_ls8c_ard_3-1-0_095071_2019-08-29_final
2019-09-02 09:26:40	ga_ls8c_ard_3-1-0_091084_2019-09-01_final
2019-09-14 09:46:40	ga_ls8c_ard_3-1-0_095072_2019-09-14_final
2019-09-14 09:49:52	ga_ls8c_ard_3-1-0_095080_2019-09-14_final
2019-09-14 09:50:16	ga_ls8c_ard_3-1-0_095081_2019-09-14_final
2019-09-30 09:49:57	ga_ls8c_ard_3-1-0_095080_2019-09-30_final
2019-10-16 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-10-16_final
2019-11-01 09:47:11	ga_ls8c_ard_3-1-0_095073_2019-11-01_final
2019-11-01 09:51:11	ga_ls8c_ard_3-1-0_095083_2019-11-01_final
2019-11-01 09:52:23	ga_ls8c_ard_3-1-0_095086_2019-11-01_final
2019-11-05 09:24:51	ga_ls8c_ard_3-1-0_091079_2019-11-04_final
2019-11-17 09:46:45	ga_ls8c_ard_3-1-0_095072_2019-11-17_final
2019-11-21 09:25:36	ga_ls8c_ard_3-1-0_091081_2019-11-20_final
2019-12-03 09:51:07	ga_ls8c_ard_3-1-0_095083_2019-12-03_final
2020-01-04 09:47:24	ga_ls8c_ard_3-1-0_095074_2020-01-04_final
2020-01-04 09:49:24	ga_ls8c_ard_3-1-0_095079_2020-01-04_final
2020-01-20 09:46:57	ga_ls8c_ard_3-1-0_095073_2020-01-20_final
2020-01-20 09:49:45	ga_ls8c_ard_3-1-0_095080_2020-01-20_final
2020-02-05 09:51:39	ga_ls8c_ard_3-1-0_095085_2020-02-05_final
2020-02-21 09:49:36	ga_ls8c_ard_3-1-0_095080_2020-02-21_final
2020-02-21 09:50:00	ga_ls8c_ard_3-1-0_095081_2020-02-21_final
2020-03-08 09:51:06	ga_ls8c_ard_3-1-0_095084_2020-03-08_final
2020-03-24 09:49:46	ga_ls8c_ard_3-1-0_095081_2020-03-24_final
2020-03-28 09:25:49	ga_ls8c_ard_3-1-0_091083_2020-03-27_final
2020-04-09 09:48:50	ga_ls8c_ard_3-1-0_095079_2020-04-09_final
2020-04-13 09:25:41	ga_ls8c_ard_3-1-0_091083_2020-04-12_final
2020-04-25 09:46:19	ga_ls8c_ard_3-1-0_095073_2020-04-25_final
2022-03-29 10:44:34	ga_ls8c_ard_3-2-1_104079_2022-03-29_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-03-31 10:30:36	ga_ls8c_ard_3-2-1_102075_2022-03-31_final
2022-04-01 09:37:46	ga_ls8c_ard_3-2-1_093082_2022-04-01_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-05 09:11:05	ga_ls8c_ard_3-2-1_089077_2022-04-04_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-08 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-08_final
2022-04-09 10:24:05	ga_ls8c_ard_3-2-1_101074_2022-04-09_final
2022-04-10 09:30:28	ga_ls8c_ard_3-2-1_092079_2022-04-10_final
2022-04-10 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-04-10_final
2022-04-12 10:56:12	ga_ls8c_ard_3-2-1_106077_2022-04-12_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-13 09:59:48	ga_ls8c_ard_3-2-1_097075_2022-04-13_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-15 09:52:14	ga_ls8c_ard_3-2-1_095087_2022-04-15_final
2022-04-16 10:30:18	ga_ls8c_ard_3-2-1_102074_2022-04-16_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-19 11:03:35	ga_ls8c_ard_3-2-1_107080_2022-04-19_final
2022-04-20 10:09:09	ga_ls8c_ard_3-2-1_098083_2022-04-20_final
2022-04-22 09:55:11	ga_ls8c_ard_3-2-1_096079_2022-04-22_final
2022-04-22 09:56:23	ga_ls8c_ard_3-2-1_096082_2022-04-22_final
2022-04-23 10:34:27	ga_ls8c_ard_3-2-1_103069_2022-04-23_final
2022-04-23 10:38:03	ga_ls8c_ard_3-2-1_103078_2022-04-23_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:09:19	ga_ls8c_ard_3-2-1_108079_2022-04-26_final
2022-04-26 11:10:07	ga_ls8c_ard_3-2-1_108081_2022-04-26_final
2022-04-26 11:10:31	ga_ls8c_ard_3-2-1_108082_2022-04-26_final
2022-05-01 11:25:04	ga_ls8c_ard_3-2-1_111072_2022-05-01_final
2022-05-02 10:30:40	ga_ls8c_ard_3-2-1_102075_2022-05-02_final
2022-05-04 10:21:31	ga_ls8c_ard_3-2-1_100083_2022-05-04_final
2022-05-04 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-05-04_final
2022-05-05 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-05-04_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-09 10:36:31	ga_ls8c_ard_3-2-1_103074_2022-05-09_final
2022-05-10 09:44:06	ga_ls8c_ard_3-2-1_094082_2022-05-10_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-05-14 10:55:06	ga_ls8c_ard_3-2-1_106074_2022-05-14_final
2022-05-15 10:03:53	ga_ls8c_ard_3-2-1_097085_2022-05-15_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2022-05-17_final
2022-05-24 09:55:19	ga_ls8c_ard_3-2-1_096079_2022-05-24_final
2022-05-24 11:34:12	ga_ls8c_ard_3-2-1_112079_2022-05-24_final
2022-05-24 11:34:36	ga_ls8c_ard_3-2-1_112080_2022-05-24_final
2022-05-25 10:36:35	ga_ls8c_ard_3-2-1_103074_2022-05-25_final
2022-05-26 09:42:33	ga_ls8c_ard_3-2-1_094078_2022-05-26_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-30 10:56:20	ga_ls8c_ard_3-2-1_106077_2022-05-30_final
2022-06-08 10:49:06	ga_ls8c_ard_3-2-1_105074_2022-06-08_final
2022-06-13 11:09:41	ga_ls8c_ard_3-2-1_108079_2022-06-13_final
2022-06-13 11:10:29	ga_ls8c_ard_3-2-1_108081_2022-06-13_final
2022-06-13 11:10:53	ga_ls8c_ard_3-2-1_108082_2022-06-13_final
2022-06-15 10:57:45	ga_ls8c_ard_3-2-1_106080_2022-06-15_final
2022-06-16 10:02:08	ga_ls8c_ard_3-2-1_097080_2022-06-16_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 09:49:00	ga_ls8c_ard_3-2-1_095078_2022-06-18_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-19 10:33:04	ga_ls8c_ard_3-2-1_102080_2022-06-19_final
2022-06-20 11:15:32	ga_ls8c_ard_3-2-1_109078_2022-06-20_final
2022-06-20 11:15:56	ga_ls8c_ard_3-2-1_109079_2022-06-20_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-21 10:20:43	ga_ls8c_ard_3-2-1_100080_2022-06-21_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