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
2022-03-03 10:07:45	ga_ls8c_ard_3-2-1_098079_2022-03-03_final
2022-03-05 11:36:16	ga_ls8c_ard_3-2-1_112084_2022-03-05_final
2022-03-09 11:07:08	ga_ls8c_ard_3-2-1_108073_2022-03-09_final
2022-03-10 11:53:11	ga_ls8c_ard_3-2-1_115080_2022-03-10_final
2022-03-14 11:26:50	ga_ls8c_ard_3-2-1_111076_2022-03-14_final
2022-03-19 11:44:55	ga_ls8c_ard_3-2-1_114075_2022-03-19_final
2022-03-20 09:12:24	ga_ls8c_ard_3-2-1_089080_2022-03-19_final
2022-03-20 09:14:23	ga_ls8c_ard_3-2-1_089085_2022-03-19_final
2022-03-29 10:40:11	ga_ls8c_ard_3-2-1_104068_2022-03-29_final
2022-04-01 11:13:52	ga_ls8c_ard_3-2-1_109075_2022-04-01_final
2022-04-08 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-08_final
2022-04-09 10:24:05	ga_ls8c_ard_3-2-1_101074_2022-04-09_final
2022-04-10 09:31:40	ga_ls8c_ard_3-2-1_092082_2022-04-10_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-15 11:28:43	ga_ls8c_ard_3-2-1_111081_2022-04-15_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-29 10:01:19	ga_ls8c_ard_3-2-1_097079_2022-04-29_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-10 11:19:24	ga_ls8c_ard_3-2-1_110073_2022-05-10_final
2022-05-15 10:03:53	ga_ls8c_ard_3-2-1_097085_2022-05-15_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-20 10:17:15	ga_ls8c_ard_3-2-1_100072_2022-05-20_final
2022-05-23 09:12:51	ga_ls8c_ard_3-2-1_089081_2022-05-22_final
2022-05-28 11:07:04	ga_ls8c_ard_3-2-1_108073_2022-05-28_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-06 10:59:50	ga_ls8c_ard_3-2-1_107070_2022-06-06_final
2022-06-07 11:44:42	ga_ls8c_ard_3-2-1_114074_2022-06-07_final
2022-06-08 09:12:36	ga_ls8c_ard_3-2-1_089080_2022-06-07_final
2022-06-13 11:11:41	ga_ls8c_ard_3-2-1_108084_2022-06-13_final
2022-06-25 09:57:36	ga_ls8c_ard_3-2-1_096084_2022-06-25_final
2022-06-25 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-06-25_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_final
2022-06-29 11:10:11	ga_ls8c_ard_3-2-1_108080_2022-06-29_final
2022-07-02 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-02_final
2022-07-04 09:52:38	ga_ls8c_ard_3-2-1_095087_2022-07-04_final
2022-07-08 11:00:24	ga_ls8c_ard_3-2-1_107071_2022-07-08_final
2022-07-15 11:11:21	ga_ls8c_ard_3-2-1_108083_2022-07-15_final
2022-07-17 10:53:25	ga_ls8c_ard_3-2-1_106069_2022-07-17_final
2022-07-20 11:29:34	ga_ls8c_ard_3-2-1_111082_2022-07-20_final
2022-07-25 10:08:05	ga_ls8c_ard_3-2-1_098079_2022-07-25_final
2022-07-29 11:19:54	ga_ls8c_ard_3-2-1_110073_2022-07-29_final
2022-08-02 09:19:32	ga_ls8c_ard_3-2-1_090081_2022-08-01_final
2022-08-09 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-08-09_final
2022-08-11 10:46:43	ga_ls8c_ard_3-2-1_105067_2022-08-11_final
2022-08-15 10:26:24	ga_ls8c_ard_3-2-1_101078_2022-08-15_final
2022-08-20 09:06:52	ga_ls8c_ard_3-2-1_088080_2022-08-19_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-08-31 10:23:37	ga_ls8c_ard_3-2-1_101071_2022-08-31_final
2022-08-31 10:26:25	ga_ls8c_ard_3-2-1_101078_2022-08-31_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-04 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-09-04_final
2022-09-11 10:05:33	ga_ls8c_ard_3-2-1_098072_2022-09-11_final
2022-09-12 10:50:01	ga_ls8c_ard_3-2-1_105075_2022-09-12_final
2022-09-15 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-09-15_final
2022-09-17 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-09-16_final
2022-09-19 10:56:38	ga_ls8c_ard_3-2-1_106076_2022-09-19_final
2022-09-20 09:58:37	ga_ls8c_ard_3-2-1_097070_2022-09-20_final
2022-09-24 11:13:11	ga_ls8c_ard_3-2-1_109071_2022-09-24_final
2022-09-27 10:08:23	ga_ls8c_ard_3-2-1_098079_2022-09-27_final
2022-10-01 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-10-01_final
2022-10-06 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-06_final
2022-10-08 11:30:15	ga_ls8c_ard_3-2-1_111083_2022-10-08_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-15 09:52:18	ga_ls8c_ard_3-2-1_096070_2022-10-15_final
2022-10-24 09:50:36	ga_ls8c_ard_3-2-1_095081_2022-10-24_final
2022-11-14 10:05:30	ga_ls8c_ard_3-2-1_098072_2022-11-14_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-12-04 09:46:22	ga_ls8c_ard_3-2-1_094086_2022-12-04_final
2022-12-06 09:34:00	ga_ls8c_ard_3-2-1_092086_2022-12-06_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-11 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-12-11_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-20 11:20:19	ga_ls8c_ard_3-2-1_110074_2022-12-20_final
2022-12-21 10:27:52	ga_ls8c_ard_3-2-1_101082_2022-12-21_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-26 10:44:25	ga_ls8c_ard_3-2-1_104077_2022-12-26_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-08 11:51:12	ga_ls8c_ard_3-2-1_115074_2023-01-08_final
2023-01-17 11:46:06	ga_ls8c_ard_3-2-1_114077_2023-01-17_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-25 09:19:51	ga_ls8c_ard_3-2-1_090082_2023-01-24_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-01-31 10:20:05	ga_ls8c_ard_3-2-1_100078_2023-01-31_final
2023-02-01 09:24:52	ga_ls8c_ard_3-2-1_091079_2023-01-31_final
2023-02-08 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-02-08_final
2023-02-13 09:50:41	ga_ls8c_ard_3-2-1_095082_2023-02-13_final
2023-02-14 10:33:56	ga_ls8c_ard_3-2-1_102082_2023-02-14_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-22 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-02-22_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-05 11:01:23	ga_ls8c_ard_3-2-1_107074_2023-03-05_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