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
2021-08-15 10:53:44	ga_ls8c_ard_3-2-0_106070_2021-08-15_final
2021-08-24 10:46:48	ga_ls8c_ard_3-2-0_105068_2021-08-24_final
2021-09-04 10:28:19	ga_ls8c_ard_3-2-0_102068_2021-09-04_final
2021-09-25 10:46:55	ga_ls8c_ard_3-2-0_105068_2021-09-25_final
2021-09-26 11:30:59	ga_ls8c_ard_3-2-0_112070_2021-09-26_final
2021-10-04 09:07:30	ga_ls8c_ard_3-2-0_088082_2021-10-03_final
2021-10-08 11:58:59	ga_ls8c_ard_3-2-0_116078_2021-10-08_final
2021-10-09 09:22:05	ga_ls8c_ard_3-2-0_091072_2021-10-08_final
2021-10-19 09:58:00	ga_ls8c_ard_3-2-0_097069_2021-10-19_final
2021-10-26 10:10:10	ga_ls8c_ard_3-2-0_098084_2021-10-26_final
2021-11-01 11:07:58	ga_ls8c_ard_3-2-0_108074_2021-11-01_final
2021-11-12 10:46:59	ga_ls8c_ard_3-2-0_105068_2021-11-12_final
2021-11-14 10:40:12	ga_ls8c_ard_3-2-0_103082_2021-11-14_final
2021-11-19 10:53:31	ga_ls8c_ard_3-2-0_106069_2021-11-19_final
2021-11-24 09:32:24	ga_ls8c_ard_3-2-0_093067_2021-11-24_final
2021-12-04 10:09:06	ga_ls8c_ard_3-2-1_099066_2021-12-04_final
2021-12-05 10:54:45	ga_ls8c_ard_3-2-1_106072_2021-12-05_final
2021-12-21 09:21:01	ga_ls8c_ard_3-2-1_090085_2021-12-20_final
2021-12-30 09:16:22	ga_ls8c_ard_3-2-1_089089_2021-12-29_final
2022-01-29 11:05:06	ga_ls8c_ard_3-2-1_107083_2022-01-29_final
2022-01-31 09:13:51	ga_ls8c_ard_3-2-1_089083_2022-01-30_final
2022-02-03 11:20:50	ga_ls8c_ard_3-2-1_110076_2022-02-03_final
2022-02-04 10:24:25	ga_ls8c_ard_3-2-1_101074_2022-02-04_final
2022-02-09 10:46:08	ga_ls8c_ard_3-2-1_104082_2022-02-09_final
2022-02-10 09:46:55	ga_ls8c_ard_3-2-1_095073_2022-02-10_final
2022-02-10 11:26:12	ga_ls8c_ard_3-2-1_111074_2022-02-10_final
2022-02-16 09:13:23	ga_ls8c_ard_3-2-1_089082_2022-02-15_final
2022-02-16 10:49:04	ga_ls8c_ard_3-2-1_105074_2022-02-16_final
2022-02-16 10:49:52	ga_ls8c_ard_3-2-1_105076_2022-02-16_final
2022-03-12 09:57:32	ga_ls8c_ard_3-2-1_097069_2022-03-12_final
2022-03-23 11:18:33	ga_ls8c_ard_3-2-1_110071_2022-03-23_final
2022-03-27 09:21:16	ga_ls8c_ard_3-2-1_090087_2022-03-26_final
2022-04-02 10:19:26	ga_ls8c_ard_3-2-1_100078_2022-04-02_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-21 09:11:08	ga_ls8c_ard_3-2-1_089077_2022-04-20_final
2022-05-05 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-05-04_final
2022-05-22 10:09:41	ga_ls8c_ard_3-2-1_098084_2022-05-22_final
2022-05-23 09:16:27	ga_ls8c_ard_3-2-1_089090_2022-05-22_final
2022-05-28 11:06:16	ga_ls8c_ard_3-2-1_108071_2022-05-28_final
2022-07-17 09:22:55	ga_ls8c_ard_3-2-1_090090_2022-07-16_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-27 11:32:38	ga_ls8c_ard_3-2-1_112074_2022-07-27_final
2022-08-05 09:52:03	ga_ls8c_ard_3-2-1_095085_2022-08-05_final
2022-08-09 09:28:34	ga_ls8c_ard_3-2-1_091088_2022-08-08_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-10-03 09:29:41	ga_ls8c_ard_3-2-1_092075_2022-10-02_final
2022-10-06 11:39:03	ga_ls8c_ard_3-2-1_113074_2022-10-06_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-11-04 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-11-04_final
2022-11-06 09:23:19	ga_ls8c_ard_3-2-1_090090_2022-11-05_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-12 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-11-12_final
2022-11-22 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-11-21_final
2022-12-05 10:24:03	ga_ls8c_ard_3-2-1_101072_2022-12-05_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-08 10:56:32	ga_ls8c_ard_3-2-1_106076_2022-12-08_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2023-02-05 10:34:37	ga_ls8c_ard_3-2-1_103068_2023-02-05_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-03-21 09:28:21	ga_ls8c_ard_3-2-1_091089_2023-03-20_final
2023-05-04 11:24:44	ga_ls8c_ard_3-2-1_111072_2023-05-04_final
2023-05-05 10:27:30	ga_ls8c_ard_3-2-1_102068_2023-05-05_final
2023-05-07 10:21:05	ga_ls8c_ard_3-2-1_100083_2023-05-07_final
2023-05-16 10:08:24	ga_ls8c_ard_3-2-1_099067_2023-05-16_final
2023-05-21 10:27:45	ga_ls8c_ard_3-2-1_102069_2023-05-21_final
2023-05-21 10:32:56	ga_ls8c_ard_3-2-1_102082_2023-05-21_final
2023-05-24 09:26:34	ga_ls8c_ard_3-2-1_091086_2023-05-23_final
2023-05-25 10:06:15	ga_ls8c_ard_3-2-1_098077_2023-05-25_final
2023-06-01 10:09:38	ga_ls8c_ard_3-2-1_099070_2023-06-01_final
2023-06-05 11:28:14	ga_ls8c_ard_3-2-1_111081_2023-06-05_final
2023-06-06 10:28:14	ga_ls8c_ard_3-2-1_102070_2023-06-06_final
2023-06-10 11:44:03	ga_ls8c_ard_3-2-1_114074_2023-06-10_final
2023-06-11 09:14:20	ga_ls8c_ard_3-2-1_089086_2023-06-10_final
2023-06-14 09:45:16	ga_ls8c_ard_3-2-1_094086_2023-06-14_final
2023-06-16 11:11:00	ga_ls8c_ard_3-2-1_108084_2023-06-16_final
2023-06-20 10:44:41	ga_ls8c_ard_3-2-1_104080_2023-06-20_final
2023-07-05 11:41:41	ga_ls8c_ard_3-2-1_113083_2023-07-05_final
2023-07-26 10:16:41	ga_ls8c_ard_3-2-1_100071_2023-07-26_final
2023-07-29 10:48:49	ga_ls8c_ard_3-2-1_105074_2023-07-29_final
2023-08-21 09:21:28	ga_ls8c_ard_3-2-1_090087_2023-08-20_final
2023-08-22 09:57:33	ga_ls8c_ard_3-2-1_097069_2023-08-22_final
2023-08-25 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-08-25_final
2023-08-30 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-08-30_final
2023-09-23 09:57:38	ga_ls8c_ard_3-2-1_097069_2023-09-23_final
2023-09-29 09:26:36	ga_ls8c_ard_3-2-1_091084_2023-09-28_final
2023-10-07 10:08:51	ga_ls8c_ard_3-2-1_099066_2023-10-07_final
2023-10-10 10:42:35	ga_ls8c_ard_3-2-1_104073_2023-10-10_final
2023-10-23 10:11:18	ga_ls8c_ard_3-2-1_099072_2023-10-23_final
2023-11-07 09:29:38	ga_ls8c_ard_3-2-1_092076_2023-11-06_final
2023-11-07 11:08:07	ga_ls8c_ard_3-2-1_108075_2023-11-07_final
2023-11-08 11:51:21	ga_ls8c_ard_3-2-1_115075_2023-11-08_final
2023-12-16 11:17:07	ga_ls8c_ard_3-2-1_109082_2023-12-16_final
2023-12-18 11:05:10	ga_ls8c_ard_3-2-1_107083_2023-12-18_final
2023-12-19 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-12-19_final
2023-12-27 10:53:47	ga_ls8c_ard_3-2-1_106070_2023-12-27_final
2024-01-04 11:44:42	ga_ls8c_ard_3-2-1_114074_2024-01-04_final
2024-01-25 10:23:07	ga_ls8c_ard_3-2-1_101071_2024-01-25_final
2024-01-25 10:23:07	ga_ls8c_ard_3-2-1_101071_2024-01-25_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years