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
2022-05-21 09:28:01	ga_ls8c_ard_3-2-1_091088_2022-05-20_final
2022-05-30 09:21:03	ga_ls8c_ard_3-2-1_090086_2022-05-29_final
2022-06-05 10:18:33	ga_ls8c_ard_3-2-1_100075_2022-06-05_final
2022-06-09 09:56:17	ga_ls8c_ard_3-2-1_096081_2022-06-09_final
2022-06-19 10:33:04	ga_ls8c_ard_3-2-1_102080_2022-06-19_final
2022-07-07 10:21:32	ga_ls8c_ard_3-2-1_100082_2022-07-07_final
2022-07-08 09:27:55	ga_ls8c_ard_3-2-1_091087_2022-07-07_final
2022-07-15 09:34:28	ga_ls8c_ard_3-2-1_092088_2022-07-15_final
2022-07-22 11:14:26	ga_ls8c_ard_3-2-1_109075_2022-07-22_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-08-03 11:41:17	ga_ls8c_ard_3-2-1_113080_2022-08-03_final
2022-08-03 11:42:29	ga_ls8c_ard_3-2-1_113083_2022-08-03_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-16 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-08-16_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-25 09:23:25	ga_ls8c_ard_3-2-1_091075_2022-08-24_final
2022-09-03 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-09-02_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-15 11:21:44	ga_ls8c_ard_3-2-1_110077_2022-09-15_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-25 10:19:57	ga_ls8c_ard_3-2-1_100077_2022-09-25_final
2022-09-26 09:25:31	ga_ls8c_ard_3-2-1_091080_2022-09-25_final
2022-10-01 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-10-01_final
2022-10-04 10:10:33	ga_ls8c_ard_3-2-1_099069_2022-10-04_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-15 09:58:41	ga_ls8c_ard_3-2-1_096086_2022-10-15_final
2022-10-24 11:26:18	ga_ls8c_ard_3-2-1_111073_2022-10-24_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-11-04 11:08:35	ga_ls8c_ard_3-2-1_108075_2022-11-04_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-14 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-14_final
2022-11-17 10:37:10	ga_ls8c_ard_3-2-1_103074_2022-11-17_final
2022-11-21 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-11-21_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-22 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-11-22_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-11-29 09:22:15	ga_ls8c_ard_3-2-1_091072_2022-11-28_final
2022-11-30 10:05:30	ga_ls8c_ard_3-2-1_098072_2022-11-30_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-16 11:47:06	ga_ls8c_ard_3-2-1_114079_2022-12-16_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-23 10:09:54	ga_ls8c_ard_3-2-1_099068_2022-12-23_final
2022-12-29 11:13:44	ga_ls8c_ard_3-2-1_109073_2022-12-29_final
2023-01-07 11:06:45	ga_ls8c_ard_3-2-1_108071_2023-01-07_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-12 11:25:39	ga_ls8c_ard_3-2-1_111072_2023-01-12_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-20 10:39:45	ga_ls8c_ard_3-2-1_103081_2023-01-20_final
2023-01-23 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-01-23_final
2023-01-24 10:11:29	ga_ls8c_ard_3-2-1_099072_2023-01-24_final
2023-01-25 10:59:08	ga_ls8c_ard_3-2-1_106083_2023-01-25_final
2023-02-06 09:40:12	ga_ls8c_ard_3-2-1_094071_2023-02-06_final
2023-02-13 11:25:11	ga_ls8c_ard_3-2-1_111071_2023-02-13_final
2023-02-15 11:12:00	ga_ls8c_ard_3-2-1_109069_2023-02-15_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-01 11:24:33	ga_ls8c_ard_3-2-1_111070_2023-03-01_final
2023-03-13 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-03-13_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-19 09:39:09	ga_ls8c_ard_3-2-1_093085_2023-03-19_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-31 10:02:09	ga_ls8c_ard_3-2-1_097081_2023-03-31_final
2023-04-13 09:27:25	ga_ls8c_ard_3-2-1_092072_2023-04-12_final
2023-04-13 09:34:36	ga_ls8c_ard_3-2-1_092090_2023-04-13_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-05-01 10:52:16	ga_ls8c_ard_3-2-1_106068_2023-05-01_final
2023-05-08 11:01:08	ga_ls8c_ard_3-2-1_107075_2023-05-08_final
2023-05-09 11:45:59	ga_ls8c_ard_3-2-1_114079_2023-05-09_final
2023-05-13 11:21:59	ga_ls8c_ard_3-2-1_110081_2023-05-13_final
2023-05-16 10:08:48	ga_ls8c_ard_3-2-1_099068_2023-05-16_final
2023-05-16 11:52:04	ga_ls8c_ard_3-2-1_115079_2023-05-16_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-26 10:51:30	ga_ls8c_ard_3-2-1_105082_2023-05-26_final
2023-05-31 09:32:46	ga_ls8c_ard_3-2-1_092086_2023-05-31_final
2023-05-31 11:10:03	ga_ls8c_ard_3-2-1_108082_2023-05-31_final
2023-06-05 11:24:39	ga_ls8c_ard_3-2-1_111072_2023-06-05_final
2023-06-11 10:45:38	ga_ls8c_ard_3-2-1_105067_2023-06-11_final
2023-06-15 10:22:09	ga_ls8c_ard_3-2-1_101070_2023-06-15_final
2023-06-24 10:21:11	ga_ls8c_ard_3-2-1_100083_2023-06-24_final
2023-06-26 10:09:16	ga_ls8c_ard_3-2-1_098084_2023-06-26_final
2023-06-27 09:09:40	ga_ls8c_ard_3-2-1_089074_2023-06-26_final
2023-07-04 10:52:26	ga_ls8c_ard_3-2-1_106068_2023-07-04_final
2023-07-09 11:13:25	ga_ls8c_ard_3-2-1_109074_2023-07-09_final
2023-07-10 10:21:23	ga_ls8c_ard_3-2-1_100083_2023-07-10_final
2023-07-16 11:20:25	ga_ls8c_ard_3-2-1_110076_2023-07-16_final
2023-07-29 09:11:56	ga_ls8c_ard_3-2-1_089079_2023-07-28_final
2023-07-30 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-07-30_final
2023-08-01 11:19:45	ga_ls8c_ard_3-2-1_110074_2023-08-01_final
2023-08-02 10:27:43	ga_ls8c_ard_3-2-1_101083_2023-08-02_final
2023-08-11 10:19:33	ga_ls8c_ard_3-2-1_100078_2023-08-11_final
2023-08-12 09:27:56	ga_ls8c_ard_3-2-1_091088_2023-08-11_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-09-07 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-09-07_final
2023-09-30 11:46:45	ga_ls8c_ard_3-2-1_114079_2023-09-30_final
2023-10-04 11:21:13	ga_ls8c_ard_3-2-1_110077_2023-10-04_final
2023-10-07 11:52:56	ga_ls8c_ard_3-2-1_115079_2023-10-07_final
2023-10-08 10:52:56	ga_ls8c_ard_3-2-1_106068_2023-10-08_final
2023-10-21 10:28:01	ga_ls8c_ard_3-2-1_101083_2023-10-21_final
2023-11-09 10:58:30	ga_ls8c_ard_3-2-1_106082_2023-11-09_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