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
2022-07-10 09:14:45	ga_ls8c_ard_3-2-1_089085_2022-07-09_final
2022-07-13 09:40:51	ga_ls8c_ard_3-2-1_094073_2022-07-13_final
2022-07-14 10:27:18	ga_ls8c_ard_3-2-1_101081_2022-07-14_final
2022-07-22 09:37:33	ga_ls8c_ard_3-2-1_093080_2022-07-22_final
2022-07-26 09:14:52	ga_ls8c_ard_3-2-1_089085_2022-07-25_final
2022-07-29 09:41:25	ga_ls8c_ard_3-2-1_094074_2022-07-29_final
2022-07-31 11:05:58	ga_ls8c_ard_3-2-1_108069_2022-07-31_final
2022-08-09 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-08-08_final
2022-08-09 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-08-09_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-19 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-08-19_final
2022-08-25 09:24:13	ga_ls8c_ard_3-2-1_091077_2022-08-24_final
2022-08-27 10:52:44	ga_ls8c_ard_3-2-1_105082_2022-08-27_final
2022-09-10 09:24:16	ga_ls8c_ard_3-2-1_091077_2022-09-09_final
2022-09-11 11:47:14	ga_ls8c_ard_3-2-1_114079_2022-09-11_final
2022-09-12 09:15:31	ga_ls8c_ard_3-2-1_089086_2022-09-11_final
2022-09-13 11:35:41	ga_ls8c_ard_3-2-1_112081_2022-09-13_final
2022-09-15 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-09-15_final
2022-09-17 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-09-17_final
2022-09-18 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-09-18_final
2022-10-05 10:58:59	ga_ls8c_ard_3-2-1_106082_2022-10-05_final
2022-10-12 09:24:12	ga_ls8c_ard_3-2-1_091077_2022-10-11_final
2022-10-13 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-10-13_final
2022-10-14 09:15:24	ga_ls8c_ard_3-2-1_089086_2022-10-13_final
2022-10-26 09:35:28	ga_ls8c_ard_3-2-1_093074_2022-10-26_final
2022-10-30 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-10-29_final
2022-11-02 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-11-02_final
2022-11-14 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-14_final
2022-11-14 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-14_final
2022-11-14 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-14_final
2022-11-17 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-11-17_final
2022-11-18 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-11-18_final
2022-11-21 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-11-21_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-12-01 10:51:34	ga_ls8c_ard_3-2-1_105079_2022-12-01_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-09 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-12-09_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-10 10:44:57	ga_ls8c_ard_3-2-1_104078_2022-12-10_final
2022-12-12 10:30:59	ga_ls8c_ard_3-2-1_102074_2022-12-12_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-16 10:08:13	ga_ls8c_ard_3-2-1_098079_2022-12-16_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-22 11:11:07	ga_ls8c_ard_3-2-1_108082_2022-12-22_final
2022-12-25 11:41:14	ga_ls8c_ard_3-2-1_113080_2022-12-25_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2022-12-27 11:29:17	ga_ls8c_ard_3-2-1_111081_2022-12-27_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2022-12-30 10:18:31	ga_ls8c_ard_3-2-1_100074_2022-12-30_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2023-01-01 10:06:33	ga_ls8c_ard_3-2-1_098075_2023-01-01_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-03 11:35:05	ga_ls8c_ard_3-2-1_112080_2023-01-03_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-06 10:25:29	ga_ls8c_ard_3-2-1_101076_2023-01-06_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-09 09:19:29	ga_ls8c_ard_3-2-1_090081_2023-01-08_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-14 11:15:39	ga_ls8c_ard_3-2-1_109078_2023-01-14_final
2023-01-19 09:52:52	ga_ls8c_ard_3-2-1_096072_2023-01-19_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-21 09:44:56	ga_ls8c_ard_3-2-1_094083_2023-01-21_final
2023-01-21 11:21:25	ga_ls8c_ard_3-2-1_110077_2023-01-21_final
2023-01-30 11:17:42	ga_ls8c_ard_3-2-1_109083_2023-01-30_final
2023-02-01 09:25:39	ga_ls8c_ard_3-2-1_091081_2023-01-31_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-15 09:35:54	ga_ls8c_ard_3-2-1_093076_2023-02-15_final
2023-02-18 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-02-18_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-26 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-02-25_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-06 11:45:02	ga_ls8c_ard_3-2-1_114075_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-12 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-03-11_final
2023-03-12 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-03-12_final
2023-03-14 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-03-13_final
2023-03-15 10:03:31	ga_ls8c_ard_3-2-1_097084_2023-03-15_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-26 09:41:15	ga_ls8c_ard_3-2-1_094075_2023-03-26_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-03-28 11:10:09	ga_ls8c_ard_3-2-1_108081_2023-03-28_final
2023-03-30 09:20:05	ga_ls8c_ard_3-2-1_090084_2023-03-29_final
2023-04-02 11:29:02	ga_ls8c_ard_3-2-1_111082_2023-04-02_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-13 09:33:01	ga_ls8c_ard_3-2-1_092086_2023-04-13_final
2023-04-25 11:34:58	ga_ls8c_ard_3-2-1_112082_2023-04-25_final
2023-05-01 09:18:34	ga_ls8c_ard_3-2-1_090081_2023-04-30_final
2023-05-01 10:54:16	ga_ls8c_ard_3-2-1_106073_2023-05-01_final
2023-05-08 11:03:32	ga_ls8c_ard_3-2-1_107081_2023-05-08_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-10 09:13:03	ga_ls8c_ard_3-2-1_089083_2023-05-09_final
2023-05-10 09:13:27	ga_ls8c_ard_3-2-1_089084_2023-05-09_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