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
2015-02-06 09:06:39	ga_ls8c_ard_3-1-0_088081_2015-02-05_final
2016-09-10 10:07:10	ga_ls8c_ard_3-1-0_098077_2016-09-10_final
2017-05-02 09:06:00	ga_ls8c_ard_3-1-0_088081_2017-05-01_final
2018-07-14 10:07:18	ga_ls8c_ard_3-1-0_098080_2018-07-14_final
2019-03-22 11:25:16	ga_ls8c_ard_3-1-0_111073_2019-03-22_final
2019-03-27 10:05:18	ga_ls8c_ard_3-1-0_098074_2019-03-27_final
2019-03-30 10:38:35	ga_ls8c_ard_3-1-0_103080_2019-03-30_final
2019-04-14 09:56:27	ga_ls8c_ard_3-1-0_096083_2019-04-14_final
2019-04-18 09:25:19	ga_ls8c_ard_3-1-0_092067_2019-04-17_final
2019-06-14 09:21:30	ga_ls8c_ard_3-1-0_091072_2019-06-13_final
2019-06-17 11:35:18	ga_ls8c_ard_3-1-0_112082_2019-06-17_final
2019-07-01 10:09:38	ga_ls8c_ard_3-1-0_098084_2019-07-01_final
2019-07-02 09:16:25	ga_ls8c_ard_3-1-0_089090_2019-07-01_final
2019-07-11 09:06:16	ga_ls8c_ard_3-1-0_088080_2019-07-10_final
2019-07-11 09:07:28	ga_ls8c_ard_3-1-0_088083_2019-07-10_final
2019-07-17 10:02:54	ga_ls8c_ard_3-1-0_098067_2019-07-17_final
2019-07-28 11:25:43	ga_ls8c_ard_3-1-0_111073_2019-07-28_final
2019-08-24 09:33:37	ga_ls8c_ard_3-1-0_092086_2019-08-24_final
2019-09-11 09:23:20	ga_ls8c_ard_3-1-0_090091_2019-09-10_final
2019-09-19 10:07:38	ga_ls8c_ard_3-1-0_098078_2019-09-19_final
2019-09-20 09:16:49	ga_ls8c_ard_3-1-0_089090_2019-09-19_final
2019-09-27 10:53:32	ga_ls8c_ard_3-1-0_106069_2019-09-27_final
2019-09-29 09:07:29	ga_ls8c_ard_3-1-0_088082_2019-09-28_final
2019-10-01 10:30:25	ga_ls8c_ard_3-1-0_102073_2019-10-01_final
2019-10-06 10:49:22	ga_ls8c_ard_3-1-0_105074_2019-10-06_final
2019-10-13 09:22:40	ga_ls8c_ard_3-1-0_090089_2019-10-12_final
2019-10-13 09:23:04	ga_ls8c_ard_3-1-0_090090_2019-10-12_final
2019-11-02 10:30:27	ga_ls8c_ard_3-1-0_102073_2019-11-02_final
2019-11-14 10:57:08	ga_ls8c_ard_3-1-0_106078_2019-11-14_final
2019-11-15 10:03:54	ga_ls8c_ard_3-1-0_097084_2019-11-15_final
2019-11-22 10:07:39	ga_ls8c_ard_3-1-0_098078_2019-11-22_final
2019-11-24 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-11-24_final
2019-11-28 11:06:40	ga_ls8c_ard_3-1-0_108071_2019-11-28_final
2019-11-30 10:55:54	ga_ls8c_ard_3-1-0_106075_2019-11-30_final
2019-12-09 09:16:25	ga_ls8c_ard_3-1-0_089089_2019-12-08_final
2019-12-09 10:46:55	ga_ls8c_ard_3-1-0_105068_2019-12-09_final
2019-12-09 10:50:07	ga_ls8c_ard_3-1-0_105076_2019-12-09_final
2019-12-25 10:46:52	ga_ls8c_ard_3-1-0_105068_2019-12-25_final
2019-12-30 11:07:23	ga_ls8c_ard_3-1-0_108073_2019-12-30_final
2019-12-30 11:08:10	ga_ls8c_ard_3-1-0_108075_2019-12-30_final
2020-01-01 10:54:12	ga_ls8c_ard_3-1-0_106071_2020-01-01_final
2020-01-02 09:57:23	ga_ls8c_ard_3-1-0_097068_2020-01-02_final
2020-01-08 09:26:16	ga_ls8c_ard_3-1-0_091083_2020-01-07_final
2020-01-11 09:51:59	ga_ls8c_ard_3-1-0_096070_2020-01-11_final
2020-01-15 11:07:19	ga_ls8c_ard_3-1-0_108073_2020-01-15_final
2020-01-17 10:58:57	ga_ls8c_ard_3-1-0_106083_2020-01-17_final
2020-02-01 11:52:53	ga_ls8c_ard_3-1-0_115079_2020-02-01_final
2020-02-02 10:56:52	ga_ls8c_ard_3-1-0_106078_2020-02-02_final
2020-02-05 11:26:09	ga_ls8c_ard_3-1-0_111074_2020-02-05_final
2020-02-10 10:03:00	ga_ls8c_ard_3-1-0_098067_2020-02-10_final
2020-02-10 10:09:47	ga_ls8c_ard_3-1-0_098084_2020-02-10_final
2020-02-21 11:28:05	ga_ls8c_ard_3-1-0_111079_2020-02-21_final
2020-02-27 10:48:59	ga_ls8c_ard_3-1-0_105074_2020-02-27_final
2020-03-08 09:47:07	ga_ls8c_ard_3-1-0_095074_2020-03-08_final
2020-03-13 10:04:49	ga_ls8c_ard_3-1-0_098072_2020-03-13_final
2020-03-21 10:52:36	ga_ls8c_ard_3-1-0_106068_2020-03-21_final
2020-03-22 09:56:58	ga_ls8c_ard_3-1-0_097068_2020-03-22_final
2020-03-29 10:02:41	ga_ls8c_ard_3-1-0_098067_2020-03-29_final
2020-03-29 10:07:04	ga_ls8c_ard_3-1-0_098078_2020-03-29_final
2020-04-09 11:25:43	ga_ls8c_ard_3-1-0_111074_2020-04-09_final
2020-04-20 09:33:01	ga_ls8c_ard_3-1-0_092086_2020-04-20_final
2020-04-29 09:26:45	ga_ls8c_ard_3-1-0_091086_2020-04-28_final
2020-04-30 10:07:37	ga_ls8c_ard_3-1-0_098080_2020-04-30_final
2020-05-06 09:32:52	ga_ls8c_ard_3-1-0_092086_2020-05-06_final
2022-03-31 10:29:48	ga_ls8c_ard_3-2-1_102073_2022-03-31_final
2022-04-01 09:34:58	ga_ls8c_ard_3-2-1_093075_2022-04-01_final
2022-04-01 11:14:15	ga_ls8c_ard_3-2-1_109076_2022-04-01_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-04-10 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-04-10_final
2022-04-12 09:21:43	ga_ls8c_ard_3-2-1_090088_2022-04-11_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-13 11:41:52	ga_ls8c_ard_3-2-1_113083_2022-04-13_final
2022-04-15 09:50:38	ga_ls8c_ard_3-2-1_095083_2022-04-15_final
2022-04-19 09:24:42	ga_ls8c_ard_3-2-1_091080_2022-04-18_final
2022-04-20 10:06:46	ga_ls8c_ard_3-2-1_098077_2022-04-20_final
2022-04-23 10:35:39	ga_ls8c_ard_3-2-1_103072_2022-04-23_final
2022-04-28 09:22:27	ga_ls8c_ard_3-2-1_090090_2022-04-27_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-02 10:29:52	ga_ls8c_ard_3-2-1_102073_2022-05-02_final
2022-05-04 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-05-04_final
2022-05-05 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-05-04_final
2022-05-06 10:04:24	ga_ls8c_ard_3-2-1_098071_2022-05-06_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-07 10:46:04	ga_ls8c_ard_3-2-1_105067_2022-05-07_final
2022-05-10 11:19:00	ga_ls8c_ard_3-2-1_110072_2022-05-10_final
2022-05-12 11:10:15	ga_ls8c_ard_3-2-1_108081_2022-05-12_final
2022-05-13 11:51:55	ga_ls8c_ard_3-2-1_115077_2022-05-13_final
2022-05-14 09:17:25	ga_ls8c_ard_3-2-1_090077_2022-05-13_final
2022-05-14 09:19:01	ga_ls8c_ard_3-2-1_090081_2022-05-13_final
2022-05-20 10:17:15	ga_ls8c_ard_3-2-1_100072_2022-05-20_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-06-02 09:50:48	ga_ls8c_ard_3-2-1_095083_2022-06-02_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-07 10:04:37	ga_ls8c_ard_3-2-1_098071_2022-06-07_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-15 10:56:09	ga_ls8c_ard_3-2-1_106076_2022-06-15_final
2022-06-15 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-06-15_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_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