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
2022-01-14 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-01-14_final
2022-05-21 11:04:54	ga_ls8c_ard_3-2-1_107083_2022-05-21_final
2022-05-30 10:53:09	ga_ls8c_ard_3-2-1_106069_2022-05-30_final
2022-05-31 09:57:33	ga_ls8c_ard_3-2-1_097069_2022-05-31_final
2022-05-31 10:01:56	ga_ls8c_ard_3-2-1_097080_2022-05-31_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-06-03 10:28:53	ga_ls8c_ard_3-2-1_102070_2022-06-03_final
2022-06-17 09:07:19	ga_ls8c_ard_3-2-1_088082_2022-06-16_final
2022-06-20 09:39:26	ga_ls8c_ard_3-2-1_093085_2022-06-20_final
2022-06-22 09:26:41	ga_ls8c_ard_3-2-1_091084_2022-06-21_final
2022-06-23 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-06-23_final
2022-06-24 09:12:21	ga_ls8c_ard_3-2-1_089079_2022-06-23_final
2022-06-24 09:16:20	ga_ls8c_ard_3-2-1_089089_2022-06-23_final
2022-07-05 10:29:07	ga_ls8c_ard_3-2-1_102070_2022-07-05_final
2022-07-08 09:25:55	ga_ls8c_ard_3-2-1_091082_2022-07-07_final
2022-07-08 11:02:24	ga_ls8c_ard_3-2-1_107076_2022-07-08_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-20 11:25:58	ga_ls8c_ard_3-2-1_111073_2022-07-20_final
2022-07-31 11:07:34	ga_ls8c_ard_3-2-1_108073_2022-07-31_final
2022-08-02 10:58:01	ga_ls8c_ard_3-2-1_106080_2022-08-02_final
2022-08-03 10:01:36	ga_ls8c_ard_3-2-1_097078_2022-08-03_final
2022-08-03 11:38:53	ga_ls8c_ard_3-2-1_113074_2022-08-03_final
2022-08-09 11:05:51	ga_ls8c_ard_3-2-1_107084_2022-08-09_final
2022-08-13 10:39:33	ga_ls8c_ard_3-2-1_103080_2022-08-13_final
2022-08-14 09:45:56	ga_ls8c_ard_3-2-1_094085_2022-08-14_final
2022-08-27 09:12:15	ga_ls8c_ard_3-2-1_089078_2022-08-26_final
2022-08-29 10:35:35	ga_ls8c_ard_3-2-1_103070_2022-08-29_final
2022-09-01 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-09-01_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-14 10:39:40	ga_ls8c_ard_3-2-1_103080_2022-09-14_final
2022-09-15 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-09-15_final
2022-09-15 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-09-15_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-20 11:51:47	ga_ls8c_ard_3-2-1_115075_2022-10-20_final
2022-10-24 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-10-24_final
2022-11-06 09:23:19	ga_ls8c_ard_3-2-1_090090_2022-11-05_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-12 10:18:17	ga_ls8c_ard_3-2-1_100073_2022-11-12_final
2022-12-06 09:33:36	ga_ls8c_ard_3-2-1_092085_2022-12-06_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-13 11:13:50	ga_ls8c_ard_3-2-1_109073_2022-12-13_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2023-01-08 11:51:36	ga_ls8c_ard_3-2-1_115075_2023-01-08_final
2023-01-23 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-01-23_final
2023-01-24 10:16:16	ga_ls8c_ard_3-2-1_099084_2023-01-24_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-20 11:31:38	ga_ls8c_ard_3-2-1_112072_2023-02-20_final
2023-02-22 11:22:49	ga_ls8c_ard_3-2-1_110081_2023-02-22_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-24 11:07:13	ga_ls8c_ard_3-2-1_108073_2023-02-24_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-07 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-03-07_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-10 09:40:36	ga_ls8c_ard_3-2-1_094073_2023-03-10_final
2023-03-13 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-03-13_final
2023-03-15 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-03-15_final
2023-03-17 11:23:38	ga_ls8c_ard_3-2-1_111068_2023-03-17_final
2023-03-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2023-03-18_final
2023-03-19 09:34:45	ga_ls8c_ard_3-2-1_093074_2023-03-19_final
2023-03-20 10:22:00	ga_ls8c_ard_3-2-1_100084_2023-03-20_final
2023-03-21 09:24:45	ga_ls8c_ard_3-2-1_091080_2023-03-20_final
2023-03-23 10:48:51	ga_ls8c_ard_3-2-1_105074_2023-03-23_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-05-10 10:45:57	ga_ls8c_ard_3-2-1_105068_2023-05-10_final
2023-05-11 09:56:41	ga_ls8c_ard_3-2-1_096084_2023-05-11_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-15 09:32:20	ga_ls8c_ard_3-2-1_092085_2023-05-15_final
2023-05-24 09:25:46	ga_ls8c_ard_3-2-1_091084_2023-05-23_final
2023-05-27 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-27_final
2023-05-29 09:45:07	ga_ls8c_ard_3-2-1_094086_2023-05-29_final
2023-05-31 11:06:27	ga_ls8c_ard_3-2-1_108073_2023-05-31_final
2023-05-31 11:10:03	ga_ls8c_ard_3-2-1_108082_2023-05-31_final
2023-06-01 10:12:02	ga_ls8c_ard_3-2-1_099076_2023-06-01_final
2023-06-08 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-06-08_final
2023-06-12 09:57:13	ga_ls8c_ard_3-2-1_096085_2023-06-12_final
2023-06-19 11:40:43	ga_ls8c_ard_3-2-1_113081_2023-06-19_final
2023-06-26 11:44:09	ga_ls8c_ard_3-2-1_114074_2023-06-26_final
2023-07-04 10:54:50	ga_ls8c_ard_3-2-1_106074_2023-07-04_final
2023-07-07 11:24:10	ga_ls8c_ard_3-2-1_111070_2023-07-07_final
2023-07-10 10:18:35	ga_ls8c_ard_3-2-1_100076_2023-07-10_final
2023-07-12 10:03:27	ga_ls8c_ard_3-2-1_098069_2023-07-12_final
2023-07-13 10:45:55	ga_ls8c_ard_3-2-1_105067_2023-07-13_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_final
2023-07-19 10:15:37	ga_ls8c_ard_3-2-1_099084_2023-07-19_final
2023-07-22 09:06:03	ga_ls8c_ard_3-2-1_088080_2023-07-21_final
2023-07-26 10:17:05	ga_ls8c_ard_3-2-1_100072_2023-07-26_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-08-01 09:45:39	ga_ls8c_ard_3-2-1_094086_2023-08-01_final
2023-08-01 11:20:33	ga_ls8c_ard_3-2-1_110076_2023-08-01_final
2023-08-03 09:28:55	ga_ls8c_ard_3-2-1_092075_2023-08-02_final
2023-08-05 10:52:39	ga_ls8c_ard_3-2-1_106068_2023-08-05_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-14 09:13:13	ga_ls8c_ard_3-2-1_089082_2023-08-13_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