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
2021-07-31 10:01:12	ga_ls8c_ard_3-2-0_097078_2021-07-31_final
2021-08-02 09:50:03	ga_ls8c_ard_3-2-0_095081_2021-08-02_final
2021-08-02 09:51:15	ga_ls8c_ard_3-2-0_095084_2021-08-02_final
2021-08-02 09:51:39	ga_ls8c_ard_3-2-0_095085_2021-08-02_final
2021-08-20 11:16:17	ga_ls8c_ard_3-2-0_109080_2021-08-20_final
2021-08-23 11:42:01	ga_ls8c_ard_3-2-0_114067_2021-08-23_final
2021-08-26 10:38:26	ga_ls8c_ard_3-2-0_103078_2021-08-26_final
2021-08-27 11:21:18	ga_ls8c_ard_3-2-0_110077_2021-08-27_final
2021-09-07 09:20:21	ga_ls8c_ard_3-2-0_091068_2021-09-06_final
2021-09-14 11:05:50	ga_ls8c_ard_3-2-0_108069_2021-09-14_final
2021-09-21 11:13:13	ga_ls8c_ard_3-2-0_109072_2021-09-21_final
2021-09-22 10:20:24	ga_ls8c_ard_3-2-0_100079_2021-09-22_final
2021-09-25 10:51:43	ga_ls8c_ard_3-2-0_105080_2021-09-25_final
2021-10-03 09:57:56	ga_ls8c_ard_3-2-0_097069_2021-10-03_final
2021-10-05 11:26:52	ga_ls8c_ard_3-2-0_111075_2021-10-05_final
2021-10-06 10:34:02	ga_ls8c_ard_3-2-0_102082_2021-10-06_final
2021-10-07 11:13:43	ga_ls8c_ard_3-2-0_109073_2021-10-07_final
2021-10-10 11:46:38	ga_ls8c_ard_3-2-0_114078_2021-10-10_final
2021-11-01 11:11:10	ga_ls8c_ard_3-2-0_108082_2021-11-01_final
2021-11-03 09:19:31	ga_ls8c_ard_3-2-0_090081_2021-11-02_final
2021-11-03 09:19:55	ga_ls8c_ard_3-2-0_090082_2021-11-02_final
2021-11-05 10:42:50	ga_ls8c_ard_3-2-0_104073_2021-11-05_final
2021-11-15 09:42:34	ga_ls8c_ard_3-2-0_094077_2021-11-15_final
2021-11-16 10:25:25	ga_ls8c_ard_3-2-0_101076_2021-11-16_final
2021-11-24 11:16:52	ga_ls8c_ard_3-2-0_109081_2021-11-24_final
2021-11-30 10:35:48	ga_ls8c_ard_3-2-0_103071_2021-11-30_final
2021-12-01 09:43:23	ga_ls8c_ard_3-2-0_094079_2021-12-01_final
2021-12-06 10:03:55	ga_ls8c_ard_3-2-1_097084_2021-12-06_final
2021-12-14 10:52:09	ga_ls8c_ard_3-2-1_105081_2021-12-14_final
2021-12-20 10:12:15	ga_ls8c_ard_3-2-1_099074_2021-12-20_final
2022-01-08 10:44:40	ga_ls8c_ard_3-2-1_104078_2022-01-08_final
2022-01-16 09:57:11	ga_ls8c_ard_3-2-1_096083_2022-01-16_final
2022-02-10 11:27:00	ga_ls8c_ard_3-2-1_111076_2022-02-10_final
2022-02-13 10:18:12	ga_ls8c_ard_3-2-1_100074_2022-02-13_final
2022-02-15 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-02-15_final
2022-02-15 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-02-15_final
2022-02-27 10:31:41	ga_ls8c_ard_3-2-1_102077_2022-02-27_final
2022-03-04 10:48:13	ga_ls8c_ard_3-2-1_105072_2022-03-04_final
2022-03-08 10:23:52	ga_ls8c_ard_3-2-1_101073_2022-03-08_final
2022-03-10 10:12:18	ga_ls8c_ard_3-2-1_099075_2022-03-10_final
2022-03-16 09:37:34	ga_ls8c_ard_3-2-1_093081_2022-03-16_final
2022-03-31 10:30:12	ga_ls8c_ard_3-2-1_102074_2022-03-31_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-20 11:45:39	ga_ls8c_ard_3-2-1_114077_2022-04-20_final
2022-05-03 11:12:44	ga_ls8c_ard_3-2-1_109072_2022-05-03_final
2022-05-11 10:24:59	ga_ls8c_ard_3-2-1_101076_2022-05-11_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-17 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-17_final
2022-07-24 09:26:01	ga_ls8c_ard_3-2-1_091082_2022-07-23_final
2022-07-27 09:52:33	ga_ls8c_ard_3-2-1_096071_2022-07-27_final
2022-07-31 11:05:58	ga_ls8c_ard_3-2-1_108069_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-05 11:28:32	ga_ls8c_ard_3-2-1_111079_2022-08-05_final
2022-08-07 11:13:48	ga_ls8c_ard_3-2-1_109073_2022-08-07_final
2022-08-09 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-08-08_final
2022-08-14 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-08-14_final
2022-08-16 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-08-16_final
2022-08-17 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-08-17_final
2022-08-30 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-08-30_final
2022-09-02 10:15:14	ga_ls8c_ard_3-2-1_099081_2022-09-02_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-20 10:01:00	ga_ls8c_ard_3-2-1_097076_2022-09-20_final
2022-09-29 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-09-29_final
2022-10-02 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-10-02_final
2022-10-12 09:24:36	ga_ls8c_ard_3-2-1_091078_2022-10-11_final
2022-10-15 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-10-15_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-12 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-11-12_final
2022-11-27 11:13:53	ga_ls8c_ard_3-2-1_109073_2022-11-27_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-25 09:59:09	ga_ls8c_ard_3-2-1_097072_2022-12-25_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-02-13 09:47:53	ga_ls8c_ard_3-2-1_095075_2023-02-13_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-15 11:15:11	ga_ls8c_ard_3-2-1_109077_2023-02-15_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-22 11:21:14	ga_ls8c_ard_3-2-1_110077_2023-02-22_final
2023-02-25 10:12:46	ga_ls8c_ard_3-2-1_099076_2023-02-25_final
2023-03-08 11:34:38	ga_ls8c_ard_3-2-1_112080_2023-03-08_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-21 09:27:57	ga_ls8c_ard_3-2-1_091088_2023-03-20_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-31 11:38:38	ga_ls8c_ard_3-2-1_113075_2023-03-31_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-02 09:48:09	ga_ls8c_ard_3-2-1_095077_2023-04-02_final
2023-04-09 09:52:11	ga_ls8c_ard_3-2-1_096072_2023-04-09_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-17 10:42:45	ga_ls8c_ard_3-2-1_104075_2023-04-17_final
2023-04-28 10:22:11	ga_ls8c_ard_3-2-1_101070_2023-04-28_final
2023-05-07 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-05-07_final
2023-05-13 11:20:48	ga_ls8c_ard_3-2-1_110078_2023-05-13_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