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
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-07-23 11:58:54	ga_ls8c_ard_3-2-1_116078_2022-07-23_final
2022-08-02 09:21:55	ga_ls8c_ard_3-2-1_090087_2022-08-01_final
2022-08-02 10:53:37	ga_ls8c_ard_3-2-1_106069_2022-08-02_final
2022-08-03 09:58:24	ga_ls8c_ard_3-2-1_097070_2022-08-03_final
2022-08-03 11:41:41	ga_ls8c_ard_3-2-1_113081_2022-08-03_final
2022-08-05 11:25:45	ga_ls8c_ard_3-2-1_111072_2022-08-05_final
2022-08-11 10:47:31	ga_ls8c_ard_3-2-1_105069_2022-08-11_final
2022-08-14 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-14_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-08-27 09:13:51	ga_ls8c_ard_3-2-1_089082_2022-08-26_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-08 11:17:30	ga_ls8c_ard_3-2-1_109082_2022-09-08_final
2022-09-17 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-09-17_final
2022-09-17 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-09-17_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-09-19 10:54:14	ga_ls8c_ard_3-2-1_106070_2022-09-19_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-10-01 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-10-01_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-17 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-10-17_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-20 11:53:46	ga_ls8c_ard_3-2-1_115080_2022-10-20_final
2022-10-28 11:02:00	ga_ls8c_ard_3-2-1_107074_2022-10-28_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-02 09:44:28	ga_ls8c_ard_3-2-1_094081_2022-11-02_final
2022-11-02 11:19:45	ga_ls8c_ard_3-2-1_110072_2022-11-02_final
2022-11-06 09:18:32	ga_ls8c_ard_3-2-1_090078_2022-11-05_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-07 09:58:36	ga_ls8c_ard_3-2-1_097070_2022-11-07_final
2022-11-07 10:02:11	ga_ls8c_ard_3-2-1_097079_2022-11-07_final
2022-11-10 10:34:16	ga_ls8c_ard_3-2-1_102082_2022-11-10_final
2022-11-11 09:34:38	ga_ls8c_ard_3-2-1_093072_2022-11-11_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-22 09:18:26	ga_ls8c_ard_3-2-1_090078_2022-11-21_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-11-25 11:30:14	ga_ls8c_ard_3-2-1_111083_2022-11-25_final
2022-11-26 10:32:13	ga_ls8c_ard_3-2-1_102077_2022-11-26_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-11-29 09:26:38	ga_ls8c_ard_3-2-1_091083_2022-11-28_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-16 10:04:13	ga_ls8c_ard_3-2-1_098069_2022-12-16_final
2022-12-17 09:13:46	ga_ls8c_ard_3-2-1_089082_2022-12-16_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-20 09:46:14	ga_ls8c_ard_3-2-1_094086_2022-12-20_final
2022-12-26 09:07:56	ga_ls8c_ard_3-2-1_088083_2022-12-25_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-07 09:31:28	ga_ls8c_ard_3-2-1_092080_2023-01-07_final
2023-01-11 10:43:36	ga_ls8c_ard_3-2-1_104075_2023-01-11_final
2023-01-12 11:24:03	ga_ls8c_ard_3-2-1_111068_2023-01-12_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-01-21 09:46:32	ga_ls8c_ard_3-2-1_094087_2023-01-21_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-01-30 11:12:55	ga_ls8c_ard_3-2-1_109071_2023-01-30_final
2023-01-31 10:18:53	ga_ls8c_ard_3-2-1_100075_2023-01-31_final
2023-01-31 10:20:05	ga_ls8c_ard_3-2-1_100078_2023-01-31_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-21 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-02-21_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-09 10:35:25	ga_ls8c_ard_3-2-1_103071_2023-03-09_final
2023-03-10 11:19:05	ga_ls8c_ard_3-2-1_110072_2023-03-10_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-21 09:28:45	ga_ls8c_ard_3-2-1_091090_2023-03-20_final
2023-03-26 09:45:14	ga_ls8c_ard_3-2-1_094085_2023-03-26_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-03-28 11:07:22	ga_ls8c_ard_3-2-1_108074_2023-03-28_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-04-06 09:26:57	ga_ls8c_ard_3-2-1_091086_2023-04-05_final
2023-04-06 09:28:33	ga_ls8c_ard_3-2-1_091090_2023-04-05_final
2023-04-06 11:01:51	ga_ls8c_ard_3-2-1_107076_2023-04-06_final
2023-04-14 10:14:40	ga_ls8c_ard_3-2-1_099082_2023-04-14_final
2023-04-15 10:53:56	ga_ls8c_ard_3-2-1_106072_2023-04-15_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-04-21 10:18:01	ga_ls8c_ard_3-2-1_100075_2023-04-21_final
2023-04-24 09:13:14	ga_ls8c_ard_3-2-1_089083_2023-04-23_final
2023-04-29 11:06:38	ga_ls8c_ard_3-2-1_108073_2023-04-29_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-01 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-04-30_final
2023-05-08 09:22:39	ga_ls8c_ard_3-2-1_091076_2023-05-07_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-17 09:21:09	ga_ls8c_ard_3-2-1_090088_2023-05-16_final
2023-05-20 09:46:05	ga_ls8c_ard_3-2-1_095073_2023-05-20_final
2023-05-25 10:09:26	ga_ls8c_ard_3-2-1_098085_2023-05-25_final
2023-05-26 10:45:31	ga_ls8c_ard_3-2-1_105067_2023-05-26_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