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
2022-07-16 10:09:45	ga_ls8c_ard_3-2-1_099068_2022-07-16_final
2022-07-17 10:59:01	ga_ls8c_ard_3-2-1_106083_2022-07-17_final
2022-07-22 09:39:32	ga_ls8c_ard_3-2-1_093085_2022-07-22_final
2022-07-23 10:17:38	ga_ls8c_ard_3-2-1_100072_2022-07-23_final
2022-07-24 09:25:13	ga_ls8c_ard_3-2-1_091080_2022-07-23_final
2022-07-24 11:00:30	ga_ls8c_ard_3-2-1_107071_2022-07-24_final
2022-07-30 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-07-30_final
2022-08-04 10:44:04	ga_ls8c_ard_3-2-1_104076_2022-08-04_final
2022-08-08 10:17:23	ga_ls8c_ard_3-2-1_100071_2022-08-08_final
2022-08-09 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-08-09_final
2022-08-09 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-08-09_final
2022-08-10 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-08-10_final
2022-08-10 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-08-10_final
2022-08-14 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-08-14_final
2022-08-15 10:26:24	ga_ls8c_ard_3-2-1_101078_2022-08-15_final
2022-08-18 10:54:55	ga_ls8c_ard_3-2-1_106072_2022-08-18_final
2022-08-18 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-08-18_final
2022-08-25 09:25:25	ga_ls8c_ard_3-2-1_091080_2022-08-24_final
2022-08-25 11:00:42	ga_ls8c_ard_3-2-1_107071_2022-08-25_final
2022-08-27 09:13:03	ga_ls8c_ard_3-2-1_089080_2022-08-26_final
2022-08-27 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-08-27_final
2022-08-31 10:23:37	ga_ls8c_ard_3-2-1_101071_2022-08-31_final
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-03 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-09-03_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-06 09:52:57	ga_ls8c_ard_3-2-1_095087_2022-09-06_final
2022-09-10 09:23:53	ga_ls8c_ard_3-2-1_091076_2022-09-09_final
2022-09-10 09:28:40	ga_ls8c_ard_3-2-1_091088_2022-09-09_final
2022-09-14 10:35:16	ga_ls8c_ard_3-2-1_103069_2022-09-14_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-17 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-09-17_final
2022-09-18 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-09-18_final
2022-09-26 09:29:31	ga_ls8c_ard_3-2-1_091090_2022-09-25_final
2022-09-27 11:48:04	ga_ls8c_ard_3-2-1_114081_2022-09-27_final
2022-09-29 11:36:54	ga_ls8c_ard_3-2-1_112084_2022-09-29_final
2022-10-01 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-10-01_final
2022-10-03 11:08:58	ga_ls8c_ard_3-2-1_108076_2022-10-03_final
2022-10-05 10:55:47	ga_ls8c_ard_3-2-1_106074_2022-10-05_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-13 11:46:43	ga_ls8c_ard_3-2-1_114078_2022-10-13_final
2022-10-14 10:52:17	ga_ls8c_ard_3-2-1_105081_2022-10-14_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-16 10:37:10	ga_ls8c_ard_3-2-1_103074_2022-10-16_final
2022-10-17 11:23:14	ga_ls8c_ard_3-2-1_110081_2022-10-17_final
2022-10-19 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-10-19_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-26 09:35:28	ga_ls8c_ard_3-2-1_093074_2022-10-26_final
2022-10-27 10:19:08	ga_ls8c_ard_3-2-1_100075_2022-10-27_final
2022-10-30 09:12:45	ga_ls8c_ard_3-2-1_089079_2022-10-29_final
2022-10-30 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-10-30_final
2022-11-02 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-11-02_final
2022-11-03 10:24:08	ga_ls8c_ard_3-2-1_101072_2022-11-03_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-06 09:22:08	ga_ls8c_ard_3-2-1_090087_2022-11-05_final
2022-11-12 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-11-12_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-27 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-11-27_final
2022-11-30 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-30_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-10 10:41:46	ga_ls8c_ard_3-2-1_104070_2022-12-10_final
2022-12-10 10:44:57	ga_ls8c_ard_3-2-1_104078_2022-12-10_final
2022-12-11 11:24:13	ga_ls8c_ard_3-2-1_111068_2022-12-11_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-13 11:16:14	ga_ls8c_ard_3-2-1_109079_2022-12-13_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-16 10:05:25	ga_ls8c_ard_3-2-1_098072_2022-12-16_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-08 11:52:00	ga_ls8c_ard_3-2-1_115076_2023-01-08_final
2023-01-09 09:19:05	ga_ls8c_ard_3-2-1_090080_2023-01-08_final
2023-01-13 10:30:01	ga_ls8c_ard_3-2-1_102072_2023-01-13_final
2023-01-14 11:17:15	ga_ls8c_ard_3-2-1_109082_2023-01-14_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-01-25 09:18:16	ga_ls8c_ard_3-2-1_090078_2023-01-24_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-01-25 09:22:39	ga_ls8c_ard_3-2-1_090089_2023-01-24_final
2023-01-29 10:31:38	ga_ls8c_ard_3-2-1_102076_2023-01-29_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-05 10:37:01	ga_ls8c_ard_3-2-1_103074_2023-02-05_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-08 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-02-08_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 09:16:42	ga_ls8c_ard_3-2-1_089090_2023-02-18_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_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