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
2022-02-25 10:45:15	ga_ls8c_ard_3-2-1_104080_2022-02-25_final
2022-03-02 11:02:35	ga_ls8c_ard_3-2-1_107077_2022-03-02_final
2022-03-05 09:54:35	ga_ls8c_ard_3-2-1_096077_2022-03-05_final
2022-03-05 09:54:59	ga_ls8c_ard_3-2-1_096078_2022-03-05_final
2022-03-05 09:55:47	ga_ls8c_ard_3-2-1_096080_2022-03-05_final
2022-03-05 11:33:04	ga_ls8c_ard_3-2-1_112076_2022-03-05_final
2022-03-06 10:38:38	ga_ls8c_ard_3-2-1_103079_2022-03-06_final
2022-03-09 11:09:55	ga_ls8c_ard_3-2-1_108080_2022-03-09_final
2022-03-13 10:41:35	ga_ls8c_ard_3-2-1_104071_2022-03-13_final
2022-03-13 10:44:46	ga_ls8c_ard_3-2-1_104079_2022-03-13_final
2022-03-19 10:06:26	ga_ls8c_ard_3-2-1_098076_2022-03-19_final
2022-03-21 09:56:26	ga_ls8c_ard_3-2-1_096082_2022-03-21_final
2022-03-21 09:56:50	ga_ls8c_ard_3-2-1_096083_2022-03-21_final
2022-03-26 10:12:07	ga_ls8c_ard_3-2-1_099075_2022-03-26_final
2022-03-28 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-03-28_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-07 10:36:50	ga_ls8c_ard_3-2-1_103075_2022-04-07_final
2022-04-10 09:29:40	ga_ls8c_ard_3-2-1_092077_2022-04-09_final
2022-04-10 09:32:04	ga_ls8c_ard_3-2-1_092083_2022-04-10_final
2022-04-15 11:26:19	ga_ls8c_ard_3-2-1_111075_2022-04-15_final
2022-04-17 09:37:28	ga_ls8c_ard_3-2-1_093081_2022-04-17_final
2022-04-19 11:03:11	ga_ls8c_ard_3-2-1_107079_2022-04-19_final
2022-04-21 10:48:25	ga_ls8c_ard_3-2-1_105073_2022-04-21_final
2022-04-22 11:34:52	ga_ls8c_ard_3-2-1_112081_2022-04-22_final
2022-04-27 10:14:29	ga_ls8c_ard_3-2-1_099081_2022-04-27_final
2022-04-29 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-04-29_final
2022-04-30 10:42:36	ga_ls8c_ard_3-2-1_104074_2022-04-30_final
2022-05-06 11:46:04	ga_ls8c_ard_3-2-1_114078_2022-05-06_final
2022-05-08 11:34:56	ga_ls8c_ard_3-2-1_112081_2022-05-08_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-05-18_final
2022-05-19 09:35:59	ga_ls8c_ard_3-2-1_093077_2022-05-19_final
2022-05-23 10:51:44	ga_ls8c_ard_3-2-1_105081_2022-05-23_final
2022-05-24 09:53:43	ga_ls8c_ard_3-2-1_096075_2022-05-24_final
2022-05-24 09:55:43	ga_ls8c_ard_3-2-1_096080_2022-05-24_final
2022-05-24 09:56:31	ga_ls8c_ard_3-2-1_096082_2022-05-24_final
2022-05-25 10:36:35	ga_ls8c_ard_3-2-1_103074_2022-05-25_final
2022-05-30 10:56:44	ga_ls8c_ard_3-2-1_106078_2022-05-30_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-08 10:47:30	ga_ls8c_ard_3-2-1_105070_2022-06-08_final
2022-06-08 10:50:41	ga_ls8c_ard_3-2-1_105078_2022-06-08_final
2022-06-09 09:53:05	ga_ls8c_ard_3-2-1_096073_2022-06-09_final
2022-06-11 09:44:44	ga_ls8c_ard_3-2-1_094083_2022-06-11_final
2022-06-20 09:38:38	ga_ls8c_ard_3-2-1_093083_2022-06-20_final
2022-06-24 10:47:38	ga_ls8c_ard_3-2-1_105070_2022-06-24_final
2022-06-24 10:48:50	ga_ls8c_ard_3-2-1_105073_2022-06-24_final
2022-07-04 09:49:50	ga_ls8c_ard_3-2-1_095080_2022-07-04_final
2022-07-06 09:38:41	ga_ls8c_ard_3-2-1_093083_2022-07-06_final
2022-07-08 11:04:48	ga_ls8c_ard_3-2-1_107082_2022-07-08_final
2022-07-10 10:48:03	ga_ls8c_ard_3-2-1_105071_2022-07-10_final
2022-07-14 10:26:54	ga_ls8c_ard_3-2-1_101080_2022-07-14_final
2022-07-15 11:06:58	ga_ls8c_ard_3-2-1_108072_2022-07-15_final
2022-07-22 09:36:21	ga_ls8c_ard_3-2-1_093077_2022-07-22_final
2022-07-24 11:02:54	ga_ls8c_ard_3-2-1_107077_2022-07-24_final
2022-07-24 11:03:42	ga_ls8c_ard_3-2-1_107079_2022-07-24_final
2022-07-25 10:06:53	ga_ls8c_ard_3-2-1_098076_2022-07-25_final
2022-07-26 10:48:10	ga_ls8c_ard_3-2-1_105071_2022-07-26_final
2022-07-31 09:31:04	ga_ls8c_ard_3-2-1_092079_2022-07-31_final
2022-08-11 10:51:30	ga_ls8c_ard_3-2-1_105079_2022-08-11_final
2022-08-18 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-08-18_final
2022-08-21 09:49:44	ga_ls8c_ard_3-2-1_095079_2022-08-21_final
2022-08-24 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-08-24_final
2022-08-26 10:09:28	ga_ls8c_ard_3-2-1_098082_2022-08-26_final
2022-08-26 11:45:58	ga_ls8c_ard_3-2-1_114076_2022-08-26_final
2022-08-28 09:55:31	ga_ls8c_ard_3-2-1_096078_2022-08-28_final
2022-09-06 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-09-06_final
2022-09-13 11:33:17	ga_ls8c_ard_3-2-1_112075_2022-09-13_final
2022-09-14 10:36:04	ga_ls8c_ard_3-2-1_103071_2022-09-14_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-10-08 11:29:27	ga_ls8c_ard_3-2-1_111081_2022-10-08_final
2022-10-13 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-10-13_final
2022-10-15 11:35:58	ga_ls8c_ard_3-2-1_112082_2022-10-15_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-23 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-23_final
2022-10-24 11:28:17	ga_ls8c_ard_3-2-1_111078_2022-10-24_final
2022-10-25 10:31:53	ga_ls8c_ard_3-2-1_102076_2022-10-25_final
2022-11-01 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-11-01_final
2022-11-09 09:49:49	ga_ls8c_ard_3-2-1_095079_2022-11-09_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-12-02 09:56:20	ga_ls8c_ard_3-2-1_096080_2022-12-02_final
2022-12-05 10:24:50	ga_ls8c_ard_3-2-1_101074_2022-12-05_final
2022-12-11 11:29:00	ga_ls8c_ard_3-2-1_111080_2022-12-11_final
2022-12-14 10:19:24	ga_ls8c_ard_3-2-1_100076_2022-12-14_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-26 10:43:13	ga_ls8c_ard_3-2-1_104074_2022-12-26_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-05 11:22:19	ga_ls8c_ard_3-2-1_110079_2023-01-05_final
2023-01-09 10:59:10	ga_ls8c_ard_3-2-1_106083_2023-01-09_final
2023-01-10 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-10_final
2023-01-13 10:32:48	ga_ls8c_ard_3-2-1_102079_2023-01-13_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-02-05 10:37:25	ga_ls8c_ard_3-2-1_103075_2023-02-05_final
2023-02-06 11:23:04	ga_ls8c_ard_3-2-1_110081_2023-02-06_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-12 10:44:43	ga_ls8c_ard_3-2-1_104078_2023-02-12_final
2023-02-20 11:35:14	ga_ls8c_ard_3-2-1_112081_2023-02-20_final
2023-02-28 10:44:05	ga_ls8c_ard_3-2-1_104077_2023-02-28_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