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
2022-01-20 09:30:03	ga_ls8c_ard_3-2-1_092077_2022-01-20_final
2022-01-20 09:31:39	ga_ls8c_ard_3-2-1_092081_2022-01-20_final
2022-01-20 11:08:56	ga_ls8c_ard_3-2-1_108077_2022-01-20_final
2022-01-20 11:09:20	ga_ls8c_ard_3-2-1_108078_2022-01-20_final
2022-01-20 11:09:44	ga_ls8c_ard_3-2-1_108079_2022-01-20_final
2022-01-20 11:10:08	ga_ls8c_ard_3-2-1_108080_2022-01-20_final
2022-01-20 11:10:32	ga_ls8c_ard_3-2-1_108081_2022-01-20_final
2022-01-20 11:11:20	ga_ls8c_ard_3-2-1_108083_2022-01-20_final
2022-01-20 11:11:44	ga_ls8c_ard_3-2-1_108084_2022-01-20_final
2022-01-21 10:09:43	ga_ls8c_ard_3-2-1_099068_2022-01-21_final
2022-01-21 10:10:07	ga_ls8c_ard_3-2-1_099069_2022-01-21_final
2022-01-21 10:10:31	ga_ls8c_ard_3-2-1_099070_2022-01-21_final
2022-01-21 11:52:59	ga_ls8c_ard_3-2-1_115079_2022-01-21_final
2022-01-22 09:21:40	ga_ls8c_ard_3-2-1_090087_2022-01-21_final
2022-01-22 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-01-21_final
2022-01-22 09:22:28	ga_ls8c_ard_3-2-1_090089_2022-01-21_final
2022-01-22 09:22:52	ga_ls8c_ard_3-2-1_090090_2022-01-21_final
2022-01-22 10:53:46	ga_ls8c_ard_3-2-1_106070_2022-01-22_final
2022-01-22 10:54:34	ga_ls8c_ard_3-2-1_106072_2022-01-22_final
2022-01-22 10:54:58	ga_ls8c_ard_3-2-1_106073_2022-01-22_final
2022-01-22 10:55:22	ga_ls8c_ard_3-2-1_106074_2022-01-22_final
2022-01-22 10:55:46	ga_ls8c_ard_3-2-1_106075_2022-01-22_final
2022-01-22 10:56:10	ga_ls8c_ard_3-2-1_106076_2022-01-22_final
2022-01-23 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-01-23_final
2022-01-23 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-01-23_final
2022-01-23 10:02:08	ga_ls8c_ard_3-2-1_097080_2022-01-23_final
2022-01-23 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-01-23_final
2022-01-23 10:02:56	ga_ls8c_ard_3-2-1_097082_2022-01-23_final
2022-01-23 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-01-23_final
2022-01-23 11:40:37	ga_ls8c_ard_3-2-1_113079_2022-01-23_final
2022-01-23 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-01-23_final
2022-01-23 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-01-23_final
2022-01-23 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-01-23_final
2022-01-24 09:06:30	ga_ls8c_ard_3-2-1_088080_2022-01-23_final
2022-01-24 10:45:23	ga_ls8c_ard_3-2-1_104080_2022-01-24_final
2022-01-24 10:45:47	ga_ls8c_ard_3-2-1_104081_2022-01-24_final
2022-01-24 10:46:11	ga_ls8c_ard_3-2-1_104082_2022-01-24_final
2022-01-25 09:47:22	ga_ls8c_ard_3-2-1_095074_2022-01-25_final
2022-01-25 09:47:46	ga_ls8c_ard_3-2-1_095075_2022-01-25_final
2022-01-25 09:48:09	ga_ls8c_ard_3-2-1_095076_2022-01-25_final
2022-01-25 09:48:57	ga_ls8c_ard_3-2-1_095078_2022-01-25_final
2022-01-25 09:49:21	ga_ls8c_ard_3-2-1_095079_2022-01-25_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-01-25 09:52:09	ga_ls8c_ard_3-2-1_095086_2022-01-25_final
2022-01-25 11:24:15	ga_ls8c_ard_3-2-1_111069_2022-01-25_final
2022-01-25 11:24:39	ga_ls8c_ard_3-2-1_111070_2022-01-25_final
2022-01-26 10:29:01	ga_ls8c_ard_3-2-1_102070_2022-01-26_final
2022-01-26 10:30:37	ga_ls8c_ard_3-2-1_102074_2022-01-26_final
2022-01-26 10:31:01	ga_ls8c_ard_3-2-1_102075_2022-01-26_final
2022-01-26 10:31:25	ga_ls8c_ard_3-2-1_102076_2022-01-26_final
2022-01-26 10:31:49	ga_ls8c_ard_3-2-1_102077_2022-01-26_final
2022-01-26 10:32:13	ga_ls8c_ard_3-2-1_102078_2022-01-26_final
2022-01-26 10:33:00	ga_ls8c_ard_3-2-1_102080_2022-01-26_final
2022-01-26 10:33:24	ga_ls8c_ard_3-2-1_102081_2022-01-26_final
2022-01-27 09:34:35	ga_ls8c_ard_3-2-1_093073_2022-01-27_final
2022-01-27 09:35:23	ga_ls8c_ard_3-2-1_093075_2022-01-27_final
2022-01-27 09:35:47	ga_ls8c_ard_3-2-1_093076_2022-01-27_final
2022-01-27 09:37:23	ga_ls8c_ard_3-2-1_093080_2022-01-27_final
2022-01-28 10:17:02	ga_ls8c_ard_3-2-1_100071_2022-01-28_final
2022-01-28 10:17:26	ga_ls8c_ard_3-2-1_100072_2022-01-28_final
2022-01-28 10:18:38	ga_ls8c_ard_3-2-1_100075_2022-01-28_final
2022-01-28 11:57:55	ga_ls8c_ard_3-2-1_116076_2022-01-28_final
2022-01-28 11:58:19	ga_ls8c_ard_3-2-1_116077_2022-01-28_final
2022-01-29 09:21:49	ga_ls8c_ard_3-2-1_091072_2022-01-28_final
2022-01-29 09:22:37	ga_ls8c_ard_3-2-1_091074_2022-01-28_final
2022-01-29 09:23:25	ga_ls8c_ard_3-2-1_091076_2022-01-28_final
2022-01-29 11:02:18	ga_ls8c_ard_3-2-1_107076_2022-01-29_final
2022-01-29 11:02:42	ga_ls8c_ard_3-2-1_107077_2022-01-29_final
2022-01-29 11:03:06	ga_ls8c_ard_3-2-1_107078_2022-01-29_final
2022-01-29 11:03:30	ga_ls8c_ard_3-2-1_107079_2022-01-29_final
2022-01-30 10:03:53	ga_ls8c_ard_3-2-1_098069_2022-01-30_final
2022-01-30 10:04:17	ga_ls8c_ard_3-2-1_098070_2022-01-30_final
2022-01-30 10:04:41	ga_ls8c_ard_3-2-1_098071_2022-01-30_final
2022-01-30 10:05:05	ga_ls8c_ard_3-2-1_098072_2022-01-30_final
2022-01-30 10:10:16	ga_ls8c_ard_3-2-1_098085_2022-01-30_final
2022-01-30 11:44:46	ga_ls8c_ard_3-2-1_114074_2022-01-30_final
2022-01-30 11:45:10	ga_ls8c_ard_3-2-1_114075_2022-01-30_final
2022-01-30 11:45:34	ga_ls8c_ard_3-2-1_114076_2022-01-30_final
2022-01-30 11:45:58	ga_ls8c_ard_3-2-1_114077_2022-01-30_final
2022-01-30 11:46:46	ga_ls8c_ard_3-2-1_114079_2022-01-30_final
2022-01-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2022-01-30_final
2022-01-30 11:47:33	ga_ls8c_ard_3-2-1_114081_2022-01-30_final
2022-01-31 09:14:15	ga_ls8c_ard_3-2-1_089084_2022-01-30_final
2022-01-31 09:14:39	ga_ls8c_ard_3-2-1_089085_2022-01-30_final
2022-01-31 09:16:15	ga_ls8c_ard_3-2-1_089089_2022-01-30_final
2022-01-31 09:16:39	ga_ls8c_ard_3-2-1_089090_2022-01-30_final
2022-01-31 10:46:21	ga_ls8c_ard_3-2-1_105067_2022-01-31_final
2022-01-31 10:46:45	ga_ls8c_ard_3-2-1_105068_2022-01-31_final
2022-01-31 10:47:57	ga_ls8c_ard_3-2-1_105071_2022-01-31_final
2022-01-31 10:49:08	ga_ls8c_ard_3-2-1_105074_2022-01-31_final
2022-02-01 09:55:55	ga_ls8c_ard_3-2-1_096080_2022-02-01_final
2022-02-01 09:56:19	ga_ls8c_ard_3-2-1_096081_2022-02-01_final
2022-02-01 09:56:43	ga_ls8c_ard_3-2-1_096082_2022-02-01_final
2022-02-01 09:57:07	ga_ls8c_ard_3-2-1_096083_2022-02-01_final
2022-02-01 09:57:31	ga_ls8c_ard_3-2-1_096084_2022-02-01_final
2022-02-01 09:57:55	ga_ls8c_ard_3-2-1_096085_2022-02-01_final
2022-02-01 11:31:36	ga_ls8c_ard_3-2-1_112072_2022-02-01_final
2022-02-01 11:32:24	ga_ls8c_ard_3-2-1_112074_2022-02-01_final
2022-02-01 11:32:48	ga_ls8c_ard_3-2-1_112075_2022-02-01_final
2022-02-01 11:33:12	ga_ls8c_ard_3-2-1_112076_2022-02-01_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