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
2017-07-26 09:27:35	ga_ls8c_ard_3-1-0_091087_2017-07-25_final
2019-03-10 09:22:06	ga_ls8c_ard_3-1-0_091074_2019-03-09_final
2019-03-10 09:23:18	ga_ls8c_ard_3-1-0_091077_2019-03-09_final
2019-03-10 09:27:18	ga_ls8c_ard_3-1-0_091087_2019-03-09_final
2019-03-13 09:57:23	ga_ls8c_ard_3-1-0_096085_2019-03-13_final
2019-03-17 11:09:56	ga_ls8c_ard_3-1-0_108081_2019-03-17_final
2019-03-26 09:26:50	ga_ls8c_ard_3-1-0_091086_2019-03-25_final
2019-03-29 09:52:08	ga_ls8c_ard_3-1-0_096072_2019-03-29_final
2019-04-02 11:05:05	ga_ls8c_ard_3-1-0_108069_2019-04-02_final
2019-04-13 10:50:05	ga_ls8c_ard_3-1-0_105078_2019-04-13_final
2019-04-18 11:09:47	ga_ls8c_ard_3-1-0_108081_2019-04-18_final
2019-06-21 11:06:36	ga_ls8c_ard_3-1-0_108072_2019-06-21_final
2019-07-02 10:50:30	ga_ls8c_ard_3-1-0_105078_2019-07-02_final
2019-07-03 09:51:42	ga_ls8c_ard_3-1-0_096070_2019-07-03_final
2019-07-16 09:21:38	ga_ls8c_ard_3-1-0_091072_2019-07-15_final
2019-07-16 09:26:25	ga_ls8c_ard_3-1-0_091084_2019-07-15_final
2019-07-18 10:49:21	ga_ls8c_ard_3-1-0_105075_2019-07-18_final
2019-07-19 09:54:56	ga_ls8c_ard_3-1-0_096078_2019-07-19_final
2019-07-23 11:05:32	ga_ls8c_ard_3-1-0_108069_2019-07-23_final
2019-07-23 11:09:55	ga_ls8c_ard_3-1-0_108080_2019-07-23_final
2019-08-13 09:48:55	ga_ls8c_ard_3-1-0_095078_2019-08-13_final
2019-08-13 09:49:43	ga_ls8c_ard_3-1-0_095080_2019-08-13_final
2019-08-24 11:05:43	ga_ls8c_ard_3-1-0_108069_2019-08-24_final
2019-09-02 09:27:04	ga_ls8c_ard_3-1-0_091085_2019-09-01_final
2019-09-05 09:55:11	ga_ls8c_ard_3-1-0_096078_2019-09-05_final
2019-09-05 09:56:23	ga_ls8c_ard_3-1-0_096081_2019-09-05_final
2019-09-05 09:56:47	ga_ls8c_ard_3-1-0_096082_2019-09-05_final
2019-09-05 09:57:59	ga_ls8c_ard_3-1-0_096085_2019-09-05_final
2019-09-14 09:47:52	ga_ls8c_ard_3-1-0_095075_2019-09-14_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-21 09:55:17	ga_ls8c_ard_3-1-0_096078_2019-09-21_final
2019-10-07 09:55:21	ga_ls8c_ard_3-1-0_096078_2019-10-07_final
2019-10-20 09:24:28	ga_ls8c_ard_3-1-0_091078_2019-10-19_final
2019-10-22 10:47:24	ga_ls8c_ard_3-1-0_105069_2019-10-22_final
2019-10-23 09:56:10	ga_ls8c_ard_3-1-0_096080_2019-10-23_final
2019-11-01 09:52:23	ga_ls8c_ard_3-1-0_095086_2019-11-01_final
2019-11-08 09:55:21	ga_ls8c_ard_3-1-0_096078_2019-11-08_final
2019-11-08 09:56:33	ga_ls8c_ard_3-1-0_096081_2019-11-08_final
2019-11-21 09:25:59	ga_ls8c_ard_3-1-0_091082_2019-11-20_final
2019-11-23 10:47:20	ga_ls8c_ard_3-1-0_105069_2019-11-23_final
2019-11-23 10:48:07	ga_ls8c_ard_3-1-0_105071_2019-11-23_final
2019-11-28 11:05:52	ga_ls8c_ard_3-1-0_108069_2019-11-28_final
2019-12-03 09:47:55	ga_ls8c_ard_3-1-0_095075_2019-12-03_final
2019-12-09 10:48:55	ga_ls8c_ard_3-1-0_105073_2019-12-09_final
2019-12-10 09:55:41	ga_ls8c_ard_3-1-0_096079_2019-12-10_final
2019-12-23 09:24:21	ga_ls8c_ard_3-1-0_091078_2019-12-22_final
2019-12-23 09:26:44	ga_ls8c_ard_3-1-0_091084_2019-12-22_final
2020-01-08 09:25:52	ga_ls8c_ard_3-1-0_091082_2020-01-07_final
2020-01-08 09:26:40	ga_ls8c_ard_3-1-0_091084_2020-01-07_final
2020-01-27 09:55:54	ga_ls8c_ard_3-1-0_096080_2020-01-27_final
2020-02-16 11:05:59	ga_ls8c_ard_3-1-0_108070_2020-02-16_final
2020-02-25 09:25:40	ga_ls8c_ard_3-1-0_091082_2020-02-24_final
2020-03-08 09:51:30	ga_ls8c_ard_3-1-0_095085_2020-03-08_final
2020-03-31 09:51:53	ga_ls8c_ard_3-1-0_096071_2020-03-31_final
2020-03-31 09:54:41	ga_ls8c_ard_3-1-0_096078_2020-03-31_final
2020-03-31 09:57:29	ga_ls8c_ard_3-1-0_096085_2020-03-31_final
2020-04-09 09:49:38	ga_ls8c_ard_3-1-0_095081_2020-04-09_final
2020-04-16 09:56:10	ga_ls8c_ard_3-1-0_096082_2020-04-16_final
2020-04-20 11:08:18	ga_ls8c_ard_3-1-0_108077_2020-04-20_final
2020-04-25 09:47:07	ga_ls8c_ard_3-1-0_095075_2020-04-25_final
2020-05-01 10:46:28	ga_ls8c_ard_3-1-0_105069_2020-05-01_final
2020-05-01 10:50:04	ga_ls8c_ard_3-1-0_105078_2020-05-01_final
2020-05-01 10:50:28	ga_ls8c_ard_3-1-0_105079_2020-05-01_final
2022-03-29 10:40:58	ga_ls8c_ard_3-2-1_104070_2022-03-29_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-04-01 09:37:46	ga_ls8c_ard_3-2-1_093082_2022-04-01_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-05 10:48:46	ga_ls8c_ard_3-2-1_105074_2022-04-05_final
2022-04-08 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-08_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-14 10:44:39	ga_ls8c_ard_3-2-1_104079_2022-04-14_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-17 09:38:40	ga_ls8c_ard_3-2-1_093084_2022-04-17_final
2022-04-19 09:25:54	ga_ls8c_ard_3-2-1_091083_2022-04-18_final
2022-04-22 09:56:23	ga_ls8c_ard_3-2-1_096082_2022-04-22_final
2022-04-23 10:36:27	ga_ls8c_ard_3-2-1_103074_2022-04-23_final
2022-04-24 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-24_final
2022-04-24 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-24_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-24 11:23:42	ga_ls8c_ard_3-2-1_110084_2022-04-24_final
2022-04-26 11:10:07	ga_ls8c_ard_3-2-1_108081_2022-04-26_final
2022-04-28 10:56:56	ga_ls8c_ard_3-2-1_106079_2022-04-28_final
2022-04-28 10:57:44	ga_ls8c_ard_3-2-1_106081_2022-04-28_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-07 10:51:39	ga_ls8c_ard_3-2-1_105081_2022-05-07_final
2022-05-10 11:21:00	ga_ls8c_ard_3-2-1_110077_2022-05-10_final
2022-05-14 10:55:30	ga_ls8c_ard_3-2-1_106075_2022-05-14_final
2022-05-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2022-05-17_final
2022-05-26 09:42:57	ga_ls8c_ard_3-2-1_094079_2022-05-26_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-06-02 09:48:24	ga_ls8c_ard_3-2-1_095077_2022-06-02_final
2022-06-13 11:10:05	ga_ls8c_ard_3-2-1_108080_2022-06-13_final
2022-06-15 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-06-15_final
2022-06-16 09:58:33	ga_ls8c_ard_3-2-1_097071_2022-06-16_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 09:49:00	ga_ls8c_ard_3-2-1_095078_2022-06-18_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_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