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

99 results

Time (local)	Label
2021-10-16 09:26:18	ga_ls8c_ard_3-2-0_092067_2021-10-15_final
2021-10-16 09:26:41	ga_ls8c_ard_3-2-0_092068_2021-10-15_final
2021-10-16 09:27:53	ga_ls8c_ard_3-2-0_092071_2021-10-15_final
2021-10-16 09:28:17	ga_ls8c_ard_3-2-0_092072_2021-10-15_final
2021-10-16 09:28:41	ga_ls8c_ard_3-2-0_092073_2021-10-15_final
2021-10-16 09:29:05	ga_ls8c_ard_3-2-0_092074_2021-10-15_final
2021-10-16 09:29:29	ga_ls8c_ard_3-2-0_092075_2021-10-15_final
2021-10-16 09:29:53	ga_ls8c_ard_3-2-0_092076_2021-10-15_final
2021-10-16 09:30:17	ga_ls8c_ard_3-2-0_092077_2021-10-16_final
2021-10-16 09:30:41	ga_ls8c_ard_3-2-0_092078_2021-10-16_final
2021-10-16 09:31:05	ga_ls8c_ard_3-2-0_092079_2021-10-16_final
2021-10-16 09:31:29	ga_ls8c_ard_3-2-0_092080_2021-10-16_final
2021-10-16 09:31:53	ga_ls8c_ard_3-2-0_092081_2021-10-16_final
2021-10-16 09:32:17	ga_ls8c_ard_3-2-0_092082_2021-10-16_final
2021-10-16 09:32:41	ga_ls8c_ard_3-2-0_092083_2021-10-16_final
2021-10-16 09:33:04	ga_ls8c_ard_3-2-0_092084_2021-10-16_final
2021-10-16 09:33:28	ga_ls8c_ard_3-2-0_092085_2021-10-16_final
2021-10-16 09:33:52	ga_ls8c_ard_3-2-0_092086_2021-10-16_final
2021-10-16 09:34:16	ga_ls8c_ard_3-2-0_092087_2021-10-16_final
2021-10-16 09:34:40	ga_ls8c_ard_3-2-0_092088_2021-10-16_final
2021-10-16 09:35:04	ga_ls8c_ard_3-2-0_092089_2021-10-16_final
2021-10-16 09:35:28	ga_ls8c_ard_3-2-0_092090_2021-10-16_final
2021-10-16 11:05:11	ga_ls8c_ard_3-2-0_108067_2021-10-16_final
2021-10-16 11:05:34	ga_ls8c_ard_3-2-0_108068_2021-10-16_final
2021-10-16 11:05:58	ga_ls8c_ard_3-2-0_108069_2021-10-16_final
2021-10-16 11:06:22	ga_ls8c_ard_3-2-0_108070_2021-10-16_final
2021-10-16 11:06:46	ga_ls8c_ard_3-2-0_108071_2021-10-16_final
2021-10-16 11:07:10	ga_ls8c_ard_3-2-0_108072_2021-10-16_final
2021-10-16 11:07:34	ga_ls8c_ard_3-2-0_108073_2021-10-16_final
2021-10-16 11:07:58	ga_ls8c_ard_3-2-0_108074_2021-10-16_final
2021-10-16 11:08:22	ga_ls8c_ard_3-2-0_108075_2021-10-16_final
2021-10-16 11:08:46	ga_ls8c_ard_3-2-0_108076_2021-10-16_final
2021-10-16 11:09:10	ga_ls8c_ard_3-2-0_108077_2021-10-16_final
2021-10-16 11:09:34	ga_ls8c_ard_3-2-0_108078_2021-10-16_final
2021-10-16 11:09:58	ga_ls8c_ard_3-2-0_108079_2021-10-16_final
2021-10-16 11:10:22	ga_ls8c_ard_3-2-0_108080_2021-10-16_final
2021-10-16 11:10:46	ga_ls8c_ard_3-2-0_108081_2021-10-16_final
2021-10-16 11:11:10	ga_ls8c_ard_3-2-0_108082_2021-10-16_final
2021-10-16 11:11:34	ga_ls8c_ard_3-2-0_108083_2021-10-16_final
2021-10-16 11:11:58	ga_ls8c_ard_3-2-0_108084_2021-10-16_final
2021-10-16 11:12:21	ga_ls8c_ard_3-2-0_108085_2021-10-16_final
2021-10-17 10:09:33	ga_ls8c_ard_3-2-0_099067_2021-10-17_final
2021-10-17 10:09:57	ga_ls8c_ard_3-2-0_099068_2021-10-17_final
2021-10-17 10:10:21	ga_ls8c_ard_3-2-0_099069_2021-10-17_final
2021-10-17 10:10:45	ga_ls8c_ard_3-2-0_099070_2021-10-17_final
2021-10-17 10:11:09	ga_ls8c_ard_3-2-0_099071_2021-10-17_final
2021-10-17 10:11:33	ga_ls8c_ard_3-2-0_099072_2021-10-17_final
2021-10-17 10:12:45	ga_ls8c_ard_3-2-0_099075_2021-10-17_final
2021-10-17 10:13:09	ga_ls8c_ard_3-2-0_099076_2021-10-17_final
2021-10-17 10:13:33	ga_ls8c_ard_3-2-0_099077_2021-10-17_final
2021-10-17 10:13:57	ga_ls8c_ard_3-2-0_099078_2021-10-17_final
2021-10-17 10:14:21	ga_ls8c_ard_3-2-0_099079_2021-10-17_final
2021-10-17 10:14:45	ga_ls8c_ard_3-2-0_099080_2021-10-17_final
2021-10-17 10:15:08	ga_ls8c_ard_3-2-0_099081_2021-10-17_final
2021-10-17 10:15:32	ga_ls8c_ard_3-2-0_099082_2021-10-17_final
2021-10-17 10:15:56	ga_ls8c_ard_3-2-0_099083_2021-10-17_final
2021-10-17 10:16:20	ga_ls8c_ard_3-2-0_099084_2021-10-17_final
2021-10-17 10:16:44	ga_ls8c_ard_3-2-0_099085_2021-10-17_final
2021-10-17 11:50:50	ga_ls8c_ard_3-2-0_115073_2021-10-17_final
2021-10-17 11:51:14	ga_ls8c_ard_3-2-0_115074_2021-10-17_final
2021-10-17 11:51:38	ga_ls8c_ard_3-2-0_115075_2021-10-17_final
2021-10-17 11:52:02	ga_ls8c_ard_3-2-0_115076_2021-10-17_final
2021-10-17 11:52:26	ga_ls8c_ard_3-2-0_115077_2021-10-17_final
2021-10-17 11:52:50	ga_ls8c_ard_3-2-0_115078_2021-10-17_final
2021-10-17 11:53:14	ga_ls8c_ard_3-2-0_115079_2021-10-17_final
2021-10-17 11:53:38	ga_ls8c_ard_3-2-0_115080_2021-10-17_final
2021-10-18 09:16:44	ga_ls8c_ard_3-2-0_090074_2021-10-17_final
2021-10-18 09:17:08	ga_ls8c_ard_3-2-0_090075_2021-10-17_final
2021-10-18 09:17:32	ga_ls8c_ard_3-2-0_090076_2021-10-17_final
2021-10-18 09:17:55	ga_ls8c_ard_3-2-0_090077_2021-10-17_final
2021-10-18 09:18:19	ga_ls8c_ard_3-2-0_090078_2021-10-17_final
2021-10-18 09:18:43	ga_ls8c_ard_3-2-0_090079_2021-10-17_final
2021-10-18 09:19:07	ga_ls8c_ard_3-2-0_090080_2021-10-17_final
2021-10-18 09:19:31	ga_ls8c_ard_3-2-0_090081_2021-10-17_final
2021-10-18 09:19:55	ga_ls8c_ard_3-2-0_090082_2021-10-17_final
2021-10-18 09:20:19	ga_ls8c_ard_3-2-0_090083_2021-10-17_final
2021-10-18 09:21:55	ga_ls8c_ard_3-2-0_090087_2021-10-17_final
2021-10-18 09:22:19	ga_ls8c_ard_3-2-0_090088_2021-10-17_final
2021-10-18 09:22:43	ga_ls8c_ard_3-2-0_090089_2021-10-17_final
2021-10-18 09:23:07	ga_ls8c_ard_3-2-0_090090_2021-10-17_final
2021-10-18 09:23:31	ga_ls8c_ard_3-2-0_090091_2021-10-17_final
2021-10-18 10:52:49	ga_ls8c_ard_3-2-0_106067_2021-10-18_final
2021-10-18 10:53:13	ga_ls8c_ard_3-2-0_106068_2021-10-18_final
2021-10-18 10:53:37	ga_ls8c_ard_3-2-0_106069_2021-10-18_final
2021-10-18 10:54:01	ga_ls8c_ard_3-2-0_106070_2021-10-18_final
2021-10-18 10:54:25	ga_ls8c_ard_3-2-0_106071_2021-10-18_final
2021-10-18 10:54:49	ga_ls8c_ard_3-2-0_106072_2021-10-18_final
2021-10-18 10:55:13	ga_ls8c_ard_3-2-0_106073_2021-10-18_final
2021-10-18 10:55:37	ga_ls8c_ard_3-2-0_106074_2021-10-18_final
2021-10-18 10:56:01	ga_ls8c_ard_3-2-0_106075_2021-10-18_final
2021-10-18 10:56:25	ga_ls8c_ard_3-2-0_106076_2021-10-18_final
2021-10-18 10:56:48	ga_ls8c_ard_3-2-0_106077_2021-10-18_final
2021-10-18 10:57:12	ga_ls8c_ard_3-2-0_106078_2021-10-18_final
2021-10-18 10:57:36	ga_ls8c_ard_3-2-0_106079_2021-10-18_final
2021-10-18 10:58:00	ga_ls8c_ard_3-2-0_106080_2021-10-18_final
2021-10-18 10:58:24	ga_ls8c_ard_3-2-0_106081_2021-10-18_final
2021-10-18 10:58:48	ga_ls8c_ard_3-2-0_106082_2021-10-18_final
2021-10-18 10:59:12	ga_ls8c_ard_3-2-0_106083_2021-10-18_final
2021-10-18 10:59:36	ga_ls8c_ard_3-2-0_106084_2021-10-18_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years