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
2022-05-10 09:44:54	ga_ls8c_ard_3-2-1_094084_2022-05-10_final
2022-05-18 10:33:36	ga_ls8c_ard_3-2-1_102082_2022-05-18_final
2022-05-21 11:00:07	ga_ls8c_ard_3-2-1_107071_2022-05-21_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-05-28 09:29:23	ga_ls8c_ard_3-2-1_092076_2022-05-27_final
2022-05-28 09:30:59	ga_ls8c_ard_3-2-1_092080_2022-05-28_final
2022-05-29 11:52:45	ga_ls8c_ard_3-2-1_115079_2022-05-29_final
2022-06-06 09:24:32	ga_ls8c_ard_3-2-1_091079_2022-06-05_final
2022-06-06 11:00:14	ga_ls8c_ard_3-2-1_107071_2022-06-06_final
2022-06-09 11:34:22	ga_ls8c_ard_3-2-1_112079_2022-06-09_final
2022-06-11 11:19:38	ga_ls8c_ard_3-2-1_110073_2022-06-11_final
2022-06-16 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-06-16_final
2022-06-16 10:02:08	ga_ls8c_ard_3-2-1_097080_2022-06-16_final
2022-06-20 11:12:44	ga_ls8c_ard_3-2-1_109071_2022-06-20_final
2022-06-25 09:52:25	ga_ls8c_ard_3-2-1_096071_2022-06-25_final
2022-06-25 09:58:00	ga_ls8c_ard_3-2-1_096085_2022-06-25_final
2022-06-27 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-06-27_final
2022-06-29 09:32:06	ga_ls8c_ard_3-2-1_092082_2022-06-29_final
2022-06-29 11:05:47	ga_ls8c_ard_3-2-1_108069_2022-06-29_final
2022-06-29 11:06:35	ga_ls8c_ard_3-2-1_108071_2022-06-29_final
2022-06-30 11:51:51	ga_ls8c_ard_3-2-1_115076_2022-06-30_final
2022-07-03 10:41:52	ga_ls8c_ard_3-2-1_104071_2022-07-03_final
2022-07-17 10:53:49	ga_ls8c_ard_3-2-1_106070_2022-07-17_final
2022-07-21 10:31:10	ga_ls8c_ard_3-2-1_102075_2022-07-21_final
2022-07-23 10:20:25	ga_ls8c_ard_3-2-1_100079_2022-07-23_final
2022-07-23 10:21:37	ga_ls8c_ard_3-2-1_100082_2022-07-23_final
2022-07-24 11:00:30	ga_ls8c_ard_3-2-1_107071_2022-07-24_final
2022-07-25 10:05:17	ga_ls8c_ard_3-2-1_098072_2022-07-25_final
2022-07-29 11:20:18	ga_ls8c_ard_3-2-1_110074_2022-07-29_final
2022-08-13 10:38:21	ga_ls8c_ard_3-2-1_103077_2022-08-13_final
2022-08-16 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-08-16_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-23 11:17:27	ga_ls8c_ard_3-2-1_109082_2022-08-23_final
2022-09-04 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-09-04_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-10 09:23:53	ga_ls8c_ard_3-2-1_091076_2022-09-09_final
2022-09-11 11:47:14	ga_ls8c_ard_3-2-1_114079_2022-09-11_final
2022-09-13 09:52:48	ga_ls8c_ard_3-2-1_096071_2022-09-13_final
2022-09-14 10:35:16	ga_ls8c_ard_3-2-1_103069_2022-09-14_final
2022-09-18 11:51:27	ga_ls8c_ard_3-2-1_115074_2022-09-18_final
2022-09-23 10:29:55	ga_ls8c_ard_3-2-1_102071_2022-09-23_final
2022-09-27 10:05:36	ga_ls8c_ard_3-2-1_098072_2022-09-27_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-13 11:46:43	ga_ls8c_ard_3-2-1_114078_2022-10-13_final
2022-10-14 10:52:41	ga_ls8c_ard_3-2-1_105082_2022-10-14_final
2022-10-14 10:53:05	ga_ls8c_ard_3-2-1_105083_2022-10-14_final
2022-10-15 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-10-15_final
2022-10-16 10:36:22	ga_ls8c_ard_3-2-1_103072_2022-10-16_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-19 11:11:42	ga_ls8c_ard_3-2-1_108083_2022-10-19_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-26 11:13:09	ga_ls8c_ard_3-2-1_109071_2022-10-26_final
2022-10-27 10:18:44	ga_ls8c_ard_3-2-1_100074_2022-10-27_final
2022-10-31 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-10-31_final
2022-11-02 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-11-02_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-12 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-11-12_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-21 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-11-21_final
2022-11-23 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-11-23_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-11-28 11:58:21	ga_ls8c_ard_3-2-1_116076_2022-11-28_final
2022-11-30 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-30_final
2022-12-04 09:45:58	ga_ls8c_ard_3-2-1_094085_2022-12-04_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-15 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-12-14_final
2022-12-16 10:08:13	ga_ls8c_ard_3-2-1_098079_2022-12-16_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-27 11:29:17	ga_ls8c_ard_3-2-1_111081_2022-12-27_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-01 11:45:27	ga_ls8c_ard_3-2-1_114075_2023-01-01_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-08 10:13:07	ga_ls8c_ard_3-2-1_099076_2023-01-08_final
2023-01-11 10:42:00	ga_ls8c_ard_3-2-1_104071_2023-01-11_final
2023-01-16 09:25:11	ga_ls8c_ard_3-2-1_091080_2023-01-15_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-01-18 10:48:53	ga_ls8c_ard_3-2-1_105073_2023-01-18_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-02-06 11:21:04	ga_ls8c_ard_3-2-1_110076_2023-02-06_final
2023-02-06 11:23:28	ga_ls8c_ard_3-2-1_110082_2023-02-06_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_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