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
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-04 11:45:10	ga_ls8c_ard_3-2-1_114076_2022-04-04_final
2022-04-05 10:45:58	ga_ls8c_ard_3-2-1_105067_2022-04-05_final
2022-04-10 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-04-10_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-17 11:11:34	ga_ls8c_ard_3-2-1_109069_2022-04-17_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-21 09:14:44	ga_ls8c_ard_3-2-1_089086_2022-04-20_final
2022-04-27 10:15:17	ga_ls8c_ard_3-2-1_099083_2022-04-27_final
2022-04-29 09:58:07	ga_ls8c_ard_3-2-1_097071_2022-04-29_final
2022-04-29 09:58:31	ga_ls8c_ard_3-2-1_097072_2022-04-29_final
2022-05-01 09:49:23	ga_ls8c_ard_3-2-1_095080_2022-05-01_final
2022-05-04 10:21:31	ga_ls8c_ard_3-2-1_100083_2022-05-04_final
2022-05-28 09:30:59	ga_ls8c_ard_3-2-1_092080_2022-05-28_final
2022-06-03 10:31:41	ga_ls8c_ard_3-2-1_102077_2022-06-03_final
2022-06-04 11:12:34	ga_ls8c_ard_3-2-1_109071_2022-06-04_final
2022-06-12 10:22:50	ga_ls8c_ard_3-2-1_101070_2022-06-12_final
2022-06-15 09:20:28	ga_ls8c_ard_3-2-1_090084_2022-06-14_final
2022-06-16 10:02:08	ga_ls8c_ard_3-2-1_097080_2022-06-16_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-19 10:30:40	ga_ls8c_ard_3-2-1_102074_2022-06-19_final
2022-06-21 10:22:18	ga_ls8c_ard_3-2-1_100084_2022-06-21_final
2022-06-25 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-06-25_final
2022-06-27 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-06-27_final
2022-07-08 09:27:07	ga_ls8c_ard_3-2-1_091085_2022-07-07_final
2022-07-18 09:59:49	ga_ls8c_ard_3-2-1_097074_2022-07-18_final
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-08-03 11:40:53	ga_ls8c_ard_3-2-1_113079_2022-08-03_final
2022-08-08 10:17:23	ga_ls8c_ard_3-2-1_100071_2022-08-08_final
2022-08-09 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-08-08_final
2022-08-09 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-08-09_final
2022-08-09 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-08-09_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-15 10:25:36	ga_ls8c_ard_3-2-1_101076_2022-08-15_final
2022-08-15 10:26:24	ga_ls8c_ard_3-2-1_101078_2022-08-15_final
2022-08-18 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-08-18_final
2022-08-19 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-08-19_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-27 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-08-27_final
2022-08-27 10:52:44	ga_ls8c_ard_3-2-1_105082_2022-08-27_final
2022-09-02 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-09-02_final
2022-09-03 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-09-03_final
2022-09-11 11:48:02	ga_ls8c_ard_3-2-1_114081_2022-09-11_final
2022-09-12 09:13:55	ga_ls8c_ard_3-2-1_089082_2022-09-11_final
2022-09-16 10:28:07	ga_ls8c_ard_3-2-1_101082_2022-09-16_final
2022-09-19 09:18:32	ga_ls8c_ard_3-2-1_090078_2022-09-18_final
2022-09-19 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-09-18_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-22 11:30:20	ga_ls8c_ard_3-2-1_111083_2022-09-22_final
2022-09-24 09:35:29	ga_ls8c_ard_3-2-1_093074_2022-09-24_final
2022-10-12 09:25:47	ga_ls8c_ard_3-2-1_091081_2022-10-11_final
2022-10-13 11:46:43	ga_ls8c_ard_3-2-1_114078_2022-10-13_final
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-22 09:59:21	ga_ls8c_ard_3-2-1_097072_2022-10-22_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-10-26 09:35:28	ga_ls8c_ard_3-2-1_093074_2022-10-26_final
2022-11-02 09:42:52	ga_ls8c_ard_3-2-1_094077_2022-11-02_final
2022-11-06 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-11-05_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-11 11:13:55	ga_ls8c_ard_3-2-1_109073_2022-11-11_final
2022-11-14 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-14_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-26 10:32:13	ga_ls8c_ard_3-2-1_102077_2022-11-26_final
2022-11-29 09:25:50	ga_ls8c_ard_3-2-1_091081_2022-11-28_final
2022-12-01 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-12-01_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-10 10:44:09	ga_ls8c_ard_3-2-1_104076_2022-12-10_final
2022-12-12 10:30:59	ga_ls8c_ard_3-2-1_102074_2022-12-12_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-22 09:29:50	ga_ls8c_ard_3-2-1_092076_2022-12-21_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-29 11:18:08	ga_ls8c_ard_3-2-1_109084_2022-12-29_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-09 09:18:41	ga_ls8c_ard_3-2-1_090079_2023-01-08_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-16 09:25:11	ga_ls8c_ard_3-2-1_091080_2023-01-15_final
2023-01-16 09:27:34	ga_ls8c_ard_3-2-1_091086_2023-01-15_final
2023-03-13 11:51:35	ga_ls8c_ard_3-2-1_115076_2023-03-13_final
2023-03-19 11:13:14	ga_ls8c_ard_3-2-1_109073_2023-03-19_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-03-23 10:46:51	ga_ls8c_ard_3-2-1_105069_2023-03-23_final
2023-03-29 10:13:20	ga_ls8c_ard_3-2-1_099078_2023-03-29_final
2023-04-02 09:46:58	ga_ls8c_ard_3-2-1_095074_2023-04-02_final
2023-04-05 10:18:36	ga_ls8c_ard_3-2-1_100076_2023-04-05_final
2023-04-06 09:26:09	ga_ls8c_ard_3-2-1_091084_2023-04-05_final
2023-04-10 10:35:02	ga_ls8c_ard_3-2-1_103071_2023-04-10_final
2023-04-20 11:11:38	ga_ls8c_ard_3-2-1_109070_2023-04-20_final
2023-04-25 11:31:23	ga_ls8c_ard_3-2-1_112073_2023-04-25_final
2023-04-28 10:22:11	ga_ls8c_ard_3-2-1_101070_2023-04-28_final
2023-05-01 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-04-30_final
2023-05-01 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-05-01_final
2023-05-02 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-05-02_final
2023-05-03 09:06:59	ga_ls8c_ard_3-2-1_088083_2023-05-02_final
2023-05-08 11:00:44	ga_ls8c_ard_3-2-1_107074_2023-05-08_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_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