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
2018-09-16 10:07:46	ga_ls8c_ard_3-0-0_098080_2018-09-16_final
2018-09-16 10:08:10	ga_ls8c_ard_3-0-0_098081_2018-09-16_final
2018-09-16 10:08:34	ga_ls8c_ard_3-0-0_098082_2018-09-16_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-10-04 09:58:20	ga_ls8c_ard_3-0-0_096087_2018-10-04_final
2018-10-07 10:21:16	ga_ls8c_ard_3-0-0_101067_2018-10-07_final
2018-10-07 10:21:40	ga_ls8c_ard_3-0-0_101068_2018-10-07_final
2018-10-07 10:22:04	ga_ls8c_ard_3-0-0_101069_2018-10-07_final
2018-10-07 10:22:28	ga_ls8c_ard_3-0-0_101070_2018-10-07_final
2018-10-07 10:22:52	ga_ls8c_ard_3-0-0_101071_2018-10-07_final
2018-10-07 10:23:16	ga_ls8c_ard_3-1-0_101072_2018-10-07_final
2018-12-23 09:58:27	ga_ls8c_ard_3-0-0_096087_2018-12-23_final
2018-12-26 10:21:22	ga_ls8c_ard_3-0-0_101067_2018-12-26_final
2018-12-26 10:21:46	ga_ls8c_ard_3-0-0_101068_2018-12-26_final
2018-12-26 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-12-26_final
2018-12-26 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-12-26_final
2018-12-26 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-26_final
2018-12-26 10:23:22	ga_ls8c_ard_3-1-0_101072_2018-12-26_final
2019-01-06 10:08:00	ga_ls8c_ard_3-0-0_098080_2019-01-06_final
2019-01-06 10:08:24	ga_ls8c_ard_3-0-0_098081_2019-01-06_final
2019-01-06 10:08:48	ga_ls8c_ard_3-0-0_098082_2019-01-06_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-07-06 10:21:25	ga_ls8c_ard_3-1-0_101067_2019-07-06_final
2019-07-06 10:21:49	ga_ls8c_ard_3-1-0_101068_2019-07-06_final
2019-07-06 10:22:13	ga_ls8c_ard_3-1-0_101069_2019-07-06_final
2019-07-06 10:22:36	ga_ls8c_ard_3-1-0_101070_2019-07-06_final
2019-07-06 10:23:00	ga_ls8c_ard_3-1-0_101071_2019-07-06_final
2019-07-06 10:23:24	ga_ls8c_ard_3-1-0_101072_2019-07-06_final
2019-07-17 10:08:05	ga_ls8c_ard_3-1-0_098080_2019-07-17_final
2019-07-17 10:08:29	ga_ls8c_ard_3-1-0_098081_2019-07-17_final
2019-07-17 10:08:53	ga_ls8c_ard_3-1-0_098082_2019-07-17_final
2019-07-17 10:09:17	ga_ls8c_ard_3-1-0_098083_2019-07-17_final
2019-07-17 10:09:41	ga_ls8c_ard_3-1-0_098084_2019-07-17_final
2019-07-17 10:10:05	ga_ls8c_ard_3-1-0_098085_2019-07-17_final
2019-07-24 10:12:19	ga_ls8c_ard_3-1-0_099075_2019-07-24_final
2019-07-24 10:12:43	ga_ls8c_ard_3-1-0_099076_2019-07-24_final
2019-07-24 10:13:07	ga_ls8c_ard_3-1-0_099077_2019-07-24_final
2019-07-24 10:13:31	ga_ls8c_ard_3-1-0_099078_2019-07-24_final
2019-07-24 10:13:55	ga_ls8c_ard_3-1-0_099079_2019-07-24_final
2019-07-24 10:14:19	ga_ls8c_ard_3-1-0_099080_2019-07-24_final
2019-07-24 10:14:43	ga_ls8c_ard_3-1-0_099081_2019-07-24_final
2019-07-26 10:03:34	ga_ls8c_ard_3-1-0_097084_2019-07-26_final
2019-07-26 10:03:58	ga_ls8c_ard_3-1-0_097085_2019-07-26_final
2019-07-26 10:04:22	ga_ls8c_ard_3-1-0_097086_2019-07-26_final
2019-08-07 10:21:35	ga_ls8c_ard_3-1-0_101067_2019-08-07_final
2019-08-07 10:21:59	ga_ls8c_ard_3-1-0_101068_2019-08-07_final
2019-08-07 10:22:23	ga_ls8c_ard_3-1-0_101069_2019-08-07_final
2019-08-18 10:08:17	ga_ls8c_ard_3-1-0_098080_2019-08-18_final
2019-08-18 10:08:41	ga_ls8c_ard_3-1-0_098081_2019-08-18_final
2019-08-18 10:09:05	ga_ls8c_ard_3-1-0_098082_2019-08-18_final
2019-08-18 10:09:29	ga_ls8c_ard_3-1-0_098083_2019-08-18_final
2019-08-18 10:09:53	ga_ls8c_ard_3-1-0_098084_2019-08-18_final
2019-08-18 10:10:17	ga_ls8c_ard_3-1-0_098085_2019-08-18_final
2019-08-20 09:58:44	ga_ls8c_ard_3-1-0_096087_2019-08-20_final
2019-08-23 10:21:40	ga_ls8c_ard_3-1-0_101067_2019-08-23_final
2019-08-23 10:22:03	ga_ls8c_ard_3-1-0_101068_2019-08-23_final
2019-08-23 10:22:27	ga_ls8c_ard_3-1-0_101069_2019-08-23_final
2019-08-23 10:22:51	ga_ls8c_ard_3-1-0_101070_2019-08-23_final
2019-08-23 10:23:15	ga_ls8c_ard_3-1-0_101071_2019-08-23_final
2019-08-23 10:23:39	ga_ls8c_ard_3-1-0_101072_2019-08-23_final
2019-09-03 10:08:20	ga_ls8c_ard_3-1-0_098080_2019-09-03_final
2019-09-03 10:08:44	ga_ls8c_ard_3-1-0_098081_2019-09-03_final
2019-09-03 10:09:08	ga_ls8c_ard_3-1-0_098082_2019-09-03_final
2019-09-03 10:09:32	ga_ls8c_ard_3-1-0_098083_2019-09-03_final
2019-09-03 10:09:56	ga_ls8c_ard_3-1-0_098084_2019-09-03_final
2019-09-03 10:10:20	ga_ls8c_ard_3-1-0_098085_2019-09-03_final
2019-10-05 10:08:30	ga_ls8c_ard_3-1-0_098080_2019-10-05_final
2019-10-05 10:08:54	ga_ls8c_ard_3-1-0_098081_2019-10-05_final
2019-10-05 10:09:18	ga_ls8c_ard_3-1-0_098082_2019-10-05_final
2019-10-05 10:09:42	ga_ls8c_ard_3-1-0_098083_2019-10-05_final
2019-10-05 10:10:06	ga_ls8c_ard_3-1-0_098084_2019-10-05_final
2019-10-05 10:10:30	ga_ls8c_ard_3-1-0_098085_2019-10-05_final
2019-10-07 09:58:57	ga_ls8c_ard_3-1-0_096087_2019-10-07_final
2019-10-21 10:08:32	ga_ls8c_ard_3-1-0_098080_2019-10-21_final
2019-10-21 10:08:56	ga_ls8c_ard_3-1-0_098081_2019-10-21_final
2019-10-21 10:09:20	ga_ls8c_ard_3-1-0_098082_2019-10-21_final
2019-10-21 10:09:44	ga_ls8c_ard_3-1-0_098083_2019-10-21_final
2019-10-21 10:10:08	ga_ls8c_ard_3-1-0_098084_2019-10-21_final
2019-10-21 10:10:32	ga_ls8c_ard_3-1-0_098085_2019-10-21_final
2023-07-05 10:03:12	ga_ls8c_ard_3-2-1_097084_2023-07-05_final
2023-07-05 10:03:36	ga_ls8c_ard_3-2-1_097085_2023-07-05_final
2023-07-10 10:16:36	ga_ls8c_ard_3-2-1_100071_2023-07-10_final
2023-07-10 10:17:00	ga_ls8c_ard_3-2-1_100072_2023-07-10_final
2023-07-10 10:17:24	ga_ls8c_ard_3-2-1_100073_2023-07-10_final
2023-07-10 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-07-10_final
2023-07-10 10:18:11	ga_ls8c_ard_3-2-1_100075_2023-07-10_final
2023-07-10 10:18:35	ga_ls8c_ard_3-2-1_100076_2023-07-10_final
2023-07-12 10:07:50	ga_ls8c_ard_3-2-1_098080_2023-07-12_final
2023-07-12 10:08:14	ga_ls8c_ard_3-2-1_098081_2023-07-12_final
2023-07-12 10:08:38	ga_ls8c_ard_3-2-1_098082_2023-07-12_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-17 10:22:00	ga_ls8c_ard_3-2-1_101069_2023-07-17_final
2023-07-17 10:22:24	ga_ls8c_ard_3-2-1_101070_2023-07-17_final
2023-07-17 10:22:47	ga_ls8c_ard_3-2-1_101071_2023-07-17_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