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
2021-11-16 10:25:25	ga_ls8c_ard_3-2-0_101076_2021-11-16_final
2021-11-26 09:25:14	ga_ls8c_ard_3-2-0_091080_2021-11-25_final
2021-12-01 11:22:16	ga_ls8c_ard_3-2-0_110079_2021-12-01_final
2021-12-02 10:23:51	ga_ls8c_ard_3-2-0_101072_2021-12-02_final
2021-12-10 09:37:12	ga_ls8c_ard_3-2-1_093079_2021-12-10_final
2021-12-15 09:52:56	ga_ls8c_ard_3-2-1_096072_2021-12-15_final
2021-12-15 09:56:55	ga_ls8c_ard_3-2-1_096082_2021-12-15_final
2021-12-17 09:44:33	ga_ls8c_ard_3-2-1_094082_2021-12-17_final
2021-12-19 09:28:12	ga_ls8c_ard_3-2-1_092072_2021-12-18_final
2021-12-22 11:41:33	ga_ls8c_ard_3-2-1_113081_2021-12-22_final
2022-01-09 11:29:31	ga_ls8c_ard_3-2-1_111082_2022-01-09_final
2022-01-09 11:30:19	ga_ls8c_ard_3-2-1_111084_2022-01-09_final
2022-01-18 11:24:06	ga_ls8c_ard_3-2-1_110084_2022-01-18_final
2022-01-24 10:41:00	ga_ls8c_ard_3-2-1_104069_2022-01-24_final
2022-02-07 09:18:49	ga_ls8c_ard_3-2-1_090080_2022-02-06_final
2022-02-16 10:51:04	ga_ls8c_ard_3-2-1_105079_2022-02-16_final
2022-02-18 10:34:42	ga_ls8c_ard_3-2-1_103069_2022-02-18_final
2022-03-02 09:24:53	ga_ls8c_ard_3-2-1_091080_2022-03-01_final
2022-03-09 11:11:07	ga_ls8c_ard_3-2-1_108083_2022-03-09_final
2022-03-21 11:32:32	ga_ls8c_ard_3-2-1_112075_2022-03-21_final
2022-03-27 10:54:10	ga_ls8c_ard_3-2-1_106072_2022-03-27_final
2022-05-03 11:13:08	ga_ls8c_ard_3-2-1_109073_2022-05-03_final
2022-05-22 10:07:41	ga_ls8c_ard_3-2-1_098079_2022-05-22_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-30 10:56:20	ga_ls8c_ard_3-2-1_106077_2022-05-30_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-06-06 09:24:56	ga_ls8c_ard_3-2-1_091080_2022-06-05_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-13 11:05:42	ga_ls8c_ard_3-2-1_108069_2022-06-13_final
2022-06-23 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-06-23_final
2022-06-29 09:32:06	ga_ls8c_ard_3-2-1_092082_2022-06-29_final
2022-07-01 10:55:02	ga_ls8c_ard_3-2-1_106073_2022-07-01_final
2022-07-02 11:40:41	ga_ls8c_ard_3-2-1_113079_2022-07-02_final
2022-07-04 11:29:55	ga_ls8c_ard_3-2-1_111083_2022-07-04_final
2022-07-06 11:13:34	ga_ls8c_ard_3-2-1_109073_2022-07-06_final
2022-07-18 11:41:30	ga_ls8c_ard_3-2-1_113081_2022-07-18_final
2022-07-19 10:42:42	ga_ls8c_ard_3-2-1_104073_2022-07-19_final
2022-07-24 09:24:01	ga_ls8c_ard_3-2-1_091077_2022-07-23_final
2022-07-24 09:26:01	ga_ls8c_ard_3-2-1_091082_2022-07-23_final
2022-07-29 11:21:30	ga_ls8c_ard_3-2-1_110077_2022-07-29_final
2022-08-12 11:35:58	ga_ls8c_ard_3-2-1_112082_2022-08-12_final
2022-08-17 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-08-17_final
2022-08-30 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-08-30_final
2022-08-31 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-08-31_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-30 10:35:41	ga_ls8c_ard_3-2-1_103070_2022-09-30_final
2022-09-30 10:40:28	ga_ls8c_ard_3-2-1_103082_2022-09-30_final
2022-10-02 10:24:31	ga_ls8c_ard_3-2-1_101073_2022-10-02_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-12 11:01:29	ga_ls8c_ard_3-2-1_107073_2022-10-12_final
2022-10-26 11:13:33	ga_ls8c_ard_3-2-1_109072_2022-10-26_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-07 10:00:59	ga_ls8c_ard_3-2-1_097076_2022-11-07_final
2022-11-09 09:49:25	ga_ls8c_ard_3-2-1_095078_2022-11-09_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-12-02 09:57:08	ga_ls8c_ard_3-2-1_096082_2022-12-02_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_final
2022-12-05 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-12-05_final
2022-12-09 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-12-09_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-12 10:30:35	ga_ls8c_ard_3-2-1_102073_2022-12-12_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-27 11:27:41	ga_ls8c_ard_3-2-1_111077_2022-12-27_final
2022-12-30 11:58:12	ga_ls8c_ard_3-2-1_116076_2022-12-30_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-14 09:40:46	ga_ls8c_ard_3-2-1_093088_2023-01-14_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-02-05 10:38:37	ga_ls8c_ard_3-2-1_103078_2023-02-05_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-02-06 11:21:28	ga_ls8c_ard_3-2-1_110077_2023-02-06_final
2023-02-12 10:42:44	ga_ls8c_ard_3-2-1_104073_2023-02-12_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-13 11:26:46	ga_ls8c_ard_3-2-1_111075_2023-02-13_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-20 11:31:38	ga_ls8c_ard_3-2-1_112072_2023-02-20_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-23 10:24:47	ga_ls8c_ard_3-2-1_101075_2023-02-23_final
2023-02-25 10:12:46	ga_ls8c_ard_3-2-1_099076_2023-02-25_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-14 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-03-13_final
2023-04-02 11:29:02	ga_ls8c_ard_3-2-1_111082_2023-04-02_final
2023-04-04 11:15:27	ga_ls8c_ard_3-2-1_109079_2023-04-04_final
2023-04-05 11:58:17	ga_ls8c_ard_3-2-1_116078_2023-04-05_final
2023-04-08 10:49:02	ga_ls8c_ard_3-2-1_105075_2023-04-08_final
2023-04-11 11:19:52	ga_ls8c_ard_3-2-1_110075_2023-04-11_final
2023-04-14 10:11:53	ga_ls8c_ard_3-2-1_099075_2023-04-14_final
2023-04-15 09:20:38	ga_ls8c_ard_3-2-1_090086_2023-04-14_final
2023-04-17 10:42:45	ga_ls8c_ard_3-2-1_104075_2023-04-17_final
2023-04-27 11:18:13	ga_ls8c_ard_3-2-1_110071_2023-04-27_final
2023-05-10 10:51:32	ga_ls8c_ard_3-2-1_105082_2023-05-10_final
2023-05-22 11:12:13	ga_ls8c_ard_3-2-1_109072_2023-05-22_final
2023-05-24 09:22:35	ga_ls8c_ard_3-2-1_091076_2023-05-23_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