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
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-11 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-10-11_final
2022-10-20 10:14:53	ga_ls8c_ard_3-2-1_099080_2022-10-20_final
2022-10-27 10:21:31	ga_ls8c_ard_3-2-1_100081_2022-10-27_final
2022-10-28 09:23:07	ga_ls8c_ard_3-2-1_091074_2022-10-27_final
2022-10-30 09:13:33	ga_ls8c_ard_3-2-1_089081_2022-10-29_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-12 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-11-12_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-19 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-11-19_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-21 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-11-21_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-12-01 10:52:46	ga_ls8c_ard_3-2-1_105082_2022-12-01_final
2022-12-07 11:51:21	ga_ls8c_ard_3-2-1_115074_2022-12-07_final
2022-12-11 11:27:48	ga_ls8c_ard_3-2-1_111077_2022-12-11_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-16 10:03:49	ga_ls8c_ard_3-2-1_098068_2022-12-16_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-18 09:53:26	ga_ls8c_ard_3-2-1_096073_2022-12-18_final
2022-12-20 09:41:02	ga_ls8c_ard_3-2-1_094073_2022-12-20_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-26 10:43:13	ga_ls8c_ard_3-2-1_104074_2022-12-26_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-05 11:21:31	ga_ls8c_ard_3-2-1_110077_2023-01-05_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-01-14 11:14:03	ga_ls8c_ard_3-2-1_109074_2023-01-14_final
2023-01-15 10:17:37	ga_ls8c_ard_3-2-1_100072_2023-01-15_final
2023-01-17 11:44:54	ga_ls8c_ard_3-2-1_114074_2023-01-17_final
2023-01-21 11:21:25	ga_ls8c_ard_3-2-1_110077_2023-01-21_final
2023-01-23 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-01-23_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-24 10:10:41	ga_ls8c_ard_3-2-1_099070_2023-01-24_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-15 11:13:12	ga_ls8c_ard_3-2-1_109072_2023-02-15_final
2023-02-19 10:46:48	ga_ls8c_ard_3-2-1_105068_2023-02-19_final
2023-03-08 11:32:15	ga_ls8c_ard_3-2-1_112074_2023-03-08_final
2023-03-15 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-03-15_final
2023-03-17 11:26:26	ga_ls8c_ard_3-2-1_111075_2023-03-17_final
2023-03-19 09:34:45	ga_ls8c_ard_3-2-1_093074_2023-03-19_final
2023-03-19 09:39:33	ga_ls8c_ard_3-2-1_093086_2023-03-19_final
2023-03-21 09:23:10	ga_ls8c_ard_3-2-1_091076_2023-03-20_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-27 10:25:42	ga_ls8c_ard_3-2-1_101078_2023-03-27_final
2023-03-29 11:52:37	ga_ls8c_ard_3-2-1_115079_2023-03-29_final
2023-04-02 11:24:39	ga_ls8c_ard_3-2-1_111071_2023-04-02_final
2023-04-04 11:11:51	ga_ls8c_ard_3-2-1_109070_2023-04-04_final
2023-04-08 09:11:45	ga_ls8c_ard_3-2-1_089079_2023-04-07_final
2023-04-13 09:34:36	ga_ls8c_ard_3-2-1_092090_2023-04-13_final
2023-04-18 11:23:13	ga_ls8c_ard_3-2-1_111068_2023-04-18_final
2023-04-21 10:18:25	ga_ls8c_ard_3-2-1_100076_2023-04-21_final
2023-04-21 10:21:12	ga_ls8c_ard_3-2-1_100083_2023-04-21_final
2023-04-26 10:33:46	ga_ls8c_ard_3-2-1_103068_2023-04-26_final
2023-04-28 10:24:11	ga_ls8c_ard_3-2-1_101075_2023-04-28_final
2023-04-29 11:10:38	ga_ls8c_ard_3-2-1_108083_2023-04-29_final
2023-05-05 10:29:29	ga_ls8c_ard_3-2-1_102073_2023-05-05_final
2023-05-06 09:39:02	ga_ls8c_ard_3-2-1_093086_2023-05-06_final
2023-05-10 09:15:51	ga_ls8c_ard_3-2-1_089090_2023-05-09_final
2023-05-25 11:45:56	ga_ls8c_ard_3-2-1_114079_2023-05-25_final
2023-05-27 09:55:29	ga_ls8c_ard_3-2-1_096081_2023-05-27_final
2023-05-31 11:04:52	ga_ls8c_ard_3-2-1_108069_2023-05-31_final
2023-06-03 10:03:17	ga_ls8c_ard_3-2-1_097085_2023-06-03_final
2023-06-06 10:27:26	ga_ls8c_ard_3-2-1_102068_2023-06-06_final
2023-06-10 11:44:03	ga_ls8c_ard_3-2-1_114074_2023-06-10_final
2023-06-15 10:27:20	ga_ls8c_ard_3-2-1_101083_2023-06-15_final
2023-06-16 11:10:36	ga_ls8c_ard_3-2-1_108083_2023-06-16_final
2023-06-17 11:52:16	ga_ls8c_ard_3-2-1_115079_2023-06-17_final
2023-06-20 09:06:12	ga_ls8c_ard_3-2-1_088081_2023-06-19_final
2023-06-20 10:45:29	ga_ls8c_ard_3-2-1_104082_2023-06-20_final
2023-06-30 11:21:54	ga_ls8c_ard_3-2-1_110080_2023-06-30_final
2023-07-05 11:39:18	ga_ls8c_ard_3-2-1_113077_2023-07-05_final
2023-07-07 11:25:21	ga_ls8c_ard_3-2-1_111073_2023-07-07_final
2023-07-09 11:11:49	ga_ls8c_ard_3-2-1_109070_2023-07-09_final
2023-07-10 10:20:59	ga_ls8c_ard_3-2-1_100082_2023-07-10_final
2023-07-11 09:24:10	ga_ls8c_ard_3-2-1_091079_2023-07-10_final
2023-07-11 11:03:27	ga_ls8c_ard_3-2-1_107080_2023-07-11_final
2023-07-17 10:26:23	ga_ls8c_ard_3-2-1_101080_2023-07-17_final
2023-07-18 11:10:02	ga_ls8c_ard_3-2-1_108081_2023-07-18_final
2023-07-21 10:02:03	ga_ls8c_ard_3-2-1_097081_2023-07-21_final
2023-07-21 11:39:21	ga_ls8c_ard_3-2-1_113077_2023-07-21_final
2023-07-25 09:35:24	ga_ls8c_ard_3-2-1_093076_2023-07-25_final
2023-07-25 09:39:24	ga_ls8c_ard_3-2-1_093086_2023-07-25_final
2023-07-27 11:03:33	ga_ls8c_ard_3-2-1_107080_2023-07-27_final
2023-07-28 10:07:56	ga_ls8c_ard_3-2-1_098080_2023-07-28_final
2023-07-28 11:45:38	ga_ls8c_ard_3-2-1_114077_2023-07-28_final
2023-07-28 11:46:02	ga_ls8c_ard_3-2-1_114078_2023-07-28_final
2023-08-01 09:45:15	ga_ls8c_ard_3-2-1_094085_2023-08-01_final
2023-08-04 11:51:52	ga_ls8c_ard_3-2-1_115077_2023-08-04_final
2023-08-10 09:39:53	ga_ls8c_ard_3-2-1_093087_2023-08-10_final
2023-08-13 10:03:14	ga_ls8c_ard_3-2-1_098068_2023-08-13_final
2023-08-15 09:58:05	ga_ls8c_ard_3-2-1_096086_2023-08-15_final
2023-08-19 11:07:30	ga_ls8c_ard_3-2-1_108074_2023-08-19_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