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
2020-06-16 12:37:07	ga_ls8c_ard_3-2-1_123067_2020-06-16_final
2022-01-05 10:08:59	ga_ls8c_ard_3-2-1_099066_2022-01-05_final
2022-02-08 10:04:04	ga_ls8c_ard_3-2-1_097085_2022-02-08_final
2022-02-21 09:34:17	ga_ls8c_ard_3-2-1_092088_2022-02-21_final
2022-02-22 10:14:21	ga_ls8c_ard_3-2-1_099080_2022-02-22_final
2022-02-24 11:37:41	ga_ls8c_ard_3-2-1_113072_2022-02-24_final
2022-03-01 10:18:55	ga_ls8c_ard_3-2-1_100076_2022-03-01_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_2022-03-03_final
2022-03-04 10:49:25	ga_ls8c_ard_3-2-1_105075_2022-03-04_final
2022-03-09 09:28:39	ga_ls8c_ard_3-2-1_092074_2022-03-08_final
2022-03-16 11:11:39	ga_ls8c_ard_3-2-1_109069_2022-03-16_final
2022-03-17 10:18:49	ga_ls8c_ard_3-2-1_100076_2022-03-17_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-11 10:08:57	ga_ls8c_ard_3-2-1_099067_2022-04-11_final
2022-04-13 09:57:00	ga_ls8c_ard_3-2-1_097068_2022-04-13_final
2022-04-15 11:25:08	ga_ls8c_ard_3-2-1_111072_2022-04-15_final
2022-04-26 11:07:43	ga_ls8c_ard_3-2-1_108075_2022-04-26_final
2022-04-28 09:16:51	ga_ls8c_ard_3-2-1_090076_2022-04-27_final
2022-04-29 10:02:54	ga_ls8c_ard_3-2-1_097083_2022-04-29_final
2022-05-10 11:18:12	ga_ls8c_ard_3-2-1_110070_2022-05-10_final
2022-05-10 11:20:12	ga_ls8c_ard_3-2-1_110075_2022-05-10_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-06-01 09:06:43	ga_ls8c_ard_3-2-1_088081_2022-05-31_final
2022-06-04 09:39:40	ga_ls8c_ard_3-2-1_093086_2022-06-04_final
2022-06-07 10:07:49	ga_ls8c_ard_3-2-1_098079_2022-06-07_final
2022-06-29 11:11:23	ga_ls8c_ard_3-2-1_108083_2022-06-29_final
2022-06-30 11:51:27	ga_ls8c_ard_3-2-1_115075_2022-06-30_final
2022-08-02 09:23:07	ga_ls8c_ard_3-2-1_090090_2022-08-01_final
2022-08-05 11:26:09	ga_ls8c_ard_3-2-1_111073_2022-08-05_final
2022-08-17 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-08-17_final
2022-08-18 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-08-17_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-09-13 11:36:05	ga_ls8c_ard_3-2-1_112082_2022-09-13_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-09-18 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-09-18_final
2022-09-29 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-09-29_final
2022-10-14 10:50:18	ga_ls8c_ard_3-2-1_105076_2022-10-14_final
2022-10-26 11:14:45	ga_ls8c_ard_3-2-1_109075_2022-10-26_final
2022-11-13 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-12_final
2022-11-17 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-11-17_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-26 10:28:37	ga_ls8c_ard_3-2-1_102068_2022-11-26_final
2022-12-03 10:36:24	ga_ls8c_ard_3-2-1_103072_2022-12-03_final
2022-12-07 10:09:17	ga_ls8c_ard_3-2-1_099066_2022-12-07_final
2022-12-30 10:18:07	ga_ls8c_ard_3-2-1_100073_2022-12-30_final
2022-12-31 09:27:17	ga_ls8c_ard_3-2-1_091085_2022-12-30_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-13 10:28:25	ga_ls8c_ard_3-2-1_102068_2023-01-13_final
2023-01-14 11:12:52	ga_ls8c_ard_3-2-1_109071_2023-01-14_final
2023-02-02 10:07:43	ga_ls8c_ard_3-2-1_098078_2023-02-02_final
2023-02-28 09:06:24	ga_ls8c_ard_3-2-1_088080_2023-02-27_final
2023-03-01 09:52:27	ga_ls8c_ard_3-2-1_095087_2023-03-01_final
2023-03-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2023-03-17_final
2023-03-19 09:39:33	ga_ls8c_ard_3-2-1_093086_2023-03-19_final
2023-03-31 09:57:45	ga_ls8c_ard_3-2-1_097070_2023-03-31_final
2023-04-04 09:33:22	ga_ls8c_ard_3-2-1_093071_2023-04-04_final
2023-04-17 10:39:58	ga_ls8c_ard_3-2-1_104068_2023-04-17_final
2023-04-27 11:18:37	ga_ls8c_ard_3-2-1_110072_2023-04-27_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-07 11:57:11	ga_ls8c_ard_3-2-1_116076_2023-05-07_final
2023-05-20 11:24:58	ga_ls8c_ard_3-2-1_111073_2023-05-20_final
2023-05-24 09:20:59	ga_ls8c_ard_3-2-1_091072_2023-05-23_final
2023-05-24 09:22:11	ga_ls8c_ard_3-2-1_091075_2023-05-23_final
2023-05-24 11:04:15	ga_ls8c_ard_3-2-1_107083_2023-05-24_final
2023-05-29 11:17:37	ga_ls8c_ard_3-2-1_110070_2023-05-29_final
2023-06-14 09:44:52	ga_ls8c_ard_3-2-1_094085_2023-06-14_final
2023-06-14 09:45:16	ga_ls8c_ard_3-2-1_094086_2023-06-14_final
2023-06-16 09:27:19	ga_ls8c_ard_3-2-1_092072_2023-06-15_final
2023-06-18 09:21:21	ga_ls8c_ard_3-2-1_090088_2023-06-17_final
2023-06-19 09:56:38	ga_ls8c_ard_3-2-1_097068_2023-06-19_final
2023-07-09 11:14:12	ga_ls8c_ard_3-2-1_109076_2023-07-09_final
2023-07-10 10:18:35	ga_ls8c_ard_3-2-1_100076_2023-07-10_final
2023-07-20 10:53:17	ga_ls8c_ard_3-2-1_106070_2023-07-20_final
2023-07-22 09:06:51	ga_ls8c_ard_3-2-1_088082_2023-07-21_final
2023-08-13 10:07:13	ga_ls8c_ard_3-2-1_098078_2023-08-13_final
2023-08-26 09:39:38	ga_ls8c_ard_3-2-1_093086_2023-08-26_final
2023-09-25 11:25:47	ga_ls8c_ard_3-2-1_111073_2023-09-25_final
2023-10-07 11:52:32	ga_ls8c_ard_3-2-1_115078_2023-10-07_final
2023-10-09 09:56:55	ga_ls8c_ard_3-2-1_097067_2023-10-09_final
2023-10-25 11:38:38	ga_ls8c_ard_3-2-1_113074_2023-10-25_final
2023-10-27 11:25:30	ga_ls8c_ard_3-2-1_111072_2023-10-27_final
2023-10-31 09:26:41	ga_ls8c_ard_3-2-1_091084_2023-10-30_final
2023-10-31 09:27:53	ga_ls8c_ard_3-2-1_091087_2023-10-30_final
2023-11-04 10:39:38	ga_ls8c_ard_3-2-1_103081_2023-11-04_final
2023-11-09 09:22:01	ga_ls8c_ard_3-2-1_090088_2023-11-08_final
2023-11-22 10:23:20	ga_ls8c_ard_3-2-1_101071_2023-11-22_final
2023-12-02 09:26:39	ga_ls8c_ard_3-2-1_091084_2023-12-01_final
2024-01-07 10:34:44	ga_ls8c_ard_3-2-1_103069_2024-01-07_final
2024-01-16 10:29:00	ga_ls8c_ard_3-2-1_102070_2024-01-16_final
2024-01-19 09:23:23	ga_ls8c_ard_3-2-1_091076_2024-01-18_final
2024-01-24 09:41:04	ga_ls8c_ard_3-2-1_094074_2024-01-24_final
2024-02-06 09:13:25	ga_ls8c_ard_3-2-1_089082_2024-02-05_final
2024-02-06 10:49:54	ga_ls8c_ard_3-2-1_105076_2024-02-06_final
2024-02-19 10:19:46	ga_ls8c_ard_3-2-1_100078_2024-02-19_final
2024-02-22 09:12:58	ga_ls8c_ard_3-2-1_089081_2024-02-21_final
2024-03-14 11:06:35	ga_ls8c_ard_3-2-1_108072_2024-03-14_final
2024-03-16 09:20:30	ga_ls8c_ard_3-2-1_090085_2024-03-15_final
2024-03-24 10:09:25	ga_ls8c_ard_3-2-1_098084_2024-03-24_final
2024-03-25 10:45:52	ga_ls8c_ard_3-2-1_105067_2024-03-25_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years