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
2013-12-06 09:29:17	ga_ls8c_ard_3-1-0_091087_2013-12-05_final
2019-03-10 09:23:18	ga_ls8c_ard_3-1-0_091077_2019-03-09_final
2019-03-10 09:27:42	ga_ls8c_ard_3-1-0_091088_2019-03-09_final
2019-06-14 09:25:05	ga_ls8c_ard_3-1-0_091081_2019-06-13_final
2019-06-14 09:25:53	ga_ls8c_ard_3-1-0_091083_2019-06-13_final
2019-06-30 09:24:22	ga_ls8c_ard_3-1-0_091079_2019-06-29_final
2019-07-19 09:57:43	ga_ls8c_ard_3-1-0_096085_2019-07-19_final
2019-08-01 09:24:56	ga_ls8c_ard_3-1-0_091080_2019-07-31_final
2019-08-17 09:25:25	ga_ls8c_ard_3-1-0_091081_2019-08-16_final
2019-08-20 09:57:56	ga_ls8c_ard_3-1-0_096085_2019-08-20_final
2019-08-29 09:47:00	ga_ls8c_ard_3-1-0_095073_2019-08-29_final
2019-09-14 09:46:40	ga_ls8c_ard_3-1-0_095072_2019-09-14_final
2019-09-14 09:47:04	ga_ls8c_ard_3-1-0_095073_2019-09-14_final
2019-09-18 09:25:34	ga_ls8c_ard_3-1-0_091081_2019-09-17_final
2019-10-04 09:27:38	ga_ls8c_ard_3-1-0_091086_2019-10-03_final
2019-10-20 09:28:28	ga_ls8c_ard_3-1-0_091088_2019-10-19_final
2019-11-05 09:26:51	ga_ls8c_ard_3-1-0_091084_2019-11-04_final
2019-11-08 09:53:45	ga_ls8c_ard_3-1-0_096074_2019-11-08_final
2019-11-17 09:47:08	ga_ls8c_ard_3-1-0_095073_2019-11-17_final
2019-11-21 09:27:35	ga_ls8c_ard_3-1-0_091086_2019-11-20_final
2019-11-24 09:58:29	ga_ls8c_ard_3-1-0_096086_2019-11-24_final
2019-12-03 09:46:19	ga_ls8c_ard_3-1-0_095071_2019-12-03_final
2019-12-03 09:50:19	ga_ls8c_ard_3-1-0_095081_2019-12-03_final
2020-01-04 09:50:36	ga_ls8c_ard_3-1-0_095082_2020-01-04_final
2020-01-08 09:20:17	ga_ls8c_ard_3-1-0_091068_2020-01-07_final
2020-01-08 09:25:04	ga_ls8c_ard_3-1-0_091080_2020-01-07_final
2020-01-11 09:57:58	ga_ls8c_ard_3-1-0_096085_2020-01-11_final
2020-02-25 09:24:04	ga_ls8c_ard_3-1-0_091078_2020-02-24_final
2020-02-25 09:26:52	ga_ls8c_ard_3-1-0_091085_2020-02-24_final
2020-03-08 09:49:31	ga_ls8c_ard_3-1-0_095080_2020-03-08_final
2020-03-08 09:50:18	ga_ls8c_ard_3-1-0_095082_2020-03-08_final
2020-03-12 09:25:57	ga_ls8c_ard_3-1-0_091083_2020-03-11_final
2020-03-12 09:26:21	ga_ls8c_ard_3-1-0_091084_2020-03-11_final
2020-03-15 09:52:27	ga_ls8c_ard_3-1-0_096072_2020-03-15_final
2020-03-24 09:47:23	ga_ls8c_ard_3-1-0_095075_2020-03-24_final
2020-03-24 09:49:46	ga_ls8c_ard_3-1-0_095081_2020-03-24_final
2020-03-31 09:51:53	ga_ls8c_ard_3-1-0_096071_2020-03-31_final
2020-04-16 09:56:58	ga_ls8c_ard_3-1-0_096084_2020-04-16_final
2020-04-29 09:19:34	ga_ls8c_ard_3-1-0_091068_2020-04-28_final
2022-04-01 11:13:52	ga_ls8c_ard_3-2-1_109075_2022-04-01_final
2022-04-01 11:15:27	ga_ls8c_ard_3-2-1_109079_2022-04-01_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-08 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-08_final
2022-04-10 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-04-10_final
2022-04-10 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-04-10_final
2022-04-10 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-04-10_final
2022-04-12 10:53:49	ga_ls8c_ard_3-2-1_106071_2022-04-12_final
2022-04-15 11:28:43	ga_ls8c_ard_3-2-1_111081_2022-04-15_final
2022-04-15 11:29:31	ga_ls8c_ard_3-2-1_111083_2022-04-15_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-17 11:13:10	ga_ls8c_ard_3-2-1_109073_2022-04-17_final
2022-04-18 10:19:56	ga_ls8c_ard_3-2-1_100079_2022-04-18_final
2022-04-19 09:24:18	ga_ls8c_ard_3-2-1_091079_2022-04-18_final
2022-04-20 11:46:03	ga_ls8c_ard_3-2-1_114078_2022-04-20_final
2022-04-23 10:39:14	ga_ls8c_ard_3-2-1_103081_2022-04-23_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_final
2022-04-24 11:23:42	ga_ls8c_ard_3-2-1_110084_2022-04-24_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-04-29 10:00:55	ga_ls8c_ard_3-2-1_097078_2022-04-29_final
2022-04-29 11:39:24	ga_ls8c_ard_3-2-1_113077_2022-04-29_final
2022-04-30 10:40:12	ga_ls8c_ard_3-2-1_104068_2022-04-30_final
2022-04-30 10:41:00	ga_ls8c_ard_3-2-1_104070_2022-04-30_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-05 09:23:31	ga_ls8c_ard_3-2-1_091077_2022-05-04_final
2022-05-06 11:46:04	ga_ls8c_ard_3-2-1_114078_2022-05-06_final
2022-05-12 11:07:51	ga_ls8c_ard_3-2-1_108075_2022-05-12_final
2022-05-12 11:09:27	ga_ls8c_ard_3-2-1_108079_2022-05-12_final
2022-05-15 09:58:41	ga_ls8c_ard_3-2-1_097072_2022-05-15_final
2022-05-15 09:59:29	ga_ls8c_ard_3-2-1_097074_2022-05-15_final
2022-05-15 10:03:53	ga_ls8c_ard_3-2-1_097085_2022-05-15_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-18 10:28:01	ga_ls8c_ard_3-2-1_102068_2022-05-18_final
2022-05-18 10:28:25	ga_ls8c_ard_3-2-1_102069_2022-05-18_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-05-19 11:14:04	ga_ls8c_ard_3-2-1_109075_2022-05-19_final
2022-05-19 11:14:52	ga_ls8c_ard_3-2-1_109077_2022-05-19_final
2022-05-20 10:20:02	ga_ls8c_ard_3-2-1_100079_2022-05-20_final
2022-05-26 09:40:57	ga_ls8c_ard_3-2-1_094074_2022-05-26_final
2022-05-26 11:22:38	ga_ls8c_ard_3-2-1_110081_2022-05-26_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-06-02 09:50:00	ga_ls8c_ard_3-2-1_095081_2022-06-02_final
2022-06-03 10:30:29	ga_ls8c_ard_3-2-1_102074_2022-06-03_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-13 09:32:24	ga_ls8c_ard_3-2-1_092083_2022-06-13_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-16 10:02:08	ga_ls8c_ard_3-2-1_097080_2022-06-16_final
2022-06-18 09:47:48	ga_ls8c_ard_3-2-1_095075_2022-06-18_final
2022-06-20 09:34:15	ga_ls8c_ard_3-2-1_093072_2022-06-20_final
2022-06-20 09:36:15	ga_ls8c_ard_3-2-1_093077_2022-06-20_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_2022-06-20_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