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

68 results

Time (local)	Label
2020-10-14 10:09:28	ga_ls8c_ard_3-1-0_099067_2020-10-14_final
2020-10-14 10:10:16	ga_ls8c_ard_3-1-0_099069_2020-10-14_final
2020-10-14 10:10:40	ga_ls8c_ard_3-1-0_099070_2020-10-14_final
2020-10-14 10:11:04	ga_ls8c_ard_3-1-0_099071_2020-10-14_final
2020-10-14 10:11:28	ga_ls8c_ard_3-1-0_099072_2020-10-14_final
2020-10-14 10:11:51	ga_ls8c_ard_3-1-0_099073_2020-10-14_final
2020-10-14 10:12:15	ga_ls8c_ard_3-1-0_099074_2020-10-14_final
2020-10-14 10:12:39	ga_ls8c_ard_3-1-0_099075_2020-10-14_final
2020-10-14 10:13:27	ga_ls8c_ard_3-1-0_099077_2020-10-14_final
2020-10-14 10:13:51	ga_ls8c_ard_3-1-0_099078_2020-10-14_final
2020-10-14 10:15:27	ga_ls8c_ard_3-1-0_099082_2020-10-14_final
2020-10-14 10:16:15	ga_ls8c_ard_3-1-0_099084_2020-10-14_final
2020-10-14 10:16:39	ga_ls8c_ard_3-1-0_099085_2020-10-14_final
2020-10-15 09:18:38	ga_ls8c_ard_3-1-0_090079_2020-10-14_final
2020-10-15 09:19:26	ga_ls8c_ard_3-1-0_090081_2020-10-14_final
2020-10-15 09:19:50	ga_ls8c_ard_3-1-0_090082_2020-10-14_final
2020-10-16 10:02:17	ga_ls8c_ard_3-1-0_097080_2020-10-16_final
2020-10-16 10:02:41	ga_ls8c_ard_3-1-0_097081_2020-10-16_final
2020-10-16 10:04:41	ga_ls8c_ard_3-1-0_097086_2020-10-16_final
2020-10-17 09:06:40	ga_ls8c_ard_3-1-0_088080_2020-10-16_final
2020-10-17 10:40:46	ga_ls8c_ard_3-1-0_104068_2020-10-17_final
2020-10-17 10:41:10	ga_ls8c_ard_3-1-0_104069_2020-10-17_final
2020-10-17 10:41:34	ga_ls8c_ard_3-1-0_104070_2020-10-17_final
2020-10-17 10:41:58	ga_ls8c_ard_3-1-0_104071_2020-10-17_final
2020-10-17 10:42:22	ga_ls8c_ard_3-1-0_104072_2020-10-17_final
2020-10-17 10:42:46	ga_ls8c_ard_3-1-0_104073_2020-10-17_final
2020-10-17 10:43:10	ga_ls8c_ard_3-1-0_104074_2020-10-17_final
2020-10-17 10:43:33	ga_ls8c_ard_3-1-0_104075_2020-10-17_final
2020-10-17 10:44:21	ga_ls8c_ard_3-1-0_104077_2020-10-17_final
2020-10-17 10:44:45	ga_ls8c_ard_3-1-0_104078_2020-10-17_final
2020-10-17 10:45:09	ga_ls8c_ard_3-1-0_104079_2020-10-17_final
2020-10-17 10:45:33	ga_ls8c_ard_3-1-0_104080_2020-10-17_final
2020-10-18 09:44:45	ga_ls8c_ard_3-1-0_095067_2020-10-18_final
2020-10-18 09:45:57	ga_ls8c_ard_3-1-0_095070_2020-10-18_final
2020-10-18 09:46:44	ga_ls8c_ard_3-1-0_095072_2020-10-18_final
2020-10-18 09:47:32	ga_ls8c_ard_3-1-0_095074_2020-10-18_final
2020-10-18 09:47:56	ga_ls8c_ard_3-1-0_095075_2020-10-18_final
2020-10-18 09:51:32	ga_ls8c_ard_3-1-0_095084_2020-10-18_final
2020-10-18 09:52:44	ga_ls8c_ard_3-1-0_095087_2020-10-18_final
2020-10-18 09:53:08	ga_ls8c_ard_3-1-0_095088_2020-10-18_final
2020-10-19 10:28:00	ga_ls8c_ard_3-1-0_102067_2020-10-19_final
2020-10-19 10:28:24	ga_ls8c_ard_3-1-0_102068_2020-10-19_final
2020-10-19 10:28:48	ga_ls8c_ard_3-1-0_102069_2020-10-19_final
2020-10-19 10:29:36	ga_ls8c_ard_3-1-0_102071_2020-10-19_final
2020-10-19 10:30:00	ga_ls8c_ard_3-1-0_102072_2020-10-19_final
2020-10-19 10:30:24	ga_ls8c_ard_3-1-0_102073_2020-10-19_final
2020-10-19 10:30:48	ga_ls8c_ard_3-1-0_102074_2020-10-19_final
2020-10-19 10:31:12	ga_ls8c_ard_3-1-0_102075_2020-10-19_final
2020-10-19 10:31:36	ga_ls8c_ard_3-1-0_102076_2020-10-19_final
2020-10-19 10:32:00	ga_ls8c_ard_3-1-0_102077_2020-10-19_final
2020-10-19 10:32:24	ga_ls8c_ard_3-1-0_102078_2020-10-19_final
2020-10-19 10:32:48	ga_ls8c_ard_3-1-0_102079_2020-10-19_final
2020-10-19 10:33:12	ga_ls8c_ard_3-1-0_102080_2020-10-19_final
2020-10-19 10:33:59	ga_ls8c_ard_3-1-0_102082_2020-10-19_final
2020-10-20 09:37:58	ga_ls8c_ard_3-1-0_093081_2020-10-20_final
2020-10-20 09:38:46	ga_ls8c_ard_3-1-0_093083_2020-10-20_final
2020-10-20 09:39:10	ga_ls8c_ard_3-1-0_093084_2020-10-20_final
2020-10-20 09:39:58	ga_ls8c_ard_3-1-0_093086_2020-10-20_final
2020-10-20 09:40:22	ga_ls8c_ard_3-1-0_093087_2020-10-20_final
2020-10-20 09:40:46	ga_ls8c_ard_3-1-0_093088_2020-10-20_final
2020-10-21 10:15:39	ga_ls8c_ard_3-1-0_100067_2020-10-21_final
2020-10-21 10:16:03	ga_ls8c_ard_3-1-0_100068_2020-10-21_final
2020-10-21 10:16:51	ga_ls8c_ard_3-1-0_100070_2020-10-21_final
2020-10-21 10:17:14	ga_ls8c_ard_3-1-0_100071_2020-10-21_final
2020-10-21 10:17:38	ga_ls8c_ard_3-1-0_100072_2020-10-21_final
2020-10-21 10:18:26	ga_ls8c_ard_3-1-0_100074_2020-10-21_final
2020-10-21 10:21:38	ga_ls8c_ard_3-1-0_100082_2020-10-21_final
2020-10-21 10:22:50	ga_ls8c_ard_3-1-0_100085_2020-10-21_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