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
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-24 09:51:43	ga_ls8c_ard_3-2-1_096070_2022-05-24_final
2022-06-03 10:32:29	ga_ls8c_ard_3-2-1_102079_2022-06-03_final
2022-06-13 09:29:13	ga_ls8c_ard_3-2-1_092075_2022-06-12_final
2022-06-15 10:57:45	ga_ls8c_ard_3-2-1_106080_2022-06-15_final
2022-06-22 10:59:59	ga_ls8c_ard_3-2-1_107070_2022-06-22_final
2022-06-27 09:44:27	ga_ls8c_ard_3-2-1_094082_2022-06-27_final
2022-07-08 11:02:24	ga_ls8c_ard_3-2-1_107076_2022-07-08_final
2022-07-10 09:11:33	ga_ls8c_ard_3-2-1_089077_2022-07-09_final
2022-07-12 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-07-12_final
2022-07-20 09:46:17	ga_ls8c_ard_3-2-1_095071_2022-07-20_final
2022-07-26 09:10:29	ga_ls8c_ard_3-2-1_089074_2022-07-25_final
2022-08-09 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-08-09_final
2022-08-14 09:45:56	ga_ls8c_ard_3-2-1_094085_2022-08-14_final
2022-08-18 09:18:02	ga_ls8c_ard_3-2-1_090077_2022-08-17_final
2022-08-18 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-08-18_final
2022-08-24 11:59:07	ga_ls8c_ard_3-2-1_116078_2022-08-24_final
2022-08-26 10:07:29	ga_ls8c_ard_3-2-1_098077_2022-08-26_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-12 10:47:13	ga_ls8c_ard_3-2-1_105068_2022-09-12_final
2022-09-15 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-09-15_final
2022-09-17 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-09-16_final
2022-09-21 10:41:29	ga_ls8c_ard_3-2-1_104069_2022-09-21_final
2022-09-22 09:47:27	ga_ls8c_ard_3-2-1_095073_2022-09-22_final
2022-09-28 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-09-27_final
2022-10-03 09:34:04	ga_ls8c_ard_3-2-1_092086_2022-10-03_final
2022-10-13 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-10-13_final
2022-10-15 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-10-15_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-11-06 09:23:19	ga_ls8c_ard_3-2-1_090090_2022-11-05_final
2022-11-11 11:17:07	ga_ls8c_ard_3-2-1_109081_2022-11-11_final
2022-11-13 11:02:44	ga_ls8c_ard_3-2-1_107076_2022-11-13_final
2022-11-14 11:47:59	ga_ls8c_ard_3-2-1_114081_2022-11-14_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-21 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-11-21_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-03 10:40:00	ga_ls8c_ard_3-2-1_103081_2022-12-03_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-13 11:13:50	ga_ls8c_ard_3-2-1_109073_2022-12-13_final
2022-12-14 10:20:12	ga_ls8c_ard_3-2-1_100078_2022-12-14_final
2022-12-22 11:07:08	ga_ls8c_ard_3-2-1_108072_2022-12-22_final
2022-12-23 11:52:47	ga_ls8c_ard_3-2-1_115078_2022-12-23_final
2022-12-29 09:40:02	ga_ls8c_ard_3-2-1_093086_2022-12-29_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-23 11:11:53	ga_ls8c_ard_3-2-1_108084_2023-01-23_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-06 11:21:04	ga_ls8c_ard_3-2-1_110076_2023-02-06_final
2023-02-08 09:34:12	ga_ls8c_ard_3-2-1_092087_2023-02-08_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-03-07 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-03-07_final
2023-03-14 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-03-13_final
2023-03-20 10:19:36	ga_ls8c_ard_3-2-1_100078_2023-03-20_final
2023-03-23 09:13:09	ga_ls8c_ard_3-2-1_089082_2023-03-22_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-03-26 11:18:56	ga_ls8c_ard_3-2-1_110072_2023-03-26_final
2023-03-29 10:15:19	ga_ls8c_ard_3-2-1_099083_2023-03-29_final
2023-03-31 09:58:09	ga_ls8c_ard_3-2-1_097071_2023-03-31_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-11 09:40:11	ga_ls8c_ard_3-2-1_094073_2023-04-11_final
2023-04-11 09:40:35	ga_ls8c_ard_3-2-1_094074_2023-04-11_final
2023-04-11 11:23:27	ga_ls8c_ard_3-2-1_110084_2023-04-11_final
2023-04-24 09:10:50	ga_ls8c_ard_3-2-1_089077_2023-04-23_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-04-28 10:24:59	ga_ls8c_ard_3-2-1_101077_2023-04-28_final
2023-05-06 09:34:39	ga_ls8c_ard_3-2-1_093075_2023-05-06_final
2023-05-10 10:45:57	ga_ls8c_ard_3-2-1_105068_2023-05-10_final
2023-05-10 10:47:56	ga_ls8c_ard_3-2-1_105073_2023-05-10_final
2023-05-10 10:51:08	ga_ls8c_ard_3-2-1_105081_2023-05-10_final
2023-05-24 09:27:46	ga_ls8c_ard_3-2-1_091089_2023-05-23_final
2023-05-31 11:06:51	ga_ls8c_ard_3-2-1_108074_2023-05-31_final
2023-06-01 10:10:02	ga_ls8c_ard_3-2-1_099071_2023-06-01_final
2023-06-08 10:21:06	ga_ls8c_ard_3-2-1_100083_2023-06-08_final
2023-06-09 09:21:53	ga_ls8c_ard_3-2-1_091074_2023-06-08_final
2023-06-09 09:26:41	ga_ls8c_ard_3-2-1_091086_2023-06-08_final
2023-06-10 10:03:58	ga_ls8c_ard_3-2-1_098071_2023-06-10_final
2023-06-21 11:29:09	ga_ls8c_ard_3-2-1_111083_2023-06-21_final
2023-06-25 11:04:52	ga_ls8c_ard_3-2-1_107084_2023-06-25_final
2023-06-26 11:44:09	ga_ls8c_ard_3-2-1_114074_2023-06-26_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_final
2023-07-28 10:04:21	ga_ls8c_ard_3-2-1_098071_2023-07-28_final
2023-08-06 10:03:25	ga_ls8c_ard_3-2-1_097084_2023-08-06_final
2023-08-12 11:02:26	ga_ls8c_ard_3-2-1_107077_2023-08-12_final
2023-08-13 10:03:14	ga_ls8c_ard_3-2-1_098068_2023-08-13_final
2023-08-19 11:07:06	ga_ls8c_ard_3-2-1_108073_2023-08-19_final
2023-08-19 11:09:54	ga_ls8c_ard_3-2-1_108080_2023-08-19_final
2023-08-29 11:47:25	ga_ls8c_ard_3-2-1_114081_2023-08-29_final
2023-09-02 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-09-02_final
2023-09-06 10:53:09	ga_ls8c_ard_3-2-1_106069_2023-09-06_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