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
2022-01-14 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-01-14_final
2022-07-15 11:07:46	ga_ls8c_ard_3-2-1_108074_2022-07-15_final
2022-07-16 11:52:13	ga_ls8c_ard_3-2-1_115077_2022-07-16_final
2022-07-17 09:20:32	ga_ls8c_ard_3-2-1_090084_2022-07-16_final
2022-07-24 11:00:06	ga_ls8c_ard_3-2-1_107070_2022-07-24_final
2022-07-25 10:04:54	ga_ls8c_ard_3-2-1_098071_2022-07-25_final
2022-08-03 09:58:24	ga_ls8c_ard_3-2-1_097070_2022-08-03_final
2022-08-09 11:05:27	ga_ls8c_ard_3-2-1_107083_2022-08-09_final
2022-08-21 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-08-21_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-04 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-09-04_final
2022-09-12 10:47:13	ga_ls8c_ard_3-2-1_105068_2022-09-12_final
2022-09-13 11:32:53	ga_ls8c_ard_3-2-1_112074_2022-09-13_final
2022-09-18 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-09-18_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-24 09:34:18	ga_ls8c_ard_3-2-1_093071_2022-09-24_final
2022-09-28 09:13:58	ga_ls8c_ard_3-2-1_089082_2022-09-27_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-21 10:54:10	ga_ls8c_ard_3-2-1_106070_2022-10-21_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-10-28 11:00:48	ga_ls8c_ard_3-2-1_107071_2022-10-28_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-10-31 09:57:13	ga_ls8c_ard_3-2-1_096082_2022-10-31_final
2022-11-03 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-11-03_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-07 09:58:36	ga_ls8c_ard_3-2-1_097070_2022-11-07_final
2022-11-07 09:59:00	ga_ls8c_ard_3-2-1_097071_2022-11-07_final
2022-11-09 09:47:49	ga_ls8c_ard_3-2-1_095074_2022-11-09_final
2022-11-13 09:24:15	ga_ls8c_ard_3-2-1_091077_2022-11-12_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-18 09:44:43	ga_ls8c_ard_3-2-1_094082_2022-11-18_final
2022-11-20 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-11-20_final
2022-11-23 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-11-23_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-06 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-12-06_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-17 10:50:40	ga_ls8c_ard_3-2-1_105077_2022-12-17_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-23 10:14:41	ga_ls8c_ard_3-2-1_099080_2022-12-23_final
2022-12-26 10:44:25	ga_ls8c_ard_3-2-1_104077_2022-12-26_final
2022-12-28 10:28:53	ga_ls8c_ard_3-2-1_102069_2022-12-28_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2023-01-07 09:34:15	ga_ls8c_ard_3-2-1_092087_2023-01-07_final
2023-01-07 11:06:45	ga_ls8c_ard_3-2-1_108071_2023-01-07_final
2023-01-10 10:04:20	ga_ls8c_ard_3-2-1_097085_2023-01-10_final
2023-01-16 11:00:52	ga_ls8c_ard_3-2-1_107072_2023-01-16_final
2023-01-17 10:06:49	ga_ls8c_ard_3-2-1_098076_2023-01-17_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-01-21 11:19:26	ga_ls8c_ard_3-2-1_110072_2023-01-21_final
2023-01-22 10:28:13	ga_ls8c_ard_3-2-1_101083_2023-01-22_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-01-25 10:55:33	ga_ls8c_ard_3-2-1_106074_2023-01-25_final
2023-01-30 09:40:49	ga_ls8c_ard_3-2-1_093088_2023-01-30_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-23 10:23:35	ga_ls8c_ard_3-2-1_101072_2023-02-23_final
2023-02-24 11:07:13	ga_ls8c_ard_3-2-1_108073_2023-02-24_final
2023-02-25 10:14:22	ga_ls8c_ard_3-2-1_099080_2023-02-25_final
2023-03-01 11:26:08	ga_ls8c_ard_3-2-1_111074_2023-03-01_final
2023-03-07 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-03-07_final
2023-03-12 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-03-12_final
2023-03-14 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-03-13_final
2023-03-15 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-03-15_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-16 09:07:29	ga_ls8c_ard_3-2-1_088083_2023-03-15_final
2023-03-23 09:12:45	ga_ls8c_ard_3-2-1_089081_2023-03-22_final
2023-03-25 10:34:29	ga_ls8c_ard_3-2-1_103069_2023-03-25_final
2023-03-28 09:32:28	ga_ls8c_ard_3-2-1_092084_2023-03-28_final
2023-03-28 09:32:52	ga_ls8c_ard_3-2-1_092085_2023-03-28_final
2023-03-30 10:58:11	ga_ls8c_ard_3-2-1_106082_2023-03-30_final
2023-04-06 09:25:45	ga_ls8c_ard_3-2-1_091083_2023-04-05_final
2023-04-06 10:59:27	ga_ls8c_ard_3-2-1_107070_2023-04-06_final
2023-04-08 10:49:02	ga_ls8c_ard_3-2-1_105075_2023-04-08_final
2023-04-14 10:10:41	ga_ls8c_ard_3-2-1_099072_2023-04-14_final
2023-04-14 10:15:52	ga_ls8c_ard_3-2-1_099085_2023-04-14_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-04-24 10:51:19	ga_ls8c_ard_3-2-1_105081_2023-04-24_final
2023-04-26 10:35:21	ga_ls8c_ard_3-2-1_103072_2023-04-26_final
2023-05-04 11:24:20	ga_ls8c_ard_3-2-1_111071_2023-05-04_final
2023-05-11 09:57:29	ga_ls8c_ard_3-2-1_096086_2023-05-11_final
2023-05-13 09:45:30	ga_ls8c_ard_3-2-1_094087_2023-05-13_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-15 11:06:49	ga_ls8c_ard_3-2-1_108074_2023-05-15_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years