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
2022-03-28 10:03:43	ga_ls8c_ard_3-2-1_097085_2022-03-28_final
2022-03-30 11:26:13	ga_ls8c_ard_3-2-1_111075_2022-03-30_final
2022-03-31 10:30:36	ga_ls8c_ard_3-2-1_102075_2022-03-31_final
2022-04-01 09:34:35	ga_ls8c_ard_3-2-1_093074_2022-04-01_final
2022-04-01 09:35:22	ga_ls8c_ard_3-2-1_093076_2022-04-01_final
2022-04-02 10:19:50	ga_ls8c_ard_3-2-1_100079_2022-04-02_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-09 10:25:41	ga_ls8c_ard_3-2-1_101078_2022-04-09_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-22 09:56:47	ga_ls8c_ard_3-2-1_096083_2022-04-22_final
2022-04-23 10:37:39	ga_ls8c_ard_3-2-1_103077_2022-04-23_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:11:18	ga_ls8c_ard_3-2-1_099073_2022-04-27_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-08 11:35:20	ga_ls8c_ard_3-2-1_112082_2022-05-08_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-06-02 11:26:53	ga_ls8c_ard_3-2-1_111076_2022-06-02_final
2022-06-03 10:29:17	ga_ls8c_ard_3-2-1_102071_2022-06-03_final
2022-06-10 10:36:22	ga_ls8c_ard_3-2-1_103073_2022-06-10_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-20 09:36:15	ga_ls8c_ard_3-2-1_093077_2022-06-20_final
2022-06-20 11:15:08	ga_ls8c_ard_3-2-1_109077_2022-06-20_final
2022-06-22 11:04:23	ga_ls8c_ard_3-2-1_107081_2022-06-22_final
2022-06-27 09:40:52	ga_ls8c_ard_3-2-1_094073_2022-06-27_final
2022-07-02 10:01:00	ga_ls8c_ard_3-2-1_097077_2022-07-02_final
2022-07-02 10:03:24	ga_ls8c_ard_3-2-1_097083_2022-07-02_final
2022-07-05 10:30:42	ga_ls8c_ard_3-2-1_102074_2022-07-05_final
2022-07-07 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-07-07_final
2022-07-09 10:09:34	ga_ls8c_ard_3-2-1_098083_2022-07-09_final
2022-07-09 11:46:04	ga_ls8c_ard_3-2-1_114077_2022-07-09_final
2022-07-11 09:56:48	ga_ls8c_ard_3-2-1_096082_2022-07-11_final
2022-07-17 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-07-16_final
2022-07-22 09:35:33	ga_ls8c_ard_3-2-1_093075_2022-07-22_final
2022-07-22 09:37:33	ga_ls8c_ard_3-2-1_093080_2022-07-22_final
2022-07-25 10:08:29	ga_ls8c_ard_3-2-1_098080_2022-07-25_final
2022-07-29 09:41:25	ga_ls8c_ard_3-2-1_094074_2022-07-29_final
2022-07-29 11:21:30	ga_ls8c_ard_3-2-1_110077_2022-07-29_final
2022-07-30 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-07-30_final
2022-07-30 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-07-30_final
2022-08-03 09:59:12	ga_ls8c_ard_3-2-1_097072_2022-08-03_final
2022-08-03 10:00:00	ga_ls8c_ard_3-2-1_097074_2022-08-03_final
2022-08-03 10:02:24	ga_ls8c_ard_3-2-1_097080_2022-08-03_final
2022-08-03 11:40:29	ga_ls8c_ard_3-2-1_113078_2022-08-03_final
2022-08-06 10:33:19	ga_ls8c_ard_3-2-1_102080_2022-08-06_final
2022-08-08 10:20:35	ga_ls8c_ard_3-2-1_100079_2022-08-08_final
2022-08-15 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-08-15_final
2022-08-18 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-08-18_final
2022-08-18 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-08-18_final
2022-08-19 10:02:05	ga_ls8c_ard_3-2-1_097079_2022-08-19_final
2022-08-19 11:41:22	ga_ls8c_ard_3-2-1_113080_2022-08-19_final
2022-08-24 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-08-24_final
2022-08-25 11:04:18	ga_ls8c_ard_3-2-1_107080_2022-08-25_final
2022-08-27 10:52:20	ga_ls8c_ard_3-2-1_105081_2022-08-27_final
2022-08-28 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-08-28_final
2022-08-30 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-08-30_final
2022-08-30 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-08-30_final
2022-08-31 10:24:01	ga_ls8c_ard_3-2-1_101072_2022-08-31_final
2022-09-03 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-09-03_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-05 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-09-05_final
2022-09-08 11:13:06	ga_ls8c_ard_3-2-1_109071_2022-09-08_final
2022-09-11 11:46:26	ga_ls8c_ard_3-2-1_114077_2022-09-11_final
2022-09-12 10:48:01	ga_ls8c_ard_3-2-1_105070_2022-09-12_final
2022-09-14 10:35:40	ga_ls8c_ard_3-2-1_103070_2022-09-14_final
2022-09-19 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-09-18_final
2022-09-20 11:41:29	ga_ls8c_ard_3-2-1_113080_2022-09-20_final
2022-09-21 10:41:53	ga_ls8c_ard_3-2-1_104070_2022-09-21_final
2022-09-26 11:04:48	ga_ls8c_ard_3-2-1_107081_2022-09-26_final
2022-09-27 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-09-27_final
2022-09-27 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-09-27_final
2022-09-29 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-09-29_final
2022-09-30 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-09-30_final
2022-10-02 10:24:55	ga_ls8c_ard_3-2-1_101074_2022-10-02_final
2022-10-04 10:12:08	ga_ls8c_ard_3-2-1_099073_2022-10-04_final
2022-10-04 11:51:25	ga_ls8c_ard_3-2-1_115074_2022-10-04_final
2022-10-06 10:01:21	ga_ls8c_ard_3-2-1_097077_2022-10-06_final
2022-10-06 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-06_final
2022-10-10 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-10-10_final
2022-10-13 11:45:31	ga_ls8c_ard_3-2-1_114075_2022-10-13_final
2022-10-15 09:53:05	ga_ls8c_ard_3-2-1_096072_2022-10-15_final
2022-10-15 09:56:41	ga_ls8c_ard_3-2-1_096081_2022-10-15_final
2022-10-17 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-10-17_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-12-01 10:51:34	ga_ls8c_ard_3-2-1_105079_2022-12-01_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-15 09:36:42	ga_ls8c_ard_3-2-1_093078_2023-02-15_final
2023-02-15 11:17:11	ga_ls8c_ard_3-2-1_109082_2023-02-15_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-17 09:27:30	ga_ls8c_ard_3-2-1_091086_2023-02-16_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_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