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
2022-08-21 09:51:44	ga_ls8c_ard_3-2-1_095084_2022-08-21_final
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-25 11:04:18	ga_ls8c_ard_3-2-1_107080_2022-08-25_final
2022-08-25 11:05:30	ga_ls8c_ard_3-2-1_107083_2022-08-25_final
2022-09-01 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-09-01_final
2022-09-14 10:35:40	ga_ls8c_ard_3-2-1_103070_2022-09-14_final
2022-09-20 11:41:29	ga_ls8c_ard_3-2-1_113080_2022-09-20_final
2022-09-24 09:38:17	ga_ls8c_ard_3-2-1_093081_2022-09-24_final
2022-09-24 11:13:35	ga_ls8c_ard_3-2-1_109072_2022-09-24_final
2022-09-24 11:13:59	ga_ls8c_ard_3-2-1_109073_2022-09-24_final
2022-09-26 11:06:00	ga_ls8c_ard_3-2-1_107084_2022-09-26_final
2022-09-29 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-09-29_final
2022-09-30 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-09-30_final
2022-10-02 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-10-02_final
2022-10-03 11:07:22	ga_ls8c_ard_3-2-1_108072_2022-10-03_final
2022-10-06 10:00:10	ga_ls8c_ard_3-2-1_097074_2022-10-06_final
2022-10-08 11:30:39	ga_ls8c_ard_3-2-1_111084_2022-10-08_final
2022-10-10 11:18:16	ga_ls8c_ard_3-2-1_109084_2022-10-10_final
2022-10-13 10:08:38	ga_ls8c_ard_3-2-1_098080_2022-10-13_final
2022-10-15 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-10-15_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-28 11:05:59	ga_ls8c_ard_3-2-1_107084_2022-10-28_final
2022-11-01 10:35:42	ga_ls8c_ard_3-2-1_103070_2022-11-01_final
2022-11-03 10:24:08	ga_ls8c_ard_3-2-1_101072_2022-11-03_final
2022-11-03 10:25:20	ga_ls8c_ard_3-2-1_101075_2022-11-03_final
2022-11-03 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-11-03_final
2022-11-16 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-11-16_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-25 11:27:26	ga_ls8c_ard_3-2-1_111076_2022-11-25_final
2022-11-30 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-30_final
2022-11-30 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-30_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2022-12-22 11:06:44	ga_ls8c_ard_3-2-1_108071_2022-12-22_final
2022-12-23 11:52:23	ga_ls8c_ard_3-2-1_115077_2022-12-23_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-07 09:31:51	ga_ls8c_ard_3-2-1_092081_2023-01-07_final
2023-01-09 09:19:05	ga_ls8c_ard_3-2-1_090080_2023-01-08_final
2023-01-11 10:45:11	ga_ls8c_ard_3-2-1_104079_2023-01-11_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-17 11:44:54	ga_ls8c_ard_3-2-1_114074_2023-01-17_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-01-24 11:51:10	ga_ls8c_ard_3-2-1_115074_2023-01-24_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-02-09 11:51:09	ga_ls8c_ard_3-2-1_115074_2023-02-09_final
2023-02-15 11:13:12	ga_ls8c_ard_3-2-1_109072_2023-02-15_final
2023-02-22 11:22:25	ga_ls8c_ard_3-2-1_110080_2023-02-22_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-06 11:45:26	ga_ls8c_ard_3-2-1_114076_2023-03-06_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-12 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-03-12_final
2023-03-13 11:51:35	ga_ls8c_ard_3-2-1_115076_2023-03-13_final
2023-03-15 11:41:12	ga_ls8c_ard_3-2-1_113081_2023-03-15_final
2023-03-17 11:29:13	ga_ls8c_ard_3-2-1_111082_2023-03-17_final
2023-03-19 11:12:27	ga_ls8c_ard_3-2-1_109071_2023-03-19_final
2023-03-25 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-03-25_final
2023-04-08 10:48:14	ga_ls8c_ard_3-2-1_105073_2023-04-08_final
2023-04-20 11:12:50	ga_ls8c_ard_3-2-1_109073_2023-04-20_final
2023-05-01 10:57:03	ga_ls8c_ard_3-2-1_106080_2023-05-01_final
2023-05-02 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-05-02_final
2023-05-03 10:43:04	ga_ls8c_ard_3-2-1_104076_2023-05-03_final
2023-05-11 09:51:30	ga_ls8c_ard_3-2-1_096071_2023-05-11_final
2023-05-13 11:20:00	ga_ls8c_ard_3-2-1_110076_2023-05-13_final
2023-05-18 10:01:13	ga_ls8c_ard_3-2-1_097080_2023-05-18_final
2023-05-22 11:11:01	ga_ls8c_ard_3-2-1_109069_2023-05-22_final
2023-05-22 11:12:37	ga_ls8c_ard_3-2-1_109073_2023-05-22_final
2023-05-30 10:25:11	ga_ls8c_ard_3-2-1_101078_2023-05-30_final
2023-06-06 10:31:02	ga_ls8c_ard_3-2-1_102077_2023-06-06_final
2023-06-08 10:17:54	ga_ls8c_ard_3-2-1_100075_2023-06-08_final
2023-06-12 11:35:18	ga_ls8c_ard_3-2-1_112083_2023-06-12_final
2023-06-15 10:25:20	ga_ls8c_ard_3-2-1_101078_2023-06-15_final
2023-06-18 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-06-18_final
2023-06-22 10:30:20	ga_ls8c_ard_3-2-1_102075_2023-06-22_final
2023-06-23 11:14:24	ga_ls8c_ard_3-2-1_109077_2023-06-23_final
2023-07-05 10:03:36	ga_ls8c_ard_3-2-1_097085_2023-07-05_final
2023-07-16 11:22:48	ga_ls8c_ard_3-2-1_110082_2023-07-16_final
2023-07-21 10:03:15	ga_ls8c_ard_3-2-1_097084_2023-07-21_final
2023-07-21 11:40:56	ga_ls8c_ard_3-2-1_113081_2023-07-21_final
2023-07-27 09:24:40	ga_ls8c_ard_3-2-1_091080_2023-07-26_final
2023-08-01 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-08-01_final
2023-08-03 11:08:12	ga_ls8c_ard_3-2-1_108076_2023-08-03_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-18 10:25:02	ga_ls8c_ard_3-2-1_101076_2023-08-18_final
2023-08-19 11:05:31	ga_ls8c_ard_3-2-1_108069_2023-08-19_final
2023-08-19 11:11:30	ga_ls8c_ard_3-2-1_108084_2023-08-19_final
2023-08-24 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-08-24_final
2023-08-30 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-08-29_final
2023-09-10 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-09-10_final
2023-09-11 11:13:21	ga_ls8c_ard_3-2-1_109073_2023-09-11_final
2023-09-13 09:23:43	ga_ls8c_ard_3-2-1_091077_2023-09-12_final
2023-09-15 10:48:40	ga_ls8c_ard_3-2-1_105073_2023-09-15_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