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
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-04 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-09-04_final
2022-09-11 10:03:57	ga_ls8c_ard_3-2-1_098068_2022-09-11_final
2022-09-18 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-09-18_final
2022-09-20 10:01:24	ga_ls8c_ard_3-2-1_097077_2022-09-20_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-22 11:24:21	ga_ls8c_ard_3-2-1_111068_2022-09-22_final
2022-09-23 10:29:55	ga_ls8c_ard_3-2-1_102071_2022-09-23_final
2022-09-27 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-09-27_final
2022-10-03 11:07:46	ga_ls8c_ard_3-2-1_108073_2022-10-03_final
2022-10-04 11:51:25	ga_ls8c_ard_3-2-1_115074_2022-10-04_final
2022-10-04 11:52:37	ga_ls8c_ard_3-2-1_115077_2022-10-04_final
2022-10-05 10:59:23	ga_ls8c_ard_3-2-1_106083_2022-10-05_final
2022-10-06 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-06_final
2022-10-09 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-10-09_final
2022-10-10 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-10-10_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-18 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-10-18_final
2022-10-18 10:27:13	ga_ls8c_ard_3-2-1_101080_2022-10-18_final
2022-10-20 11:52:34	ga_ls8c_ard_3-2-1_115077_2022-10-20_final
2022-10-24 11:24:42	ga_ls8c_ard_3-2-1_111069_2022-10-24_final
2022-10-28 09:25:06	ga_ls8c_ard_3-2-1_091079_2022-10-27_final
2022-11-01 10:35:42	ga_ls8c_ard_3-2-1_103070_2022-11-01_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-09 11:29:30	ga_ls8c_ard_3-2-1_111081_2022-11-09_final
2022-11-12 10:19:05	ga_ls8c_ard_3-2-1_100075_2022-11-12_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-23 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-11-23_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-26 10:29:49	ga_ls8c_ard_3-2-1_102071_2022-11-26_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-07 10:11:17	ga_ls8c_ard_3-2-1_099071_2022-12-07_final
2022-12-07 11:52:57	ga_ls8c_ard_3-2-1_115078_2022-12-07_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-24 09:17:05	ga_ls8c_ard_3-2-1_090075_2022-12-23_final
2022-12-27 11:27:17	ga_ls8c_ard_3-2-1_111076_2022-12-27_final
2022-12-28 10:30:04	ga_ls8c_ard_3-2-1_102072_2022-12-28_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-02 09:13:44	ga_ls8c_ard_3-2-1_089082_2023-01-01_final
2023-01-03 11:32:41	ga_ls8c_ard_3-2-1_112074_2023-01-03_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-08 11:52:48	ga_ls8c_ard_3-2-1_115078_2023-01-08_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-11 10:44:00	ga_ls8c_ard_3-2-1_104076_2023-01-11_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-14 09:37:10	ga_ls8c_ard_3-2-1_093079_2023-01-14_final
2023-01-19 11:31:46	ga_ls8c_ard_3-2-1_112072_2023-01-19_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-11 11:41:09	ga_ls8c_ard_3-2-1_113080_2023-02-11_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_final
2023-02-24 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-02-24_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-08 09:53:22	ga_ls8c_ard_3-2-1_096074_2023-03-08_final
2023-03-12 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-03-12_final
2023-03-13 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-03-13_final
2023-03-14 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-03-14_final
2023-03-15 11:39:36	ga_ls8c_ard_3-2-1_113077_2023-03-15_final
2023-03-17 11:27:13	ga_ls8c_ard_3-2-1_111077_2023-03-17_final
2023-03-21 09:23:34	ga_ls8c_ard_3-2-1_091077_2023-03-20_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-03-28 11:06:10	ga_ls8c_ard_3-2-1_108071_2023-03-28_final
2023-03-29 10:13:44	ga_ls8c_ard_3-2-1_099079_2023-03-29_final
2023-04-02 09:50:57	ga_ls8c_ard_3-2-1_095084_2023-04-02_final
2023-04-04 09:36:34	ga_ls8c_ard_3-2-1_093079_2023-04-04_final
2023-04-06 09:26:57	ga_ls8c_ard_3-2-1_091086_2023-04-05_final
2023-04-15 09:17:03	ga_ls8c_ard_3-2-1_090077_2023-04-14_final
2023-04-16 09:56:43	ga_ls8c_ard_3-2-1_097068_2023-04-16_final
2023-04-16 10:00:42	ga_ls8c_ard_3-2-1_097078_2023-04-16_final
2023-04-16 10:01:30	ga_ls8c_ard_3-2-1_097080_2023-04-16_final
2023-04-16 11:37:59	ga_ls8c_ard_3-2-1_113074_2023-04-16_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-04-20 11:11:38	ga_ls8c_ard_3-2-1_109070_2023-04-20_final
2023-04-29 11:11:02	ga_ls8c_ard_3-2-1_108084_2023-04-29_final
2023-04-30 11:50:17	ga_ls8c_ard_3-2-1_115074_2023-04-30_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-04 11:27:55	ga_ls8c_ard_3-2-1_111080_2023-05-04_final
2023-05-07 10:18:18	ga_ls8c_ard_3-2-1_100076_2023-05-07_final
2023-05-09 10:03:30	ga_ls8c_ard_3-2-1_098070_2023-05-09_final
2023-05-10 10:46:21	ga_ls8c_ard_3-2-1_105069_2023-05-10_final
2023-05-17 09:16:45	ga_ls8c_ard_3-2-1_090077_2023-05-16_final
2023-05-17 09:20:45	ga_ls8c_ard_3-2-1_090087_2023-05-16_final
2023-05-20 11:26:34	ga_ls8c_ard_3-2-1_111077_2023-05-20_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