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
2022-01-20 09:34:03	ga_ls8c_ard_3-2-1_092087_2022-01-20_final
2022-01-30 10:10:16	ga_ls8c_ard_3-2-1_098085_2022-01-30_final
2022-01-30 11:45:10	ga_ls8c_ard_3-2-1_114075_2022-01-30_final
2022-01-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2022-01-30_final
2022-02-05 11:07:40	ga_ls8c_ard_3-2-1_108074_2022-02-05_final
2022-02-23 10:55:13	ga_ls8c_ard_3-2-1_106074_2022-02-23_final
2022-02-26 09:52:01	ga_ls8c_ard_3-2-1_095086_2022-02-26_final
2022-02-28 09:38:27	ga_ls8c_ard_3-2-1_093083_2022-02-28_final
2022-03-11 09:19:04	ga_ls8c_ard_3-2-1_090081_2022-03-10_final
2022-03-18 11:05:15	ga_ls8c_ard_3-2-1_107084_2022-03-18_final
2022-03-23 09:40:52	ga_ls8c_ard_3-2-1_094074_2022-03-23_final
2022-04-11 11:51:49	ga_ls8c_ard_3-2-1_115077_2022-04-11_final
2022-04-14 10:40:16	ga_ls8c_ard_3-2-1_104068_2022-04-14_final
2022-04-24 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-24_final
2022-04-27 10:12:29	ga_ls8c_ard_3-2-1_099076_2022-04-27_final
2022-04-30 10:45:47	ga_ls8c_ard_3-2-1_104082_2022-04-30_final
2022-05-05 11:01:36	ga_ls8c_ard_3-2-1_107075_2022-05-05_final
2022-05-12 11:07:03	ga_ls8c_ard_3-2-1_108073_2022-05-12_final
2022-05-28 09:34:58	ga_ls8c_ard_3-2-1_092090_2022-05-28_final
2022-05-30 09:21:51	ga_ls8c_ard_3-2-1_090088_2022-05-29_final
2022-06-01 09:06:20	ga_ls8c_ard_3-2-1_088080_2022-05-31_final
2022-06-08 09:13:00	ga_ls8c_ard_3-2-1_089081_2022-06-07_final
2022-06-09 09:56:17	ga_ls8c_ard_3-2-1_096081_2022-06-09_final
2022-06-10 10:34:22	ga_ls8c_ard_3-2-1_103068_2022-06-10_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_final
2022-06-20 09:33:51	ga_ls8c_ard_3-2-1_093071_2022-06-20_final
2022-06-24 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-06-23_final
2022-07-03 09:06:35	ga_ls8c_ard_3-2-1_088080_2022-07-02_final
2022-07-06 09:39:28	ga_ls8c_ard_3-2-1_093085_2022-07-06_final
2022-07-09 10:07:11	ga_ls8c_ard_3-2-1_098077_2022-07-09_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-07-12 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-07-12_final
2022-07-13 09:45:14	ga_ls8c_ard_3-2-1_094084_2022-07-13_final
2022-07-15 11:08:09	ga_ls8c_ard_3-2-1_108075_2022-07-15_final
2022-07-18 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-18_final
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-07-23 10:22:01	ga_ls8c_ard_3-2-1_100083_2022-07-23_final
2022-07-26 09:14:04	ga_ls8c_ard_3-2-1_089083_2022-07-25_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-08-03 11:38:53	ga_ls8c_ard_3-2-1_113074_2022-08-03_final
2022-08-08 10:18:35	ga_ls8c_ard_3-2-1_100074_2022-08-08_final
2022-08-09 09:26:58	ga_ls8c_ard_3-2-1_091084_2022-08-08_final
2022-08-17 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-08-17_final
2022-08-23 09:39:22	ga_ls8c_ard_3-2-1_093084_2022-08-23_final
2022-08-23 09:40:10	ga_ls8c_ard_3-2-1_093086_2022-08-23_final
2022-08-29 10:34:47	ga_ls8c_ard_3-2-1_103068_2022-08-29_final
2022-09-10 11:00:46	ga_ls8c_ard_3-2-1_107071_2022-09-10_final
2022-09-18 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-09-18_final
2022-09-20 09:58:13	ga_ls8c_ard_3-2-1_097069_2022-09-20_final
2022-09-29 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-09-29_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-03 11:08:10	ga_ls8c_ard_3-2-1_108074_2022-10-03_final
2022-10-04 11:51:49	ga_ls8c_ard_3-2-1_115075_2022-10-04_final
2022-10-10 09:37:23	ga_ls8c_ard_3-2-1_093079_2022-10-10_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-12 11:00:41	ga_ls8c_ard_3-2-1_107071_2022-10-12_final
2022-10-13 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-10-13_final
2022-10-22 09:58:57	ga_ls8c_ard_3-2-1_097071_2022-10-22_final
2022-10-26 09:34:40	ga_ls8c_ard_3-2-1_093072_2022-10-26_final
2022-11-07 09:59:00	ga_ls8c_ard_3-2-1_097071_2022-11-07_final
2022-11-07 10:00:12	ga_ls8c_ard_3-2-1_097074_2022-11-07_final
2022-11-09 09:51:01	ga_ls8c_ard_3-2-1_095082_2022-11-09_final
2022-11-14 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-14_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-07 09:29:52	ga_ls8c_ard_3-2-1_092076_2023-01-06_final
2023-01-09 09:18:17	ga_ls8c_ard_3-2-1_090078_2023-01-08_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-01-25 09:22:39	ga_ls8c_ard_3-2-1_090089_2023-01-24_final
2023-01-25 10:55:33	ga_ls8c_ard_3-2-1_106074_2023-01-25_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-06 11:19:53	ga_ls8c_ard_3-2-1_110073_2023-02-06_final
2023-02-07 10:23:51	ga_ls8c_ard_3-2-1_101072_2023-02-07_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-24 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-02-24_final
2023-03-06 10:10:09	ga_ls8c_ard_3-2-1_098085_2023-03-06_final
2023-03-16 10:45:58	ga_ls8c_ard_3-2-1_104082_2023-03-16_final
2023-03-31 09:58:09	ga_ls8c_ard_3-2-1_097071_2023-03-31_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-15 09:17:03	ga_ls8c_ard_3-2-1_090077_2023-04-14_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-04-20 09:33:09	ga_ls8c_ard_3-2-1_093071_2023-04-20_final
2023-04-30 10:10:37	ga_ls8c_ard_3-2-1_099072_2023-04-30_final
2023-05-15 11:06:25	ga_ls8c_ard_3-2-1_108073_2023-05-15_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