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
2022-07-20 09:46:41	ga_ls8c_ard_3-2-1_095072_2022-07-20_final
2022-07-30 10:25:53	ga_ls8c_ard_3-2-1_101077_2022-07-30_final
2022-08-05 09:46:52	ga_ls8c_ard_3-2-1_095072_2022-08-05_final
2022-08-05 11:26:33	ga_ls8c_ard_3-2-1_111074_2022-08-05_final
2022-08-07 09:40:30	ga_ls8c_ard_3-2-1_093087_2022-08-07_final
2022-08-09 09:27:46	ga_ls8c_ard_3-2-1_091086_2022-08-08_final
2022-08-14 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-08-14_final
2022-08-18 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-08-18_final
2022-08-18 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-08-18_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-09-15 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-09-15_final
2022-09-26 11:02:25	ga_ls8c_ard_3-2-1_107075_2022-09-26_final
2022-09-29 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-09-29_final
2022-10-04 11:51:49	ga_ls8c_ard_3-2-1_115075_2022-10-04_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-17 09:45:57	ga_ls8c_ard_3-2-1_094085_2022-10-17_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-26 11:14:21	ga_ls8c_ard_3-2-1_109074_2022-10-26_final
2022-10-28 11:02:48	ga_ls8c_ard_3-2-1_107076_2022-10-28_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-17 10:37:34	ga_ls8c_ard_3-2-1_103075_2022-11-17_final
2022-11-20 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-11-20_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-12-01 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-30_final
2022-12-15 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-12-14_final
2022-12-15 09:28:33	ga_ls8c_ard_3-2-1_091088_2022-12-14_final
2023-01-09 10:55:10	ga_ls8c_ard_3-2-1_106073_2023-01-09_final
2023-01-18 09:12:47	ga_ls8c_ard_3-2-1_089080_2023-01-17_final
2023-01-19 09:53:16	ga_ls8c_ard_3-2-1_096073_2023-01-19_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-02-03 09:11:42	ga_ls8c_ard_3-2-1_089077_2023-02-02_final
2023-02-07 10:24:15	ga_ls8c_ard_3-2-1_101073_2023-02-07_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-02-10 09:21:25	ga_ls8c_ard_3-2-1_090086_2023-02-09_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-14 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-03-13_final
2023-03-15 11:38:24	ga_ls8c_ard_3-2-1_113074_2023-03-15_final
2023-03-16 10:45:58	ga_ls8c_ard_3-2-1_104082_2023-03-16_final
2023-03-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2023-03-17_final
2023-03-21 09:25:57	ga_ls8c_ard_3-2-1_091083_2023-03-20_final
2023-03-21 09:26:45	ga_ls8c_ard_3-2-1_091085_2023-03-20_final
2023-03-26 09:40:27	ga_ls8c_ard_3-2-1_094073_2023-03-26_final
2023-03-29 10:10:56	ga_ls8c_ard_3-2-1_099072_2023-03-29_final
2023-03-31 10:03:20	ga_ls8c_ard_3-2-1_097084_2023-03-31_final
2023-04-08 10:46:38	ga_ls8c_ard_3-2-1_105069_2023-04-08_final
2023-04-11 09:40:35	ga_ls8c_ard_3-2-1_094074_2023-04-11_final
2023-04-19 10:27:59	ga_ls8c_ard_3-2-1_102069_2023-04-19_final
2023-04-24 10:46:32	ga_ls8c_ard_3-2-1_105069_2023-04-24_final
2023-04-28 10:27:22	ga_ls8c_ard_3-2-1_101083_2023-04-28_final
2023-05-02 11:41:54	ga_ls8c_ard_3-2-1_113084_2023-05-02_final
2023-05-13 11:23:11	ga_ls8c_ard_3-2-1_110084_2023-05-13_final
2023-05-15 09:29:56	ga_ls8c_ard_3-2-1_092079_2023-05-14_final
2023-05-23 10:20:59	ga_ls8c_ard_3-2-1_100083_2023-05-23_final
2023-05-25 10:07:03	ga_ls8c_ard_3-2-1_098079_2023-05-25_final
2023-05-27 11:30:47	ga_ls8c_ard_3-2-1_112072_2023-05-27_final
2023-05-29 09:44:43	ga_ls8c_ard_3-2-1_094085_2023-05-29_final
2023-05-29 09:45:31	ga_ls8c_ard_3-2-1_094087_2023-05-29_final
2023-06-02 10:52:30	ga_ls8c_ard_3-2-1_106069_2023-06-02_final
2023-06-19 09:57:02	ga_ls8c_ard_3-2-1_097069_2023-06-19_final
2023-06-20 09:06:12	ga_ls8c_ard_3-2-1_088081_2023-06-19_final
2023-06-26 10:03:17	ga_ls8c_ard_3-2-1_098069_2023-06-26_final
2023-07-04 10:57:13	ga_ls8c_ard_3-2-1_106080_2023-07-04_final
2023-07-13 10:51:54	ga_ls8c_ard_3-2-1_105082_2023-07-13_final
2023-07-26 10:17:05	ga_ls8c_ard_3-2-1_100072_2023-07-26_final
2023-07-28 10:04:21	ga_ls8c_ard_3-2-1_098071_2023-07-28_final
2023-08-03 09:32:54	ga_ls8c_ard_3-2-1_092085_2023-08-03_final
2023-08-03 11:07:24	ga_ls8c_ard_3-2-1_108074_2023-08-03_final
2023-08-04 10:10:35	ga_ls8c_ard_3-2-1_099071_2023-08-04_final
2023-08-11 11:58:26	ga_ls8c_ard_3-2-1_116078_2023-08-11_final
2023-08-12 09:22:45	ga_ls8c_ard_3-2-1_091075_2023-08-11_final
2023-08-17 11:19:03	ga_ls8c_ard_3-2-1_110072_2023-08-17_final
2023-09-05 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-09-05_final
2023-09-06 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-09-05_final
2023-09-20 09:33:07	ga_ls8c_ard_3-2-1_092085_2023-09-20_final
2023-09-21 11:52:52	ga_ls8c_ard_3-2-1_115079_2023-09-21_final
2023-10-07 10:11:15	ga_ls8c_ard_3-2-1_099072_2023-10-07_final
2023-10-11 11:25:51	ga_ls8c_ard_3-2-1_111073_2023-10-11_final
2023-10-25 09:58:10	ga_ls8c_ard_3-2-1_097070_2023-10-25_final
2023-10-30 10:22:19	ga_ls8c_ard_3-2-1_100084_2023-10-30_final
2023-11-09 10:54:55	ga_ls8c_ard_3-2-1_106073_2023-11-09_final
2023-11-28 09:50:38	ga_ls8c_ard_3-2-1_095082_2023-11-28_final
2023-12-07 09:41:06	ga_ls8c_ard_3-2-1_094074_2023-12-07_final
2023-12-08 10:23:11	ga_ls8c_ard_3-2-1_101071_2023-12-08_final
2023-12-15 10:29:03	ga_ls8c_ard_3-2-1_102070_2023-12-15_final
2023-12-16 09:40:14	ga_ls8c_ard_3-2-1_093087_2023-12-16_final
2023-12-27 10:54:11	ga_ls8c_ard_3-2-1_106071_2023-12-27_final
2023-12-28 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-12-28_final
2024-01-06 09:57:27	ga_ls8c_ard_3-2-1_096084_2024-01-06_final
2024-01-12 09:23:13	ga_ls8c_ard_3-2-1_090091_2024-01-11_final
2024-02-16 11:28:56	ga_ls8c_ard_3-2-1_111081_2024-02-16_final
2024-02-28 10:10:44	ga_ls8c_ard_3-2-1_099071_2024-02-28_final
2024-03-07 09:23:08	ga_ls8c_ard_3-2-1_091076_2024-03-06_final
2024-03-13 10:22:56	ga_ls8c_ard_3-2-1_101071_2024-03-13_final
2024-03-23 10:59:29	ga_ls8c_ard_3-2-1_107070_2024-03-23_final
2024-03-25 10:47:52	ga_ls8c_ard_3-2-1_105072_2024-03-25_final
2024-03-26 11:35:53	ga_ls8c_ard_3-2-1_112084_2024-03-26_final
2024-04-09 10:09:44	ga_ls8c_ard_3-2-1_098085_2024-04-09_nrt

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