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
2022-08-22 10:30:12	ga_ls8c_ard_3-2-1_102072_2022-08-22_final
2022-08-23 09:36:58	ga_ls8c_ard_3-2-1_093078_2022-08-23_final
2022-08-24 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-08-24_final
2022-08-28 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-08-28_final
2022-08-30 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-08-30_final
2022-09-01 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-09-01_final
2022-09-11 11:46:02	ga_ls8c_ard_3-2-1_114076_2022-09-11_final
2022-09-13 09:53:12	ga_ls8c_ard_3-2-1_096072_2022-09-13_final
2022-09-13 09:54:00	ga_ls8c_ard_3-2-1_096074_2022-09-13_final
2022-09-13 09:57:12	ga_ls8c_ard_3-2-1_096082_2022-09-13_final
2022-09-14 10:38:52	ga_ls8c_ard_3-2-1_103078_2022-09-14_final
2022-09-23 10:33:30	ga_ls8c_ard_3-2-1_102080_2022-09-23_final
2022-09-24 09:38:41	ga_ls8c_ard_3-2-1_093082_2022-09-24_final
2022-09-27 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-09-27_final
2022-09-29 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-09-29_final
2022-10-04 11:53:49	ga_ls8c_ard_3-2-1_115080_2022-10-04_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-08 11:28:15	ga_ls8c_ard_3-2-1_111078_2022-10-08_final
2022-10-14 10:51:53	ga_ls8c_ard_3-2-1_105080_2022-10-14_final
2022-10-15 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-10-15_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-22 10:01:21	ga_ls8c_ard_3-2-1_097077_2022-10-22_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-23 10:45:01	ga_ls8c_ard_3-2-1_104078_2022-10-23_final
2022-10-24 09:48:36	ga_ls8c_ard_3-2-1_095076_2022-10-24_final
2022-10-29 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-10-29_final
2022-10-29 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-10-29_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-09 09:48:37	ga_ls8c_ard_3-2-1_095076_2022-11-09_final
2022-11-10 10:33:28	ga_ls8c_ard_3-2-1_102080_2022-11-10_final
2022-11-11 11:16:19	ga_ls8c_ard_3-2-1_109079_2022-11-11_final
2022-11-15 10:48:21	ga_ls8c_ard_3-2-1_105071_2022-11-15_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-18 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-11-18_final
2022-11-18 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-11-18_final
2022-11-19 10:24:48	ga_ls8c_ard_3-2-1_101074_2022-11-19_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-29 11:05:07	ga_ls8c_ard_3-2-1_107082_2022-11-29_final
2022-12-02 09:53:57	ga_ls8c_ard_3-2-1_096074_2022-12-02_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-20 11:22:43	ga_ls8c_ard_3-2-1_110080_2022-12-20_final
2022-12-22 09:31:02	ga_ls8c_ard_3-2-1_092079_2022-12-22_final
2022-12-26 10:43:13	ga_ls8c_ard_3-2-1_104074_2022-12-26_final
2022-12-26 10:46:01	ga_ls8c_ard_3-2-1_104081_2022-12-26_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-06 10:27:29	ga_ls8c_ard_3-2-1_101081_2023-01-06_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-10 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-10_final
2023-01-11 10:45:59	ga_ls8c_ard_3-2-1_104081_2023-01-11_final
2023-01-12 11:26:51	ga_ls8c_ard_3-2-1_111075_2023-01-12_final
2023-01-12 11:29:38	ga_ls8c_ard_3-2-1_111082_2023-01-12_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-18 10:51:16	ga_ls8c_ard_3-2-1_105079_2023-01-18_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-21 11:22:13	ga_ls8c_ard_3-2-1_110079_2023-01-21_final
2023-01-26 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-26_final
2023-02-01 09:26:03	ga_ls8c_ard_3-2-1_091082_2023-01-31_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-06 09:44:59	ga_ls8c_ard_3-2-1_094083_2023-02-06_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-12 10:44:19	ga_ls8c_ard_3-2-1_104077_2023-02-12_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-18 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-02-18_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-24 09:32:44	ga_ls8c_ard_3-2-1_092084_2023-02-24_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-03-03 11:16:10	ga_ls8c_ard_3-2-1_109080_2023-03-03_final
2023-03-07 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-03-07_final
2023-03-16 10:44:22	ga_ls8c_ard_3-2-1_104078_2023-03-16_final
2023-03-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2023-03-17_final
2023-03-19 09:36:21	ga_ls8c_ard_3-2-1_093078_2023-03-19_final
2023-03-24 09:54:25	ga_ls8c_ard_3-2-1_096077_2023-03-24_final
2023-03-25 10:35:17	ga_ls8c_ard_3-2-1_103071_2023-03-25_final
2023-03-29 10:12:32	ga_ls8c_ard_3-2-1_099076_2023-03-29_final
2023-04-01 10:43:00	ga_ls8c_ard_3-2-1_104075_2023-04-01_final
2023-04-06 11:03:02	ga_ls8c_ard_3-2-1_107079_2023-04-06_final
2023-04-09 09:54:35	ga_ls8c_ard_3-2-1_096078_2023-04-09_final
2023-04-13 11:10:18	ga_ls8c_ard_3-2-1_108082_2023-04-13_final
2023-04-17 10:43:33	ga_ls8c_ard_3-2-1_104077_2023-04-17_final
2023-04-20 11:15:14	ga_ls8c_ard_3-2-1_109079_2023-04-20_final
2023-04-21 11:57:42	ga_ls8c_ard_3-2-1_116077_2023-04-21_final
2023-04-29 11:06:14	ga_ls8c_ard_3-2-1_108072_2023-04-29_final
2023-04-30 10:15:48	ga_ls8c_ard_3-2-1_099085_2023-04-30_final
2023-05-01 09:19:22	ga_ls8c_ard_3-2-1_090083_2023-04-30_final
2023-05-01 10:55:51	ga_ls8c_ard_3-2-1_106077_2023-05-01_final
2023-05-02 11:38:42	ga_ls8c_ard_3-2-1_113076_2023-05-02_final
2023-05-06 09:35:03	ga_ls8c_ard_3-2-1_093076_2023-05-06_final
2023-05-14 10:22:46	ga_ls8c_ard_3-2-1_101072_2023-05-14_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