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

82 results

Time (local)	Label
2023-10-14 10:17:28	ga_ls8c_ard_3-2-1_100072_2023-10-14_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-14 11:57:57	ga_ls8c_ard_3-2-1_116076_2023-10-14_final
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_final
2023-10-15 09:23:51	ga_ls8c_ard_3-2-1_091077_2023-10-14_final
2023-10-15 09:25:02	ga_ls8c_ard_3-2-1_091080_2023-10-14_final
2023-10-15 09:28:38	ga_ls8c_ard_3-2-1_091089_2023-10-14_final
2023-10-15 09:29:02	ga_ls8c_ard_3-2-1_091090_2023-10-14_final
2023-10-15 10:59:56	ga_ls8c_ard_3-2-1_107070_2023-10-15_final
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_final
2023-10-16 10:03:07	ga_ls8c_ard_3-2-1_098067_2023-10-16_final
2023-10-16 10:03:31	ga_ls8c_ard_3-2-1_098068_2023-10-16_final
2023-10-16 10:04:42	ga_ls8c_ard_3-2-1_098071_2023-10-16_final
2023-10-16 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-10-16_final
2023-10-16 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-10-16_final
2023-10-16 10:07:06	ga_ls8c_ard_3-2-1_098077_2023-10-16_final
2023-10-16 10:09:54	ga_ls8c_ard_3-2-1_098084_2023-10-16_final
2023-10-16 11:45:35	ga_ls8c_ard_3-2-1_114076_2023-10-16_final
2023-10-16 11:46:47	ga_ls8c_ard_3-2-1_114079_2023-10-16_final
2023-10-22 09:27:38	ga_ls8c_ard_3-2-1_092071_2023-10-21_final
2023-10-22 09:28:01	ga_ls8c_ard_3-2-1_092072_2023-10-21_final
2023-10-22 09:28:25	ga_ls8c_ard_3-2-1_092073_2023-10-21_final
2023-10-22 09:29:13	ga_ls8c_ard_3-2-1_092075_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-10-22 09:30:01	ga_ls8c_ard_3-2-1_092077_2023-10-22_final
2023-10-22 09:30:25	ga_ls8c_ard_3-2-1_092078_2023-10-22_final
2023-10-22 09:30:49	ga_ls8c_ard_3-2-1_092079_2023-10-22_final
2023-10-22 09:31:13	ga_ls8c_ard_3-2-1_092080_2023-10-22_final
2023-10-22 09:31:37	ga_ls8c_ard_3-2-1_092081_2023-10-22_final
2023-10-22 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-10-22_final
2023-10-22 09:32:49	ga_ls8c_ard_3-2-1_092084_2023-10-22_final
2023-10-22 09:33:13	ga_ls8c_ard_3-2-1_092085_2023-10-22_final
2023-10-22 09:33:37	ga_ls8c_ard_3-2-1_092086_2023-10-22_final
2023-10-22 09:34:01	ga_ls8c_ard_3-2-1_092087_2023-10-22_final
2023-10-22 09:34:49	ga_ls8c_ard_3-2-1_092089_2023-10-22_final
2023-10-22 11:05:43	ga_ls8c_ard_3-2-1_108069_2023-10-22_final
2023-10-22 11:06:07	ga_ls8c_ard_3-2-1_108070_2023-10-22_final
2023-10-22 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-10-22_final
2023-10-22 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-10-22_final
2023-10-22 11:07:18	ga_ls8c_ard_3-2-1_108073_2023-10-22_final
2023-10-22 11:07:42	ga_ls8c_ard_3-2-1_108074_2023-10-22_final
2023-10-22 11:08:06	ga_ls8c_ard_3-2-1_108075_2023-10-22_final
2023-10-22 11:08:54	ga_ls8c_ard_3-2-1_108077_2023-10-22_final
2023-10-22 11:09:18	ga_ls8c_ard_3-2-1_108078_2023-10-22_final
2023-10-22 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-10-22_final
2023-10-22 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-10-22_final
2023-10-22 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-10-22_final
2023-10-22 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-10-22_final
2023-10-23 10:12:06	ga_ls8c_ard_3-2-1_099074_2023-10-23_final
2023-10-23 10:13:42	ga_ls8c_ard_3-2-1_099078_2023-10-23_final
2023-10-23 10:14:05	ga_ls8c_ard_3-2-1_099079_2023-10-23_final
2023-10-23 10:14:29	ga_ls8c_ard_3-2-1_099080_2023-10-23_final
2023-10-23 10:14:53	ga_ls8c_ard_3-2-1_099081_2023-10-23_final
2023-10-23 10:15:17	ga_ls8c_ard_3-2-1_099082_2023-10-23_final
2023-10-23 10:16:05	ga_ls8c_ard_3-2-1_099084_2023-10-23_final
2023-10-23 10:16:29	ga_ls8c_ard_3-2-1_099085_2023-10-23_final
2023-10-23 11:50:59	ga_ls8c_ard_3-2-1_115074_2023-10-23_final
2023-10-23 11:51:23	ga_ls8c_ard_3-2-1_115075_2023-10-23_final
2023-10-23 11:52:59	ga_ls8c_ard_3-2-1_115079_2023-10-23_final
2023-10-23 11:53:23	ga_ls8c_ard_3-2-1_115080_2023-10-23_final
2023-10-24 09:16:29	ga_ls8c_ard_3-2-1_090074_2023-10-23_final
2023-10-24 09:16:53	ga_ls8c_ard_3-2-1_090075_2023-10-23_final
2023-10-24 09:17:17	ga_ls8c_ard_3-2-1_090076_2023-10-23_final
2023-10-24 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-10-23_final
2023-10-24 09:18:29	ga_ls8c_ard_3-2-1_090079_2023-10-23_final
2023-10-24 09:18:53	ga_ls8c_ard_3-2-1_090080_2023-10-23_final
2023-10-24 09:19:17	ga_ls8c_ard_3-2-1_090081_2023-10-23_final
2023-10-24 09:19:41	ga_ls8c_ard_3-2-1_090082_2023-10-23_final
2023-10-24 09:20:05	ga_ls8c_ard_3-2-1_090083_2023-10-23_final
2023-10-24 09:20:28	ga_ls8c_ard_3-2-1_090084_2023-10-23_final
2023-10-24 09:20:52	ga_ls8c_ard_3-2-1_090085_2023-10-23_final
2023-10-24 09:21:16	ga_ls8c_ard_3-2-1_090086_2023-10-23_final
2023-10-24 09:21:40	ga_ls8c_ard_3-2-1_090087_2023-10-23_final
2023-10-24 09:22:28	ga_ls8c_ard_3-2-1_090089_2023-10-23_final
2023-10-24 09:22:52	ga_ls8c_ard_3-2-1_090090_2023-10-23_final
2023-10-24 10:52:58	ga_ls8c_ard_3-2-1_106068_2023-10-24_final
2023-10-24 10:53:46	ga_ls8c_ard_3-2-1_106070_2023-10-24_final
2023-10-24 10:54:34	ga_ls8c_ard_3-2-1_106072_2023-10-24_final
2023-10-24 10:54:58	ga_ls8c_ard_3-2-1_106073_2023-10-24_final
2023-10-24 10:55:46	ga_ls8c_ard_3-2-1_106075_2023-10-24_final
2023-10-24 10:58:58	ga_ls8c_ard_3-2-1_106083_2023-10-24_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years