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
2022-05-31 10:01:32	ga_ls8c_ard_3-2-1_097079_2022-05-31_final
2022-06-02 11:25:18	ga_ls8c_ard_3-2-1_111072_2022-06-02_final
2022-06-03 10:28:05	ga_ls8c_ard_3-2-1_102068_2022-06-03_final
2022-06-04 09:38:04	ga_ls8c_ard_3-2-1_093082_2022-06-04_final
2022-06-13 11:11:41	ga_ls8c_ard_3-2-1_108084_2022-06-13_final
2022-06-15 09:20:52	ga_ls8c_ard_3-2-1_090085_2022-06-14_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-29 09:33:18	ga_ls8c_ard_3-2-1_092085_2022-06-29_final
2022-06-30 11:53:03	ga_ls8c_ard_3-2-1_115079_2022-06-30_final
2022-07-09 11:46:52	ga_ls8c_ard_3-2-1_114079_2022-07-09_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-07-17 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-07-16_final
2022-07-20 11:29:10	ga_ls8c_ard_3-2-1_111081_2022-07-20_final
2022-07-21 10:29:34	ga_ls8c_ard_3-2-1_102071_2022-07-21_final
2022-07-23 10:20:01	ga_ls8c_ard_3-2-1_100078_2022-07-23_final
2022-07-24 11:02:06	ga_ls8c_ard_3-2-1_107075_2022-07-24_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-08-09 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-08-08_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-27 09:15:03	ga_ls8c_ard_3-2-1_089085_2022-08-26_final
2022-09-01 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-09-01_final
2022-09-04 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-09-04_final
2022-09-08 11:17:30	ga_ls8c_ard_3-2-1_109082_2022-09-08_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-20 10:03:00	ga_ls8c_ard_3-2-1_097081_2022-09-20_final
2022-09-27 10:10:23	ga_ls8c_ard_3-2-1_098084_2022-09-27_final
2022-10-01 11:19:44	ga_ls8c_ard_3-2-1_110072_2022-10-01_final
2022-10-05 09:18:06	ga_ls8c_ard_3-2-1_090077_2022-10-04_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-24 11:26:18	ga_ls8c_ard_3-2-1_111073_2022-10-24_final
2022-10-26 09:35:04	ga_ls8c_ard_3-2-1_093073_2022-10-26_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-25 09:59:33	ga_ls8c_ard_3-2-1_097073_2022-12-25_final
2022-12-30 10:20:07	ga_ls8c_ard_3-2-1_100078_2022-12-30_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-10 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-10_final
2023-01-17 11:45:42	ga_ls8c_ard_3-2-1_114076_2023-01-17_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-21 11:19:26	ga_ls8c_ard_3-2-1_110072_2023-01-21_final
2023-01-24 10:10:41	ga_ls8c_ard_3-2-1_099070_2023-01-24_final
2023-01-25 10:55:33	ga_ls8c_ard_3-2-1_106074_2023-01-25_final
2023-02-02 10:07:43	ga_ls8c_ard_3-2-1_098078_2023-02-02_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-04 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-03-04_final
2023-03-06 11:45:26	ga_ls8c_ard_3-2-1_114076_2023-03-06_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-15 09:57:32	ga_ls8c_ard_3-2-1_097069_2023-03-15_final
2023-03-15 09:58:20	ga_ls8c_ard_3-2-1_097071_2023-03-15_final
2023-03-17 11:24:02	ga_ls8c_ard_3-2-1_111069_2023-03-17_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-04-10 10:35:25	ga_ls8c_ard_3-2-1_103072_2023-04-10_final
2023-04-13 09:31:01	ga_ls8c_ard_3-2-1_092081_2023-04-13_final
2023-04-14 11:51:34	ga_ls8c_ard_3-2-1_115077_2023-04-14_final
2023-04-16 09:57:55	ga_ls8c_ard_3-2-1_097071_2023-04-16_final
2023-04-17 10:39:58	ga_ls8c_ard_3-2-1_104068_2023-04-17_final
2023-04-28 10:22:11	ga_ls8c_ard_3-2-1_101070_2023-04-28_final
2023-05-11 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-11_final
2023-05-12 10:39:08	ga_ls8c_ard_3-2-1_103082_2023-05-12_final
2023-05-15 11:09:13	ga_ls8c_ard_3-2-1_108080_2023-05-15_final
2023-05-17 09:18:21	ga_ls8c_ard_3-2-1_090081_2023-05-16_final
2023-05-23 10:16:12	ga_ls8c_ard_3-2-1_100071_2023-05-23_final
2023-05-29 09:43:32	ga_ls8c_ard_3-2-1_094082_2023-05-29_final
2023-06-03 11:41:22	ga_ls8c_ard_3-2-1_113083_2023-06-03_final
2023-06-05 09:51:45	ga_ls8c_ard_3-2-1_095087_2023-06-05_final
2023-06-06 10:28:38	ga_ls8c_ard_3-2-1_102071_2023-06-06_final
2023-06-08 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-06-08_final
2023-06-09 11:04:46	ga_ls8c_ard_3-2-1_107084_2023-06-09_final
2023-06-11 09:10:45	ga_ls8c_ard_3-2-1_089077_2023-06-10_final
2023-06-18 09:16:10	ga_ls8c_ard_3-2-1_090075_2023-06-17_final
2023-06-22 10:29:32	ga_ls8c_ard_3-2-1_102073_2023-06-22_final
2023-06-24 10:16:24	ga_ls8c_ard_3-2-1_100071_2023-06-24_final
2023-06-24 10:19:11	ga_ls8c_ard_3-2-1_100078_2023-06-24_final
2023-06-30 11:23:29	ga_ls8c_ard_3-2-1_110084_2023-06-30_final
2023-07-02 11:05:58	ga_ls8c_ard_3-2-1_108071_2023-07-02_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-13 09:12:37	ga_ls8c_ard_3-2-1_089081_2023-07-12_final
2023-07-20 10:55:41	ga_ls8c_ard_3-2-1_106076_2023-07-20_final
2023-07-25 11:14:17	ga_ls8c_ard_3-2-1_109076_2023-07-25_final
2023-07-28 10:03:57	ga_ls8c_ard_3-2-1_098070_2023-07-28_final
2023-07-29 10:51:37	ga_ls8c_ard_3-2-1_105081_2023-07-29_final
2023-07-31 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-07-31_final
2023-08-03 11:05:48	ga_ls8c_ard_3-2-1_108070_2023-08-03_final
2023-08-07 10:42:41	ga_ls8c_ard_3-2-1_104074_2023-08-07_final
2023-08-11 10:16:45	ga_ls8c_ard_3-2-1_100071_2023-08-11_final
2023-08-14 09:11:37	ga_ls8c_ard_3-2-1_089078_2023-08-13_final
2023-08-20 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-08-20_final
2023-09-04 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-09-04_final
2023-09-05 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-09-05_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