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
2023-02-03 10:48:35	ga_ls8c_ard_3-2-1_105072_2023-02-03_final
2023-02-28 10:43:17	ga_ls8c_ard_3-2-1_104075_2023-02-28_final
2023-03-02 10:33:42	ga_ls8c_ard_3-2-1_102082_2023-03-02_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-05 11:01:47	ga_ls8c_ard_3-2-1_107075_2023-03-05_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-03-19 11:16:50	ga_ls8c_ard_3-2-1_109082_2023-03-19_final
2023-03-20 11:58:05	ga_ls8c_ard_3-2-1_116077_2023-03-20_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-27 10:24:06	ga_ls8c_ard_3-2-1_101074_2023-03-27_final
2023-03-29 10:11:20	ga_ls8c_ard_3-2-1_099073_2023-03-29_final
2023-04-04 11:17:26	ga_ls8c_ard_3-2-1_109084_2023-04-04_final
2023-04-08 09:12:57	ga_ls8c_ard_3-2-1_089082_2023-04-07_final
2023-04-11 09:45:22	ga_ls8c_ard_3-2-1_094086_2023-04-11_final
2023-04-16 10:01:54	ga_ls8c_ard_3-2-1_097081_2023-04-16_final
2023-04-16 10:02:42	ga_ls8c_ard_3-2-1_097083_2023-04-16_final
2023-04-29 11:10:38	ga_ls8c_ard_3-2-1_108083_2023-04-29_final
2023-05-01 10:54:16	ga_ls8c_ard_3-2-1_106073_2023-05-01_final
2023-05-02 11:40:18	ga_ls8c_ard_3-2-1_113080_2023-05-02_final
2023-05-08 09:24:39	ga_ls8c_ard_3-2-1_091081_2023-05-07_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-10 09:13:03	ga_ls8c_ard_3-2-1_089083_2023-05-09_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-16 11:51:16	ga_ls8c_ard_3-2-1_115077_2023-05-16_final
2023-05-28 10:33:34	ga_ls8c_ard_3-2-1_103068_2023-05-28_final
2023-06-01 11:51:19	ga_ls8c_ard_3-2-1_115077_2023-06-01_final
2023-06-07 09:34:37	ga_ls8c_ard_3-2-1_093075_2023-06-07_final
2023-06-17 10:10:35	ga_ls8c_ard_3-2-1_099072_2023-06-17_final
2023-06-18 10:53:03	ga_ls8c_ard_3-2-1_106070_2023-06-18_final
2023-06-27 09:12:28	ga_ls8c_ard_3-2-1_089081_2023-06-26_final
2023-06-30 09:41:25	ga_ls8c_ard_3-2-1_094076_2023-06-30_final
2023-06-30 11:22:41	ga_ls8c_ard_3-2-1_110082_2023-06-30_final
2023-07-06 09:06:00	ga_ls8c_ard_3-2-1_088080_2023-07-05_final
2023-07-10 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-07-10_final
2023-07-11 11:03:51	ga_ls8c_ard_3-2-1_107081_2023-07-11_final
2023-07-23 09:50:32	ga_ls8c_ard_3-2-1_095083_2023-07-23_final
2023-07-29 09:13:56	ga_ls8c_ard_3-2-1_089084_2023-07-28_final
2023-08-03 11:10:35	ga_ls8c_ard_3-2-1_108082_2023-08-03_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-13 10:06:49	ga_ls8c_ard_3-2-1_098077_2023-08-13_final
2023-08-14 09:11:37	ga_ls8c_ard_3-2-1_089078_2023-08-13_final
2023-08-21 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-08-20_final
2023-08-23 10:46:00	ga_ls8c_ard_3-2-1_104082_2023-08-23_final
2023-08-27 10:18:06	ga_ls8c_ard_3-2-1_100074_2023-08-27_final
2023-09-03 10:23:04	ga_ls8c_ard_3-2-1_101071_2023-09-03_final
2023-09-05 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-09-05_final
2023-09-13 09:28:07	ga_ls8c_ard_3-2-1_091088_2023-09-12_final
2023-09-14 10:10:11	ga_ls8c_ard_3-2-1_098085_2023-09-14_final
2023-09-15 10:47:04	ga_ls8c_ard_3-2-1_105069_2023-09-15_final
2023-09-20 11:10:48	ga_ls8c_ard_3-2-1_108082_2023-09-20_final
2023-09-24 10:42:54	ga_ls8c_ard_3-2-1_104074_2023-09-24_final
2023-09-25 09:51:41	ga_ls8c_ard_3-2-1_095085_2023-09-25_final
2023-10-03 10:39:57	ga_ls8c_ard_3-2-1_103082_2023-10-03_final
2023-10-07 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-10-07_final
2023-10-13 09:40:36	ga_ls8c_ard_3-2-1_093088_2023-10-13_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_final
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_final
2023-10-16 11:45:59	ga_ls8c_ard_3-2-1_114077_2023-10-16_final
2023-10-17 09:12:40	ga_ls8c_ard_3-2-1_089080_2023-10-16_final
2023-10-20 11:21:14	ga_ls8c_ard_3-2-1_110077_2023-10-20_final
2023-11-07 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-11-07_final
2023-11-17 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-11-17_final
2023-11-19 09:58:00	ga_ls8c_ard_3-2-1_096085_2023-11-19_final
2023-11-21 11:22:56	ga_ls8c_ard_3-2-1_110081_2023-11-21_final
2023-11-21 11:24:08	ga_ls8c_ard_3-2-1_110084_2023-11-21_final
2023-11-23 09:33:18	ga_ls8c_ard_3-2-1_092085_2023-11-23_final
2023-11-23 11:11:23	ga_ls8c_ard_3-2-1_108083_2023-11-23_final
2023-11-26 09:59:01	ga_ls8c_ard_3-2-1_097072_2023-11-26_final
2023-11-28 11:27:07	ga_ls8c_ard_3-2-1_111076_2023-11-28_final
2023-11-29 10:30:41	ga_ls8c_ard_3-2-1_102074_2023-11-29_final
2023-12-06 10:36:21	ga_ls8c_ard_3-2-1_103073_2023-12-06_final
2023-12-09 11:08:27	ga_ls8c_ard_3-2-1_108076_2023-12-09_final
2023-12-10 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-12-10_final
2023-12-16 11:15:31	ga_ls8c_ard_3-2-1_109078_2023-12-16_final
2023-12-22 10:35:16	ga_ls8c_ard_3-2-1_103070_2023-12-22_final
2023-12-28 11:41:25	ga_ls8c_ard_3-2-1_113081_2023-12-28_final
2024-01-01 09:34:58	ga_ls8c_ard_3-2-1_093074_2024-01-01_final
2024-01-08 11:21:12	ga_ls8c_ard_3-2-1_110077_2024-01-08_final
2024-01-10 11:09:39	ga_ls8c_ard_3-2-1_108079_2024-01-10_final
2024-01-19 09:25:47	ga_ls8c_ard_3-2-1_091082_2024-01-18_final
2024-02-14 10:01:14	ga_ls8c_ard_3-2-1_097078_2024-02-14_final
2024-02-14 11:41:19	ga_ls8c_ard_3-2-1_113081_2024-02-14_final
2024-02-17 10:33:43	ga_ls8c_ard_3-2-1_102082_2024-02-17_final
2024-02-18 11:17:47	ga_ls8c_ard_3-2-1_109084_2024-02-18_final
2024-02-19 10:20:10	ga_ls8c_ard_3-2-1_100079_2024-02-19_final
2024-02-25 11:20:44	ga_ls8c_ard_3-2-1_110076_2024-02-25_final
2024-03-01 09:59:32	ga_ls8c_ard_3-2-1_097074_2024-03-01_final
2024-03-01 10:01:08	ga_ls8c_ard_3-2-1_097078_2024-03-01_final
2024-03-01 11:41:13	ga_ls8c_ard_3-2-1_113081_2024-03-01_final
2024-03-03 09:51:56	ga_ls8c_ard_3-2-1_095086_2024-03-03_final
2024-03-05 09:33:33	ga_ls8c_ard_3-2-1_093071_2024-03-05_final
2024-03-07 09:26:20	ga_ls8c_ard_3-2-1_091084_2024-03-06_final
2024-03-08 11:45:17	ga_ls8c_ard_3-2-1_114076_2024-03-08_final
2024-03-13 10:25:43	ga_ls8c_ard_3-2-1_101078_2024-03-13_nrt
2024-03-16 10:54:36	ga_ls8c_ard_3-2-1_106073_2024-03-16_nrt
2024-03-22 10:18:14	ga_ls8c_ard_3-2-1_100075_2024-03-22_nrt
2024-03-25 09:12:59	ga_ls8c_ard_3-2-1_089082_2024-03-24_nrt
2024-03-27 10:39:02	ga_ls8c_ard_3-2-1_103081_2024-03-27_nrt
2024-03-28 11:18:18	ga_ls8c_ard_3-2-1_110071_2024-03-28_nrt
2024-03-29 10:23:05	ga_ls8c_ard_3-2-1_101072_2024-03-29_nrt

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