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
2022-05-16 10:43:33	ga_ls8c_ard_3-2-1_104076_2022-05-16_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-15 10:54:33	ga_ls8c_ard_3-2-1_106072_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-06-21_final
2022-06-27 11:23:44	ga_ls8c_ard_3-2-1_110083_2022-06-27_final
2022-06-29 11:10:35	ga_ls8c_ard_3-2-1_108081_2022-06-29_final
2022-07-02 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-02_final
2022-07-04 11:30:19	ga_ls8c_ard_3-2-1_111084_2022-07-04_final
2022-07-05 10:30:42	ga_ls8c_ard_3-2-1_102074_2022-07-05_final
2022-07-05 10:33:06	ga_ls8c_ard_3-2-1_102080_2022-07-05_final
2022-07-08 09:23:55	ga_ls8c_ard_3-2-1_091077_2022-07-07_final
2022-07-09 11:47:16	ga_ls8c_ard_3-2-1_114080_2022-07-09_final
2022-07-14 10:23:42	ga_ls8c_ard_3-2-1_101072_2022-07-14_final
2022-07-17 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-07-16_final
2022-07-18 09:58:37	ga_ls8c_ard_3-2-1_097071_2022-07-18_final
2022-07-22 11:12:26	ga_ls8c_ard_3-2-1_109070_2022-07-22_final
2022-07-23 10:21:13	ga_ls8c_ard_3-2-1_100081_2022-07-23_final
2022-07-24 09:25:37	ga_ls8c_ard_3-2-1_091081_2022-07-23_final
2022-07-25 11:47:22	ga_ls8c_ard_3-2-1_114080_2022-07-25_final
2022-07-27 09:52:33	ga_ls8c_ard_3-2-1_096071_2022-07-27_final
2022-07-28 10:36:38	ga_ls8c_ard_3-2-1_103073_2022-07-28_final
2022-07-30 10:23:53	ga_ls8c_ard_3-2-1_101072_2022-07-30_final
2022-07-30 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-07-30_final
2022-08-03 09:59:12	ga_ls8c_ard_3-2-1_097072_2022-08-03_final
2022-08-06 10:30:08	ga_ls8c_ard_3-2-1_102072_2022-08-06_final
2022-08-08 10:21:47	ga_ls8c_ard_3-2-1_100082_2022-08-08_final
2022-08-13 10:36:45	ga_ls8c_ard_3-2-1_103073_2022-08-13_final
2022-08-14 09:44:20	ga_ls8c_ard_3-2-1_094081_2022-08-14_final
2022-08-16 11:06:04	ga_ls8c_ard_3-2-1_108069_2022-08-16_final
2022-08-18 09:20:25	ga_ls8c_ard_3-2-1_090083_2022-08-17_final
2022-08-19 11:42:34	ga_ls8c_ard_3-2-1_113083_2022-08-19_final
2022-08-21 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-08-21_final
2022-08-21 11:29:49	ga_ls8c_ard_3-2-1_111082_2022-08-21_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-06 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-09-06_final
2022-09-07 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-09-07_final
2022-09-08 11:17:06	ga_ls8c_ard_3-2-1_109081_2022-09-08_final
2022-09-09 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-09-09_final
2022-09-24 09:36:17	ga_ls8c_ard_3-2-1_093076_2022-09-24_final
2022-09-28 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-09-28_final
2022-09-29 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-09-29_final
2022-09-30 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-09-30_final
2022-10-01 09:44:03	ga_ls8c_ard_3-2-1_094080_2022-10-01_final
2022-10-01 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-10-01_final
2022-10-01 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-10-01_final
2022-10-01 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-10-01_final
2022-10-04 10:12:08	ga_ls8c_ard_3-2-1_099073_2022-10-04_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-10 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-10-10_final
2022-10-11 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-10-11_final
2022-10-12 09:24:36	ga_ls8c_ard_3-2-1_091078_2022-10-11_final
2022-10-16 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-10-16_final
2022-10-20 10:16:53	ga_ls8c_ard_3-2-1_099085_2022-10-20_final
2022-10-22 10:00:09	ga_ls8c_ard_3-2-1_097074_2022-10-22_final
2022-10-23 10:45:49	ga_ls8c_ard_3-2-1_104080_2022-10-23_final
2022-10-24 09:50:12	ga_ls8c_ard_3-2-1_095080_2022-10-24_final
2022-10-26 09:36:16	ga_ls8c_ard_3-2-1_093076_2022-10-26_final
2022-10-29 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-10-29_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-11 09:36:14	ga_ls8c_ard_3-2-1_093076_2022-11-11_final
2022-11-13 09:25:03	ga_ls8c_ard_3-2-1_091079_2022-11-12_final
2022-11-15 10:48:21	ga_ls8c_ard_3-2-1_105071_2022-11-15_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-23 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-11-23_final
2022-11-25 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-11-25_final
2022-11-29 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-29_final
2022-11-29 11:03:55	ga_ls8c_ard_3-2-1_107079_2022-11-29_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-07 10:13:16	ga_ls8c_ard_3-2-1_099076_2022-12-07_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-19 10:38:40	ga_ls8c_ard_3-2-1_103078_2022-12-19_final
2022-12-20 09:43:50	ga_ls8c_ard_3-2-1_094080_2022-12-20_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-27 09:51:12	ga_ls8c_ard_3-2-1_095083_2022-12-27_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-09 10:57:10	ga_ls8c_ard_3-2-1_106078_2023-01-09_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-14 09:39:58	ga_ls8c_ard_3-2-1_093086_2023-01-14_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-22 10:27:25	ga_ls8c_ard_3-2-1_101081_2023-01-22_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-01-25 10:57:32	ga_ls8c_ard_3-2-1_106079_2023-01-25_final
2023-01-26 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-26_final
2023-02-06 09:41:47	ga_ls8c_ard_3-2-1_094075_2023-02-06_final
2023-02-06 11:23:52	ga_ls8c_ard_3-2-1_110083_2023-02-06_final
2023-02-11 11:41:09	ga_ls8c_ard_3-2-1_113080_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-23 10:24:47	ga_ls8c_ard_3-2-1_101075_2023-02-23_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