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
2021-07-05 09:23:35	ga_ls8c_ard_3-2-0_091077_2021-07-04_final
2021-07-05 10:59:40	ga_ls8c_ard_3-2-0_107070_2021-07-05_final
2021-07-17 09:45:55	ga_ls8c_ard_3-2-0_095071_2021-07-17_final
2021-07-23 10:51:23	ga_ls8c_ard_3-2-0_105080_2021-07-23_final
2021-07-24 09:55:22	ga_ls8c_ard_3-2-0_096079_2021-07-24_final
2021-08-04 09:34:55	ga_ls8c_ard_3-2-0_093074_2021-08-04_final
2021-08-04 11:16:36	ga_ls8c_ard_3-2-0_109081_2021-08-04_final
2021-08-04 11:17:00	ga_ls8c_ard_3-2-0_109082_2021-08-04_final
2021-08-06 09:23:46	ga_ls8c_ard_3-2-0_091077_2021-08-05_final
2021-08-07 10:03:27	ga_ls8c_ard_3-2-0_098068_2021-08-07_final
2021-08-16 10:02:30	ga_ls8c_ard_3-2-0_097081_2021-08-16_final
2021-08-19 10:31:02	ga_ls8c_ard_3-2-0_102075_2021-08-19_final
2021-09-15 10:15:48	ga_ls8c_ard_3-2-0_099083_2021-09-15_final
2021-09-20 10:30:45	ga_ls8c_ard_3-2-0_102074_2021-09-20_final
2021-09-30 09:28:13	ga_ls8c_ard_3-2-0_092072_2021-09-29_final
2021-10-21 11:25:19	ga_ls8c_ard_3-2-0_111071_2021-10-21_final
2021-10-23 09:39:40	ga_ls8c_ard_3-2-0_093085_2021-10-23_final
2021-10-26 10:04:11	ga_ls8c_ard_3-2-0_098069_2021-10-26_final
2021-10-27 09:13:21	ga_ls8c_ard_3-2-0_089081_2021-10-26_final
2021-11-02 11:52:02	ga_ls8c_ard_3-2-0_115076_2021-11-02_final
2021-11-04 10:01:10	ga_ls8c_ard_3-2-0_097077_2021-11-04_final
2021-11-08 09:35:14	ga_ls8c_ard_3-2-0_093074_2021-11-08_final
2021-11-20 10:02:17	ga_ls8c_ard_3-2-0_097080_2021-11-20_final
2021-11-22 09:52:44	ga_ls8c_ard_3-2-0_095087_2021-11-22_final
2021-11-24 11:17:16	ga_ls8c_ard_3-2-0_109082_2021-11-24_final
2021-11-28 10:51:45	ga_ls8c_ard_3-2-0_105080_2021-11-28_final
2021-12-01 09:45:22	ga_ls8c_ard_3-2-0_094084_2021-12-01_final
2021-12-02 10:24:15	ga_ls8c_ard_3-2-0_101073_2021-12-02_final
2021-12-06 11:41:12	ga_ls8c_ard_3-2-1_113080_2021-12-06_final
2021-12-08 11:25:39	ga_ls8c_ard_3-2-1_111072_2021-12-08_final
2021-12-08 11:30:02	ga_ls8c_ard_3-2-1_111083_2021-12-08_final
2021-12-15 09:54:55	ga_ls8c_ard_3-2-1_096077_2021-12-15_final
2021-12-23 10:42:44	ga_ls8c_ard_3-2-1_104073_2021-12-23_final
2021-12-24 09:50:18	ga_ls8c_ard_3-2-1_095081_2021-12-24_final
2022-01-06 09:18:56	ga_ls8c_ard_3-2-1_090080_2022-01-05_final
2022-01-13 09:26:18	ga_ls8c_ard_3-2-1_091083_2022-01-12_final
2022-01-14 11:46:27	ga_ls8c_ard_3-2-1_114078_2022-01-14_final
2022-02-07 10:56:54	ga_ls8c_ard_3-2-1_106078_2022-02-07_final
2022-02-12 11:13:25	ga_ls8c_ard_3-2-1_109073_2022-02-12_final
2022-02-13 10:21:23	ga_ls8c_ard_3-2-1_100082_2022-02-13_final
2022-02-19 11:22:44	ga_ls8c_ard_3-2-1_110081_2022-02-19_final
2022-03-08 10:25:52	ga_ls8c_ard_3-2-1_101078_2022-03-08_final
2022-03-09 09:32:14	ga_ls8c_ard_3-2-1_092083_2022-03-09_final
2022-03-16 11:16:50	ga_ls8c_ard_3-2-1_109082_2022-03-16_final
2022-03-16 11:17:14	ga_ls8c_ard_3-2-1_109083_2022-03-16_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-26 09:32:26	ga_ls8c_ard_3-2-1_092084_2022-04-26_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-05-23 10:46:57	ga_ls8c_ard_3-2-1_105069_2022-05-23_final
2022-06-23 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-06-23_final
2022-06-26 10:34:53	ga_ls8c_ard_3-2-1_103069_2022-06-26_final
2022-07-08 09:27:07	ga_ls8c_ard_3-2-1_091085_2022-07-07_final
2022-07-16 10:12:56	ga_ls8c_ard_3-2-1_099076_2022-07-16_final
2022-07-20 09:50:41	ga_ls8c_ard_3-2-1_095082_2022-07-20_final
2022-08-23 11:13:28	ga_ls8c_ard_3-2-1_109072_2022-08-23_final
2022-08-30 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-08-30_final
2022-09-10 09:23:53	ga_ls8c_ard_3-2-1_091076_2022-09-09_final
2022-09-15 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-09-15_final
2022-09-16 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-09-16_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-24 11:17:34	ga_ls8c_ard_3-2-1_109082_2022-09-24_final
2022-09-26 09:23:08	ga_ls8c_ard_3-2-1_091074_2022-09-25_final
2022-10-01 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-10-01_final
2022-10-05 10:57:23	ga_ls8c_ard_3-2-1_106078_2022-10-05_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-17 11:19:39	ga_ls8c_ard_3-2-1_110072_2022-10-17_final
2022-10-23 10:45:25	ga_ls8c_ard_3-2-1_104079_2022-10-23_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-07 11:42:40	ga_ls8c_ard_3-2-1_113083_2022-11-07_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-11-23 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-11-23_final
2022-12-09 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-12-09_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-25 11:40:26	ga_ls8c_ard_3-2-1_113078_2022-12-25_final
2022-12-27 09:51:12	ga_ls8c_ard_3-2-1_095083_2022-12-27_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2023-01-17 11:45:42	ga_ls8c_ard_3-2-1_114076_2023-01-17_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-20 11:34:02	ga_ls8c_ard_3-2-1_112078_2023-02-20_final
2023-03-07 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-03-06_final
2023-03-12 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-03-12_final
2023-03-14 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-03-14_final
2023-03-26 09:44:26	ga_ls8c_ard_3-2-1_094083_2023-03-26_final
2023-04-05 11:58:17	ga_ls8c_ard_3-2-1_116078_2023-04-05_final
2023-04-10 10:34:14	ga_ls8c_ard_3-2-1_103069_2023-04-10_final
2023-04-10 10:35:02	ga_ls8c_ard_3-2-1_103071_2023-04-10_final
2023-04-10 10:35:49	ga_ls8c_ard_3-2-1_103073_2023-04-10_final
2023-04-14 10:11:53	ga_ls8c_ard_3-2-1_099075_2023-04-14_final
2023-04-20 11:16:25	ga_ls8c_ard_3-2-1_109082_2023-04-20_final
2023-04-21 10:18:25	ga_ls8c_ard_3-2-1_100076_2023-04-21_final
2023-04-21 11:58:06	ga_ls8c_ard_3-2-1_116078_2023-04-21_final
2023-05-04 09:46:38	ga_ls8c_ard_3-2-1_095074_2023-05-04_final
2023-05-12 10:35:56	ga_ls8c_ard_3-2-1_103074_2023-05-12_final
2023-05-15 11:04:49	ga_ls8c_ard_3-2-1_108069_2023-05-15_final
2023-05-25 11:43:56	ga_ls8c_ard_3-2-1_114074_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