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
2022-02-18 10:35:30	ga_ls8c_ard_3-2-1_103071_2022-02-18_final
2022-02-18 10:35:54	ga_ls8c_ard_3-2-1_103072_2022-02-18_final
2022-02-18 10:36:41	ga_ls8c_ard_3-2-1_103074_2022-02-18_final
2022-02-18 10:37:05	ga_ls8c_ard_3-2-1_103075_2022-02-18_final
2022-02-18 10:37:29	ga_ls8c_ard_3-2-1_103076_2022-02-18_final
2022-02-18 10:37:53	ga_ls8c_ard_3-2-1_103077_2022-02-18_final
2022-02-18 10:38:17	ga_ls8c_ard_3-2-1_103078_2022-02-18_final
2022-02-18 10:39:29	ga_ls8c_ard_3-2-1_103081_2022-02-18_final
2022-02-18 10:39:53	ga_ls8c_ard_3-2-1_103082_2022-02-18_final
2022-02-19 09:41:51	ga_ls8c_ard_3-2-1_094076_2022-02-19_final
2022-02-19 09:43:51	ga_ls8c_ard_3-2-1_094081_2022-02-19_final
2022-02-19 09:45:03	ga_ls8c_ard_3-2-1_094084_2022-02-19_final
2022-02-19 09:45:27	ga_ls8c_ard_3-2-1_094085_2022-02-19_final
2022-02-19 09:45:51	ga_ls8c_ard_3-2-1_094086_2022-02-19_final
2022-02-19 11:18:21	ga_ls8c_ard_3-2-1_110070_2022-02-19_final
2022-02-19 11:19:57	ga_ls8c_ard_3-2-1_110074_2022-02-19_final
2022-02-19 11:20:21	ga_ls8c_ard_3-2-1_110075_2022-02-19_final
2022-02-19 11:21:08	ga_ls8c_ard_3-2-1_110077_2022-02-19_final
2022-02-19 11:21:56	ga_ls8c_ard_3-2-1_110079_2022-02-19_final
2022-02-19 11:22:20	ga_ls8c_ard_3-2-1_110080_2022-02-19_final
2022-02-19 11:22:44	ga_ls8c_ard_3-2-1_110081_2022-02-19_final
2022-02-19 11:23:08	ga_ls8c_ard_3-2-1_110082_2022-02-19_final
2022-02-19 11:23:56	ga_ls8c_ard_3-2-1_110084_2022-02-19_final
2022-02-21 09:29:05	ga_ls8c_ard_3-2-1_092075_2022-02-20_final
2022-02-21 09:29:29	ga_ls8c_ard_3-2-1_092076_2022-02-20_final
2022-02-21 09:30:17	ga_ls8c_ard_3-2-1_092078_2022-02-21_final
2022-02-21 09:30:41	ga_ls8c_ard_3-2-1_092079_2022-02-21_final
2022-02-21 09:31:05	ga_ls8c_ard_3-2-1_092080_2022-02-21_final
2022-02-21 09:31:29	ga_ls8c_ard_3-2-1_092081_2022-02-21_final
2022-02-21 09:31:53	ga_ls8c_ard_3-2-1_092082_2022-02-21_final
2022-02-21 09:32:17	ga_ls8c_ard_3-2-1_092083_2022-02-21_final
2022-02-21 09:32:41	ga_ls8c_ard_3-2-1_092084_2022-02-21_final
2022-02-21 09:33:05	ga_ls8c_ard_3-2-1_092085_2022-02-21_final
2022-02-21 09:33:29	ga_ls8c_ard_3-2-1_092086_2022-02-21_final
2022-02-21 09:33:53	ga_ls8c_ard_3-2-1_092087_2022-02-21_final
2022-02-21 09:34:17	ga_ls8c_ard_3-2-1_092088_2022-02-21_final
2022-02-21 09:34:41	ga_ls8c_ard_3-2-1_092089_2022-02-21_final
2022-02-21 09:35:04	ga_ls8c_ard_3-2-1_092090_2022-02-21_final
2022-02-21 11:05:59	ga_ls8c_ard_3-2-1_108070_2022-02-21_final
2022-02-21 11:06:22	ga_ls8c_ard_3-2-1_108071_2022-02-21_final
2022-02-21 11:06:46	ga_ls8c_ard_3-2-1_108072_2022-02-21_final
2022-02-21 11:07:10	ga_ls8c_ard_3-2-1_108073_2022-02-21_final
2022-02-21 11:07:34	ga_ls8c_ard_3-2-1_108074_2022-02-21_final
2022-02-21 11:07:58	ga_ls8c_ard_3-2-1_108075_2022-02-21_final
2022-02-21 11:08:22	ga_ls8c_ard_3-2-1_108076_2022-02-21_final
2022-02-21 11:08:46	ga_ls8c_ard_3-2-1_108077_2022-02-21_final
2022-02-21 11:09:10	ga_ls8c_ard_3-2-1_108078_2022-02-21_final
2022-02-21 11:09:34	ga_ls8c_ard_3-2-1_108079_2022-02-21_final
2022-02-21 11:09:58	ga_ls8c_ard_3-2-1_108080_2022-02-21_final
2022-02-21 11:10:22	ga_ls8c_ard_3-2-1_108081_2022-02-21_final
2022-02-21 11:10:46	ga_ls8c_ard_3-2-1_108082_2022-02-21_final
2022-02-21 11:11:10	ga_ls8c_ard_3-2-1_108083_2022-02-21_final
2022-02-21 11:11:34	ga_ls8c_ard_3-2-1_108084_2022-02-21_final
2022-02-22 10:09:09	ga_ls8c_ard_3-2-1_099067_2022-02-22_final
2022-02-22 10:09:33	ga_ls8c_ard_3-2-1_099068_2022-02-22_final
2022-02-22 10:10:21	ga_ls8c_ard_3-2-1_099070_2022-02-22_final
2022-02-22 10:10:45	ga_ls8c_ard_3-2-1_099071_2022-02-22_final
2022-02-22 10:11:33	ga_ls8c_ard_3-2-1_099073_2022-02-22_final
2022-02-22 10:15:56	ga_ls8c_ard_3-2-1_099084_2022-02-22_final
2022-02-22 11:50:50	ga_ls8c_ard_3-2-1_115074_2022-02-22_final
2022-02-22 11:51:14	ga_ls8c_ard_3-2-1_115075_2022-02-22_final
2022-02-22 11:52:02	ga_ls8c_ard_3-2-1_115077_2022-02-22_final
2022-02-23 09:16:20	ga_ls8c_ard_3-2-1_090074_2022-02-22_final
2022-02-23 09:16:44	ga_ls8c_ard_3-2-1_090075_2022-02-22_final
2022-02-23 09:17:08	ga_ls8c_ard_3-2-1_090076_2022-02-22_final
2022-02-23 09:19:07	ga_ls8c_ard_3-2-1_090081_2022-02-22_final
2022-02-23 09:21:31	ga_ls8c_ard_3-2-1_090087_2022-02-22_final
2022-02-23 09:21:55	ga_ls8c_ard_3-2-1_090088_2022-02-22_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