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
2022-02-22 10:11:33	ga_ls8c_ard_3-2-1_099073_2022-02-22_final
2022-02-26 09:51:37	ga_ls8c_ard_3-2-1_095085_2022-02-26_final
2022-02-28 09:36:04	ga_ls8c_ard_3-2-1_093077_2022-02-28_final
2022-03-02 11:00:59	ga_ls8c_ard_3-2-1_107073_2022-03-02_final
2022-03-03 10:08:09	ga_ls8c_ard_3-2-1_098080_2022-03-03_final
2022-03-08 10:23:29	ga_ls8c_ard_3-2-1_101072_2022-03-08_final
2022-03-09 09:31:02	ga_ls8c_ard_3-2-1_092080_2022-03-09_final
2022-03-11 09:19:52	ga_ls8c_ard_3-2-1_090083_2022-03-10_final
2022-03-16 09:35:58	ga_ls8c_ard_3-2-1_093077_2022-03-16_final
2022-03-16 09:37:34	ga_ls8c_ard_3-2-1_093081_2022-03-16_final
2022-03-18 09:25:35	ga_ls8c_ard_3-2-1_091082_2022-03-17_final
2022-03-18 11:02:28	ga_ls8c_ard_3-2-1_107077_2022-03-18_final
2022-03-19 11:46:07	ga_ls8c_ard_3-2-1_114078_2022-03-19_final
2022-03-23 09:45:39	ga_ls8c_ard_3-2-1_094086_2022-03-23_final
2022-03-23 11:22:32	ga_ls8c_ard_3-2-1_110081_2022-03-23_final
2022-03-24 10:24:06	ga_ls8c_ard_3-2-1_101074_2022-03-24_final
2022-03-25 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-03-25_final
2022-03-25 11:11:21	ga_ls8c_ard_3-2-1_108084_2022-03-25_final
2022-03-26 10:11:19	ga_ls8c_ard_3-2-1_099073_2022-03-26_final
2022-03-26 10:12:31	ga_ls8c_ard_3-2-1_099076_2022-03-26_final
2022-03-27 10:56:34	ga_ls8c_ard_3-2-1_106078_2022-03-27_final
2022-03-30 09:46:56	ga_ls8c_ard_3-2-1_095074_2022-03-30_final
2022-03-31 10:29:24	ga_ls8c_ard_3-2-1_102072_2022-03-31_final
2022-03-31 10:30:12	ga_ls8c_ard_3-2-1_102074_2022-03-31_final
2022-04-01 09:33:23	ga_ls8c_ard_3-2-1_093071_2022-04-01_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-11 10:11:20	ga_ls8c_ard_3-2-1_099073_2022-04-11_final
2022-04-11 10:12:32	ga_ls8c_ard_3-2-1_099076_2022-04-11_final
2022-04-13 10:01:47	ga_ls8c_ard_3-2-1_097080_2022-04-13_final
2022-04-16 10:30:18	ga_ls8c_ard_3-2-1_102074_2022-04-16_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-19 09:25:54	ga_ls8c_ard_3-2-1_091083_2022-04-18_final
2022-04-19 11:03:35	ga_ls8c_ard_3-2-1_107080_2022-04-19_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-26 11:10:07	ga_ls8c_ard_3-2-1_108081_2022-04-26_final
2022-04-28 10:54:09	ga_ls8c_ard_3-2-1_106072_2022-04-28_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-19 11:16:52	ga_ls8c_ard_3-2-1_109082_2022-05-19_final
2022-05-21 11:02:30	ga_ls8c_ard_3-2-1_107077_2022-05-21_final
2022-05-22 10:05:17	ga_ls8c_ard_3-2-1_098073_2022-05-22_final
2022-05-22 10:10:04	ga_ls8c_ard_3-2-1_098085_2022-05-22_final
2022-05-23 10:48:09	ga_ls8c_ard_3-2-1_105072_2022-05-23_final
2022-05-23 10:51:20	ga_ls8c_ard_3-2-1_105080_2022-05-23_final
2022-06-04 11:12:10	ga_ls8c_ard_3-2-1_109070_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-07 10:06:37	ga_ls8c_ard_3-2-1_098076_2022-06-07_final
2022-06-10 10:39:09	ga_ls8c_ard_3-2-1_103080_2022-06-10_final
2022-06-10 10:39:57	ga_ls8c_ard_3-2-1_103082_2022-06-10_final
2022-06-13 09:30:48	ga_ls8c_ard_3-2-1_092079_2022-06-13_final
2022-06-13 11:06:54	ga_ls8c_ard_3-2-1_108072_2022-06-13_final
2022-06-16 09:59:21	ga_ls8c_ard_3-2-1_097073_2022-06-16_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-18 11:29:04	ga_ls8c_ard_3-2-1_111081_2022-06-18_final
2022-06-21 10:18:43	ga_ls8c_ard_3-2-1_100075_2022-06-21_final
2022-06-23 10:10:21	ga_ls8c_ard_3-2-1_098085_2022-06-23_final
2022-06-26 10:38:28	ga_ls8c_ard_3-2-1_103078_2022-06-26_final
2022-06-27 11:22:56	ga_ls8c_ard_3-2-1_110081_2022-06-27_final
2022-06-28 10:26:55	ga_ls8c_ard_3-2-1_101080_2022-06-28_final
2022-06-29 09:30:06	ga_ls8c_ard_3-2-1_092077_2022-06-29_final
2022-07-05 10:31:06	ga_ls8c_ard_3-2-1_102075_2022-07-05_final
2022-07-06 09:39:05	ga_ls8c_ard_3-2-1_093084_2022-07-06_final
2022-07-06 11:13:10	ga_ls8c_ard_3-2-1_109072_2022-07-06_final
2022-07-07 10:18:21	ga_ls8c_ard_3-2-1_100074_2022-07-07_final
2022-07-09 11:47:16	ga_ls8c_ard_3-2-1_114080_2022-07-09_final
2022-07-18 10:01:25	ga_ls8c_ard_3-2-1_097078_2022-07-18_final
2022-07-18 11:41:30	ga_ls8c_ard_3-2-1_113081_2022-07-18_final
2022-07-24 09:25:37	ga_ls8c_ard_3-2-1_091081_2022-07-23_final
2022-07-25 11:45:46	ga_ls8c_ard_3-2-1_114076_2022-07-25_final
2022-07-26 10:46:34	ga_ls8c_ard_3-2-1_105067_2022-07-26_final
2022-07-29 11:21:54	ga_ls8c_ard_3-2-1_110078_2022-07-29_final
2022-07-31 11:10:21	ga_ls8c_ard_3-2-1_108080_2022-07-31_final
2022-08-04 10:41:41	ga_ls8c_ard_3-2-1_104070_2022-08-04_final
2022-08-09 11:03:03	ga_ls8c_ard_3-2-1_107077_2022-08-09_final
2022-08-12 09:53:29	ga_ls8c_ard_3-2-1_096073_2022-08-12_final
2022-08-14 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-08-14_final
2022-08-14 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-08-14_final
2022-08-21 09:48:08	ga_ls8c_ard_3-2-1_095075_2022-08-21_final
2022-08-21 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-08-21_final
2022-09-06 11:27:51	ga_ls8c_ard_3-2-1_111077_2022-09-06_final
2022-09-08 09:35:49	ga_ls8c_ard_3-2-1_093075_2022-09-08_final
2022-09-08 11:17:06	ga_ls8c_ard_3-2-1_109081_2022-09-08_final
2022-09-09 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-09-09_final
2022-09-10 11:01:10	ga_ls8c_ard_3-2-1_107072_2022-09-10_final
2022-09-10 11:04:45	ga_ls8c_ard_3-2-1_107081_2022-09-10_final
2022-09-11 11:45:14	ga_ls8c_ard_3-2-1_114074_2022-09-11_final
2022-09-11 11:46:50	ga_ls8c_ard_3-2-1_114078_2022-09-11_final
2022-09-12 10:48:49	ga_ls8c_ard_3-2-1_105072_2022-09-12_final
2022-09-16 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-09-16_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-12-04 11:22:28	ga_ls8c_ard_3-2-1_110079_2022-12-04_final
2022-12-09 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-12-09_final
2022-12-15 11:01:27	ga_ls8c_ard_3-2-1_107073_2022-12-15_final
2022-12-21 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-12-21_final
2022-12-25 10:02:21	ga_ls8c_ard_3-2-1_097080_2022-12-25_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years