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
2022-01-14 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-01-14_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-05 11:23:31	ga_ls8c_ard_3-2-1_110082_2023-01-05_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-06 10:25:29	ga_ls8c_ard_3-2-1_101076_2023-01-06_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-11 10:41:36	ga_ls8c_ard_3-2-1_104070_2023-01-11_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-19 09:56:28	ga_ls8c_ard_3-2-1_096081_2023-01-19_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-24 10:12:17	ga_ls8c_ard_3-2-1_099074_2023-01-24_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-01-30 09:36:25	ga_ls8c_ard_3-2-1_093077_2023-01-30_final
2023-01-30 09:36:49	ga_ls8c_ard_3-2-1_093078_2023-01-30_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-01 09:28:51	ga_ls8c_ard_3-2-1_091089_2023-01-31_final
2023-02-05 10:35:49	ga_ls8c_ard_3-2-1_103071_2023-02-05_final
2023-02-05 10:38:37	ga_ls8c_ard_3-2-1_103078_2023-02-05_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-13 09:50:17	ga_ls8c_ard_3-2-1_095081_2023-02-13_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-02-22 09:45:32	ga_ls8c_ard_3-2-1_094085_2023-02-22_final
2023-02-24 09:31:56	ga_ls8c_ard_3-2-1_092082_2023-02-24_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-02-25 10:12:22	ga_ls8c_ard_3-2-1_099075_2023-02-25_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-07 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-03-06_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-10 09:45:47	ga_ls8c_ard_3-2-1_094086_2023-03-10_final
2023-03-10 11:20:41	ga_ls8c_ard_3-2-1_110076_2023-03-10_final
2023-03-10 11:23:52	ga_ls8c_ard_3-2-1_110084_2023-03-10_final
2023-03-12 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-03-12_final
2023-03-12 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-03-12_final
2023-03-13 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-03-13_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-18 10:30:47	ga_ls8c_ard_3-2-1_102075_2023-03-18_final
2023-03-19 09:36:21	ga_ls8c_ard_3-2-1_093078_2023-03-19_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-24 09:57:36	ga_ls8c_ard_3-2-1_096085_2023-03-24_final
2023-03-28 11:10:33	ga_ls8c_ard_3-2-1_108082_2023-03-28_final
2023-03-28 11:11:21	ga_ls8c_ard_3-2-1_108084_2023-03-28_final
2023-03-29 10:14:32	ga_ls8c_ard_3-2-1_099081_2023-03-29_final
2023-03-30 09:20:05	ga_ls8c_ard_3-2-1_090084_2023-03-29_final
2023-03-30 10:54:11	ga_ls8c_ard_3-2-1_106072_2023-03-30_final
2023-04-02 09:50:09	ga_ls8c_ard_3-2-1_095082_2023-04-02_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-04 11:17:26	ga_ls8c_ard_3-2-1_109084_2023-04-04_final
2023-04-06 09:24:09	ga_ls8c_ard_3-2-1_091079_2023-04-05_final
2023-04-07 10:05:48	ga_ls8c_ard_3-2-1_098075_2023-04-07_final
2023-04-08 09:12:09	ga_ls8c_ard_3-2-1_089080_2023-04-07_final
2023-04-08 10:49:50	ga_ls8c_ard_3-2-1_105077_2023-04-08_final
2023-04-11 11:22:16	ga_ls8c_ard_3-2-1_110081_2023-04-11_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-14 10:11:05	ga_ls8c_ard_3-2-1_099073_2023-04-14_final
2023-04-18 09:50:43	ga_ls8c_ard_3-2-1_095084_2023-04-18_final
2023-04-20 11:12:26	ga_ls8c_ard_3-2-1_109072_2023-04-20_final
2023-04-21 10:21:12	ga_ls8c_ard_3-2-1_100083_2023-04-21_final
2023-04-24 10:51:19	ga_ls8c_ard_3-2-1_105081_2023-04-24_final
2023-04-24 10:52:07	ga_ls8c_ard_3-2-1_105083_2023-04-24_final
2023-04-26 10:38:33	ga_ls8c_ard_3-2-1_103080_2023-04-26_final
2023-04-30 10:14:36	ga_ls8c_ard_3-2-1_099082_2023-04-30_final
2023-05-01 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-05-01_final
2023-05-02 09:59:02	ga_ls8c_ard_3-2-1_097074_2023-05-02_final
2023-05-03 10:39:53	ga_ls8c_ard_3-2-1_104068_2023-05-03_final
2023-05-08 09:23:51	ga_ls8c_ard_3-2-1_091079_2023-05-07_final
2023-05-08 11:04:44	ga_ls8c_ard_3-2-1_107084_2023-05-08_final
2023-05-10 10:47:33	ga_ls8c_ard_3-2-1_105072_2023-05-10_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-11 09:51:30	ga_ls8c_ard_3-2-1_096071_2023-05-11_final
2023-05-13 11:20:00	ga_ls8c_ard_3-2-1_110076_2023-05-13_final
2023-05-15 11:04:49	ga_ls8c_ard_3-2-1_108069_2023-05-15_final
2023-05-16 10:14:23	ga_ls8c_ard_3-2-1_099082_2023-05-16_final
2023-05-17 09:18:45	ga_ls8c_ard_3-2-1_090082_2023-05-16_final
2023-05-17 10:54:02	ga_ls8c_ard_3-2-1_106073_2023-05-17_final
2023-05-18 10:00:25	ga_ls8c_ard_3-2-1_097078_2023-05-18_final
2023-05-22 11:14:13	ga_ls8c_ard_3-2-1_109077_2023-05-22_final
2023-05-23 10:20:36	ga_ls8c_ard_3-2-1_100082_2023-05-23_final
2023-05-24 09:25:22	ga_ls8c_ard_3-2-1_091083_2023-05-23_final
2023-05-24 10:59:52	ga_ls8c_ard_3-2-1_107072_2023-05-24_final
2023-05-25 10:04:39	ga_ls8c_ard_3-2-1_098073_2023-05-25_final
2023-05-26 09:10:38	ga_ls8c_ard_3-2-1_089077_2023-05-25_final
2023-05-26 09:13:49	ga_ls8c_ard_3-2-1_089085_2023-05-25_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