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
2022-05-06 10:09:11	ga_ls8c_ard_3-2-1_098083_2022-05-06_final
2022-05-15 11:41:34	ga_ls8c_ard_3-2-1_113082_2022-05-15_final
2022-05-16 10:45:57	ga_ls8c_ard_3-2-1_104082_2022-05-16_final
2022-05-21 09:25:37	ga_ls8c_ard_3-2-1_091082_2022-05-20_final
2022-06-02 09:52:24	ga_ls8c_ard_3-2-1_095087_2022-06-02_final
2022-06-06 09:21:45	ga_ls8c_ard_3-2-1_091072_2022-06-05_final
2022-06-18 09:47:00	ga_ls8c_ard_3-2-1_095073_2022-06-18_final
2022-06-27 11:18:09	ga_ls8c_ard_3-2-1_110069_2022-06-27_final
2022-06-28 10:27:43	ga_ls8c_ard_3-2-1_101082_2022-06-28_final
2022-06-29 09:31:18	ga_ls8c_ard_3-2-1_092080_2022-06-29_final
2022-07-03 09:06:59	ga_ls8c_ard_3-2-1_088081_2022-07-02_final
2022-07-10 09:11:57	ga_ls8c_ard_3-2-1_089078_2022-07-09_final
2022-07-24 11:04:06	ga_ls8c_ard_3-2-1_107080_2022-07-24_final
2022-07-29 11:19:30	ga_ls8c_ard_3-2-1_110072_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-08-09 09:27:46	ga_ls8c_ard_3-2-1_091086_2022-08-08_final
2022-08-11 10:47:07	ga_ls8c_ard_3-2-1_105068_2022-08-11_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-09-06 11:25:51	ga_ls8c_ard_3-2-1_111072_2022-09-06_final
2022-09-08 09:34:37	ga_ls8c_ard_3-2-1_093072_2022-09-08_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-09-19 09:21:44	ga_ls8c_ard_3-2-1_090086_2022-09-18_final
2022-09-19 09:22:08	ga_ls8c_ard_3-2-1_090087_2022-09-18_final
2022-09-22 09:46:39	ga_ls8c_ard_3-2-1_095071_2022-09-22_final
2022-09-25 10:21:57	ga_ls8c_ard_3-2-1_100082_2022-09-25_final
2022-09-29 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-09-29_final
2022-09-30 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-09-30_final
2022-10-06 09:58:10	ga_ls8c_ard_3-2-1_097069_2022-10-06_final
2022-10-08 09:51:46	ga_ls8c_ard_3-2-1_095084_2022-10-08_final
2022-10-14 09:12:12	ga_ls8c_ard_3-2-1_089078_2022-10-13_final
2022-10-22 09:58:09	ga_ls8c_ard_3-2-1_097069_2022-10-22_final
2022-10-24 09:51:00	ga_ls8c_ard_3-2-1_095082_2022-10-24_final
2022-10-24 11:24:18	ga_ls8c_ard_3-2-1_111068_2022-10-24_final
2022-10-28 09:23:07	ga_ls8c_ard_3-2-1_091074_2022-10-27_final
2022-10-28 09:25:30	ga_ls8c_ard_3-2-1_091080_2022-10-27_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-05 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-11-05_final
2022-11-10 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-11-10_final
2022-11-15 09:13:52	ga_ls8c_ard_3-2-1_089082_2022-11-14_final
2022-11-18 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-11-18_final
2022-11-20 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-11-19_final
2022-12-06 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-12-06_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2023-01-01 10:07:45	ga_ls8c_ard_3-2-1_098078_2023-01-01_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-10 11:38:50	ga_ls8c_ard_3-2-1_113074_2023-01-10_final
2023-01-15 10:20:01	ga_ls8c_ard_3-2-1_100078_2023-01-15_final
2023-01-16 11:01:40	ga_ls8c_ard_3-2-1_107074_2023-01-16_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-22 10:23:25	ga_ls8c_ard_3-2-1_101071_2023-01-22_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-01-25 10:55:09	ga_ls8c_ard_3-2-1_106073_2023-01-25_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-02-03 09:11:42	ga_ls8c_ard_3-2-1_089077_2023-02-02_final
2023-02-04 09:52:58	ga_ls8c_ard_3-2-1_096072_2023-02-04_final
2023-02-08 09:34:12	ga_ls8c_ard_3-2-1_092087_2023-02-08_final
2023-02-10 09:22:13	ga_ls8c_ard_3-2-1_090088_2023-02-09_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-03-01 11:23:45	ga_ls8c_ard_3-2-1_111068_2023-03-01_final
2023-03-03 11:12:58	ga_ls8c_ard_3-2-1_109072_2023-03-03_final
2023-03-13 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-03-13_final
2023-03-27 10:25:18	ga_ls8c_ard_3-2-1_101077_2023-03-27_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-03-31 11:41:26	ga_ls8c_ard_3-2-1_113082_2023-03-31_final
2023-04-06 09:22:34	ga_ls8c_ard_3-2-1_091075_2023-04-05_final
2023-04-09 11:31:52	ga_ls8c_ard_3-2-1_112074_2023-04-09_final
2023-04-11 09:39:47	ga_ls8c_ard_3-2-1_094072_2023-04-11_final
2023-04-16 09:56:43	ga_ls8c_ard_3-2-1_097068_2023-04-16_final
2023-04-18 09:47:08	ga_ls8c_ard_3-2-1_095075_2023-04-18_final
2023-04-20 09:38:44	ga_ls8c_ard_3-2-1_093085_2023-04-20_final
2023-05-04 11:29:07	ga_ls8c_ard_3-2-1_111083_2023-05-04_final
2023-05-24 09:27:46	ga_ls8c_ard_3-2-1_091089_2023-05-23_final
2023-05-24 10:59:04	ga_ls8c_ard_3-2-1_107070_2023-05-24_final
2023-05-25 10:02:15	ga_ls8c_ard_3-2-1_098067_2023-05-25_final
2023-05-27 11:31:35	ga_ls8c_ard_3-2-1_112074_2023-05-27_final
2023-06-09 09:21:53	ga_ls8c_ard_3-2-1_091074_2023-06-08_final
2023-06-10 11:44:03	ga_ls8c_ard_3-2-1_114074_2023-06-10_final
2023-06-14 11:18:34	ga_ls8c_ard_3-2-1_110072_2023-06-14_final
2023-06-16 11:10:36	ga_ls8c_ard_3-2-1_108083_2023-06-16_final
2023-06-30 11:19:30	ga_ls8c_ard_3-2-1_110074_2023-06-30_final
2023-07-02 09:28:41	ga_ls8c_ard_3-2-1_092075_2023-07-01_final
2023-07-02 09:32:16	ga_ls8c_ard_3-2-1_092084_2023-07-02_final
2023-07-03 10:15:33	ga_ls8c_ard_3-2-1_099084_2023-07-03_final
2023-07-07 11:25:21	ga_ls8c_ard_3-2-1_111073_2023-07-07_final
2023-07-08 10:29:44	ga_ls8c_ard_3-2-1_102073_2023-07-08_final
2023-07-11 09:21:23	ga_ls8c_ard_3-2-1_091072_2023-07-10_final
2023-07-11 09:26:10	ga_ls8c_ard_3-2-1_091084_2023-07-10_final
2023-07-12 10:03:03	ga_ls8c_ard_3-2-1_098068_2023-07-12_final
2023-07-13 09:09:49	ga_ls8c_ard_3-2-1_089074_2023-07-12_final
2023-07-17 10:26:47	ga_ls8c_ard_3-2-1_101081_2023-07-17_final
2023-07-23 11:25:01	ga_ls8c_ard_3-2-1_111072_2023-07-23_final
2023-07-30 11:32:05	ga_ls8c_ard_3-2-1_112074_2023-07-30_final
2023-08-06 09:56:38	ga_ls8c_ard_3-2-1_097067_2023-08-06_final
2023-08-12 09:24:45	ga_ls8c_ard_3-2-1_091080_2023-08-11_final
2023-08-14 10:49:18	ga_ls8c_ard_3-2-1_105075_2023-08-14_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