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 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-01-14_final
2022-05-17 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-05-17_final
2022-05-19 11:14:04	ga_ls8c_ard_3-2-1_109075_2022-05-19_final
2022-05-20 10:22:02	ga_ls8c_ard_3-2-1_100084_2022-05-20_final
2022-05-21 11:01:42	ga_ls8c_ard_3-2-1_107075_2022-05-21_final
2022-05-30 10:53:33	ga_ls8c_ard_3-2-1_106070_2022-05-30_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-04 09:34:29	ga_ls8c_ard_3-2-1_093073_2022-06-04_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-05 10:17:21	ga_ls8c_ard_3-2-1_100072_2022-06-05_final
2022-06-18 11:25:53	ga_ls8c_ard_3-2-1_111073_2022-06-18_final
2022-06-18 11:26:17	ga_ls8c_ard_3-2-1_111074_2022-06-18_final
2022-06-24 09:13:32	ga_ls8c_ard_3-2-1_089082_2022-06-23_final
2022-06-24 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-06-24_final
2022-06-27 11:18:57	ga_ls8c_ard_3-2-1_110071_2022-06-27_final
2022-06-30 11:52:15	ga_ls8c_ard_3-2-1_115077_2022-06-30_final
2022-07-11 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-07-11_final
2022-07-15 11:06:10	ga_ls8c_ard_3-2-1_108070_2022-07-15_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-07-16 11:53:01	ga_ls8c_ard_3-2-1_115079_2022-07-16_final
2022-07-19 10:42:42	ga_ls8c_ard_3-2-1_104073_2022-07-19_final
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-02 10:54:01	ga_ls8c_ard_3-2-1_106070_2022-08-02_final
2022-08-03 11:42:05	ga_ls8c_ard_3-2-1_113082_2022-08-03_final
2022-08-17 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-08-17_final
2022-09-01 11:06:29	ga_ls8c_ard_3-2-1_108070_2022-09-01_final
2022-09-03 09:21:13	ga_ls8c_ard_3-2-1_090085_2022-09-02_final
2022-09-04 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-09-04_final
2022-09-09 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-09-09_final
2022-09-12 10:47:37	ga_ls8c_ard_3-2-1_105069_2022-09-12_final
2022-09-16 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-09-16_final
2022-09-18 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-09-18_final
2022-09-24 09:37:29	ga_ls8c_ard_3-2-1_093079_2022-09-24_final
2022-09-25 10:19:33	ga_ls8c_ard_3-2-1_100076_2022-09-25_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-24 09:47:48	ga_ls8c_ard_3-2-1_095074_2022-10-24_final
2022-10-24 11:29:53	ga_ls8c_ard_3-2-1_111082_2022-10-24_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-02 09:42:52	ga_ls8c_ard_3-2-1_094077_2022-11-02_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-06 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-11-05_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-08 10:41:03	ga_ls8c_ard_3-2-1_104068_2022-11-08_final
2022-11-09 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-11-09_final
2022-11-13 09:27:03	ga_ls8c_ard_3-2-1_091084_2022-11-12_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-13 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-13_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_final
2022-11-20 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-11-20_final
2022-11-20 09:33:58	ga_ls8c_ard_3-2-1_092086_2022-11-20_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-11-27 11:14:17	ga_ls8c_ard_3-2-1_109074_2022-11-27_final
2022-12-08 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-12-07_final
2022-12-09 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-12-09_final
2022-12-10 10:40:58	ga_ls8c_ard_3-2-1_104068_2022-12-10_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-16 11:45:54	ga_ls8c_ard_3-2-1_114076_2022-12-16_final
2022-12-17 10:53:03	ga_ls8c_ard_3-2-1_105083_2022-12-17_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-25 09:59:33	ga_ls8c_ard_3-2-1_097073_2022-12-25_final
2022-12-25 11:39:14	ga_ls8c_ard_3-2-1_113075_2022-12-25_final
2022-12-31 09:24:06	ga_ls8c_ard_3-2-1_091077_2022-12-30_final
2023-01-08 11:52:00	ga_ls8c_ard_3-2-1_115076_2023-01-08_final
2023-01-17 10:07:13	ga_ls8c_ard_3-2-1_098077_2023-01-17_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-02-10 09:19:26	ga_ls8c_ard_3-2-1_090081_2023-02-09_final
2023-02-10 10:55:07	ga_ls8c_ard_3-2-1_106073_2023-02-10_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-24 09:33:08	ga_ls8c_ard_3-2-1_092085_2023-02-24_final
2023-02-24 11:11:36	ga_ls8c_ard_3-2-1_108084_2023-02-24_final
2023-02-25 11:53:15	ga_ls8c_ard_3-2-1_115080_2023-02-25_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-05 11:05:23	ga_ls8c_ard_3-2-1_107084_2023-03-05_final
2023-03-07 10:49:48	ga_ls8c_ard_3-2-1_105076_2023-03-07_final
2023-03-14 10:55:57	ga_ls8c_ard_3-2-1_106076_2023-03-14_final
2023-03-17 11:25:14	ga_ls8c_ard_3-2-1_111072_2023-03-17_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-03-29 10:15:19	ga_ls8c_ard_3-2-1_099083_2023-03-29_final
2023-04-13 09:34:12	ga_ls8c_ard_3-2-1_092089_2023-04-13_final
2023-04-16 10:01:06	ga_ls8c_ard_3-2-1_097079_2023-04-16_final
2023-04-21 10:16:49	ga_ls8c_ard_3-2-1_100072_2023-04-21_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-04-29 11:05:03	ga_ls8c_ard_3-2-1_108069_2023-04-29_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-10 10:47:56	ga_ls8c_ard_3-2-1_105073_2023-05-10_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-05-16 10:13:35	ga_ls8c_ard_3-2-1_099080_2023-05-16_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