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
2015-10-20 09:06:47	ga_ls8c_ard_3-1-0_088081_2015-10-19_final
2016-11-29 10:04:53	ga_ls8c_ard_3-1-0_098071_2016-11-29_final
2017-12-23 10:23:41	ga_ls8c_ard_3-1-0_101072_2017-12-23_final
2018-03-07 09:28:07	ga_ls8c_ard_3-1-0_091089_2018-03-06_final
2019-03-07 10:30:31	ga_ls8c_ard_3-1-0_102075_2019-03-07_final
2019-03-09 11:57:49	ga_ls8c_ard_3-1-0_116077_2019-03-09_final
2019-03-11 10:03:46	ga_ls8c_ard_3-1-0_098070_2019-03-11_final
2019-03-12 10:49:01	ga_ls8c_ard_3-1-0_105075_2019-03-12_final
2019-03-13 09:56:59	ga_ls8c_ard_3-1-0_096084_2019-03-13_final
2019-03-17 09:29:27	ga_ls8c_ard_3-1-0_092077_2019-03-16_final
2019-03-23 10:30:26	ga_ls8c_ard_3-1-0_102075_2019-03-23_final
2019-04-02 09:32:11	ga_ls8c_ard_3-1-0_092084_2019-04-02_final
2019-04-07 09:51:06	ga_ls8c_ard_3-1-0_095085_2019-04-07_final
2019-04-08 10:30:22	ga_ls8c_ard_3-1-0_102075_2019-04-08_final
2019-04-18 11:06:35	ga_ls8c_ard_3-1-0_108073_2019-04-18_final
2019-06-23 10:54:15	ga_ls8c_ard_3-1-0_106072_2019-06-23_final
2019-06-26 11:24:46	ga_ls8c_ard_3-1-0_111071_2019-06-26_final
2019-06-26 11:25:10	ga_ls8c_ard_3-1-0_111072_2019-06-26_final
2019-06-29 11:58:05	ga_ls8c_ard_3-1-0_116077_2019-06-29_final
2019-07-03 09:56:29	ga_ls8c_ard_3-1-0_096082_2019-07-03_final
2019-07-07 11:07:04	ga_ls8c_ard_3-1-0_108073_2019-07-07_final
2019-07-18 10:52:33	ga_ls8c_ard_3-1-0_105083_2019-07-18_final
2019-07-23 09:29:03	ga_ls8c_ard_3-1-0_092075_2019-07-22_final
2019-07-23 11:07:08	ga_ls8c_ard_3-1-0_108073_2019-07-23_final
2019-07-25 10:55:11	ga_ls8c_ard_3-1-0_106074_2019-07-25_final
2019-08-03 10:46:40	ga_ls8c_ard_3-1-0_105068_2019-08-03_final
2019-08-04 09:52:39	ga_ls8c_ard_3-1-0_096072_2019-08-04_final
2019-08-10 10:56:05	ga_ls8c_ard_3-1-0_106076_2019-08-10_final
2019-08-17 09:23:25	ga_ls8c_ard_3-1-0_091076_2019-08-16_final
2019-08-30 10:29:04	ga_ls8c_ard_3-1-0_102070_2019-08-30_final
2019-08-30 10:31:03	ga_ls8c_ard_3-1-0_102075_2019-08-30_final
2019-09-03 10:03:09	ga_ls8c_ard_3-1-0_098067_2019-09-03_final
2019-09-11 10:55:50	ga_ls8c_ard_3-1-0_106075_2019-09-11_final
2019-09-14 09:46:40	ga_ls8c_ard_3-1-0_095072_2019-09-14_final
2019-09-24 10:28:12	ga_ls8c_ard_3-1-0_101083_2019-09-24_final
2019-09-25 11:06:17	ga_ls8c_ard_3-1-0_108070_2019-09-25_final
2019-10-01 10:31:13	ga_ls8c_ard_3-1-0_102075_2019-10-01_final
2019-10-11 09:26:15	ga_ls8c_ard_3-1-0_092067_2019-10-10_final
2019-10-11 09:31:26	ga_ls8c_ard_3-1-0_092080_2019-10-11_final
2019-10-27 11:11:32	ga_ls8c_ard_3-1-0_108083_2019-10-27_final
2019-11-12 09:31:25	ga_ls8c_ard_3-1-0_092080_2019-11-12_final
2019-11-12 09:33:01	ga_ls8c_ard_3-1-0_092084_2019-11-12_final
2019-11-17 11:30:25	ga_ls8c_ard_3-1-0_111084_2019-11-17_final
2019-11-20 11:58:30	ga_ls8c_ard_3-1-0_116077_2019-11-20_final
2019-11-22 10:04:52	ga_ls8c_ard_3-1-0_098071_2019-11-22_final
2019-11-28 09:31:22	ga_ls8c_ard_3-1-0_092080_2019-11-28_final
2019-11-28 09:32:58	ga_ls8c_ard_3-1-0_092084_2019-11-28_final
2019-12-03 09:51:07	ga_ls8c_ard_3-1-0_095083_2019-12-03_final
2019-12-04 10:28:23	ga_ls8c_ard_3-1-0_102068_2019-12-04_final
2019-12-08 10:05:15	ga_ls8c_ard_3-1-0_098072_2019-12-08_final
2019-12-09 10:47:43	ga_ls8c_ard_3-1-0_105070_2019-12-09_final
2019-12-10 09:52:53	ga_ls8c_ard_3-1-0_096072_2019-12-10_final
2019-12-25 10:46:28	ga_ls8c_ard_3-1-0_105067_2019-12-25_final
2019-12-26 09:52:50	ga_ls8c_ard_3-1-0_096072_2019-12-26_final
2020-01-09 10:09:08	ga_ls8c_ard_3-1-0_098082_2020-01-09_final
2020-01-21 10:31:25	ga_ls8c_ard_3-1-0_102076_2020-01-21_final
2020-01-23 11:57:32	ga_ls8c_ard_3-1-0_116075_2020-01-23_final
2020-01-26 10:47:56	ga_ls8c_ard_3-1-0_105071_2020-01-26_final
2020-01-27 09:54:42	ga_ls8c_ard_3-1-0_096077_2020-01-27_final
2020-02-02 10:53:16	ga_ls8c_ard_3-1-0_106069_2020-02-02_final
2020-02-12 09:51:50	ga_ls8c_ard_3-1-0_096070_2020-02-12_final
2020-02-16 09:30:41	ga_ls8c_ard_3-1-0_092079_2020-02-16_final
2020-02-24 11:58:11	ga_ls8c_ard_3-1-0_116077_2020-02-24_final
2020-02-28 09:56:09	ga_ls8c_ard_3-1-0_096081_2020-02-28_final
2020-03-19 09:33:40	ga_ls8c_ard_3-1-0_092087_2020-03-19_final
2020-03-27 11:57:56	ga_ls8c_ard_3-1-0_116077_2020-03-27_final
2020-03-28 09:23:25	ga_ls8c_ard_3-1-0_091077_2020-03-27_final
2020-03-28 09:28:36	ga_ls8c_ard_3-1-0_091090_2020-03-27_final
2020-04-13 09:22:30	ga_ls8c_ard_3-1-0_091075_2020-04-12_final
2020-05-01 10:48:28	ga_ls8c_ard_3-1-0_105074_2020-05-01_final
2022-03-31 10:29:00	ga_ls8c_ard_3-2-1_102071_2022-03-31_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-06 09:56:45	ga_ls8c_ard_3-2-1_096083_2022-04-06_final
2022-04-07 10:39:37	ga_ls8c_ard_3-2-1_103082_2022-04-07_final
2022-04-08 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-08_final
2022-04-10 11:08:33	ga_ls8c_ard_3-2-1_108077_2022-04-10_final
2022-04-10 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-04-10_final
2022-04-17 11:15:09	ga_ls8c_ard_3-2-1_109078_2022-04-17_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-22 09:57:11	ga_ls8c_ard_3-2-1_096084_2022-04-22_final
2022-04-24 09:43:37	ga_ls8c_ard_3-2-1_094081_2022-04-24_final
2022-04-29 10:01:43	ga_ls8c_ard_3-2-1_097080_2022-04-29_final
2022-05-01 09:48:35	ga_ls8c_ard_3-2-1_095078_2022-05-01_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-03 11:14:44	ga_ls8c_ard_3-2-1_109077_2022-05-03_final
2022-05-04 10:20:19	ga_ls8c_ard_3-2-1_100080_2022-05-04_final
2022-05-07 10:50:28	ga_ls8c_ard_3-2-1_105078_2022-05-07_final
2022-05-10 11:21:23	ga_ls8c_ard_3-2-1_110078_2022-05-10_final
2022-05-10 11:21:47	ga_ls8c_ard_3-2-1_110079_2022-05-10_final
2022-05-11 10:24:11	ga_ls8c_ard_3-2-1_101074_2022-05-11_final
2022-05-14 10:57:54	ga_ls8c_ard_3-2-1_106081_2022-05-14_final
2022-05-16 10:43:57	ga_ls8c_ard_3-2-1_104077_2022-05-16_final
2022-05-24 09:57:19	ga_ls8c_ard_3-2-1_096084_2022-05-24_final
2022-05-26 11:21:02	ga_ls8c_ard_3-2-1_110077_2022-05-26_final
2022-05-31 09:57:09	ga_ls8c_ard_3-2-1_097068_2022-05-31_final
2022-06-01 10:41:13	ga_ls8c_ard_3-2-1_104070_2022-06-01_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-18 09:52:11	ga_ls8c_ard_3-2-1_095086_2022-06-18_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