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

84 results

Time (local)	Label
2023-04-25 09:55:17	ga_ls8c_ard_3-2-1_096080_2023-04-25_final
2023-04-25 09:56:05	ga_ls8c_ard_3-2-1_096082_2023-04-25_final
2023-04-25 09:56:29	ga_ls8c_ard_3-2-1_096083_2023-04-25_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-04-26 10:36:33	ga_ls8c_ard_3-2-1_103075_2023-04-26_final
2023-04-26 10:37:45	ga_ls8c_ard_3-2-1_103078_2023-04-26_final
2023-04-27 09:40:32	ga_ls8c_ard_3-2-1_094074_2023-04-27_final
2023-04-27 09:40:56	ga_ls8c_ard_3-2-1_094075_2023-04-27_final
2023-04-27 09:42:31	ga_ls8c_ard_3-2-1_094079_2023-04-27_final
2023-04-27 11:17:49	ga_ls8c_ard_3-2-1_110070_2023-04-27_final
2023-04-27 11:21:24	ga_ls8c_ard_3-2-1_110079_2023-04-27_final
2023-04-28 10:24:59	ga_ls8c_ard_3-2-1_101077_2023-04-28_final
2023-04-29 09:27:21	ga_ls8c_ard_3-2-1_092072_2023-04-28_final
2023-04-29 09:30:09	ga_ls8c_ard_3-2-1_092079_2023-04-29_final
2023-04-29 09:30:33	ga_ls8c_ard_3-2-1_092080_2023-04-29_final
2023-04-29 09:30:57	ga_ls8c_ard_3-2-1_092081_2023-04-29_final
2023-04-29 09:31:21	ga_ls8c_ard_3-2-1_092082_2023-04-29_final
2023-04-29 09:31:45	ga_ls8c_ard_3-2-1_092083_2023-04-29_final
2023-04-29 09:32:09	ga_ls8c_ard_3-2-1_092084_2023-04-29_final
2023-04-29 09:32:33	ga_ls8c_ard_3-2-1_092085_2023-04-29_final
2023-04-29 09:32:57	ga_ls8c_ard_3-2-1_092086_2023-04-29_final
2023-04-29 09:33:21	ga_ls8c_ard_3-2-1_092087_2023-04-29_final
2023-04-29 09:33:44	ga_ls8c_ard_3-2-1_092088_2023-04-29_final
2023-04-29 09:34:08	ga_ls8c_ard_3-2-1_092089_2023-04-29_final
2023-04-29 09:34:32	ga_ls8c_ard_3-2-1_092090_2023-04-29_final
2023-04-29 11:05:03	ga_ls8c_ard_3-2-1_108069_2023-04-29_final
2023-04-29 11:05:26	ga_ls8c_ard_3-2-1_108070_2023-04-29_final
2023-04-29 11:05:50	ga_ls8c_ard_3-2-1_108071_2023-04-29_final
2023-04-29 11:06:14	ga_ls8c_ard_3-2-1_108072_2023-04-29_final
2023-04-29 11:06:38	ga_ls8c_ard_3-2-1_108073_2023-04-29_final
2023-04-29 11:07:02	ga_ls8c_ard_3-2-1_108074_2023-04-29_final
2023-04-29 11:07:26	ga_ls8c_ard_3-2-1_108075_2023-04-29_final
2023-04-29 11:07:50	ga_ls8c_ard_3-2-1_108076_2023-04-29_final
2023-04-29 11:08:14	ga_ls8c_ard_3-2-1_108077_2023-04-29_final
2023-04-29 11:08:38	ga_ls8c_ard_3-2-1_108078_2023-04-29_final
2023-04-29 11:09:02	ga_ls8c_ard_3-2-1_108079_2023-04-29_final
2023-04-29 11:09:26	ga_ls8c_ard_3-2-1_108080_2023-04-29_final
2023-04-29 11:09:50	ga_ls8c_ard_3-2-1_108081_2023-04-29_final
2023-04-29 11:10:14	ga_ls8c_ard_3-2-1_108082_2023-04-29_final
2023-04-29 11:10:38	ga_ls8c_ard_3-2-1_108083_2023-04-29_final
2023-04-29 11:11:02	ga_ls8c_ard_3-2-1_108084_2023-04-29_final
2023-04-30 10:08:37	ga_ls8c_ard_3-2-1_099067_2023-04-30_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-04-30 10:09:25	ga_ls8c_ard_3-2-1_099069_2023-04-30_final
2023-04-30 10:09:49	ga_ls8c_ard_3-2-1_099070_2023-04-30_final
2023-04-30 10:10:13	ga_ls8c_ard_3-2-1_099071_2023-04-30_final
2023-04-30 10:10:37	ga_ls8c_ard_3-2-1_099072_2023-04-30_final
2023-04-30 10:11:00	ga_ls8c_ard_3-2-1_099073_2023-04-30_final
2023-04-30 10:11:24	ga_ls8c_ard_3-2-1_099074_2023-04-30_final
2023-04-30 10:11:48	ga_ls8c_ard_3-2-1_099075_2023-04-30_final
2023-04-30 10:12:12	ga_ls8c_ard_3-2-1_099076_2023-04-30_final
2023-04-30 10:12:36	ga_ls8c_ard_3-2-1_099077_2023-04-30_final
2023-04-30 10:13:00	ga_ls8c_ard_3-2-1_099078_2023-04-30_final
2023-04-30 10:13:24	ga_ls8c_ard_3-2-1_099079_2023-04-30_final
2023-04-30 10:13:48	ga_ls8c_ard_3-2-1_099080_2023-04-30_final
2023-04-30 10:14:12	ga_ls8c_ard_3-2-1_099081_2023-04-30_final
2023-04-30 10:14:36	ga_ls8c_ard_3-2-1_099082_2023-04-30_final
2023-04-30 10:15:00	ga_ls8c_ard_3-2-1_099083_2023-04-30_final
2023-04-30 10:15:24	ga_ls8c_ard_3-2-1_099084_2023-04-30_final
2023-04-30 10:15:48	ga_ls8c_ard_3-2-1_099085_2023-04-30_final
2023-04-30 11:50:17	ga_ls8c_ard_3-2-1_115074_2023-04-30_final
2023-04-30 11:50:41	ga_ls8c_ard_3-2-1_115075_2023-04-30_final
2023-04-30 11:51:05	ga_ls8c_ard_3-2-1_115076_2023-04-30_final
2023-04-30 11:51:29	ga_ls8c_ard_3-2-1_115077_2023-04-30_final
2023-04-30 11:51:53	ga_ls8c_ard_3-2-1_115078_2023-04-30_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-01 09:15:47	ga_ls8c_ard_3-2-1_090074_2023-04-30_final
2023-05-01 09:16:10	ga_ls8c_ard_3-2-1_090075_2023-04-30_final
2023-05-01 09:16:34	ga_ls8c_ard_3-2-1_090076_2023-04-30_final
2023-05-01 09:16:58	ga_ls8c_ard_3-2-1_090077_2023-04-30_final
2023-05-01 09:17:22	ga_ls8c_ard_3-2-1_090078_2023-04-30_final
2023-05-01 09:17:46	ga_ls8c_ard_3-2-1_090079_2023-04-30_final
2023-05-01 09:18:10	ga_ls8c_ard_3-2-1_090080_2023-04-30_final
2023-05-01 09:18:34	ga_ls8c_ard_3-2-1_090081_2023-04-30_final
2023-05-01 09:18:58	ga_ls8c_ard_3-2-1_090082_2023-04-30_final
2023-05-01 09:19:22	ga_ls8c_ard_3-2-1_090083_2023-04-30_final
2023-05-01 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-04-30_final
2023-05-01 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-04-30_final
2023-05-01 09:20:34	ga_ls8c_ard_3-2-1_090086_2023-04-30_final
2023-05-01 09:20:58	ga_ls8c_ard_3-2-1_090087_2023-04-30_final
2023-05-01 09:21:22	ga_ls8c_ard_3-2-1_090088_2023-04-30_final
2023-05-01 09:21:46	ga_ls8c_ard_3-2-1_090089_2023-04-30_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_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