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
2021-10-27 10:49:50	ga_ls8c_ard_3-2-0_105075_2021-10-27_final
2021-11-09 10:17:42	ga_ls8c_ard_3-2-0_100072_2021-11-09_final
2021-11-14 10:40:12	ga_ls8c_ard_3-2-0_103082_2021-11-14_final
2021-11-17 09:29:00	ga_ls8c_ard_3-2-0_092074_2021-11-16_final
2021-11-18 10:11:03	ga_ls8c_ard_3-2-0_099071_2021-11-18_final
2021-12-03 09:29:25	ga_ls8c_ard_3-2-0_092075_2021-12-02_final
2021-12-26 11:14:49	ga_ls8c_ard_3-2-1_109076_2021-12-26_final
2022-01-15 10:46:50	ga_ls8c_ard_3-2-1_105068_2022-01-15_final
2022-01-18 09:40:26	ga_ls8c_ard_3-2-1_094072_2022-01-18_final
2022-01-23 09:58:32	ga_ls8c_ard_3-2-1_097071_2022-01-23_final
2022-01-27 11:12:16	ga_ls8c_ard_3-2-1_109070_2022-01-27_final
2022-02-05 09:33:59	ga_ls8c_ard_3-2-1_092087_2022-02-05_final
2022-02-07 09:22:01	ga_ls8c_ard_3-2-1_090088_2022-02-06_final
2022-02-07 10:55:42	ga_ls8c_ard_3-2-1_106075_2022-02-07_final
2022-02-08 11:38:34	ga_ls8c_ard_3-2-1_113074_2022-02-08_final
2022-03-05 11:31:28	ga_ls8c_ard_3-2-1_112072_2022-03-05_final
2022-03-12 09:56:44	ga_ls8c_ard_3-2-1_097067_2022-03-12_final
2022-03-20 10:49:41	ga_ls8c_ard_3-2-1_105076_2022-03-20_final
2022-03-31 10:28:12	ga_ls8c_ard_3-2-1_102069_2022-03-31_final
2022-04-03 09:21:25	ga_ls8c_ard_3-2-1_091072_2022-04-02_final
2022-04-24 11:18:06	ga_ls8c_ard_3-2-1_110070_2022-04-24_final
2022-05-28 09:34:58	ga_ls8c_ard_3-2-1_092090_2022-05-28_final
2022-05-30 10:57:08	ga_ls8c_ard_3-2-1_106079_2022-05-30_final
2022-06-05 10:16:57	ga_ls8c_ard_3-2-1_100071_2022-06-05_final
2022-06-11 11:18:50	ga_ls8c_ard_3-2-1_110071_2022-06-11_final
2022-06-15 10:56:09	ga_ls8c_ard_3-2-1_106076_2022-06-15_final
2022-06-23 10:07:34	ga_ls8c_ard_3-2-1_098078_2022-06-23_final
2022-06-30 10:10:10	ga_ls8c_ard_3-2-1_099069_2022-06-30_final
2022-07-06 11:11:58	ga_ls8c_ard_3-2-1_109069_2022-07-06_final
2022-07-13 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-07-13_final
2022-07-17 10:58:13	ga_ls8c_ard_3-2-1_106081_2022-07-17_final
2022-07-26 10:49:22	ga_ls8c_ard_3-2-1_105074_2022-07-26_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-31 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-08-31_final
2022-09-13 11:32:05	ga_ls8c_ard_3-2-1_112072_2022-09-13_final
2022-09-15 09:40:27	ga_ls8c_ard_3-2-1_094071_2022-09-15_final
2022-10-05 10:56:11	ga_ls8c_ard_3-2-1_106075_2022-10-05_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-30 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-10-30_final
2022-11-05 10:14:09	ga_ls8c_ard_3-2-1_099078_2022-11-05_final
2022-11-05 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-11-05_final
2022-11-08 10:44:39	ga_ls8c_ard_3-2-1_104077_2022-11-08_final
2022-11-22 10:53:44	ga_ls8c_ard_3-2-1_106069_2022-11-22_final
2022-11-29 09:22:15	ga_ls8c_ard_3-2-1_091072_2022-11-28_final
2022-12-04 09:41:11	ga_ls8c_ard_3-2-1_094073_2022-12-04_final
2022-12-15 11:05:26	ga_ls8c_ard_3-2-1_107083_2022-12-15_final
2022-12-16 10:03:25	ga_ls8c_ard_3-2-1_098067_2022-12-16_final
2022-12-17 09:14:34	ga_ls8c_ard_3-2-1_089084_2022-12-16_final
2022-12-24 09:17:29	ga_ls8c_ard_3-2-1_090076_2022-12-23_final
2023-01-07 09:29:04	ga_ls8c_ard_3-2-1_092074_2023-01-06_final
2023-01-18 10:47:17	ga_ls8c_ard_3-2-1_105069_2023-01-18_final
2023-01-21 09:40:57	ga_ls8c_ard_3-2-1_094073_2023-01-21_final
2023-01-25 10:53:33	ga_ls8c_ard_3-2-1_106069_2023-01-25_final
2023-01-30 09:34:49	ga_ls8c_ard_3-2-1_093073_2023-01-30_final
2023-02-04 09:58:09	ga_ls8c_ard_3-2-1_096085_2023-02-04_final
2023-02-09 10:11:28	ga_ls8c_ard_3-2-1_099072_2023-02-09_final
2023-02-09 10:14:16	ga_ls8c_ard_3-2-1_099079_2023-02-09_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-02-10 09:17:26	ga_ls8c_ard_3-2-1_090076_2023-02-09_final
2023-02-10 09:17:50	ga_ls8c_ard_3-2-1_090077_2023-02-09_final
2023-02-13 11:25:58	ga_ls8c_ard_3-2-1_111073_2023-02-13_final
2023-03-04 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-03-04_final
2023-03-22 10:02:49	ga_ls8c_ard_3-2-1_098067_2023-03-22_final
2023-04-14 10:09:53	ga_ls8c_ard_3-2-1_099070_2023-04-14_final
2023-05-07 10:18:42	ga_ls8c_ard_3-2-1_100077_2023-05-07_final
2023-05-20 09:51:16	ga_ls8c_ard_3-2-1_095086_2023-05-20_final
2023-05-31 09:33:10	ga_ls8c_ard_3-2-1_092087_2023-05-31_final
2023-06-01 10:13:13	ga_ls8c_ard_3-2-1_099079_2023-06-01_final
2023-06-11 10:48:50	ga_ls8c_ard_3-2-1_105075_2023-06-11_final
2023-06-25 09:28:23	ga_ls8c_ard_3-2-1_091090_2023-06-24_final
2023-07-10 10:19:23	ga_ls8c_ard_3-2-1_100078_2023-07-10_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-19 11:52:06	ga_ls8c_ard_3-2-1_115078_2023-07-19_final
2023-07-21 11:38:09	ga_ls8c_ard_3-2-1_113074_2023-07-21_final
2023-07-25 09:33:25	ga_ls8c_ard_3-2-1_093071_2023-07-25_final
2023-07-30 09:57:12	ga_ls8c_ard_3-2-1_096084_2023-07-30_final
2023-08-03 09:28:31	ga_ls8c_ard_3-2-1_092074_2023-08-02_final
2023-08-08 11:25:57	ga_ls8c_ard_3-2-1_111074_2023-08-08_final
2023-08-19 09:34:13	ga_ls8c_ard_3-2-1_092088_2023-08-19_final
2023-08-19 11:07:54	ga_ls8c_ard_3-2-1_108075_2023-08-19_final
2023-09-07 09:58:20	ga_ls8c_ard_3-2-1_097071_2023-09-07_final
2023-09-20 11:11:12	ga_ls8c_ard_3-2-1_108083_2023-09-20_final
2023-09-27 09:34:33	ga_ls8c_ard_3-2-1_093073_2023-09-27_final
2023-09-29 09:21:48	ga_ls8c_ard_3-2-1_091072_2023-09-28_final
2023-10-01 10:49:08	ga_ls8c_ard_3-2-1_105074_2023-10-01_final
2023-10-15 09:28:14	ga_ls8c_ard_3-2-1_091088_2023-10-14_final
2023-10-15 11:01:56	ga_ls8c_ard_3-2-1_107075_2023-10-15_final
2023-10-24 10:52:35	ga_ls8c_ard_3-2-1_106067_2023-10-24_final
2023-11-05 11:18:30	ga_ls8c_ard_3-2-1_110070_2023-11-05_final
2023-11-09 09:22:49	ga_ls8c_ard_3-2-1_090090_2023-11-08_final
2023-11-14 11:13:54	ga_ls8c_ard_3-2-1_109074_2023-11-14_final
2023-11-17 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-11-17_final
2023-11-25 09:16:57	ga_ls8c_ard_3-2-1_090075_2023-11-24_final
2023-12-03 10:04:43	ga_ls8c_ard_3-2-1_098071_2023-12-03_final
2023-12-18 11:01:58	ga_ls8c_ard_3-2-1_107075_2023-12-18_final
2024-01-10 09:28:46	ga_ls8c_ard_3-2-1_092074_2024-01-09_final
2024-01-20 10:03:51	ga_ls8c_ard_3-2-1_098069_2024-01-20_final
2024-01-21 10:47:06	ga_ls8c_ard_3-2-1_105069_2024-01-21_final
2024-01-24 11:20:45	ga_ls8c_ard_3-2-1_110076_2024-01-24_final
2024-01-27 11:50:48	ga_ls8c_ard_3-2-1_115074_2024-01-27_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