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
2015-06-04 10:06:54	ga_ls8c_ard_3-1-0_098079_2015-06-04_final
2015-09-29 10:23:30	ga_ls8c_ard_3-1-0_101072_2015-09-29_final
2016-06-18 10:28:59	ga_ls8c_ard_3-1-0_102071_2016-06-18_final
2018-07-14 10:03:42	ga_ls8c_ard_3-1-0_098071_2018-07-14_final
2019-03-10 09:24:30	ga_ls8c_ard_3-1-0_091080_2019-03-09_final
2019-03-12 10:47:01	ga_ls8c_ard_3-1-0_105070_2019-03-12_final
2019-03-17 11:10:44	ga_ls8c_ard_3-1-0_108083_2019-03-17_final
2019-04-08 10:33:10	ga_ls8c_ard_3-1-0_102082_2019-04-08_final
2019-04-14 09:56:27	ga_ls8c_ard_3-1-0_096083_2019-04-14_final
2019-06-15 10:08:22	ga_ls8c_ard_3-1-0_098081_2019-06-15_final
2019-06-16 10:52:26	ga_ls8c_ard_3-1-0_105083_2019-06-16_final
2019-06-26 09:47:29	ga_ls8c_ard_3-1-0_095075_2019-06-26_final
2019-07-12 11:25:13	ga_ls8c_ard_3-1-0_111072_2019-07-12_final
2019-07-19 09:57:20	ga_ls8c_ard_3-1-0_096084_2019-07-19_final
2019-07-19 11:31:49	ga_ls8c_ard_3-1-0_112073_2019-07-19_final
2019-07-28 11:24:55	ga_ls8c_ard_3-1-0_111071_2019-07-28_final
2019-07-28 11:29:18	ga_ls8c_ard_3-1-0_111082_2019-07-28_final
2019-07-31 11:57:26	ga_ls8c_ard_3-1-0_116075_2019-07-31_final
2019-07-31 11:57:50	ga_ls8c_ard_3-1-0_116076_2019-07-31_final
2019-08-01 09:25:20	ga_ls8c_ard_3-1-0_091081_2019-07-31_final
2019-08-02 10:03:00	ga_ls8c_ard_3-1-0_098067_2019-08-02_final
2019-08-04 11:34:44	ga_ls8c_ard_3-1-0_112080_2019-08-04_final
2019-08-13 09:46:08	ga_ls8c_ard_3-1-0_095071_2019-08-13_final
2019-08-17 09:25:25	ga_ls8c_ard_3-1-0_091081_2019-08-16_final
2019-09-03 10:04:21	ga_ls8c_ard_3-1-0_098070_2019-09-03_final
2019-09-03 10:05:09	ga_ls8c_ard_3-1-0_098072_2019-09-03_final
2019-09-05 09:52:00	ga_ls8c_ard_3-1-0_096070_2019-09-05_final
2019-09-15 10:30:44	ga_ls8c_ard_3-1-0_102074_2019-09-15_final
2019-09-19 10:05:14	ga_ls8c_ard_3-1-0_098072_2019-09-19_final
2019-10-04 09:24:02	ga_ls8c_ard_3-1-0_091077_2019-10-03_final
2019-10-04 09:26:50	ga_ls8c_ard_3-1-0_091084_2019-10-03_final
2019-10-07 11:36:38	ga_ls8c_ard_3-1-0_112084_2019-10-07_final
2019-10-16 11:24:05	ga_ls8c_ard_3-1-0_111068_2019-10-16_final
2019-10-17 10:34:03	ga_ls8c_ard_3-1-0_102082_2019-10-17_final
2019-10-20 09:24:04	ga_ls8c_ard_3-1-0_091077_2019-10-19_final
2019-10-21 10:08:08	ga_ls8c_ard_3-1-0_098079_2019-10-21_final
2019-10-26 10:24:17	ga_ls8c_ard_3-1-0_101073_2019-10-26_final
2019-11-08 11:36:14	ga_ls8c_ard_3-1-0_112083_2019-11-08_final
2019-11-24 09:53:42	ga_ls8c_ard_3-1-0_096074_2019-11-24_final
2019-11-28 11:07:04	ga_ls8c_ard_3-1-0_108072_2019-11-28_final
2019-12-03 09:50:19	ga_ls8c_ard_3-1-0_095081_2019-12-03_final
2019-12-04 10:29:11	ga_ls8c_ard_3-1-0_102070_2019-12-04_final
2019-12-07 09:28:23	ga_ls8c_ard_3-1-0_091088_2019-12-06_final
2019-12-08 10:04:27	ga_ls8c_ard_3-1-0_098070_2019-12-08_final
2019-12-10 09:53:41	ga_ls8c_ard_3-1-0_096074_2019-12-10_final
2019-12-25 10:47:40	ga_ls8c_ard_3-1-0_105070_2019-12-25_final
2019-12-30 11:05:47	ga_ls8c_ard_3-1-0_108069_2019-12-30_final
2019-12-30 11:11:46	ga_ls8c_ard_3-1-0_108084_2019-12-30_final
2020-01-05 10:33:52	ga_ls8c_ard_3-1-0_102082_2020-01-05_final
2020-01-15 11:10:31	ga_ls8c_ard_3-1-0_108081_2020-01-15_final
2020-01-26 10:47:56	ga_ls8c_ard_3-1-0_105071_2020-01-26_final
2020-01-30 10:27:11	ga_ls8c_ard_3-1-0_101081_2020-01-30_final
2020-02-06 10:31:43	ga_ls8c_ard_3-1-0_102077_2020-02-06_final
2020-02-12 11:35:30	ga_ls8c_ard_3-1-0_112082_2020-02-12_final
2020-02-21 11:30:05	ga_ls8c_ard_3-1-0_111084_2020-02-21_final
2020-02-26 10:06:31	ga_ls8c_ard_3-1-0_098076_2020-02-26_final
2020-02-28 09:53:21	ga_ls8c_ard_3-1-0_096074_2020-02-28_final
2020-03-08 09:49:54	ga_ls8c_ard_3-1-0_095081_2020-03-08_final
2020-03-12 09:27:09	ga_ls8c_ard_3-1-0_091086_2020-03-11_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-14 10:47:16	ga_ls8c_ard_3-1-0_105070_2020-03-14_final
2020-03-31 09:52:17	ga_ls8c_ard_3-1-0_096072_2020-03-31_final
2020-04-25 11:29:36	ga_ls8c_ard_3-1-0_111084_2020-04-25_final
2020-05-01 10:50:52	ga_ls8c_ard_3-1-0_105080_2020-05-01_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-04-01 09:34:35	ga_ls8c_ard_3-2-1_093074_2022-04-01_final
2022-04-02 10:21:26	ga_ls8c_ard_3-2-1_100083_2022-04-02_final
2022-04-03 09:24:13	ga_ls8c_ard_3-2-1_091079_2022-04-02_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-08 11:19:42	ga_ls8c_ard_3-2-1_110074_2022-04-08_final
2022-04-08 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-08_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-11 10:12:32	ga_ls8c_ard_3-2-1_099076_2022-04-11_final
2022-04-12 09:18:07	ga_ls8c_ard_3-2-1_090079_2022-04-11_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-22 11:35:16	ga_ls8c_ard_3-2-1_112082_2022-04-22_final
2022-04-24 09:44:49	ga_ls8c_ard_3-2-1_094084_2022-04-24_final
2022-04-24 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-24_final
2022-04-26 11:06:08	ga_ls8c_ard_3-2-1_108071_2022-04-26_final
2022-04-27 10:11:18	ga_ls8c_ard_3-2-1_099073_2022-04-27_final
2022-04-27 10:12:05	ga_ls8c_ard_3-2-1_099075_2022-04-27_final
2022-04-28 09:18:51	ga_ls8c_ard_3-2-1_090081_2022-04-27_final
2022-05-08 11:32:32	ga_ls8c_ard_3-2-1_112075_2022-05-08_final
2022-05-09 10:34:32	ga_ls8c_ard_3-2-1_103069_2022-05-09_final
2022-05-10 09:44:30	ga_ls8c_ard_3-2-1_094083_2022-05-10_final
2022-05-13 10:11:26	ga_ls8c_ard_3-2-1_099073_2022-05-13_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-21 09:21:38	ga_ls8c_ard_3-2-1_091072_2022-05-20_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-05-31 09:56:45	ga_ls8c_ard_3-2-1_097067_2022-05-31_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-06-03 10:32:29	ga_ls8c_ard_3-2-1_102079_2022-06-03_final
2022-06-07 10:06:37	ga_ls8c_ard_3-2-1_098076_2022-06-07_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-06-18 11:26:41	ga_ls8c_ard_3-2-1_111075_2022-06-18_final
2022-06-19 10:30:40	ga_ls8c_ard_3-2-1_102074_2022-06-19_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