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
2021-05-02 12:36:59	ga_ls8c_ard_3-2-1_123067_2021-05-02_final
2022-05-01 09:50:11	ga_ls8c_ard_3-2-1_095082_2022-05-01_final
2022-05-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-05-17_final
2022-05-19 09:33:59	ga_ls8c_ard_3-2-1_093072_2022-05-19_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-23 10:46:33	ga_ls8c_ard_3-2-1_105068_2022-05-23_final
2022-06-01 09:06:20	ga_ls8c_ard_3-2-1_088080_2022-05-31_final
2022-06-11 11:19:38	ga_ls8c_ard_3-2-1_110073_2022-06-11_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-27 09:40:52	ga_ls8c_ard_3-2-1_094073_2022-06-27_final
2022-06-29 09:32:54	ga_ls8c_ard_3-2-1_092084_2022-06-29_final
2022-07-02 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-02_final
2022-07-03 09:06:35	ga_ls8c_ard_3-2-1_088080_2022-07-02_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-07-13 09:44:02	ga_ls8c_ard_3-2-1_094081_2022-07-13_final
2022-07-21 10:28:46	ga_ls8c_ard_3-2-1_102069_2022-07-21_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-29 09:41:25	ga_ls8c_ard_3-2-1_094074_2022-07-29_final
2022-08-19 11:41:46	ga_ls8c_ard_3-2-1_113081_2022-08-19_final
2022-08-30 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-30_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-11 11:47:14	ga_ls8c_ard_3-2-1_114079_2022-09-11_final
2022-09-13 09:52:48	ga_ls8c_ard_3-2-1_096071_2022-09-13_final
2022-09-27 10:03:12	ga_ls8c_ard_3-2-1_098066_2022-09-27_final
2022-10-06 10:00:10	ga_ls8c_ard_3-2-1_097074_2022-10-06_final
2022-10-12 09:24:12	ga_ls8c_ard_3-2-1_091077_2022-10-11_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-16 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-10-16_final
2022-10-16 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-10-16_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-23 10:46:37	ga_ls8c_ard_3-2-1_104082_2022-10-23_final
2022-10-26 11:13:57	ga_ls8c_ard_3-2-1_109073_2022-10-26_final
2022-10-27 10:21:31	ga_ls8c_ard_3-2-1_100081_2022-10-27_final
2022-10-29 10:04:23	ga_ls8c_ard_3-2-1_098069_2022-10-29_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-23 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-11-23_final
2022-11-29 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-28_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2023-01-02 09:10:32	ga_ls8c_ard_3-2-1_089074_2023-01-01_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-02-02 10:03:44	ga_ls8c_ard_3-2-1_098068_2023-02-02_final
2023-02-10 10:55:07	ga_ls8c_ard_3-2-1_106073_2023-02-10_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-03-15 10:01:31	ga_ls8c_ard_3-2-1_097079_2023-03-15_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-04-04 09:39:45	ga_ls8c_ard_3-2-1_093087_2023-04-04_final
2023-05-01 10:53:04	ga_ls8c_ard_3-2-1_106070_2023-05-01_final
2023-05-01 10:54:16	ga_ls8c_ard_3-2-1_106073_2023-05-01_final
2023-05-07 10:21:29	ga_ls8c_ard_3-2-1_100084_2023-05-07_final
2023-05-08 09:24:39	ga_ls8c_ard_3-2-1_091081_2023-05-07_final
2023-05-08 10:59:33	ga_ls8c_ard_3-2-1_107071_2023-05-08_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-16 10:11:59	ga_ls8c_ard_3-2-1_099076_2023-05-16_final
2023-05-23 10:19:24	ga_ls8c_ard_3-2-1_100079_2023-05-23_final
2023-05-26 10:45:31	ga_ls8c_ard_3-2-1_105067_2023-05-26_final
2023-05-31 11:06:27	ga_ls8c_ard_3-2-1_108073_2023-05-31_final
2023-06-03 10:01:17	ga_ls8c_ard_3-2-1_097080_2023-06-03_final
2023-06-14 09:43:40	ga_ls8c_ard_3-2-1_094082_2023-06-14_final
2023-07-05 09:58:25	ga_ls8c_ard_3-2-1_097072_2023-07-05_final
2023-07-05 10:00:25	ga_ls8c_ard_3-2-1_097077_2023-07-05_final
2023-07-11 09:24:58	ga_ls8c_ard_3-2-1_091081_2023-07-10_final
2023-07-21 10:03:39	ga_ls8c_ard_3-2-1_097085_2023-07-21_final
2023-07-27 09:21:28	ga_ls8c_ard_3-2-1_091072_2023-07-26_final
2023-08-10 09:38:41	ga_ls8c_ard_3-2-1_093084_2023-08-10_final
2023-08-15 09:51:42	ga_ls8c_ard_3-2-1_096070_2023-08-15_final
2023-08-20 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-08-20_final
2023-08-21 10:55:34	ga_ls8c_ard_3-2-1_106075_2023-08-21_final
2023-08-28 09:24:53	ga_ls8c_ard_3-2-1_091080_2023-08-27_final
2023-08-30 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-08-29_final
2023-09-17 10:37:54	ga_ls8c_ard_3-2-1_103077_2023-09-17_final
2023-09-22 10:54:51	ga_ls8c_ard_3-2-1_106073_2023-09-22_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-01 10:48:44	ga_ls8c_ard_3-2-1_105073_2023-10-01_final
2023-10-24 09:21:40	ga_ls8c_ard_3-2-1_090087_2023-10-23_final
2023-10-25 11:37:50	ga_ls8c_ard_3-2-1_113072_2023-10-25_final
2023-10-26 10:41:26	ga_ls8c_ard_3-2-1_104070_2023-10-26_final
2023-11-06 10:23:40	ga_ls8c_ard_3-2-1_101072_2023-11-06_final
2023-11-06 10:24:52	ga_ls8c_ard_3-2-1_101075_2023-11-06_final
2023-11-15 10:18:18	ga_ls8c_ard_3-2-1_100074_2023-11-15_final
2023-11-26 11:41:29	ga_ls8c_ard_3-2-1_113081_2023-11-26_final
2023-12-11 09:20:26	ga_ls8c_ard_3-2-1_090084_2023-12-10_final
2023-12-14 11:23:52	ga_ls8c_ard_3-2-1_111068_2023-12-14_final
2023-12-19 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-12-19_final
2023-12-27 09:17:41	ga_ls8c_ard_3-2-1_090077_2023-12-26_final
2023-12-28 10:00:56	ga_ls8c_ard_3-2-1_097077_2023-12-28_final
2024-01-08 09:43:55	ga_ls8c_ard_3-2-1_094081_2024-01-08_final
2024-01-10 11:07:39	ga_ls8c_ard_3-2-1_108074_2024-01-10_final
2024-01-15 11:25:01	ga_ls8c_ard_3-2-1_111071_2024-01-15_final
2024-01-18 10:22:12	ga_ls8c_ard_3-2-1_100084_2024-01-18_final
2024-01-22 09:57:51	ga_ls8c_ard_3-2-1_096085_2024-01-22_final
2024-01-22 11:32:44	ga_ls8c_ard_3-2-1_112075_2024-01-22_final
2024-01-23 10:36:18	ga_ls8c_ard_3-2-1_103073_2024-01-23_final
2024-02-11 09:30:21	ga_ls8c_ard_3-2-1_092078_2024-02-11_final
2024-02-15 10:43:17	ga_ls8c_ard_3-2-1_104075_2024-02-15_final
2024-02-20 11:02:14	ga_ls8c_ard_3-2-1_107076_2024-02-20_final
2024-03-16 09:22:06	ga_ls8c_ard_3-2-1_090089_2024-03-15_final
2024-03-17 10:00:58	ga_ls8c_ard_3-2-1_097078_2024-03-17_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