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
2022-02-17 09:52:15	ga_ls8c_ard_3-2-1_096071_2022-02-17_final
2022-02-17 11:35:31	ga_ls8c_ard_3-2-1_112082_2022-02-17_final
2022-02-24 11:42:04	ga_ls8c_ard_3-2-1_113083_2022-02-24_final
2022-02-25 10:40:27	ga_ls8c_ard_3-2-1_104068_2022-02-25_final
2022-03-05 09:52:35	ga_ls8c_ard_3-2-1_096072_2022-03-05_final
2022-03-11 09:19:04	ga_ls8c_ard_3-2-1_090081_2022-03-10_final
2022-03-12 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-03-12_final
2022-03-12 11:41:36	ga_ls8c_ard_3-2-1_113082_2022-03-12_final
2022-03-14 11:30:01	ga_ls8c_ard_3-2-1_111084_2022-03-14_final
2022-03-18 11:05:15	ga_ls8c_ard_3-2-1_107084_2022-03-18_final
2022-03-21 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-03-21_final
2022-04-10 11:11:21	ga_ls8c_ard_3-2-1_108084_2022-04-10_final
2022-04-19 09:22:18	ga_ls8c_ard_3-2-1_091074_2022-04-18_final
2022-04-19 11:04:47	ga_ls8c_ard_3-2-1_107083_2022-04-19_final
2022-04-29 11:38:36	ga_ls8c_ard_3-2-1_113075_2022-04-29_final
2022-05-07 09:15:58	ga_ls8c_ard_3-2-1_089089_2022-05-06_final
2022-05-10 11:18:12	ga_ls8c_ard_3-2-1_110070_2022-05-10_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-05-14 10:56:18	ga_ls8c_ard_3-2-1_106077_2022-05-14_final
2022-05-15 11:41:10	ga_ls8c_ard_3-2-1_113081_2022-05-15_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-06-03 10:28:29	ga_ls8c_ard_3-2-1_102069_2022-06-03_final
2022-06-03 10:33:17	ga_ls8c_ard_3-2-1_102081_2022-06-03_final
2022-06-13 09:34:00	ga_ls8c_ard_3-2-1_092087_2022-06-13_final
2022-06-18 11:30:16	ga_ls8c_ard_3-2-1_111084_2022-06-18_final
2022-06-19 10:28:16	ga_ls8c_ard_3-2-1_102068_2022-06-19_final
2022-06-22 09:28:41	ga_ls8c_ard_3-2-1_091089_2022-06-21_final
2022-06-26 10:39:40	ga_ls8c_ard_3-2-1_103081_2022-06-26_final
2022-06-30 10:12:58	ga_ls8c_ard_3-2-1_099076_2022-06-30_final
2022-06-30 10:14:10	ga_ls8c_ard_3-2-1_099079_2022-06-30_final
2022-07-01 09:21:20	ga_ls8c_ard_3-2-1_090086_2022-06-30_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final
2022-07-08 11:04:24	ga_ls8c_ard_3-2-1_107081_2022-07-08_final
2022-07-15 09:32:52	ga_ls8c_ard_3-2-1_092084_2022-07-15_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-08-06 10:28:32	ga_ls8c_ard_3-2-1_102068_2022-08-06_final
2022-08-09 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-08-08_final
2022-08-19 11:42:10	ga_ls8c_ard_3-2-1_113082_2022-08-19_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_final
2022-08-25 11:04:42	ga_ls8c_ard_3-2-1_107081_2022-08-25_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-09-06 09:47:22	ga_ls8c_ard_3-2-1_095073_2022-09-06_final
2022-09-12 10:52:25	ga_ls8c_ard_3-2-1_105081_2022-09-12_final
2022-09-26 09:27:07	ga_ls8c_ard_3-2-1_091084_2022-09-25_final
2022-09-26 11:00:25	ga_ls8c_ard_3-2-1_107070_2022-09-26_final
2022-09-26 11:05:36	ga_ls8c_ard_3-2-1_107083_2022-09-26_final
2022-10-01 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-10-01_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-25 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-10-25_final
2022-10-28 11:00:24	ga_ls8c_ard_3-2-1_107070_2022-10-28_final
2022-11-04 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-11-03_final
2022-11-04 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-11-04_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-12 10:17:53	ga_ls8c_ard_3-2-1_100072_2022-11-12_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-12-12 10:33:46	ga_ls8c_ard_3-2-1_102081_2022-12-12_final
2022-12-14 11:58:17	ga_ls8c_ard_3-2-1_116076_2022-12-14_final
2022-12-17 10:53:03	ga_ls8c_ard_3-2-1_105083_2022-12-17_final
2022-12-19 10:36:17	ga_ls8c_ard_3-2-1_103072_2022-12-19_final
2022-12-24 09:19:52	ga_ls8c_ard_3-2-1_090082_2022-12-23_final
2022-12-24 10:55:58	ga_ls8c_ard_3-2-1_106075_2022-12-24_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-12 09:46:22	ga_ls8c_ard_3-2-1_095071_2023-01-12_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-25 10:53:33	ga_ls8c_ard_3-2-1_106069_2023-01-25_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-01-31 10:22:29	ga_ls8c_ard_3-2-1_100084_2023-01-31_final
2023-02-08 11:08:18	ga_ls8c_ard_3-2-1_108075_2023-02-08_final
2023-02-10 09:22:13	ga_ls8c_ard_3-2-1_090088_2023-02-09_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-03-01 09:46:51	ga_ls8c_ard_3-2-1_095073_2023-03-01_final
2023-03-02 10:28:07	ga_ls8c_ard_3-2-1_102068_2023-03-02_final
2023-03-10 09:44:11	ga_ls8c_ard_3-2-1_094082_2023-03-10_final
2023-03-10 09:45:47	ga_ls8c_ard_3-2-1_094086_2023-03-10_final
2023-03-17 09:46:45	ga_ls8c_ard_3-2-1_095073_2023-03-17_final
2023-03-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2023-03-17_final
2023-03-25 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-03-25_final
2023-03-28 11:08:57	ga_ls8c_ard_3-2-1_108078_2023-03-28_final
2023-04-02 09:46:34	ga_ls8c_ard_3-2-1_095073_2023-04-02_final
2023-04-07 10:04:36	ga_ls8c_ard_3-2-1_098072_2023-04-07_final
2023-04-08 09:14:09	ga_ls8c_ard_3-2-1_089085_2023-04-07_final
2023-04-18 09:51:31	ga_ls8c_ard_3-2-1_095086_2023-04-18_final
2023-04-20 09:38:44	ga_ls8c_ard_3-2-1_093085_2023-04-20_final
2023-04-20 09:39:56	ga_ls8c_ard_3-2-1_093088_2023-04-20_final
2023-04-21 11:57:18	ga_ls8c_ard_3-2-1_116076_2023-04-21_final
2023-04-25 09:52:06	ga_ls8c_ard_3-2-1_096072_2023-04-25_final
2023-04-30 10:13:00	ga_ls8c_ard_3-2-1_099078_2023-04-30_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-06 09:39:50	ga_ls8c_ard_3-2-1_093088_2023-05-06_final
2023-05-10 10:51:56	ga_ls8c_ard_3-2-1_105083_2023-05-10_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_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