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
2022-07-05 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-07-05_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-07-30 10:23:29	ga_ls8c_ard_3-2-1_101071_2022-07-30_final
2022-08-11 09:12:37	ga_ls8c_ard_3-2-1_089079_2022-08-10_final
2022-08-14 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-08-14_final
2022-08-19 11:42:10	ga_ls8c_ard_3-2-1_113082_2022-08-19_final
2022-08-22 10:30:36	ga_ls8c_ard_3-2-1_102073_2022-08-22_final
2022-08-25 09:23:01	ga_ls8c_ard_3-2-1_091074_2022-08-24_final
2022-08-27 09:12:15	ga_ls8c_ard_3-2-1_089078_2022-08-26_final
2022-09-05 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-09-05_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-12 10:50:01	ga_ls8c_ard_3-2-1_105075_2022-09-12_final
2022-09-19 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-09-19_final
2022-09-26 09:25:31	ga_ls8c_ard_3-2-1_091080_2022-09-25_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-10-03 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-10-03_final
2022-10-04 10:16:08	ga_ls8c_ard_3-2-1_099083_2022-10-04_final
2022-10-05 10:53:48	ga_ls8c_ard_3-2-1_106069_2022-10-05_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-08 09:48:11	ga_ls8c_ard_3-2-1_095075_2022-10-08_final
2022-10-08 09:51:46	ga_ls8c_ard_3-2-1_095084_2022-10-08_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-13 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-10-13_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-21 10:59:21	ga_ls8c_ard_3-2-1_106083_2022-10-21_final
2022-10-25 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-10-25_final
2022-10-29 10:04:23	ga_ls8c_ard_3-2-1_098069_2022-10-29_final
2022-10-31 11:32:55	ga_ls8c_ard_3-2-1_112074_2022-10-31_final
2022-11-03 10:28:31	ga_ls8c_ard_3-2-1_101083_2022-11-03_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-13 11:00:45	ga_ls8c_ard_3-2-1_107071_2022-11-13_final
2022-11-21 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-11-21_final
2022-11-21 10:15:39	ga_ls8c_ard_3-2-1_099082_2022-11-21_final
2022-11-27 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-11-27_final
2022-11-29 09:28:14	ga_ls8c_ard_3-2-1_091087_2022-11-28_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-02 11:32:50	ga_ls8c_ard_3-2-1_112074_2022-12-02_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-08 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-12-07_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2022-12-29 09:39:38	ga_ls8c_ard_3-2-1_093085_2022-12-29_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2023-01-02 10:50:37	ga_ls8c_ard_3-2-1_105077_2023-01-02_final
2023-01-04 10:36:40	ga_ls8c_ard_3-2-1_103073_2023-01-04_final
2023-01-07 09:29:52	ga_ls8c_ard_3-2-1_092076_2023-01-06_final
2023-01-07 09:34:39	ga_ls8c_ard_3-2-1_092088_2023-01-07_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-10 11:38:50	ga_ls8c_ard_3-2-1_113074_2023-01-10_final
2023-01-11 10:43:36	ga_ls8c_ard_3-2-1_104075_2023-01-11_final
2023-01-12 09:46:46	ga_ls8c_ard_3-2-1_095072_2023-01-12_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-01-18 10:49:41	ga_ls8c_ard_3-2-1_105075_2023-01-18_final
2023-01-21 11:24:13	ga_ls8c_ard_3-2-1_110084_2023-01-21_final
2023-01-22 10:23:25	ga_ls8c_ard_3-2-1_101071_2023-01-22_final
2023-01-25 09:17:52	ga_ls8c_ard_3-2-1_090077_2023-01-24_final
2023-01-31 11:58:34	ga_ls8c_ard_3-2-1_116077_2023-01-31_final
2023-02-10 09:22:13	ga_ls8c_ard_3-2-1_090088_2023-02-09_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-11 11:42:21	ga_ls8c_ard_3-2-1_113083_2023-02-11_final
2023-02-19 09:13:07	ga_ls8c_ard_3-2-1_089081_2023-02-18_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-02-25 10:15:58	ga_ls8c_ard_3-2-1_099084_2023-02-25_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-15 11:38:24	ga_ls8c_ard_3-2-1_113074_2023-03-15_final
2023-03-21 09:23:34	ga_ls8c_ard_3-2-1_091077_2023-03-20_final
2023-03-21 10:59:39	ga_ls8c_ard_3-2-1_107070_2023-03-21_final
2023-03-26 09:40:51	ga_ls8c_ard_3-2-1_094074_2023-03-26_final
2023-03-31 10:03:20	ga_ls8c_ard_3-2-1_097084_2023-03-31_final
2023-04-05 10:17:00	ga_ls8c_ard_3-2-1_100072_2023-04-05_final
2023-04-07 10:04:12	ga_ls8c_ard_3-2-1_098071_2023-04-07_final
2023-04-09 11:31:52	ga_ls8c_ard_3-2-1_112074_2023-04-09_final
2023-04-12 10:25:02	ga_ls8c_ard_3-2-1_101077_2023-04-12_final
2023-04-21 11:57:18	ga_ls8c_ard_3-2-1_116076_2023-04-21_final
2023-04-24 10:46:08	ga_ls8c_ard_3-2-1_105068_2023-04-24_final
2023-04-29 11:05:26	ga_ls8c_ard_3-2-1_108070_2023-04-29_final
2023-04-30 11:51:05	ga_ls8c_ard_3-2-1_115076_2023-04-30_final
2023-05-04 09:46:15	ga_ls8c_ard_3-2-1_095073_2023-05-04_final
2023-05-05 10:33:05	ga_ls8c_ard_3-2-1_102082_2023-05-05_final
2023-05-07 10:21:05	ga_ls8c_ard_3-2-1_100083_2023-05-07_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-05-19 09:06:00	ga_ls8c_ard_3-2-1_088081_2023-05-18_final
2023-05-21 10:32:56	ga_ls8c_ard_3-2-1_102082_2023-05-21_final
2023-05-22 09:38:31	ga_ls8c_ard_3-2-1_093085_2023-05-22_final
2023-05-24 11:04:15	ga_ls8c_ard_3-2-1_107083_2023-05-24_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years