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
2021-11-22 09:51:56	ga_ls8c_ard_3-2-0_095085_2021-11-22_final
2021-11-27 10:06:06	ga_ls8c_ard_3-2-0_098074_2021-11-27_final
2021-12-07 10:45:35	ga_ls8c_ard_3-2-1_104080_2021-12-07_final
2021-12-15 09:52:56	ga_ls8c_ard_3-2-1_096072_2021-12-15_final
2021-12-16 10:35:47	ga_ls8c_ard_3-2-1_103071_2021-12-16_final
2021-12-21 09:20:37	ga_ls8c_ard_3-2-1_090084_2021-12-20_final
2021-12-30 10:52:03	ga_ls8c_ard_3-2-1_105081_2021-12-30_final
2022-01-09 09:51:26	ga_ls8c_ard_3-2-1_095084_2022-01-09_final
2022-01-11 09:35:52	ga_ls8c_ard_3-2-1_093076_2022-01-11_final
2022-01-13 11:03:35	ga_ls8c_ard_3-2-1_107079_2022-01-13_final
2022-01-18 09:45:13	ga_ls8c_ard_3-2-1_094084_2022-01-18_final
2022-01-19 10:27:17	ga_ls8c_ard_3-2-1_101081_2022-01-19_final
2022-02-03 09:43:33	ga_ls8c_ard_3-2-1_094080_2022-02-03_final
2022-02-04 10:24:49	ga_ls8c_ard_3-2-1_101075_2022-02-04_final
2022-02-06 10:11:39	ga_ls8c_ard_3-2-1_099073_2022-02-06_final
2022-02-08 10:03:16	ga_ls8c_ard_3-2-1_097083_2022-02-08_final
2022-02-16 09:12:35	ga_ls8c_ard_3-2-1_089080_2022-02-15_final
2022-02-26 11:26:31	ga_ls8c_ard_3-2-1_111075_2022-02-26_final
2022-02-26 11:29:18	ga_ls8c_ard_3-2-1_111082_2022-02-26_final
2022-03-10 10:15:29	ga_ls8c_ard_3-2-1_099083_2022-03-10_final
2022-03-14 09:47:57	ga_ls8c_ard_3-2-1_095076_2022-03-14_final
2022-03-15 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-03-15_final
2022-03-17 10:20:25	ga_ls8c_ard_3-2-1_100080_2022-03-17_final
2022-03-19 11:46:31	ga_ls8c_ard_3-2-1_114079_2022-03-19_final
2022-03-20 10:51:40	ga_ls8c_ard_3-2-1_105081_2022-03-20_final
2022-03-21 11:32:32	ga_ls8c_ard_3-2-1_112075_2022-03-21_final
2022-03-24 10:26:30	ga_ls8c_ard_3-2-1_101080_2022-03-24_final
2022-04-04 10:07:53	ga_ls8c_ard_3-2-1_098080_2022-04-04_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-05-11 10:24:11	ga_ls8c_ard_3-2-1_101074_2022-05-11_final
2022-05-22 10:07:41	ga_ls8c_ard_3-2-1_098079_2022-05-22_final
2022-06-01 10:41:13	ga_ls8c_ard_3-2-1_104070_2022-06-01_final
2022-07-04 11:29:31	ga_ls8c_ard_3-2-1_111082_2022-07-04_final
2022-07-06 11:15:10	ga_ls8c_ard_3-2-1_109077_2022-07-06_final
2022-07-14 10:24:06	ga_ls8c_ard_3-2-1_101073_2022-07-14_final
2022-07-19 10:44:41	ga_ls8c_ard_3-2-1_104078_2022-07-19_final
2022-07-20 09:50:17	ga_ls8c_ard_3-2-1_095081_2022-07-20_final
2022-07-29 09:44:36	ga_ls8c_ard_3-2-1_094082_2022-07-29_final
2022-08-03 09:59:36	ga_ls8c_ard_3-2-1_097073_2022-08-03_final
2022-08-03 10:01:12	ga_ls8c_ard_3-2-1_097077_2022-08-03_final
2022-08-14 09:45:32	ga_ls8c_ard_3-2-1_094084_2022-08-14_final
2022-08-18 09:19:37	ga_ls8c_ard_3-2-1_090081_2022-08-17_final
2022-09-26 11:01:13	ga_ls8c_ard_3-2-1_107072_2022-09-26_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-30 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-30_final
2022-12-05 10:27:38	ga_ls8c_ard_3-2-1_101081_2022-12-05_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-13 09:37:45	ga_ls8c_ard_3-2-1_093080_2022-12-13_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-10 11:39:14	ga_ls8c_ard_3-2-1_113075_2023-01-10_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-25 10:57:56	ga_ls8c_ard_3-2-1_106080_2023-01-25_final
2023-02-02 10:09:19	ga_ls8c_ard_3-2-1_098082_2023-02-02_final
2023-02-12 10:43:31	ga_ls8c_ard_3-2-1_104075_2023-02-12_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-22 11:23:37	ga_ls8c_ard_3-2-1_110083_2023-02-22_final
2023-03-12 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-03-12_final
2023-03-19 11:14:50	ga_ls8c_ard_3-2-1_109077_2023-03-19_final
2023-03-19 11:15:38	ga_ls8c_ard_3-2-1_109079_2023-03-19_final
2023-03-23 10:48:03	ga_ls8c_ard_3-2-1_105072_2023-03-23_final
2023-04-04 11:15:50	ga_ls8c_ard_3-2-1_109080_2023-04-04_final
2023-04-05 10:18:12	ga_ls8c_ard_3-2-1_100075_2023-04-05_final
2023-04-20 11:14:50	ga_ls8c_ard_3-2-1_109078_2023-04-20_final
2023-04-30 10:12:12	ga_ls8c_ard_3-2-1_099076_2023-04-30_final
2023-05-04 11:27:07	ga_ls8c_ard_3-2-1_111078_2023-05-04_final
2023-05-25 11:45:56	ga_ls8c_ard_3-2-1_114079_2023-05-25_final
2023-06-03 10:00:05	ga_ls8c_ard_3-2-1_097077_2023-06-03_final
2023-06-07 11:11:07	ga_ls8c_ard_3-2-1_109069_2023-06-07_final
2023-06-10 11:46:03	ga_ls8c_ard_3-2-1_114079_2023-06-10_final
2023-06-17 10:14:35	ga_ls8c_ard_3-2-1_099082_2023-06-17_final
2023-06-21 09:45:28	ga_ls8c_ard_3-2-1_095071_2023-06-21_final
2023-06-26 11:45:21	ga_ls8c_ard_3-2-1_114077_2023-06-26_final
2023-07-12 10:08:14	ga_ls8c_ard_3-2-1_098081_2023-07-12_final
2023-07-25 11:15:53	ga_ls8c_ard_3-2-1_109080_2023-07-25_final
2023-08-06 11:41:06	ga_ls8c_ard_3-2-1_113081_2023-08-06_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-24 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-08-24_final
2023-08-31 11:31:52	ga_ls8c_ard_3-2-1_112073_2023-08-31_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_final
2023-09-07 10:00:43	ga_ls8c_ard_3-2-1_097077_2023-09-07_final
2023-09-09 09:49:59	ga_ls8c_ard_3-2-1_095081_2023-09-09_final
2023-09-15 10:46:16	ga_ls8c_ard_3-2-1_105067_2023-09-15_final
2023-09-17 10:36:43	ga_ls8c_ard_3-2-1_103074_2023-09-17_final
2023-09-17 10:37:30	ga_ls8c_ard_3-2-1_103076_2023-09-17_final
2023-09-18 09:43:53	ga_ls8c_ard_3-2-1_094081_2023-09-18_final
2023-09-25 11:29:46	ga_ls8c_ard_3-2-1_111083_2023-09-25_final
2023-09-26 10:32:10	ga_ls8c_ard_3-2-1_102078_2023-09-26_final
2023-10-09 09:59:19	ga_ls8c_ard_3-2-1_097073_2023-10-09_final
2023-10-11 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-10-11_final
2023-10-22 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-10-22_final
2023-10-24 09:18:29	ga_ls8c_ard_3-2-1_090079_2023-10-23_final
2023-10-29 11:15:08	ga_ls8c_ard_3-2-1_109077_2023-10-29_final
2023-11-01 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-01_final
2023-11-05 11:24:29	ga_ls8c_ard_3-2-1_110085_2023-11-05_final
2023-11-11 10:41:22	ga_ls8c_ard_3-2-1_104070_2023-11-11_final
2023-11-13 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-11-13_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years