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
2019-12-15 10:09:02	ga_ls8c_ard_3-2-1_099066_2019-12-15_final
2022-01-22 09:23:16	ga_ls8c_ard_3-2-1_090091_2022-01-21_final
2022-02-07 10:53:19	ga_ls8c_ard_3-2-1_106069_2022-02-07_final
2022-03-04 10:49:25	ga_ls8c_ard_3-2-1_105075_2022-03-04_final
2022-03-04 10:49:49	ga_ls8c_ard_3-2-1_105076_2022-03-04_final
2022-03-30 11:25:01	ga_ls8c_ard_3-2-1_111072_2022-03-30_final
2022-04-17 09:34:17	ga_ls8c_ard_3-2-1_093073_2022-04-17_final
2022-04-18 10:19:08	ga_ls8c_ard_3-2-1_100077_2022-04-18_final
2022-04-21 10:46:26	ga_ls8c_ard_3-2-1_105068_2022-04-21_final
2022-04-24 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-24_final
2022-04-27 11:50:58	ga_ls8c_ard_3-2-1_115075_2022-04-27_final
2022-05-01 09:52:10	ga_ls8c_ard_3-2-1_095087_2022-05-01_final
2022-05-17 11:23:38	ga_ls8c_ard_3-2-1_111068_2022-05-17_final
2022-05-19 09:37:11	ga_ls8c_ard_3-2-1_093080_2022-05-19_final
2022-05-26 11:20:14	ga_ls8c_ard_3-2-1_110075_2022-05-26_final
2022-06-03 10:33:41	ga_ls8c_ard_3-2-1_102082_2022-06-03_final
2022-06-06 09:27:44	ga_ls8c_ard_3-2-1_091087_2022-06-05_final
2022-06-11 11:23:14	ga_ls8c_ard_3-2-1_110082_2022-06-11_final
2022-06-15 09:17:16	ga_ls8c_ard_3-2-1_090076_2022-06-14_final
2022-06-19 10:29:04	ga_ls8c_ard_3-2-1_102070_2022-06-19_final
2022-06-20 09:35:03	ga_ls8c_ard_3-2-1_093074_2022-06-20_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_final
2022-06-25 11:32:30	ga_ls8c_ard_3-2-1_112074_2022-06-25_final
2022-07-04 11:25:08	ga_ls8c_ard_3-2-1_111071_2022-07-04_final
2022-07-21 10:28:22	ga_ls8c_ard_3-2-1_102068_2022-07-21_final
2022-07-24 11:04:30	ga_ls8c_ard_3-2-1_107081_2022-07-24_final
2022-07-25 10:10:05	ga_ls8c_ard_3-2-1_098084_2022-07-25_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-08-05 11:24:33	ga_ls8c_ard_3-2-1_111069_2022-08-05_final
2022-08-06 10:28:32	ga_ls8c_ard_3-2-1_102068_2022-08-06_final
2022-08-06 10:34:07	ga_ls8c_ard_3-2-1_102082_2022-08-06_final
2022-09-18 10:14:10	ga_ls8c_ard_3-2-1_099078_2022-09-18_final
2022-09-19 09:23:20	ga_ls8c_ard_3-2-1_090090_2022-09-18_final
2022-09-25 10:20:21	ga_ls8c_ard_3-2-1_100078_2022-09-25_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-10-12 09:23:00	ga_ls8c_ard_3-2-1_091074_2022-10-11_final
2022-10-18 10:24:26	ga_ls8c_ard_3-2-1_101073_2022-10-18_final
2022-10-27 10:19:56	ga_ls8c_ard_3-2-1_100077_2022-10-27_final
2022-10-28 09:22:19	ga_ls8c_ard_3-2-1_091072_2022-10-27_final
2022-10-31 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-10-31_final
2022-11-13 09:22:16	ga_ls8c_ard_3-2-1_091072_2022-11-12_final
2022-11-18 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-11-18_final
2022-11-18 11:18:25	ga_ls8c_ard_3-2-1_110069_2022-11-18_final
2022-11-21 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-11-21_final
2022-11-25 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-11-25_final
2022-12-21 10:23:53	ga_ls8c_ard_3-2-1_101072_2022-12-21_final
2023-01-02 09:12:08	ga_ls8c_ard_3-2-1_089078_2023-01-01_final
2023-01-09 10:53:59	ga_ls8c_ard_3-2-1_106070_2023-01-09_final
2023-01-16 11:05:15	ga_ls8c_ard_3-2-1_107083_2023-01-16_final
2023-01-22 10:28:13	ga_ls8c_ard_3-2-1_101083_2023-01-22_final
2023-02-06 09:41:00	ga_ls8c_ard_3-2-1_094073_2023-02-06_final
2023-02-09 10:10:16	ga_ls8c_ard_3-2-1_099069_2023-02-09_final
2023-02-26 09:17:09	ga_ls8c_ard_3-2-1_090076_2023-02-25_final
2023-03-28 09:33:40	ga_ls8c_ard_3-2-1_092087_2023-03-28_final
2023-04-08 10:49:26	ga_ls8c_ard_3-2-1_105076_2023-04-08_final
2023-04-24 09:11:38	ga_ls8c_ard_3-2-1_089079_2023-04-23_final
2023-05-05 10:28:18	ga_ls8c_ard_3-2-1_102070_2023-05-05_final
2023-06-01 10:15:13	ga_ls8c_ard_3-2-1_099084_2023-06-01_final
2023-06-05 09:50:57	ga_ls8c_ard_3-2-1_095085_2023-06-05_final
2023-06-05 11:25:03	ga_ls8c_ard_3-2-1_111073_2023-06-05_final
2023-06-13 10:39:17	ga_ls8c_ard_3-2-1_103082_2023-06-13_final
2023-07-07 11:24:34	ga_ls8c_ard_3-2-1_111071_2023-07-07_final
2023-07-20 10:55:41	ga_ls8c_ard_3-2-1_106076_2023-07-20_final
2023-07-27 09:21:28	ga_ls8c_ard_3-2-1_091072_2023-07-26_final
2023-08-03 11:07:24	ga_ls8c_ard_3-2-1_108074_2023-08-03_final
2023-08-05 09:16:33	ga_ls8c_ard_3-2-1_090075_2023-08-04_final
2023-08-09 10:28:19	ga_ls8c_ard_3-2-1_102069_2023-08-09_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-27 10:21:42	ga_ls8c_ard_3-2-1_100083_2023-08-27_final
2023-08-30 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-08-30_final
2023-10-07 10:08:51	ga_ls8c_ard_3-2-1_099066_2023-10-07_final
2023-10-13 09:34:37	ga_ls8c_ard_3-2-1_093073_2023-10-13_final
2023-10-15 09:21:51	ga_ls8c_ard_3-2-1_091072_2023-10-14_final
2023-10-29 09:40:39	ga_ls8c_ard_3-2-1_093088_2023-10-29_final
2023-11-18 09:12:20	ga_ls8c_ard_3-2-1_089079_2023-11-17_final
2023-11-18 09:16:20	ga_ls8c_ard_3-2-1_089089_2023-11-17_final
2023-11-18 10:50:01	ga_ls8c_ard_3-2-1_105076_2023-11-18_final
2023-11-18 10:52:25	ga_ls8c_ard_3-2-1_105082_2023-11-18_final
2023-11-23 09:29:19	ga_ls8c_ard_3-2-1_092075_2023-11-22_final
2023-11-23 11:07:24	ga_ls8c_ard_3-2-1_108073_2023-11-23_final
2023-11-24 11:53:03	ga_ls8c_ard_3-2-1_115079_2023-11-24_final
2023-11-30 09:34:15	ga_ls8c_ard_3-2-1_093072_2023-11-30_final
2023-12-01 10:19:30	ga_ls8c_ard_3-2-1_100077_2023-12-01_final
2023-12-04 10:49:57	ga_ls8c_ard_3-2-1_105076_2023-12-04_final
2023-12-10 10:10:03	ga_ls8c_ard_3-2-1_099069_2023-12-10_final
2023-12-10 11:52:56	ga_ls8c_ard_3-2-1_115079_2023-12-10_final
2023-12-12 09:56:55	ga_ls8c_ard_3-2-1_097067_2023-12-12_final
2023-12-12 09:58:07	ga_ls8c_ard_3-2-1_097070_2023-12-12_final
2023-12-16 09:33:50	ga_ls8c_ard_3-2-1_093071_2023-12-16_final
2023-12-27 10:55:47	ga_ls8c_ard_3-2-1_106075_2023-12-27_final
2024-01-03 11:01:28	ga_ls8c_ard_3-2-1_107074_2024-01-03_final
2024-01-11 10:10:03	ga_ls8c_ard_3-2-1_099069_2024-01-11_final
2024-01-21 09:12:12	ga_ls8c_ard_3-2-1_089079_2024-01-20_final
2024-02-22 10:47:28	ga_ls8c_ard_3-2-1_105070_2024-02-22_final
2024-02-24 10:34:41	ga_ls8c_ard_3-2-1_103069_2024-02-24_final
2024-03-06 10:19:35	ga_ls8c_ard_3-2-1_100078_2024-03-06_final
2024-03-08 10:02:49	ga_ls8c_ard_3-2-1_098067_2024-03-08_final
2024-03-12 11:18:09	ga_ls8c_ard_3-2-1_110070_2024-03-12_final
2024-03-14 09:28:30	ga_ls8c_ard_3-2-1_092074_2024-03-13_final
2024-03-14 09:28:54	ga_ls8c_ard_3-2-1_092075_2024-03-13_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