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
2016-02-10 09:52:23	ga_ls8c_ard_3-0-0_095087_2016-02-10_final
2016-12-26 09:51:02	ga_ls8c_ard_3-0-0_095083_2016-12-26_final
2021-03-06 11:11:29	ga_ls8c_ard_3-2-0_108084_2021-03-06_final
2021-03-09 09:57:05	ga_ls8c_ard_3-2-0_097068_2021-03-09_final
2021-03-15 09:22:20	ga_ls8c_ard_3-2-0_091074_2021-03-14_final
2021-04-01 11:46:48	ga_ls8c_ard_3-2-0_114080_2021-04-01_final
2021-04-05 11:18:04	ga_ls8c_ard_3-2-0_110070_2021-04-05_final
2021-04-23 09:29:05	ga_ls8c_ard_3-2-0_092076_2021-04-22_final
2021-05-10 11:51:08	ga_ls8c_ard_3-2-0_115076_2021-05-10_final
2021-05-14 09:45:58	ga_ls8c_ard_3-2-0_095072_2021-05-14_final
2021-06-02 10:16:39	ga_ls8c_ard_3-2-0_100071_2021-06-02_final
2021-06-24 09:46:05	ga_ls8c_ard_3-2-0_094087_2021-06-24_final
2021-06-27 10:11:00	ga_ls8c_ard_3-2-0_099072_2021-06-27_final
2021-06-28 09:17:47	ga_ls8c_ard_3-2-0_090078_2021-06-27_final
2021-07-04 10:21:36	ga_ls8c_ard_3-2-0_100083_2021-07-04_final
2021-07-14 10:52:42	ga_ls8c_ard_3-2-0_106068_2021-07-14_final
2021-07-16 10:40:20	ga_ls8c_ard_3-2-0_104068_2021-07-16_final
2021-07-18 10:30:48	ga_ls8c_ard_3-2-0_102075_2021-07-18_final
2021-07-31 11:35:42	ga_ls8c_ard_3-2-0_113067_2021-07-31_final
2021-08-11 11:24:01	ga_ls8c_ard_3-2-0_110084_2021-08-11_final
2021-09-03 09:45:51	ga_ls8c_ard_3-2-0_095070_2021-09-03_final
2021-09-17 10:01:27	ga_ls8c_ard_3-2-0_097078_2021-09-17_final
2021-09-23 09:22:47	ga_ls8c_ard_3-2-0_091074_2021-09-22_final
2021-09-24 10:10:26	ga_ls8c_ard_3-2-0_098085_2021-09-24_final
2021-09-28 09:43:45	ga_ls8c_ard_3-2-0_094080_2021-09-28_final
2021-10-13 10:40:15	ga_ls8c_ard_3-2-0_103082_2021-10-13_final
2021-11-07 10:30:52	ga_ls8c_ard_3-2-0_102074_2021-11-07_final
2021-11-08 11:16:31	ga_ls8c_ard_3-2-0_109080_2021-11-08_final
2021-12-01 11:20:40	ga_ls8c_ard_3-2-0_110075_2021-12-01_final
2021-12-06 09:57:32	ga_ls8c_ard_3-2-1_097068_2021-12-06_final
2021-12-14 09:13:40	ga_ls8c_ard_3-2-1_089082_2021-12-13_final
2022-01-19 10:28:05	ga_ls8c_ard_3-2-1_101083_2022-01-19_final
2022-03-03 11:44:38	ga_ls8c_ard_3-2-1_114074_2022-03-03_final
2022-03-06 10:34:39	ga_ls8c_ard_3-2-1_103069_2022-03-06_final
2022-03-20 09:11:36	ga_ls8c_ard_3-2-1_089078_2022-03-19_final
2022-03-25 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-03-25_final
2022-03-28 10:00:55	ga_ls8c_ard_3-2-1_097078_2022-03-28_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-05-10 11:23:47	ga_ls8c_ard_3-2-1_110084_2022-05-10_final
2022-05-14 10:55:06	ga_ls8c_ard_3-2-1_106074_2022-05-14_final
2022-05-20 11:58:32	ga_ls8c_ard_3-2-1_116078_2022-05-20_final
2022-06-16 11:37:50	ga_ls8c_ard_3-2-1_113072_2022-06-16_final
2022-07-01 09:22:32	ga_ls8c_ard_3-2-1_090089_2022-06-30_final
2022-07-09 11:45:40	ga_ls8c_ard_3-2-1_114076_2022-07-09_final
2022-07-15 09:29:40	ga_ls8c_ard_3-2-1_092076_2022-07-14_final
2022-07-16 10:12:56	ga_ls8c_ard_3-2-1_099076_2022-07-16_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-07-25 10:03:18	ga_ls8c_ard_3-2-1_098067_2022-07-25_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-08-23 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-08-23_final
2022-08-29 10:34:47	ga_ls8c_ard_3-2-1_103068_2022-08-29_final
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-03 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-09-02_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-06 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-06_final
2022-10-09 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-10-09_final
2022-10-12 09:26:35	ga_ls8c_ard_3-2-1_091083_2022-10-11_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-28 09:25:30	ga_ls8c_ard_3-2-1_091080_2022-10-27_final
2022-10-30 09:12:45	ga_ls8c_ard_3-2-1_089079_2022-10-29_final
2022-10-30 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-10-30_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-25 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-11-25_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2023-01-31 11:58:34	ga_ls8c_ard_3-2-1_116077_2023-01-31_final
2023-02-24 09:33:08	ga_ls8c_ard_3-2-1_092085_2023-02-24_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-08 11:01:32	ga_ls8c_ard_3-2-1_107076_2023-05-08_final
2023-05-09 10:03:30	ga_ls8c_ard_3-2-1_098070_2023-05-09_final
2023-05-15 09:33:07	ga_ls8c_ard_3-2-1_092087_2023-05-15_final
2023-06-02 09:22:00	ga_ls8c_ard_3-2-1_090090_2023-06-01_final
2023-06-14 11:23:21	ga_ls8c_ard_3-2-1_110084_2023-06-14_final
2023-06-24 10:20:47	ga_ls8c_ard_3-2-1_100082_2023-06-24_final
2023-06-25 09:21:36	ga_ls8c_ard_3-2-1_091073_2023-06-24_final
2023-06-26 11:46:33	ga_ls8c_ard_3-2-1_114080_2023-06-26_final
2023-07-03 10:08:46	ga_ls8c_ard_3-2-1_099067_2023-07-03_final
2023-08-14 09:10:25	ga_ls8c_ard_3-2-1_089075_2023-08-13_final
2023-08-19 09:33:01	ga_ls8c_ard_3-2-1_092085_2023-08-19_final
2023-09-03 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-09-03_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_final
2023-09-18 11:19:58	ga_ls8c_ard_3-2-1_110074_2023-09-18_final
2023-09-22 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-09-22_final
2023-09-23 09:56:50	ga_ls8c_ard_3-2-1_097067_2023-09-23_final
2023-10-11 11:23:51	ga_ls8c_ard_3-2-1_111068_2023-10-11_final
2023-10-18 09:57:31	ga_ls8c_ard_3-2-1_096084_2023-10-18_final
2023-10-26 09:06:32	ga_ls8c_ard_3-2-1_088080_2023-10-25_final
2023-11-07 09:34:01	ga_ls8c_ard_3-2-1_092087_2023-11-07_final
2023-11-17 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-11-17_final
2023-12-03 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-12-03_final
2023-12-09 11:10:03	ga_ls8c_ard_3-2-1_108080_2023-12-09_final
2023-12-17 10:21:54	ga_ls8c_ard_3-2-1_100083_2023-12-17_final
2023-12-21 09:57:59	ga_ls8c_ard_3-2-1_096085_2023-12-21_final
2024-01-15 09:47:44	ga_ls8c_ard_3-2-1_095075_2024-01-15_final
2024-01-21 09:13:24	ga_ls8c_ard_3-2-1_089082_2024-01-20_final
2024-02-01 10:30:08	ga_ls8c_ard_3-2-1_102073_2024-02-01_final
2024-02-20 09:23:44	ga_ls8c_ard_3-2-1_091077_2024-02-19_final
2024-02-22 09:11:22	ga_ls8c_ard_3-2-1_089077_2024-02-21_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