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
2022-04-19 09:23:06	ga_ls8c_ard_3-2-1_091076_2022-04-18_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-09 10:39:19	ga_ls8c_ard_3-2-1_103081_2022-05-09_final
2022-05-10 11:17:48	ga_ls8c_ard_3-2-1_110069_2022-05-10_final
2022-05-19 11:13:16	ga_ls8c_ard_3-2-1_109073_2022-05-19_final
2022-05-24 11:31:24	ga_ls8c_ard_3-2-1_112072_2022-05-24_final
2022-07-08 09:23:07	ga_ls8c_ard_3-2-1_091075_2022-07-07_final
2022-07-10 10:49:38	ga_ls8c_ard_3-2-1_105075_2022-07-10_final
2022-07-13 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-07-13_final
2022-07-22 09:34:45	ga_ls8c_ard_3-2-1_093073_2022-07-22_final
2022-08-05 09:52:03	ga_ls8c_ard_3-2-1_095085_2022-08-05_final
2022-08-09 09:22:34	ga_ls8c_ard_3-2-1_091073_2022-08-08_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-23 09:38:10	ga_ls8c_ard_3-2-1_093081_2022-08-23_final
2022-08-25 09:28:12	ga_ls8c_ard_3-2-1_091087_2022-08-24_final
2022-08-31 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-08-31_final
2022-09-01 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-08-31_final
2022-09-06 11:26:15	ga_ls8c_ard_3-2-1_111073_2022-09-06_final
2022-09-19 09:17:45	ga_ls8c_ard_3-2-1_090076_2022-09-18_final
2022-10-03 11:08:34	ga_ls8c_ard_3-2-1_108075_2022-10-03_final
2022-10-14 10:47:30	ga_ls8c_ard_3-2-1_105069_2022-10-14_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-30 09:12:21	ga_ls8c_ard_3-2-1_089078_2022-10-29_final
2022-11-04 09:29:18	ga_ls8c_ard_3-2-1_092074_2022-11-03_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-10 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-11-10_final
2022-12-01 10:49:34	ga_ls8c_ard_3-2-1_105074_2022-12-01_final
2022-12-06 09:28:25	ga_ls8c_ard_3-2-1_092072_2022-12-05_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2022-12-18 11:32:43	ga_ls8c_ard_3-2-1_112074_2022-12-18_final
2022-12-21 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-12-21_final
2022-12-24 09:21:04	ga_ls8c_ard_3-2-1_090085_2022-12-23_final
2022-12-24 09:22:16	ga_ls8c_ard_3-2-1_090088_2022-12-23_final
2022-12-27 11:30:29	ga_ls8c_ard_3-2-1_111084_2022-12-27_final
2023-01-07 11:05:57	ga_ls8c_ard_3-2-1_108069_2023-01-07_final
2023-01-16 11:00:04	ga_ls8c_ard_3-2-1_107070_2023-01-16_final
2023-01-24 11:51:34	ga_ls8c_ard_3-2-1_115075_2023-01-24_final
2023-01-24 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-01-24_final
2023-02-04 09:52:34	ga_ls8c_ard_3-2-1_096071_2023-02-04_final
2023-02-18 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-02-18_final
2023-02-19 10:47:36	ga_ls8c_ard_3-2-1_105070_2023-02-19_final
2023-02-26 09:16:45	ga_ls8c_ard_3-2-1_090075_2023-02-25_final
2023-03-03 09:34:29	ga_ls8c_ard_3-2-1_093073_2023-03-03_final
2023-03-15 09:57:32	ga_ls8c_ard_3-2-1_097069_2023-03-15_final
2023-03-15 09:57:56	ga_ls8c_ard_3-2-1_097070_2023-03-15_final
2023-03-17 09:46:45	ga_ls8c_ard_3-2-1_095073_2023-03-17_final
2023-03-19 11:11:39	ga_ls8c_ard_3-2-1_109069_2023-03-19_final
2023-03-22 10:04:01	ga_ls8c_ard_3-2-1_098070_2023-03-22_final
2023-03-28 09:32:52	ga_ls8c_ard_3-2-1_092085_2023-03-28_final
2023-03-29 10:10:56	ga_ls8c_ard_3-2-1_099072_2023-03-29_final
2023-04-04 09:33:46	ga_ls8c_ard_3-2-1_093072_2023-04-04_final
2023-04-14 10:15:04	ga_ls8c_ard_3-2-1_099083_2023-04-14_final
2023-04-15 10:53:08	ga_ls8c_ard_3-2-1_106070_2023-04-15_final
2023-05-08 09:27:51	ga_ls8c_ard_3-2-1_091089_2023-05-07_final
2023-05-15 09:28:20	ga_ls8c_ard_3-2-1_092075_2023-05-14_final
2023-05-16 10:09:12	ga_ls8c_ard_3-2-1_099069_2023-05-16_final
2023-05-20 11:22:58	ga_ls8c_ard_3-2-1_111068_2023-05-20_final
2023-07-03 10:09:33	ga_ls8c_ard_3-2-1_099069_2023-07-03_final
2023-07-05 09:56:49	ga_ls8c_ard_3-2-1_097068_2023-07-05_final
2023-07-11 09:22:34	ga_ls8c_ard_3-2-1_091075_2023-07-10_final
2023-07-26 10:16:41	ga_ls8c_ard_3-2-1_100071_2023-07-26_final
2023-07-27 09:28:40	ga_ls8c_ard_3-2-1_091090_2023-07-26_final
2023-08-14 09:13:37	ga_ls8c_ard_3-2-1_089083_2023-08-13_final
2023-08-14 10:49:42	ga_ls8c_ard_3-2-1_105076_2023-08-14_final
2023-08-27 10:21:42	ga_ls8c_ard_3-2-1_100083_2023-08-27_final
2023-09-04 09:27:50	ga_ls8c_ard_3-2-1_092072_2023-09-03_final
2023-09-13 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-09-12_final
2023-09-20 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-09-20_final
2023-09-25 11:24:59	ga_ls8c_ard_3-2-1_111071_2023-09-25_final
2023-10-06 11:06:04	ga_ls8c_ard_3-2-1_108070_2023-10-06_final
2023-10-07 10:13:39	ga_ls8c_ard_3-2-1_099078_2023-10-07_final
2023-10-09 11:38:36	ga_ls8c_ard_3-2-1_113074_2023-10-09_final
2023-10-22 09:28:01	ga_ls8c_ard_3-2-1_092072_2023-10-21_final
2023-10-22 09:34:49	ga_ls8c_ard_3-2-1_092089_2023-10-22_final
2023-10-27 11:25:30	ga_ls8c_ard_3-2-1_111072_2023-10-27_final
2023-10-28 10:30:17	ga_ls8c_ard_3-2-1_102073_2023-10-28_final
2023-11-02 09:14:43	ga_ls8c_ard_3-2-1_089085_2023-11-01_final
2023-11-05 09:40:49	ga_ls8c_ard_3-2-1_094073_2023-11-05_final
2023-11-07 11:07:43	ga_ls8c_ard_3-2-1_108074_2023-11-07_final
2023-11-08 11:52:57	ga_ls8c_ard_3-2-1_115079_2023-11-08_final
2023-11-13 10:30:14	ga_ls8c_ard_3-2-1_102073_2023-11-13_final
2023-11-27 09:07:22	ga_ls8c_ard_3-2-1_088082_2023-11-26_final
2023-12-03 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-12-03_final
2023-12-04 10:49:33	ga_ls8c_ard_3-2-1_105075_2023-12-04_final
2023-12-10 10:09:15	ga_ls8c_ard_3-2-1_099067_2023-12-10_final
2023-12-10 11:52:32	ga_ls8c_ard_3-2-1_115078_2023-12-10_final
2023-12-14 11:25:28	ga_ls8c_ard_3-2-1_111072_2023-12-14_final
2023-12-16 09:33:50	ga_ls8c_ard_3-2-1_093071_2023-12-16_final
2023-12-23 11:19:19	ga_ls8c_ard_3-2-1_110072_2023-12-23_final
2023-12-26 10:09:20	ga_ls8c_ard_3-2-1_099067_2023-12-26_final
2024-01-02 10:17:01	ga_ls8c_ard_3-2-1_100071_2024-01-02_final
2024-01-03 09:26:58	ga_ls8c_ard_3-2-1_091085_2024-01-02_final
2024-01-05 09:13:47	ga_ls8c_ard_3-2-1_089083_2024-01-04_final
2024-01-06 11:32:21	ga_ls8c_ard_3-2-1_112074_2024-01-06_final
2024-01-07 10:34:20	ga_ls8c_ard_3-2-1_103068_2024-01-07_final
2024-01-11 10:08:51	ga_ls8c_ard_3-2-1_099066_2024-01-11_final
2024-01-24 11:18:21	ga_ls8c_ard_3-2-1_110070_2024-01-24_final
2024-02-23 09:51:50	ga_ls8c_ard_3-2-1_096070_2024-02-23_final
2024-03-10 09:57:14	ga_ls8c_ard_3-2-1_096084_2024-03-10_final
2024-04-01 10:53:36	ga_ls8c_ard_3-2-1_106071_2024-04-01_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