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
2022-09-28 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
2023-02-04 09:55:45	ga_ls8c_ard_3-2-1_096079_2023-02-04_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
2023-03-03 09:36:29	ga_ls8c_ard_3-2-1_093078_2023-03-03_final
2023-03-09 10:37:25	ga_ls8c_ard_3-2-1_103076_2023-03-09_final
2023-03-25 10:36:52	ga_ls8c_ard_3-2-1_103075_2023-03-25_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-03-31 11:39:02	ga_ls8c_ard_3-2-1_113076_2023-03-31_final
2023-04-02 11:27:26	ga_ls8c_ard_3-2-1_111078_2023-04-02_final
2023-04-03 10:30:12	ga_ls8c_ard_3-2-1_102074_2023-04-03_final
2023-04-03 10:30:36	ga_ls8c_ard_3-2-1_102075_2023-04-03_final
2023-04-06 11:03:02	ga_ls8c_ard_3-2-1_107079_2023-04-06_final
2023-04-16 11:39:59	ga_ls8c_ard_3-2-1_113079_2023-04-16_final
2023-04-30 10:11:00	ga_ls8c_ard_3-2-1_099073_2023-04-30_final
2023-05-03 10:40:41	ga_ls8c_ard_3-2-1_104070_2023-05-03_final
2023-05-06 09:38:15	ga_ls8c_ard_3-2-1_093084_2023-05-06_final
2023-05-11 11:31:59	ga_ls8c_ard_3-2-1_112075_2023-05-11_final
2023-05-17 09:19:09	ga_ls8c_ard_3-2-1_090083_2023-05-16_final
2023-05-17 10:55:38	ga_ls8c_ard_3-2-1_106077_2023-05-17_final
2023-05-17 10:57:14	ga_ls8c_ard_3-2-1_106081_2023-05-17_final
2023-05-19 10:44:53	ga_ls8c_ard_3-2-1_104081_2023-05-19_final
2023-05-22 11:15:25	ga_ls8c_ard_3-2-1_109080_2023-05-22_final
2023-05-27 09:54:17	ga_ls8c_ard_3-2-1_096078_2023-05-27_final
2023-05-27 11:33:10	ga_ls8c_ard_3-2-1_112078_2023-05-27_final
2023-05-28 10:38:21	ga_ls8c_ard_3-2-1_103080_2023-05-28_final
2023-06-02 10:57:17	ga_ls8c_ard_3-2-1_106081_2023-06-02_final
2023-06-09 11:02:46	ga_ls8c_ard_3-2-1_107079_2023-06-09_final
2023-06-11 10:46:50	ga_ls8c_ard_3-2-1_105070_2023-06-11_final
2023-06-11 10:47:14	ga_ls8c_ard_3-2-1_105071_2023-06-11_final
2023-06-12 11:32:06	ga_ls8c_ard_3-2-1_112075_2023-06-12_final
2023-06-13 10:37:41	ga_ls8c_ard_3-2-1_103078_2023-06-13_final
2023-06-14 09:44:04	ga_ls8c_ard_3-2-1_094083_2023-06-14_final
2023-06-17 10:10:59	ga_ls8c_ard_3-2-1_099073_2023-06-17_final
2023-06-18 10:56:15	ga_ls8c_ard_3-2-1_106078_2023-06-18_final
2023-06-26 11:46:57	ga_ls8c_ard_3-2-1_114081_2023-06-26_final
2023-07-05 11:38:30	ga_ls8c_ard_3-2-1_113075_2023-07-05_final
2023-07-14 11:33:34	ga_ls8c_ard_3-2-1_112078_2023-07-14_final
2023-07-17 10:25:59	ga_ls8c_ard_3-2-1_101079_2023-07-17_final
2023-07-19 11:50:30	ga_ls8c_ard_3-2-1_115074_2023-07-19_final
2023-07-29 10:51:13	ga_ls8c_ard_3-2-1_105080_2023-07-29_final
2023-07-31 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-07-31_final
2023-08-17 09:41:46	ga_ls8c_ard_3-2-1_094076_2023-08-17_final
2023-08-20 10:12:17	ga_ls8c_ard_3-2-1_099075_2023-08-20_final
2023-08-22 11:40:25	ga_ls8c_ard_3-2-1_113079_2023-08-22_final
2023-08-26 11:12:32	ga_ls8c_ard_3-2-1_109071_2023-08-26_final
2023-08-28 11:00:58	ga_ls8c_ard_3-2-1_107073_2023-08-28_final
2023-08-28 11:02:34	ga_ls8c_ard_3-2-1_107077_2023-08-28_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-29 11:46:13	ga_ls8c_ard_3-2-1_114078_2023-08-29_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-09-05 10:12:17	ga_ls8c_ard_3-2-1_099075_2023-09-05_final
2023-09-08 10:44:24	ga_ls8c_ard_3-2-1_104078_2023-09-08_final
2023-09-09 09:49:35	ga_ls8c_ard_3-2-1_095080_2023-09-09_final
2023-09-19 10:27:09	ga_ls8c_ard_3-2-1_101081_2023-09-19_final
2023-09-29 11:04:17	ga_ls8c_ard_3-2-1_107081_2023-09-29_final
2023-10-04 09:41:56	ga_ls8c_ard_3-2-1_094076_2023-10-04_final
2023-10-06 11:06:51	ga_ls8c_ard_3-2-1_108072_2023-10-06_final
2023-10-10 10:41:47	ga_ls8c_ard_3-2-1_104071_2023-10-10_final
2023-10-13 09:37:24	ga_ls8c_ard_3-2-1_093080_2023-10-13_final
2023-10-20 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-10-20_final
2023-10-20 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-10-20_final
2023-10-21 10:26:26	ga_ls8c_ard_3-2-1_101079_2023-10-21_final
2023-10-23 10:12:06	ga_ls8c_ard_3-2-1_099074_2023-10-23_final
2023-10-26 10:44:37	ga_ls8c_ard_3-2-1_104078_2023-10-26_final
2023-10-29 11:16:20	ga_ls8c_ard_3-2-1_109080_2023-10-29_final
2023-11-04 10:38:26	ga_ls8c_ard_3-2-1_103078_2023-11-04_final
2023-11-07 09:35:13	ga_ls8c_ard_3-2-1_092090_2023-11-07_final
2023-11-09 09:18:50	ga_ls8c_ard_3-2-1_090080_2023-11-08_final
2023-11-11 10:41:46	ga_ls8c_ard_3-2-1_104071_2023-11-11_final
2023-11-12 11:27:50	ga_ls8c_ard_3-2-1_111078_2023-11-12_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