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
2021-07-05 09:23:11	ga_ls8c_ard_3-2-0_091076_2021-07-04_final
2021-07-21 09:26:02	ga_ls8c_ard_3-2-0_091083_2021-07-20_final
2021-07-25 10:39:02	ga_ls8c_ard_3-2-0_103080_2021-07-25_final
2021-07-28 11:11:10	ga_ls8c_ard_3-2-0_108083_2021-07-28_final
2021-07-31 10:02:00	ga_ls8c_ard_3-2-0_097080_2021-07-31_final
2021-07-31 11:42:05	ga_ls8c_ard_3-2-0_113083_2021-07-31_final
2021-08-10 10:36:46	ga_ls8c_ard_3-2-0_103074_2021-08-10_final
2021-08-11 11:23:13	ga_ls8c_ard_3-2-0_110082_2021-08-11_final
2021-08-20 09:37:24	ga_ls8c_ard_3-2-0_093080_2021-08-20_final
2021-08-29 09:29:40	ga_ls8c_ard_3-2-0_092076_2021-08-28_final
2021-09-02 09:06:34	ga_ls8c_ard_3-2-0_088080_2021-09-01_final
2021-09-03 09:49:50	ga_ls8c_ard_3-2-0_095080_2021-09-03_final
2021-09-08 11:47:17	ga_ls8c_ard_3-2-0_114080_2021-09-08_final
2021-09-13 10:27:21	ga_ls8c_ard_3-2-0_101081_2021-09-13_final
2021-10-12 09:52:12	ga_ls8c_ard_3-2-0_096070_2021-10-12_final
2021-10-21 11:28:55	ga_ls8c_ard_3-2-0_111080_2021-10-21_final
2021-11-10 11:02:57	ga_ls8c_ard_3-2-0_107077_2021-11-10_final
2021-11-14 10:35:00	ga_ls8c_ard_3-2-0_103069_2021-11-14_final
2021-11-27 10:08:53	ga_ls8c_ard_3-2-0_098081_2021-11-27_final
2021-12-10 11:13:17	ga_ls8c_ard_3-2-1_109072_2021-12-10_final
2021-12-11 10:21:39	ga_ls8c_ard_3-2-1_100082_2021-12-11_final
2021-12-21 09:23:00	ga_ls8c_ard_3-2-1_090090_2021-12-20_final
2021-12-31 09:52:26	ga_ls8c_ard_3-2-1_096071_2021-12-31_final
2022-01-15 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-01-15_final
2022-01-20 11:08:32	ga_ls8c_ard_3-2-1_108076_2022-01-20_final
2022-01-28 11:58:19	ga_ls8c_ard_3-2-1_116077_2022-01-28_final
2022-02-06 11:50:56	ga_ls8c_ard_3-2-1_115074_2022-02-06_final
2022-02-14 11:03:03	ga_ls8c_ard_3-2-1_107078_2022-02-14_final
2022-02-21 11:10:46	ga_ls8c_ard_3-2-1_108082_2022-02-21_final
2022-02-28 09:34:52	ga_ls8c_ard_3-2-1_093074_2022-02-28_final
2022-03-02 09:28:05	ga_ls8c_ard_3-2-1_091088_2022-03-01_final
2022-03-14 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-03-14_final
2022-03-16 11:16:50	ga_ls8c_ard_3-2-1_109082_2022-03-16_final
2022-03-17 10:18:25	ga_ls8c_ard_3-2-1_100075_2022-03-17_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-04-28 09:18:51	ga_ls8c_ard_3-2-1_090081_2022-04-27_final
2022-04-28 10:54:56	ga_ls8c_ard_3-2-1_106074_2022-04-28_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-15 11:39:10	ga_ls8c_ard_3-2-1_113076_2022-05-15_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-06-25 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-06-25_final
2022-07-09 11:46:28	ga_ls8c_ard_3-2-1_114078_2022-07-09_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-08-02 10:55:37	ga_ls8c_ard_3-2-1_106074_2022-08-02_final
2022-08-03 10:00:00	ga_ls8c_ard_3-2-1_097074_2022-08-03_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-10-06 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-06_final
2022-10-12 09:24:12	ga_ls8c_ard_3-2-1_091077_2022-10-11_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-31 09:53:38	ga_ls8c_ard_3-2-1_096073_2022-10-31_final
2022-11-04 11:07:23	ga_ls8c_ard_3-2-1_108072_2022-11-04_final
2022-11-22 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-11-21_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-30 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-30_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-04 09:42:47	ga_ls8c_ard_3-2-1_094077_2022-12-04_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-24 10:59:09	ga_ls8c_ard_3-2-1_106083_2022-12-24_final
2022-12-25 11:39:38	ga_ls8c_ard_3-2-1_113076_2022-12-25_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-13 10:30:49	ga_ls8c_ard_3-2-1_102074_2023-01-13_final
2023-01-14 11:16:51	ga_ls8c_ard_3-2-1_109081_2023-01-14_final
2023-01-30 11:17:18	ga_ls8c_ard_3-2-1_109082_2023-01-30_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-02-02 10:08:31	ga_ls8c_ard_3-2-1_098080_2023-02-02_final
2023-02-08 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-02-08_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-03-20 10:20:24	ga_ls8c_ard_3-2-1_100080_2023-03-20_final
2023-03-31 11:37:26	ga_ls8c_ard_3-2-1_113072_2023-03-31_final
2023-04-11 11:23:03	ga_ls8c_ard_3-2-1_110083_2023-04-11_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-29 11:09:02	ga_ls8c_ard_3-2-1_108079_2023-04-29_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-08 09:24:15	ga_ls8c_ard_3-2-1_091080_2023-05-07_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-22 11:12:37	ga_ls8c_ard_3-2-1_109073_2023-05-22_final
2023-05-28 10:39:09	ga_ls8c_ard_3-2-1_103082_2023-05-28_final
2023-06-03 10:03:17	ga_ls8c_ard_3-2-1_097085_2023-06-03_final
2023-06-04 10:42:34	ga_ls8c_ard_3-2-1_104075_2023-06-04_final
2023-07-28 10:06:45	ga_ls8c_ard_3-2-1_098077_2023-07-28_final
2023-08-14 10:50:30	ga_ls8c_ard_3-2-1_105078_2023-08-14_final
2023-08-15 09:56:05	ga_ls8c_ard_3-2-1_096081_2023-08-15_final
2023-08-17 09:46:09	ga_ls8c_ard_3-2-1_094087_2023-08-17_final
2023-09-18 09:45:05	ga_ls8c_ard_3-2-1_094084_2023-09-18_final
2023-09-19 10:26:21	ga_ls8c_ard_3-2-1_101079_2023-09-19_final
2023-09-20 11:05:37	ga_ls8c_ard_3-2-1_108069_2023-09-20_final
2023-10-01 09:12:38	ga_ls8c_ard_3-2-1_089080_2023-09-30_final
2023-10-02 11:35:59	ga_ls8c_ard_3-2-1_112083_2023-10-02_final
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_final
2023-10-16 10:07:54	ga_ls8c_ard_3-2-1_098079_2023-10-16_final
2023-10-19 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-10-19_final
2023-11-01 11:44:51	ga_ls8c_ard_3-2-1_114074_2023-11-01_final
2023-11-03 09:57:59	ga_ls8c_ard_3-2-1_096085_2023-11-03_final
2023-11-05 11:18:54	ga_ls8c_ard_3-2-1_110071_2023-11-05_final
2023-11-10 10:01:17	ga_ls8c_ard_3-2-1_097078_2023-11-10_final
2023-11-15 10:18:18	ga_ls8c_ard_3-2-1_100074_2023-11-15_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