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
2018-11-03 11:44:33	ga_ls8c_ard_3-0-0_114074_2018-11-03_final
2018-11-03 11:44:57	ga_ls8c_ard_3-0-0_114075_2018-11-03_final
2018-11-03 11:45:21	ga_ls8c_ard_3-0-0_114076_2018-11-03_final
2018-11-03 11:45:45	ga_ls8c_ard_3-0-0_114077_2018-11-03_final
2018-11-03 11:46:09	ga_ls8c_ard_3-0-0_114078_2018-11-03_final
2018-11-05 11:34:59	ga_ls8c_ard_3-0-0_112081_2018-11-05_final
2018-11-05 11:35:23	ga_ls8c_ard_3-0-0_112082_2018-11-05_final
2018-11-05 11:35:47	ga_ls8c_ard_3-0-0_112083_2018-11-05_final
2018-11-05 11:36:11	ga_ls8c_ard_3-0-0_112084_2018-11-05_final
2018-11-05 11:36:35	ga_ls8c_ard_3-0-0_112085_2018-11-05_final
2018-11-10 11:50:20	ga_ls8c_ard_3-0-0_115073_2018-11-10_final
2018-11-12 11:39:35	ga_ls8c_ard_3-0-0_113077_2018-11-12_final
2018-11-12 11:39:59	ga_ls8c_ard_3-0-0_113078_2018-11-12_final
2018-11-12 11:40:23	ga_ls8c_ard_3-0-0_113079_2018-11-12_final
2018-11-12 11:40:47	ga_ls8c_ard_3-0-0_113080_2018-11-12_final
2018-11-12 11:41:10	ga_ls8c_ard_3-0-0_113081_2018-11-12_final
2018-11-12 11:41:34	ga_ls8c_ard_3-0-0_113082_2018-11-12_final
2018-11-19 11:44:34	ga_ls8c_ard_3-0-0_114074_2018-11-19_final
2018-11-19 11:44:58	ga_ls8c_ard_3-0-0_114075_2018-11-19_final
2018-11-19 11:45:22	ga_ls8c_ard_3-0-0_114076_2018-11-19_final
2018-11-19 11:45:46	ga_ls8c_ard_3-0-0_114077_2018-11-19_final
2018-11-19 11:46:09	ga_ls8c_ard_3-0-0_114078_2018-11-19_final
2018-11-21 11:35:00	ga_ls8c_ard_3-0-0_112081_2018-11-21_final
2018-11-21 11:35:24	ga_ls8c_ard_3-0-0_112082_2018-11-21_final
2018-11-21 11:35:47	ga_ls8c_ard_3-0-0_112083_2018-11-21_final
2018-11-21 11:36:11	ga_ls8c_ard_3-0-0_112084_2018-11-21_final
2018-11-21 11:36:35	ga_ls8c_ard_3-0-0_112085_2018-11-21_final
2018-12-05 11:44:32	ga_ls8c_ard_3-0-0_114074_2018-12-05_final
2018-12-05 11:44:56	ga_ls8c_ard_3-0-0_114075_2018-12-05_final
2018-12-05 11:45:20	ga_ls8c_ard_3-0-0_114076_2018-12-05_final
2018-12-05 11:45:44	ga_ls8c_ard_3-0-0_114077_2018-12-05_final
2018-12-05 11:46:07	ga_ls8c_ard_3-0-0_114078_2018-12-05_final
2018-12-07 11:34:57	ga_ls8c_ard_3-0-0_112081_2018-12-07_final
2018-12-07 11:35:21	ga_ls8c_ard_3-0-0_112082_2018-12-07_final
2018-12-07 11:35:45	ga_ls8c_ard_3-0-0_112083_2018-12-07_final
2018-12-07 11:36:09	ga_ls8c_ard_3-0-0_112084_2018-12-07_final
2018-12-07 11:36:33	ga_ls8c_ard_3-0-0_112085_2018-12-07_final
2018-12-14 11:39:31	ga_ls8c_ard_3-0-0_113077_2018-12-14_final
2018-12-14 11:39:54	ga_ls8c_ard_3-0-0_113078_2018-12-14_final
2018-12-14 11:40:18	ga_ls8c_ard_3-0-0_113079_2018-12-14_final
2018-12-14 11:40:42	ga_ls8c_ard_3-0-0_113080_2018-12-14_final
2018-12-14 11:41:06	ga_ls8c_ard_3-0-0_113081_2018-12-14_final
2018-12-14 11:41:30	ga_ls8c_ard_3-0-0_113082_2018-12-14_final
2019-01-24 11:34:51	ga_ls8c_ard_3-0-0_112081_2019-01-24_final
2019-01-24 11:35:15	ga_ls8c_ard_3-0-0_112082_2019-01-24_final
2019-01-24 11:35:39	ga_ls8c_ard_3-0-0_112083_2019-01-24_final
2019-01-24 11:36:03	ga_ls8c_ard_3-0-0_112084_2019-01-24_final
2019-01-24 11:36:27	ga_ls8c_ard_3-0-0_112085_2019-01-24_final
2019-12-10 11:35:22	ga_ls8c_ard_3-1-0_112081_2019-12-10_final
2019-12-10 11:35:46	ga_ls8c_ard_3-1-0_112082_2019-12-10_final
2019-12-10 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-12-10_final
2019-12-10 11:36:34	ga_ls8c_ard_3-1-0_112084_2019-12-10_final
2019-12-10 11:36:58	ga_ls8c_ard_3-1-0_112085_2019-12-10_final
2020-02-05 11:30:32	ga_ls8c_ard_3-1-0_111085_2020-02-05_final
2020-02-17 11:50:26	ga_ls8c_ard_3-1-0_115073_2020-02-17_final
2020-05-16 11:44:03	ga_ls8c_ard_3-1-0_114074_2020-05-16_final
2020-05-16 11:44:27	ga_ls8c_ard_3-1-0_114075_2020-05-16_final
2020-05-16 11:44:51	ga_ls8c_ard_3-1-0_114076_2020-05-16_final
2020-05-16 11:45:15	ga_ls8c_ard_3-1-0_114077_2020-05-16_final
2020-05-16 11:45:39	ga_ls8c_ard_3-1-0_114078_2020-05-16_final
2020-05-18 11:34:29	ga_ls8c_ard_3-1-0_112081_2020-05-18_final
2020-05-18 11:34:53	ga_ls8c_ard_3-1-0_112082_2020-05-18_final
2020-05-18 11:35:17	ga_ls8c_ard_3-1-0_112083_2020-05-18_final
2020-05-18 11:35:41	ga_ls8c_ard_3-1-0_112084_2020-05-18_final
2020-05-18 11:36:05	ga_ls8c_ard_3-1-0_112085_2020-05-18_final
2023-09-25 11:30:10	ga_ls8c_ard_3-2-1_111084_2023-09-25_final
2023-09-30 11:44:45	ga_ls8c_ard_3-2-1_114074_2023-09-30_final
2023-09-30 11:45:09	ga_ls8c_ard_3-2-1_114075_2023-09-30_final
2023-09-30 11:45:33	ga_ls8c_ard_3-2-1_114076_2023-09-30_final
2023-09-30 11:45:57	ga_ls8c_ard_3-2-1_114077_2023-09-30_final
2023-09-30 11:46:21	ga_ls8c_ard_3-2-1_114078_2023-09-30_final
2023-10-02 11:35:11	ga_ls8c_ard_3-2-1_112081_2023-10-02_final
2023-10-02 11:35:35	ga_ls8c_ard_3-2-1_112082_2023-10-02_final
2023-10-02 11:35:59	ga_ls8c_ard_3-2-1_112083_2023-10-02_final
2023-10-02 11:36:23	ga_ls8c_ard_3-2-1_112084_2023-10-02_final
2023-10-16 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-10-16_final
2023-10-16 11:45:11	ga_ls8c_ard_3-2-1_114075_2023-10-16_final
2023-10-16 11:45:35	ga_ls8c_ard_3-2-1_114076_2023-10-16_final
2023-10-16 11:45:59	ga_ls8c_ard_3-2-1_114077_2023-10-16_final
2023-10-16 11:46:23	ga_ls8c_ard_3-2-1_114078_2023-10-16_final
2023-10-25 11:39:50	ga_ls8c_ard_3-2-1_113077_2023-10-25_final
2023-10-25 11:40:14	ga_ls8c_ard_3-2-1_113078_2023-10-25_final
2023-10-25 11:40:38	ga_ls8c_ard_3-2-1_113079_2023-10-25_final
2023-10-25 11:41:02	ga_ls8c_ard_3-2-1_113080_2023-10-25_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-25 11:41:50	ga_ls8c_ard_3-2-1_113082_2023-10-25_final
2023-11-17 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-11-17_final
2023-11-17 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-11-17_final
2023-11-17 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-11-17_final
2023-11-17 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-17_final
2023-11-17 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-17_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_final
2023-11-19 11:36:05	ga_ls8c_ard_3-2-1_112083_2023-11-19_final
2023-11-19 11:36:29	ga_ls8c_ard_3-2-1_112084_2023-11-19_final
2023-11-26 11:39:53	ga_ls8c_ard_3-2-1_113077_2023-11-26_final
2023-11-26 11:40:17	ga_ls8c_ard_3-2-1_113078_2023-11-26_final
2023-11-26 11:40:41	ga_ls8c_ard_3-2-1_113079_2023-11-26_final
2023-11-26 11:41:05	ga_ls8c_ard_3-2-1_113080_2023-11-26_final
2023-11-26 11:41:29	ga_ls8c_ard_3-2-1_113081_2023-11-26_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years