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
2022-06-15 09:16:52	ga_ls8c_ard_3-2-1_090075_2022-06-14_final
2022-07-20 11:24:46	ga_ls8c_ard_3-2-1_111070_2022-07-20_final
2022-07-22 09:34:45	ga_ls8c_ard_3-2-1_093073_2022-07-22_final
2022-07-23 11:58:31	ga_ls8c_ard_3-2-1_116077_2022-07-23_final
2022-08-02 10:53:13	ga_ls8c_ard_3-2-1_106068_2022-08-02_final
2022-08-05 11:26:09	ga_ls8c_ard_3-2-1_111073_2022-08-05_final
2022-08-07 09:38:54	ga_ls8c_ard_3-2-1_093083_2022-08-07_final
2022-08-25 09:26:13	ga_ls8c_ard_3-2-1_091082_2022-08-24_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-08-26 10:08:16	ga_ls8c_ard_3-2-1_098079_2022-08-26_final
2022-08-30 11:19:38	ga_ls8c_ard_3-2-1_110072_2022-08-30_final
2022-09-01 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-08-31_final
2022-09-01 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-31_final
2022-09-11 10:04:45	ga_ls8c_ard_3-2-1_098070_2022-09-11_final
2022-09-19 10:56:14	ga_ls8c_ard_3-2-1_106075_2022-09-19_final
2022-09-20 11:39:06	ga_ls8c_ard_3-2-1_113074_2022-09-20_final
2022-09-26 09:22:20	ga_ls8c_ard_3-2-1_091072_2022-09-25_final
2022-09-28 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-09-27_final
2022-10-03 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-10-03_final
2022-10-09 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-10-09_final
2022-10-14 09:12:12	ga_ls8c_ard_3-2-1_089078_2022-10-13_final
2022-10-15 09:57:29	ga_ls8c_ard_3-2-1_096083_2022-10-15_final
2022-10-28 09:22:19	ga_ls8c_ard_3-2-1_091072_2022-10-27_final
2022-10-30 10:49:39	ga_ls8c_ard_3-2-1_105074_2022-10-30_final
2022-11-03 10:23:44	ga_ls8c_ard_3-2-1_101071_2022-11-03_final
2022-11-04 09:29:18	ga_ls8c_ard_3-2-1_092074_2022-11-03_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-11-24 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-11-23_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-29 11:00:20	ga_ls8c_ard_3-2-1_107070_2022-11-29_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-12-08 09:17:39	ga_ls8c_ard_3-2-1_090076_2022-12-07_final
2022-12-08 09:18:03	ga_ls8c_ard_3-2-1_090077_2022-12-07_final
2022-12-09 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-12-09_final
2022-12-11 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-12-11_final
2022-12-13 09:35:45	ga_ls8c_ard_3-2-1_093075_2022-12-13_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-15 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-12-15_final
2022-12-17 10:50:16	ga_ls8c_ard_3-2-1_105076_2022-12-17_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2023-01-03 09:53:48	ga_ls8c_ard_3-2-1_096074_2023-01-03_final
2023-01-09 10:55:10	ga_ls8c_ard_3-2-1_106073_2023-01-09_final
2023-01-10 09:57:09	ga_ls8c_ard_3-2-1_097067_2023-01-10_final
2023-01-16 11:00:04	ga_ls8c_ard_3-2-1_107070_2023-01-16_final
2023-01-16 11:05:15	ga_ls8c_ard_3-2-1_107083_2023-01-16_final
2023-01-17 10:07:37	ga_ls8c_ard_3-2-1_098078_2023-01-17_final
2023-01-30 11:13:19	ga_ls8c_ard_3-2-1_109072_2023-01-30_final
2023-01-31 10:17:17	ga_ls8c_ard_3-2-1_100071_2023-01-31_final
2023-02-01 11:01:45	ga_ls8c_ard_3-2-1_107074_2023-02-01_final
2023-02-04 09:52:34	ga_ls8c_ard_3-2-1_096071_2023-02-04_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-19 10:47:36	ga_ls8c_ard_3-2-1_105070_2023-02-19_final
2023-02-21 10:39:35	ga_ls8c_ard_3-2-1_103081_2023-02-21_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-03-03 09:34:05	ga_ls8c_ard_3-2-1_093072_2023-03-03_final
2023-03-07 10:52:12	ga_ls8c_ard_3-2-1_105082_2023-03-07_final
2023-03-20 11:58:29	ga_ls8c_ard_3-2-1_116078_2023-03-20_final
2023-03-22 11:44:53	ga_ls8c_ard_3-2-1_114075_2023-03-22_final
2023-03-30 09:16:30	ga_ls8c_ard_3-2-1_090075_2023-03-29_final
2023-03-30 10:55:23	ga_ls8c_ard_3-2-1_106075_2023-03-30_final
2023-04-29 09:28:09	ga_ls8c_ard_3-2-1_092074_2023-04-28_final
2023-05-01 09:16:10	ga_ls8c_ard_3-2-1_090075_2023-04-30_final
2023-05-10 10:49:08	ga_ls8c_ard_3-2-1_105076_2023-05-10_final
2023-05-15 09:27:56	ga_ls8c_ard_3-2-1_092074_2023-05-14_final
2023-05-25 10:07:03	ga_ls8c_ard_3-2-1_098079_2023-05-25_final
2023-06-02 10:55:17	ga_ls8c_ard_3-2-1_106076_2023-06-02_final
2023-06-08 10:16:18	ga_ls8c_ard_3-2-1_100071_2023-06-08_final
2023-06-08 10:18:18	ga_ls8c_ard_3-2-1_100076_2023-06-08_final
2023-06-11 09:11:33	ga_ls8c_ard_3-2-1_089079_2023-06-10_final
2023-06-11 10:46:02	ga_ls8c_ard_3-2-1_105068_2023-06-11_final
2023-06-16 09:28:07	ga_ls8c_ard_3-2-1_092074_2023-06-15_final
2023-07-09 11:13:48	ga_ls8c_ard_3-2-1_109075_2023-07-09_final
2023-07-09 11:14:12	ga_ls8c_ard_3-2-1_109076_2023-07-09_final
2023-07-11 09:26:58	ga_ls8c_ard_3-2-1_091086_2023-07-10_final
2023-07-29 09:16:19	ga_ls8c_ard_3-2-1_089090_2023-07-28_final
2023-08-09 10:28:19	ga_ls8c_ard_3-2-1_102069_2023-08-09_final
2023-08-14 10:48:54	ga_ls8c_ard_3-2-1_105074_2023-08-14_final
2023-08-17 09:39:46	ga_ls8c_ard_3-2-1_094071_2023-08-17_final
2023-09-07 09:57:56	ga_ls8c_ard_3-2-1_097070_2023-09-07_final
2023-09-14 10:07:23	ga_ls8c_ard_3-2-1_098078_2023-09-14_final
2023-09-20 09:28:44	ga_ls8c_ard_3-2-1_092074_2023-09-19_final
2023-09-23 09:57:14	ga_ls8c_ard_3-2-1_097068_2023-09-23_final
2023-10-03 10:35:58	ga_ls8c_ard_3-2-1_103072_2023-10-03_final
2023-10-06 09:27:58	ga_ls8c_ard_3-2-1_092072_2023-10-05_final
2023-10-06 11:06:04	ga_ls8c_ard_3-2-1_108070_2023-10-06_final
2023-10-07 11:52:32	ga_ls8c_ard_3-2-1_115078_2023-10-07_final
2023-10-08 09:21:38	ga_ls8c_ard_3-2-1_090087_2023-10-07_final
2023-10-11 09:46:34	ga_ls8c_ard_3-2-1_095072_2023-10-11_final
2023-10-17 10:49:57	ga_ls8c_ard_3-2-1_105076_2023-10-17_final
2023-10-19 10:35:59	ga_ls8c_ard_3-2-1_103072_2023-10-19_final
2023-10-25 11:38:38	ga_ls8c_ard_3-2-1_113074_2023-10-25_final
2023-10-26 10:46:13	ga_ls8c_ard_3-2-1_104082_2023-10-26_final
2023-10-31 09:23:30	ga_ls8c_ard_3-2-1_091076_2023-10-30_final
2023-11-03 11:32:28	ga_ls8c_ard_3-2-1_112074_2023-11-03_final
2023-11-04 10:36:03	ga_ls8c_ard_3-2-1_103072_2023-11-04_final
2023-11-09 09:16:50	ga_ls8c_ard_3-2-1_090075_2023-11-08_final
2023-11-16 11:00:22	ga_ls8c_ard_3-2-1_107071_2023-11-16_final
2023-11-23 11:07:24	ga_ls8c_ard_3-2-1_108073_2023-11-23_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