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

First 100 results (query limit)

Time (local)	Label
2022-12-13 09:34:33	ga_ls8c_ard_3-2-1_093072_2022-12-13_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-13 09:40:08	ga_ls8c_ard_3-2-1_093086_2022-12-13_final
2022-12-13 09:40:56	ga_ls8c_ard_3-2-1_093088_2022-12-13_final
2022-12-13 11:15:02	ga_ls8c_ard_3-2-1_109076_2022-12-13_final
2022-12-13 11:15:26	ga_ls8c_ard_3-2-1_109077_2022-12-13_final
2022-12-13 11:15:50	ga_ls8c_ard_3-2-1_109078_2022-12-13_final
2022-12-13 11:17:25	ga_ls8c_ard_3-2-1_109082_2022-12-13_final
2022-12-13 11:17:49	ga_ls8c_ard_3-2-1_109083_2022-12-13_final
2022-12-13 11:18:13	ga_ls8c_ard_3-2-1_109084_2022-12-13_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-14 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-12-14_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-15 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-12-14_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-15 09:27:45	ga_ls8c_ard_3-2-1_091086_2022-12-14_final
2022-12-15 09:28:09	ga_ls8c_ard_3-2-1_091087_2022-12-14_final
2022-12-15 09:28:33	ga_ls8c_ard_3-2-1_091088_2022-12-14_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-12-15_final
2022-12-15 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-12-15_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-15 11:01:51	ga_ls8c_ard_3-2-1_107074_2022-12-15_final
2022-12-15 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-12-15_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-16 10:05:01	ga_ls8c_ard_3-2-1_098071_2022-12-16_final
2022-12-16 10:06:13	ga_ls8c_ard_3-2-1_098074_2022-12-16_final
2022-12-16 10:07:01	ga_ls8c_ard_3-2-1_098076_2022-12-16_final
2022-12-16 10:07:49	ga_ls8c_ard_3-2-1_098078_2022-12-16_final
2022-12-16 10:09:01	ga_ls8c_ard_3-2-1_098081_2022-12-16_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2022-12-16 11:47:54	ga_ls8c_ard_3-2-1_114081_2022-12-16_final
2022-12-17 09:11:47	ga_ls8c_ard_3-2-1_089077_2022-12-16_final
2022-12-17 09:12:11	ga_ls8c_ard_3-2-1_089078_2022-12-16_final
2022-12-17 09:12:35	ga_ls8c_ard_3-2-1_089079_2022-12-16_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-17 09:13:22	ga_ls8c_ard_3-2-1_089081_2022-12-16_final
2022-12-17 09:13:46	ga_ls8c_ard_3-2-1_089082_2022-12-16_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-17 09:16:58	ga_ls8c_ard_3-2-1_089090_2022-12-16_final
2022-12-17 10:47:04	ga_ls8c_ard_3-2-1_105068_2022-12-17_final
2022-12-17 10:50:16	ga_ls8c_ard_3-2-1_105076_2022-12-17_final
2022-12-17 10:52:15	ga_ls8c_ard_3-2-1_105081_2022-12-17_final
2022-12-17 10:52:39	ga_ls8c_ard_3-2-1_105082_2022-12-17_final
2022-12-18 11:31:55	ga_ls8c_ard_3-2-1_112072_2022-12-18_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-18 11:35:30	ga_ls8c_ard_3-2-1_112081_2022-12-18_final
2022-12-20 09:40:14	ga_ls8c_ard_3-2-1_094071_2022-12-20_final
2022-12-20 09:40:38	ga_ls8c_ard_3-2-1_094072_2022-12-20_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-20 09:42:14	ga_ls8c_ard_3-2-1_094076_2022-12-20_final
2022-12-20 09:44:14	ga_ls8c_ard_3-2-1_094081_2022-12-20_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-20 11:18:20	ga_ls8c_ard_3-2-1_110069_2022-12-20_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-20 11:19:55	ga_ls8c_ard_3-2-1_110073_2022-12-20_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-21 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-12-21_final
2022-12-21 10:23:53	ga_ls8c_ard_3-2-1_101072_2022-12-21_final
2022-12-21 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-12-21_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-22 09:27:51	ga_ls8c_ard_3-2-1_092071_2022-12-21_final
2022-12-22 09:28:15	ga_ls8c_ard_3-2-1_092072_2022-12-21_final
2022-12-22 09:28:39	ga_ls8c_ard_3-2-1_092073_2022-12-21_final
2022-12-22 09:29:03	ga_ls8c_ard_3-2-1_092074_2022-12-21_final
2022-12-22 09:32:38	ga_ls8c_ard_3-2-1_092083_2022-12-22_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-22 09:34:14	ga_ls8c_ard_3-2-1_092087_2022-12-22_final
2022-12-22 09:35:02	ga_ls8c_ard_3-2-1_092089_2022-12-22_final
2022-12-22 11:05:56	ga_ls8c_ard_3-2-1_108069_2022-12-22_final
2022-12-22 11:06:20	ga_ls8c_ard_3-2-1_108070_2022-12-22_final
2022-12-22 11:07:08	ga_ls8c_ard_3-2-1_108072_2022-12-22_final
2022-12-22 11:07:32	ga_ls8c_ard_3-2-1_108073_2022-12-22_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-22 11:08:19	ga_ls8c_ard_3-2-1_108075_2022-12-22_final
2022-12-22 11:08:43	ga_ls8c_ard_3-2-1_108076_2022-12-22_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2022-12-23 10:09:30	ga_ls8c_ard_3-2-1_099067_2022-12-23_final
2022-12-23 10:12:18	ga_ls8c_ard_3-2-1_099074_2022-12-23_final
2022-12-23 10:13:06	ga_ls8c_ard_3-2-1_099076_2022-12-23_final
2022-12-23 10:13:30	ga_ls8c_ard_3-2-1_099077_2022-12-23_final
2022-12-23 10:13:54	ga_ls8c_ard_3-2-1_099078_2022-12-23_final
2022-12-23 10:14:17	ga_ls8c_ard_3-2-1_099079_2022-12-23_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-23 11:53:35	ga_ls8c_ard_3-2-1_115080_2022-12-23_final
2022-12-24 09:20:16	ga_ls8c_ard_3-2-1_090083_2022-12-23_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-24 09:21:04	ga_ls8c_ard_3-2-1_090085_2022-12-23_final
2022-12-24 09:21:28	ga_ls8c_ard_3-2-1_090086_2022-12-23_final
2022-12-24 09:22:16	ga_ls8c_ard_3-2-1_090088_2022-12-23_final
2022-12-24 10:53:10	ga_ls8c_ard_3-2-1_106068_2022-12-24_final
2022-12-24 10:53:34	ga_ls8c_ard_3-2-1_106069_2022-12-24_final
2022-12-24 10:53:58	ga_ls8c_ard_3-2-1_106070_2022-12-24_final
2022-12-24 10:58:22	ga_ls8c_ard_3-2-1_106081_2022-12-24_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