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

83 results

Time (local)	Label
2022-07-26 10:46:34	ga_ls8c_ard_3-2-1_105067_2022-07-26_final
2022-07-26 10:47:22	ga_ls8c_ard_3-2-1_105069_2022-07-26_final
2022-07-26 10:48:58	ga_ls8c_ard_3-2-1_105073_2022-07-26_final
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-27 09:54:57	ga_ls8c_ard_3-2-1_096077_2022-07-27_final
2022-07-27 09:57:21	ga_ls8c_ard_3-2-1_096083_2022-07-27_final
2022-07-27 09:58:33	ga_ls8c_ard_3-2-1_096086_2022-07-27_final
2022-07-27 11:35:02	ga_ls8c_ard_3-2-1_112080_2022-07-27_final
2022-07-28 10:35:50	ga_ls8c_ard_3-2-1_103071_2022-07-28_final
2022-07-29 09:40:13	ga_ls8c_ard_3-2-1_094071_2022-07-29_final
2022-07-29 09:40:37	ga_ls8c_ard_3-2-1_094072_2022-07-29_final
2022-07-29 09:41:25	ga_ls8c_ard_3-2-1_094074_2022-07-29_final
2022-07-29 09:41:49	ga_ls8c_ard_3-2-1_094075_2022-07-29_final
2022-07-29 09:42:13	ga_ls8c_ard_3-2-1_094076_2022-07-29_final
2022-07-29 09:42:37	ga_ls8c_ard_3-2-1_094077_2022-07-29_final
2022-07-29 09:43:01	ga_ls8c_ard_3-2-1_094078_2022-07-29_final
2022-07-29 09:43:25	ga_ls8c_ard_3-2-1_094079_2022-07-29_final
2022-07-29 09:43:48	ga_ls8c_ard_3-2-1_094080_2022-07-29_final
2022-07-29 09:44:12	ga_ls8c_ard_3-2-1_094081_2022-07-29_final
2022-07-29 09:44:36	ga_ls8c_ard_3-2-1_094082_2022-07-29_final
2022-07-29 09:45:00	ga_ls8c_ard_3-2-1_094083_2022-07-29_final
2022-07-29 09:45:24	ga_ls8c_ard_3-2-1_094084_2022-07-29_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-07-29 09:46:12	ga_ls8c_ard_3-2-1_094086_2022-07-29_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-07-29 11:19:06	ga_ls8c_ard_3-2-1_110071_2022-07-29_final
2022-07-29 11:19:30	ga_ls8c_ard_3-2-1_110072_2022-07-29_final
2022-07-29 11:19:54	ga_ls8c_ard_3-2-1_110073_2022-07-29_final
2022-07-29 11:20:18	ga_ls8c_ard_3-2-1_110074_2022-07-29_final
2022-07-29 11:20:42	ga_ls8c_ard_3-2-1_110075_2022-07-29_final
2022-07-29 11:21:30	ga_ls8c_ard_3-2-1_110077_2022-07-29_final
2022-07-29 11:21:54	ga_ls8c_ard_3-2-1_110078_2022-07-29_final
2022-07-29 11:22:18	ga_ls8c_ard_3-2-1_110079_2022-07-29_final
2022-07-29 11:22:42	ga_ls8c_ard_3-2-1_110080_2022-07-29_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-07-29 11:23:53	ga_ls8c_ard_3-2-1_110083_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-07-30 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-07-30_final
2022-07-30 10:23:29	ga_ls8c_ard_3-2-1_101071_2022-07-30_final
2022-07-30 10:23:53	ga_ls8c_ard_3-2-1_101072_2022-07-30_final
2022-07-30 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-07-30_final
2022-07-30 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-07-30_final
2022-07-30 10:25:05	ga_ls8c_ard_3-2-1_101075_2022-07-30_final
2022-07-30 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-07-30_final
2022-07-30 10:25:53	ga_ls8c_ard_3-2-1_101077_2022-07-30_final
2022-07-30 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-07-30_final
2022-07-30 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-07-30_final
2022-07-30 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-07-30_final
2022-07-31 09:27:53	ga_ls8c_ard_3-2-1_092071_2022-07-30_final
2022-07-31 09:28:40	ga_ls8c_ard_3-2-1_092073_2022-07-30_final
2022-07-31 09:29:04	ga_ls8c_ard_3-2-1_092074_2022-07-30_final
2022-07-31 09:29:28	ga_ls8c_ard_3-2-1_092075_2022-07-30_final
2022-07-31 09:29:52	ga_ls8c_ard_3-2-1_092076_2022-07-30_final
2022-07-31 09:30:16	ga_ls8c_ard_3-2-1_092077_2022-07-31_final
2022-07-31 09:30:40	ga_ls8c_ard_3-2-1_092078_2022-07-31_final
2022-07-31 09:31:04	ga_ls8c_ard_3-2-1_092079_2022-07-31_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-07-31 09:31:52	ga_ls8c_ard_3-2-1_092081_2022-07-31_final
2022-07-31 09:33:04	ga_ls8c_ard_3-2-1_092084_2022-07-31_final
2022-07-31 09:33:28	ga_ls8c_ard_3-2-1_092085_2022-07-31_final
2022-07-31 09:33:52	ga_ls8c_ard_3-2-1_092086_2022-07-31_final
2022-07-31 09:34:16	ga_ls8c_ard_3-2-1_092087_2022-07-31_final
2022-07-31 09:34:40	ga_ls8c_ard_3-2-1_092088_2022-07-31_final
2022-07-31 09:35:04	ga_ls8c_ard_3-2-1_092089_2022-07-31_final
2022-07-31 11:06:22	ga_ls8c_ard_3-2-1_108070_2022-07-31_final
2022-07-31 11:06:46	ga_ls8c_ard_3-2-1_108071_2022-07-31_final
2022-07-31 11:07:10	ga_ls8c_ard_3-2-1_108072_2022-07-31_final
2022-07-31 11:07:34	ga_ls8c_ard_3-2-1_108073_2022-07-31_final
2022-07-31 11:07:57	ga_ls8c_ard_3-2-1_108074_2022-07-31_final
2022-07-31 11:08:21	ga_ls8c_ard_3-2-1_108075_2022-07-31_final
2022-07-31 11:08:45	ga_ls8c_ard_3-2-1_108076_2022-07-31_final
2022-07-31 11:09:09	ga_ls8c_ard_3-2-1_108077_2022-07-31_final
2022-07-31 11:09:33	ga_ls8c_ard_3-2-1_108078_2022-07-31_final
2022-07-31 11:09:57	ga_ls8c_ard_3-2-1_108079_2022-07-31_final
2022-07-31 11:10:21	ga_ls8c_ard_3-2-1_108080_2022-07-31_final
2022-07-31 11:10:45	ga_ls8c_ard_3-2-1_108081_2022-07-31_final
2022-07-31 11:11:09	ga_ls8c_ard_3-2-1_108082_2022-07-31_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-14 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-08-14_final
2022-08-18 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-08-18_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