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:

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First 100 results (query limit)

Time (local)	Label
2022-08-23 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-08-23_final
2022-08-24 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-08-24_final
2022-09-14 10:37:16	ga_ls8c_ard_3-2-1_103074_2022-09-14_final
2022-09-15 11:21:44	ga_ls8c_ard_3-2-1_110077_2022-09-15_final
2022-09-16 10:24:31	ga_ls8c_ard_3-2-1_101073_2022-09-16_final
2022-09-19 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-09-18_final
2022-09-21 10:45:52	ga_ls8c_ard_3-2-1_104080_2022-09-21_final
2022-09-24 09:36:41	ga_ls8c_ard_3-2-1_093077_2022-09-24_final
2022-09-24 11:12:23	ga_ls8c_ard_3-2-1_109069_2022-09-24_final
2022-09-25 10:18:21	ga_ls8c_ard_3-2-1_100073_2022-09-25_final
2022-09-28 10:52:27	ga_ls8c_ard_3-2-1_105081_2022-09-28_final
2022-09-30 10:40:28	ga_ls8c_ard_3-2-1_103082_2022-09-30_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-06 11:39:27	ga_ls8c_ard_3-2-1_113075_2022-10-06_final
2022-10-10 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-10-10_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-12 11:01:29	ga_ls8c_ard_3-2-1_107073_2022-10-12_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-13 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-10-13_final
2022-10-15 11:33:10	ga_ls8c_ard_3-2-1_112075_2022-10-15_final
2022-10-16 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-10-16_final
2022-10-17 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-10-17_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-22 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-22_final
2022-10-22 11:41:02	ga_ls8c_ard_3-2-1_113079_2022-10-22_final
2022-10-26 09:36:40	ga_ls8c_ard_3-2-1_093077_2022-10-26_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-10-27 11:58:49	ga_ls8c_ard_3-2-1_116077_2022-10-27_final
2022-10-28 11:01:36	ga_ls8c_ard_3-2-1_107073_2022-10-28_final
2022-11-04 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-11-04_final
2022-11-05 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-11-05_final
2022-11-06 10:57:01	ga_ls8c_ard_3-2-1_106077_2022-11-06_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-07 10:00:59	ga_ls8c_ard_3-2-1_097076_2022-11-07_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-09 09:50:37	ga_ls8c_ard_3-2-1_095081_2022-11-09_final
2022-11-09 09:51:49	ga_ls8c_ard_3-2-1_095084_2022-11-09_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-19 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-11-19_final
2022-11-20 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-11-19_final
2022-11-20 09:35:34	ga_ls8c_ard_3-2-1_092090_2022-11-20_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-23 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-11-23_final
2022-11-26 10:31:01	ga_ls8c_ard_3-2-1_102074_2022-11-26_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-11-30 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-30_final
2022-12-02 09:56:44	ga_ls8c_ard_3-2-1_096081_2022-12-02_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-05 10:26:50	ga_ls8c_ard_3-2-1_101079_2022-12-05_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-09 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-12-09_final
2022-12-11 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-12-11_final
2022-12-16 10:09:01	ga_ls8c_ard_3-2-1_098081_2022-12-16_final
2022-12-18 11:33:55	ga_ls8c_ard_3-2-1_112077_2022-12-18_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-27 09:51:36	ga_ls8c_ard_3-2-1_095084_2022-12-27_final
2022-12-28 10:33:16	ga_ls8c_ard_3-2-1_102080_2022-12-28_final
2022-12-28 10:34:04	ga_ls8c_ard_3-2-1_102082_2022-12-28_final
2022-12-29 09:38:03	ga_ls8c_ard_3-2-1_093081_2022-12-29_final
2022-12-30 10:18:31	ga_ls8c_ard_3-2-1_100074_2022-12-30_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-14 11:16:03	ga_ls8c_ard_3-2-1_109079_2023-01-14_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-17 10:09:13	ga_ls8c_ard_3-2-1_098082_2023-01-17_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-19 09:57:16	ga_ls8c_ard_3-2-1_096083_2023-01-19_final
2023-01-20 10:36:33	ga_ls8c_ard_3-2-1_103073_2023-01-20_final
2023-01-22 10:27:25	ga_ls8c_ard_3-2-1_101081_2023-01-22_final
2023-01-23 09:31:48	ga_ls8c_ard_3-2-1_092081_2023-01-23_final
2023-01-23 09:32:12	ga_ls8c_ard_3-2-1_092082_2023-01-23_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-26 10:01:08	ga_ls8c_ard_3-2-1_097077_2023-01-26_final
2023-01-26 10:03:07	ga_ls8c_ard_3-2-1_097082_2023-01-26_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-05 10:38:37	ga_ls8c_ard_3-2-1_103078_2023-02-05_final
2023-02-09 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-02-09_final
2023-02-10 10:56:43	ga_ls8c_ard_3-2-1_106077_2023-02-10_final
2023-02-12 10:44:43	ga_ls8c_ard_3-2-1_104078_2023-02-12_final
2023-02-13 09:48:17	ga_ls8c_ard_3-2-1_095076_2023-02-13_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-14 10:32:44	ga_ls8c_ard_3-2-1_102079_2023-02-14_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-21 10:37:12	ga_ls8c_ard_3-2-1_103075_2023-02-21_final
2023-02-21 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-02-21_final
2023-02-28 10:44:05	ga_ls8c_ard_3-2-1_104077_2023-02-28_final
2023-02-28 10:45:17	ga_ls8c_ard_3-2-1_104080_2023-02-28_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-10 11:21:05	ga_ls8c_ard_3-2-1_110077_2023-03-10_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