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
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-12 10:30:59	ga_ls8c_ard_3-2-1_102074_2022-12-12_final
2022-12-12 10:32:35	ga_ls8c_ard_3-2-1_102078_2022-12-12_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-15 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-12-14_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-15 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-12-15_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-17 09:13:22	ga_ls8c_ard_3-2-1_089081_2022-12-16_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-18 09:56:13	ga_ls8c_ard_3-2-1_096080_2022-12-18_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-21 10:25:53	ga_ls8c_ard_3-2-1_101077_2022-12-21_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2022-12-31 09:24:53	ga_ls8c_ard_3-2-1_091079_2022-12-30_final
2023-01-03 09:54:12	ga_ls8c_ard_3-2-1_096075_2023-01-03_final
2023-01-04 10:40:15	ga_ls8c_ard_3-2-1_103082_2023-01-04_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-09 10:53:59	ga_ls8c_ard_3-2-1_106070_2023-01-09_final
2023-01-10 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-10_final
2023-01-11 10:42:00	ga_ls8c_ard_3-2-1_104071_2023-01-11_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-14 11:12:28	ga_ls8c_ard_3-2-1_109070_2023-01-14_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-22 10:25:25	ga_ls8c_ard_3-2-1_101076_2023-01-22_final
2023-01-23 11:09:05	ga_ls8c_ard_3-2-1_108077_2023-01-23_final
2023-01-24 10:11:29	ga_ls8c_ard_3-2-1_099072_2023-01-24_final
2023-01-26 10:01:08	ga_ls8c_ard_3-2-1_097077_2023-01-26_final
2023-01-31 10:19:17	ga_ls8c_ard_3-2-1_100076_2023-01-31_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-06 11:24:16	ga_ls8c_ard_3-2-1_110084_2023-02-06_final
2023-02-08 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-02-08_final
2023-02-09 11:51:09	ga_ls8c_ard_3-2-1_115074_2023-02-09_final
2023-02-10 09:18:38	ga_ls8c_ard_3-2-1_090079_2023-02-09_final
2023-02-11 11:39:34	ga_ls8c_ard_3-2-1_113076_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-13 11:28:22	ga_ls8c_ard_3-2-1_111079_2023-02-13_final
2023-02-15 11:12:00	ga_ls8c_ard_3-2-1_109069_2023-02-15_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-23 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-02-23_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-02-27 11:39:42	ga_ls8c_ard_3-2-1_113077_2023-02-27_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-03 09:34:29	ga_ls8c_ard_3-2-1_093073_2023-03-03_final
2023-03-05 09:23:42	ga_ls8c_ard_3-2-1_091077_2023-03-04_final
2023-03-05 11:01:23	ga_ls8c_ard_3-2-1_107074_2023-03-05_final
2023-03-06 10:03:22	ga_ls8c_ard_3-2-1_098068_2023-03-06_final
2023-03-06 11:45:02	ga_ls8c_ard_3-2-1_114075_2023-03-06_final
2023-03-10 11:18:41	ga_ls8c_ard_3-2-1_110071_2023-03-10_final
2023-03-10 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-03-10_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-03-12 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-03-12_final
2023-03-12 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-03-12_final
2023-03-12 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-03-12_final
2023-03-13 10:15:53	ga_ls8c_ard_3-2-1_099084_2023-03-13_final
2023-03-15 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-03-15_final
2023-03-17 11:28:01	ga_ls8c_ard_3-2-1_111079_2023-03-17_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-28 09:30:04	ga_ls8c_ard_3-2-1_092078_2023-03-28_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-04-01 10:45:23	ga_ls8c_ard_3-2-1_104081_2023-04-01_final
2023-04-08 09:12:09	ga_ls8c_ard_3-2-1_089080_2023-04-07_final
2023-04-10 10:37:25	ga_ls8c_ard_3-2-1_103077_2023-04-10_final
2023-04-11 09:39:23	ga_ls8c_ard_3-2-1_094071_2023-04-11_final
2023-04-12 10:27:26	ga_ls8c_ard_3-2-1_101083_2023-04-12_final
2023-04-13 09:27:25	ga_ls8c_ard_3-2-1_092072_2023-04-12_final
2023-04-18 11:27:12	ga_ls8c_ard_3-2-1_111078_2023-04-18_final
2023-04-18 11:28:24	ga_ls8c_ard_3-2-1_111081_2023-04-18_final
2023-04-19 10:31:34	ga_ls8c_ard_3-2-1_102078_2023-04-19_final
2023-04-20 11:12:26	ga_ls8c_ard_3-2-1_109072_2023-04-20_final
2023-04-25 09:55:17	ga_ls8c_ard_3-2-1_096080_2023-04-25_final
2023-04-29 11:08:14	ga_ls8c_ard_3-2-1_108077_2023-04-29_final
2023-04-29 11:09:26	ga_ls8c_ard_3-2-1_108080_2023-04-29_final
2023-05-01 09:16:58	ga_ls8c_ard_3-2-1_090077_2023-04-30_final
2023-05-01 09:17:46	ga_ls8c_ard_3-2-1_090079_2023-04-30_final
2023-05-01 09:18:10	ga_ls8c_ard_3-2-1_090080_2023-04-30_final
2023-05-02 10:00:13	ga_ls8c_ard_3-2-1_097077_2023-05-02_final
2023-05-03 10:45:04	ga_ls8c_ard_3-2-1_104081_2023-05-03_final
2023-05-06 09:34:15	ga_ls8c_ard_3-2-1_093074_2023-05-06_final
2023-05-06 11:12:20	ga_ls8c_ard_3-2-1_109072_2023-05-06_final
2023-05-06 11:16:20	ga_ls8c_ard_3-2-1_109082_2023-05-06_final
2023-05-11 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-11_final
2023-05-15 11:06:49	ga_ls8c_ard_3-2-1_108074_2023-05-15_final
2023-05-15 11:08:01	ga_ls8c_ard_3-2-1_108077_2023-05-15_final
2023-05-17 10:53:38	ga_ls8c_ard_3-2-1_106072_2023-05-17_final
2023-05-17 10:58:02	ga_ls8c_ard_3-2-1_106083_2023-05-17_final
2023-05-20 11:25:22	ga_ls8c_ard_3-2-1_111074_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