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
2021-12-16 10:36:11	ga_ls8c_ard_3-2-1_103072_2021-12-16_final
2021-12-18 10:24:13	ga_ls8c_ard_3-2-1_101073_2021-12-18_final
2022-01-02 09:44:28	ga_ls8c_ard_3-2-1_094082_2022-01-02_final
2022-01-04 09:33:18	ga_ls8c_ard_3-2-1_092085_2022-01-04_final
2022-01-13 11:02:47	ga_ls8c_ard_3-2-1_107077_2022-01-13_final
2022-01-20 09:33:15	ga_ls8c_ard_3-2-1_092085_2022-01-20_final
2022-01-29 11:04:42	ga_ls8c_ard_3-2-1_107082_2022-01-29_final
2022-02-05 11:08:04	ga_ls8c_ard_3-2-1_108075_2022-02-05_final
2022-02-16 09:12:59	ga_ls8c_ard_3-2-1_089081_2022-02-15_final
2022-02-17 09:52:15	ga_ls8c_ard_3-2-1_096071_2022-02-17_final
2022-02-21 09:29:05	ga_ls8c_ard_3-2-1_092075_2022-02-20_final
2022-02-26 11:30:06	ga_ls8c_ard_3-2-1_111084_2022-02-26_final
2022-03-20 10:49:41	ga_ls8c_ard_3-2-1_105076_2022-03-20_final
2022-03-23 09:46:03	ga_ls8c_ard_3-2-1_094087_2022-03-23_final
2022-03-23 11:22:56	ga_ls8c_ard_3-2-1_110082_2022-03-23_final
2022-03-25 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-03-25_final
2022-03-26 10:10:55	ga_ls8c_ard_3-2-1_099072_2022-03-26_final
2022-04-01 09:39:46	ga_ls8c_ard_3-2-1_093087_2022-04-01_final
2022-04-07 10:35:38	ga_ls8c_ard_3-2-1_103072_2022-04-07_final
2022-04-27 10:15:41	ga_ls8c_ard_3-2-1_099084_2022-04-27_final
2022-05-14 09:20:37	ga_ls8c_ard_3-2-1_090085_2022-05-13_final
2022-05-18 10:31:36	ga_ls8c_ard_3-2-1_102077_2022-05-18_final
2022-05-21 11:02:54	ga_ls8c_ard_3-2-1_107078_2022-05-21_final
2022-05-30 10:57:56	ga_ls8c_ard_3-2-1_106081_2022-05-30_final
2022-06-04 09:34:29	ga_ls8c_ard_3-2-1_093073_2022-06-04_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-06 09:25:20	ga_ls8c_ard_3-2-1_091081_2022-06-05_final
2022-06-06 09:27:20	ga_ls8c_ard_3-2-1_091086_2022-06-05_final
2022-06-06 11:02:14	ga_ls8c_ard_3-2-1_107076_2022-06-06_final
2022-06-18 09:52:35	ga_ls8c_ard_3-2-1_095087_2022-06-18_final
2022-07-19 10:45:29	ga_ls8c_ard_3-2-1_104080_2022-07-19_final
2022-07-19 10:45:53	ga_ls8c_ard_3-2-1_104081_2022-07-19_final
2022-08-03 10:01:36	ga_ls8c_ard_3-2-1_097078_2022-08-03_final
2022-08-09 09:29:21	ga_ls8c_ard_3-2-1_091090_2022-08-08_final
2022-09-07 10:28:38	ga_ls8c_ard_3-2-1_102068_2022-09-07_final
2022-09-07 10:33:50	ga_ls8c_ard_3-2-1_102081_2022-09-07_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-09-15 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-09-15_final
2022-09-18 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-09-18_final
2022-09-22 09:48:15	ga_ls8c_ard_3-2-1_095075_2022-09-22_final
2022-10-05 10:53:24	ga_ls8c_ard_3-2-1_106068_2022-10-05_final
2022-10-16 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-10-16_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-11-04 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-11-04_final
2022-11-08 10:43:27	ga_ls8c_ard_3-2-1_104074_2022-11-08_final
2022-11-12 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-11-12_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-22 09:18:02	ga_ls8c_ard_3-2-1_090077_2022-11-21_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-06 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-12-06_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-18 09:57:49	ga_ls8c_ard_3-2-1_096084_2022-12-18_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-22 09:29:26	ga_ls8c_ard_3-2-1_092075_2022-12-21_final
2022-12-23 10:14:41	ga_ls8c_ard_3-2-1_099080_2022-12-23_final
2022-12-31 11:02:59	ga_ls8c_ard_3-2-1_107077_2022-12-31_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-09 10:53:11	ga_ls8c_ard_3-2-1_106068_2023-01-09_final
2023-01-13 10:28:25	ga_ls8c_ard_3-2-1_102068_2023-01-13_final
2023-01-25 10:53:57	ga_ls8c_ard_3-2-1_106070_2023-01-25_final
2023-01-29 10:28:27	ga_ls8c_ard_3-2-1_102068_2023-01-29_final
2023-02-11 11:42:21	ga_ls8c_ard_3-2-1_113083_2023-02-11_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-24 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-02-24_final
2023-03-13 10:13:53	ga_ls8c_ard_3-2-1_099079_2023-03-13_final
2023-03-28 09:30:28	ga_ls8c_ard_3-2-1_092079_2023-03-28_final
2023-04-17 10:45:33	ga_ls8c_ard_3-2-1_104082_2023-04-17_final
2023-04-19 10:30:23	ga_ls8c_ard_3-2-1_102075_2023-04-19_final
2023-05-08 11:03:56	ga_ls8c_ard_3-2-1_107082_2023-05-08_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-20 09:50:52	ga_ls8c_ard_3-2-1_095085_2023-05-20_final
2023-05-28 10:38:45	ga_ls8c_ard_3-2-1_103081_2023-05-28_final
2023-06-05 09:48:09	ga_ls8c_ard_3-2-1_095078_2023-06-05_final
2023-06-05 09:51:45	ga_ls8c_ard_3-2-1_095087_2023-06-05_final
2023-06-30 11:19:30	ga_ls8c_ard_3-2-1_110074_2023-06-30_final
2023-07-14 09:57:53	ga_ls8c_ard_3-2-1_096086_2023-07-14_final
2023-08-01 09:40:04	ga_ls8c_ard_3-2-1_094072_2023-08-01_final
2023-08-06 10:03:25	ga_ls8c_ard_3-2-1_097084_2023-08-06_final
2023-08-06 10:03:49	ga_ls8c_ard_3-2-1_097085_2023-08-06_final
2023-08-12 11:05:13	ga_ls8c_ard_3-2-1_107084_2023-08-12_final
2023-08-13 10:09:13	ga_ls8c_ard_3-2-1_098083_2023-08-13_final
2023-08-14 09:11:13	ga_ls8c_ard_3-2-1_089077_2023-08-13_final
2023-08-21 09:21:52	ga_ls8c_ard_3-2-1_090088_2023-08-20_final
2023-08-25 10:33:39	ga_ls8c_ard_3-2-1_102082_2023-08-25_final
2023-09-13 11:04:36	ga_ls8c_ard_3-2-1_107082_2023-09-13_final
2023-09-15 09:16:10	ga_ls8c_ard_3-2-1_089089_2023-09-14_final
2023-09-19 10:25:09	ga_ls8c_ard_3-2-1_101076_2023-09-19_final
2023-09-24 10:45:42	ga_ls8c_ard_3-2-1_104081_2023-09-24_final
2023-10-02 11:32:23	ga_ls8c_ard_3-2-1_112074_2023-10-02_final
2023-10-07 10:14:03	ga_ls8c_ard_3-2-1_099079_2023-10-07_final
2023-10-11 11:25:51	ga_ls8c_ard_3-2-1_111073_2023-10-11_final
2023-10-23 10:16:05	ga_ls8c_ard_3-2-1_099084_2023-10-23_final
2023-10-31 09:22:18	ga_ls8c_ard_3-2-1_091073_2023-10-30_final
2023-11-15 10:22:17	ga_ls8c_ard_3-2-1_100084_2023-11-15_final
2023-11-16 09:27:04	ga_ls8c_ard_3-2-1_091085_2023-11-15_final
2023-11-20 10:39:16	ga_ls8c_ard_3-2-1_103080_2023-11-20_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