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
2019-02-04 09:33:25	ga_ls8c_ard_3-0-0_093071_2019-02-04_final
2019-02-04 09:33:48	ga_ls8c_ard_3-0-0_093072_2019-02-04_final
2019-02-04 09:34:12	ga_ls8c_ard_3-0-0_093073_2019-02-04_final
2019-02-04 09:34:36	ga_ls8c_ard_3-0-0_093074_2019-02-04_final
2019-02-04 09:35:00	ga_ls8c_ard_3-0-0_093075_2019-02-04_final
2019-02-04 09:35:24	ga_ls8c_ard_3-0-0_093076_2019-02-04_final
2019-02-06 09:24:38	ga_ls8c_ard_3-0-0_091080_2019-02-05_final
2019-02-06 09:25:02	ga_ls8c_ard_3-0-0_091081_2019-02-05_final
2019-02-06 09:25:26	ga_ls8c_ard_3-0-0_091082_2019-02-05_final
2019-02-06 09:25:50	ga_ls8c_ard_3-0-0_091083_2019-02-05_final
2019-02-06 09:26:14	ga_ls8c_ard_3-0-0_091084_2019-02-05_final
2019-02-06 09:26:38	ga_ls8c_ard_3-0-0_091085_2019-02-05_final
2019-02-08 09:15:04	ga_ls8c_ard_3-0-0_089087_2019-02-07_final
2019-02-08 09:15:28	ga_ls8c_ard_3-0-0_089088_2019-02-07_final
2019-02-08 09:15:52	ga_ls8c_ard_3-0-0_089089_2019-02-07_final
2019-02-08 09:16:16	ga_ls8c_ard_3-0-0_089090_2019-02-07_final
2019-03-19 09:19:53	ga_ls8c_ard_3-1-0_090084_2019-03-18_final
2019-03-19 09:20:17	ga_ls8c_ard_3-1-0_090085_2019-03-18_final
2019-03-19 09:20:41	ga_ls8c_ard_3-1-0_090086_2019-03-18_final
2019-03-19 09:21:04	ga_ls8c_ard_3-1-0_090087_2019-03-18_final
2019-03-19 09:21:28	ga_ls8c_ard_3-1-0_090088_2019-03-18_final
2019-03-19 09:21:52	ga_ls8c_ard_3-1-0_090089_2019-03-18_final
2019-04-04 09:19:49	ga_ls8c_ard_3-1-0_090084_2019-04-03_final
2019-04-04 09:20:13	ga_ls8c_ard_3-1-0_090085_2019-04-03_final
2019-04-04 09:20:37	ga_ls8c_ard_3-1-0_090086_2019-04-03_final
2019-04-04 09:21:01	ga_ls8c_ard_3-1-0_090087_2019-04-03_final
2019-04-04 09:21:25	ga_ls8c_ard_3-1-0_090088_2019-04-03_final
2019-04-04 09:21:49	ga_ls8c_ard_3-1-0_090089_2019-04-03_final
2019-05-06 09:19:22	ga_ls8c_ard_3-0-0_090083_2019-05-05_final
2019-05-06 09:19:46	ga_ls8c_ard_3-0-0_090084_2019-05-05_final
2019-05-06 09:20:09	ga_ls8c_ard_3-0-0_090085_2019-05-05_final
2019-05-06 09:20:33	ga_ls8c_ard_3-0-0_090086_2019-05-05_final
2019-05-06 09:20:57	ga_ls8c_ard_3-0-0_090087_2019-05-05_final
2019-05-06 09:21:21	ga_ls8c_ard_3-0-0_090088_2019-05-05_final
2019-05-06 09:21:45	ga_ls8c_ard_3-0-0_090089_2019-05-05_final
2019-05-22 09:19:32	ga_ls8c_ard_3-0-0_090083_2019-05-21_final
2019-05-22 09:19:56	ga_ls8c_ard_3-0-0_090084_2019-05-21_final
2019-05-22 09:20:20	ga_ls8c_ard_3-0-0_090085_2019-05-21_final
2019-05-22 09:20:44	ga_ls8c_ard_3-0-0_090086_2019-05-21_final
2019-05-22 09:21:08	ga_ls8c_ard_3-0-0_090087_2019-05-21_final
2019-05-22 09:21:32	ga_ls8c_ard_3-0-0_090088_2019-05-21_final
2019-05-22 09:21:56	ga_ls8c_ard_3-0-0_090089_2019-05-21_final
2019-07-18 09:15:15	ga_ls8c_ard_3-1-0_089087_2019-07-17_final
2019-07-18 09:15:39	ga_ls8c_ard_3-1-0_089088_2019-07-17_final
2019-07-18 09:16:03	ga_ls8c_ard_3-1-0_089089_2019-07-17_final
2019-07-18 09:16:27	ga_ls8c_ard_3-1-0_089090_2019-07-17_final
2019-07-23 09:29:03	ga_ls8c_ard_3-1-0_092075_2019-07-22_final
2019-07-23 09:29:27	ga_ls8c_ard_3-1-0_092076_2019-07-22_final
2019-07-23 09:29:51	ga_ls8c_ard_3-1-0_092077_2019-07-22_final
2019-07-23 09:30:15	ga_ls8c_ard_3-1-0_092078_2019-07-23_final
2019-07-23 09:30:38	ga_ls8c_ard_3-1-0_092079_2019-07-23_final
2019-07-23 09:31:02	ga_ls8c_ard_3-1-0_092080_2019-07-23_final
2019-07-23 09:31:26	ga_ls8c_ard_3-1-0_092081_2019-07-23_final
2019-07-25 09:20:18	ga_ls8c_ard_3-1-0_090084_2019-07-24_final
2019-07-25 09:20:41	ga_ls8c_ard_3-1-0_090085_2019-07-24_final
2019-07-25 09:21:05	ga_ls8c_ard_3-1-0_090086_2019-07-24_final
2019-07-25 09:21:29	ga_ls8c_ard_3-1-0_090087_2019-07-24_final
2019-07-25 09:21:53	ga_ls8c_ard_3-1-0_090088_2019-07-24_final
2019-07-25 09:22:17	ga_ls8c_ard_3-1-0_090089_2019-07-24_final
2019-09-09 09:29:18	ga_ls8c_ard_3-1-0_092075_2019-09-08_final
2019-09-09 09:29:42	ga_ls8c_ard_3-1-0_092076_2019-09-08_final
2019-09-09 09:30:05	ga_ls8c_ard_3-1-0_092077_2019-09-09_final
2019-09-09 09:30:29	ga_ls8c_ard_3-1-0_092078_2019-09-09_final
2019-09-09 09:30:53	ga_ls8c_ard_3-1-0_092079_2019-09-09_final
2019-09-09 09:31:17	ga_ls8c_ard_3-1-0_092080_2019-09-09_final
2019-09-09 09:31:41	ga_ls8c_ard_3-1-0_092081_2019-09-09_final
2019-09-11 09:20:32	ga_ls8c_ard_3-1-0_090084_2019-09-10_final
2019-09-11 09:20:56	ga_ls8c_ard_3-1-0_090085_2019-09-10_final
2019-09-11 09:21:20	ga_ls8c_ard_3-1-0_090086_2019-09-10_final
2019-09-11 09:21:44	ga_ls8c_ard_3-1-0_090087_2019-09-10_final
2019-09-11 09:22:08	ga_ls8c_ard_3-1-0_090088_2019-09-10_final
2019-09-11 09:22:32	ga_ls8c_ard_3-1-0_090089_2019-09-10_final
2021-08-20 09:33:49	ga_ls8c_ard_3-2-0_093071_2021-08-20_final
2021-08-20 09:34:13	ga_ls8c_ard_3-2-0_093072_2021-08-20_final
2021-08-20 09:34:37	ga_ls8c_ard_3-2-0_093073_2021-08-20_final
2021-08-20 09:35:01	ga_ls8c_ard_3-2-0_093074_2021-08-20_final
2021-08-20 09:35:25	ga_ls8c_ard_3-2-0_093075_2021-08-20_final
2021-08-20 09:35:48	ga_ls8c_ard_3-2-0_093076_2021-08-20_final
2021-08-22 09:25:03	ga_ls8c_ard_3-2-0_091080_2021-08-21_final
2021-08-22 09:25:27	ga_ls8c_ard_3-2-0_091081_2021-08-21_final
2021-08-22 09:25:51	ga_ls8c_ard_3-2-0_091082_2021-08-21_final
2021-08-22 09:26:15	ga_ls8c_ard_3-2-0_091083_2021-08-21_final
2021-08-22 09:26:39	ga_ls8c_ard_3-2-0_091084_2021-08-21_final
2021-08-22 09:27:03	ga_ls8c_ard_3-2-0_091085_2021-08-21_final
2021-10-21 09:44:50	ga_ls8c_ard_3-2-0_095067_2021-10-21_final
2021-10-23 09:34:05	ga_ls8c_ard_3-2-0_093071_2021-10-23_final
2021-10-23 09:34:29	ga_ls8c_ard_3-2-0_093072_2021-10-23_final
2021-10-23 09:34:53	ga_ls8c_ard_3-2-0_093073_2021-10-23_final
2021-10-23 09:35:16	ga_ls8c_ard_3-2-0_093074_2021-10-23_final
2021-10-23 09:35:40	ga_ls8c_ard_3-2-0_093075_2021-10-23_final
2021-10-23 09:36:04	ga_ls8c_ard_3-2-0_093076_2021-10-23_final
2021-10-25 09:25:18	ga_ls8c_ard_3-2-0_091080_2021-10-24_final
2021-10-25 09:25:42	ga_ls8c_ard_3-2-0_091081_2021-10-24_final
2021-10-25 09:26:06	ga_ls8c_ard_3-2-0_091082_2021-10-24_final
2021-10-25 09:26:30	ga_ls8c_ard_3-2-0_091083_2021-10-24_final
2021-10-25 09:26:54	ga_ls8c_ard_3-2-0_091084_2021-10-24_final
2021-10-25 09:27:18	ga_ls8c_ard_3-2-0_091085_2021-10-24_final
2022-01-04 09:30:30	ga_ls8c_ard_3-2-1_092078_2022-01-04_final
2022-01-04 09:30:54	ga_ls8c_ard_3-2-1_092079_2022-01-04_final
2022-01-04 09:31:18	ga_ls8c_ard_3-2-1_092080_2022-01-04_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