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

73 results

Time (local)	Label
2023-12-14 11:25:04	ga_ls8c_ard_3-2-1_111071_2023-12-14_final
2023-12-19 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-12-19_final
2023-12-23 11:21:43	ga_ls8c_ard_3-2-1_110078_2023-12-23_final
2023-12-25 09:34:27	ga_ls8c_ard_3-2-1_092088_2023-12-25_final
2023-12-25 11:11:21	ga_ls8c_ard_3-2-1_108083_2023-12-25_final
2023-12-26 10:10:08	ga_ls8c_ard_3-2-1_099069_2023-12-26_final
2023-12-28 09:57:45	ga_ls8c_ard_3-2-1_097069_2023-12-28_final
2023-12-28 09:58:09	ga_ls8c_ard_3-2-1_097070_2023-12-28_final
2023-12-28 09:58:33	ga_ls8c_ard_3-2-1_097071_2023-12-28_final
2023-12-28 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-12-28_final
2023-12-28 09:59:21	ga_ls8c_ard_3-2-1_097073_2023-12-28_final
2023-12-28 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-12-28_final
2023-12-28 10:00:09	ga_ls8c_ard_3-2-1_097075_2023-12-28_final
2023-12-28 10:00:33	ga_ls8c_ard_3-2-1_097076_2023-12-28_final
2023-12-28 10:00:56	ga_ls8c_ard_3-2-1_097077_2023-12-28_final
2023-12-28 10:01:20	ga_ls8c_ard_3-2-1_097078_2023-12-28_final
2023-12-28 10:01:44	ga_ls8c_ard_3-2-1_097079_2023-12-28_final
2023-12-28 10:03:44	ga_ls8c_ard_3-2-1_097084_2023-12-28_final
2023-12-28 10:04:08	ga_ls8c_ard_3-2-1_097085_2023-12-28_final
2023-12-28 11:38:14	ga_ls8c_ard_3-2-1_113073_2023-12-28_final
2023-12-28 11:38:38	ga_ls8c_ard_3-2-1_113074_2023-12-28_final
2023-12-28 11:39:26	ga_ls8c_ard_3-2-1_113076_2023-12-28_final
2023-12-28 11:40:13	ga_ls8c_ard_3-2-1_113078_2023-12-28_final
2023-12-28 11:41:01	ga_ls8c_ard_3-2-1_113080_2023-12-28_final
2023-12-28 11:41:49	ga_ls8c_ard_3-2-1_113082_2023-12-28_final
2023-12-28 11:42:13	ga_ls8c_ard_3-2-1_113083_2023-12-28_final
2023-12-29 09:06:54	ga_ls8c_ard_3-2-1_088081_2023-12-28_final
2023-12-29 09:07:18	ga_ls8c_ard_3-2-1_088082_2023-12-28_final
2023-12-29 10:41:24	ga_ls8c_ard_3-2-1_104070_2023-12-29_final
2023-12-29 10:41:48	ga_ls8c_ard_3-2-1_104071_2023-12-29_final
2023-12-29 10:43:00	ga_ls8c_ard_3-2-1_104074_2023-12-29_final
2023-12-29 10:44:35	ga_ls8c_ard_3-2-1_104078_2023-12-29_final
2023-12-29 10:44:59	ga_ls8c_ard_3-2-1_104079_2023-12-29_final
2023-12-29 10:45:23	ga_ls8c_ard_3-2-1_104080_2023-12-29_final
2023-12-29 10:45:47	ga_ls8c_ard_3-2-1_104081_2023-12-29_final
2023-12-29 10:46:11	ga_ls8c_ard_3-2-1_104082_2023-12-29_final
2023-12-30 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-12-30_final
2023-12-30 09:46:34	ga_ls8c_ard_3-2-1_095072_2023-12-30_final
2023-12-30 09:46:58	ga_ls8c_ard_3-2-1_095073_2023-12-30_final
2023-12-30 09:47:22	ga_ls8c_ard_3-2-1_095074_2023-12-30_final
2023-12-30 09:47:46	ga_ls8c_ard_3-2-1_095075_2023-12-30_final
2023-12-30 09:48:09	ga_ls8c_ard_3-2-1_095076_2023-12-30_final
2023-12-30 09:48:33	ga_ls8c_ard_3-2-1_095077_2023-12-30_final
2023-12-30 09:48:57	ga_ls8c_ard_3-2-1_095078_2023-12-30_final
2023-12-30 09:49:45	ga_ls8c_ard_3-2-1_095080_2023-12-30_final
2023-12-30 09:50:09	ga_ls8c_ard_3-2-1_095081_2023-12-30_final
2023-12-30 09:50:57	ga_ls8c_ard_3-2-1_095083_2023-12-30_final
2023-12-30 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-12-30_final
2023-12-30 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-12-30_final
2023-12-30 09:52:09	ga_ls8c_ard_3-2-1_095086_2023-12-30_final
2023-12-30 09:52:33	ga_ls8c_ard_3-2-1_095087_2023-12-30_final
2023-12-30 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-12-30_final
2023-12-30 11:24:39	ga_ls8c_ard_3-2-1_111070_2023-12-30_final
2023-12-30 11:25:03	ga_ls8c_ard_3-2-1_111071_2023-12-30_final
2023-12-30 11:25:51	ga_ls8c_ard_3-2-1_111073_2023-12-30_final
2023-12-30 11:26:15	ga_ls8c_ard_3-2-1_111074_2023-12-30_final
2023-12-30 11:26:39	ga_ls8c_ard_3-2-1_111075_2023-12-30_final
2023-12-30 11:27:26	ga_ls8c_ard_3-2-1_111077_2023-12-30_final
2023-12-30 11:27:50	ga_ls8c_ard_3-2-1_111078_2023-12-30_final
2023-12-30 11:28:14	ga_ls8c_ard_3-2-1_111079_2023-12-30_final
2023-12-30 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-12-30_final
2023-12-30 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-12-30_final
2023-12-30 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-12-30_final
2023-12-30 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-12-30_final
2023-12-30 11:30:14	ga_ls8c_ard_3-2-1_111084_2023-12-30_final
2023-12-31 10:28:13	ga_ls8c_ard_3-2-1_102068_2023-12-31_final
2023-12-31 10:28:37	ga_ls8c_ard_3-2-1_102069_2023-12-31_final
2023-12-31 10:29:25	ga_ls8c_ard_3-2-1_102071_2023-12-31_final
2023-12-31 10:30:13	ga_ls8c_ard_3-2-1_102073_2023-12-31_final
2023-12-31 10:30:36	ga_ls8c_ard_3-2-1_102074_2023-12-31_final
2023-12-31 10:32:12	ga_ls8c_ard_3-2-1_102078_2023-12-31_final
2023-12-31 10:33:00	ga_ls8c_ard_3-2-1_102080_2023-12-31_final
2023-12-31 10:33:48	ga_ls8c_ard_3-2-1_102082_2023-12-31_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