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
2015-10-07 09:33:40	ga_ls8c_ard_3-0-0_093071_2015-10-07_final
2015-10-07 09:34:04	ga_ls8c_ard_3-0-0_093072_2015-10-07_final
2015-10-07 09:34:28	ga_ls8c_ard_3-0-0_093073_2015-10-07_final
2015-10-07 09:34:52	ga_ls8c_ard_3-0-0_093074_2015-10-07_final
2015-10-07 09:35:16	ga_ls8c_ard_3-0-0_093075_2015-10-07_final
2015-10-07 09:35:39	ga_ls8c_ard_3-0-0_093076_2015-10-07_final
2015-10-07 09:36:03	ga_ls8c_ard_3-0-0_093077_2015-10-07_final
2015-10-21 09:44:28	ga_ls8c_ard_3-0-0_095067_2015-10-21_final
2015-11-06 09:44:31	ga_ls8c_ard_3-0-0_095067_2015-11-06_final
2015-11-08 09:33:45	ga_ls8c_ard_3-0-0_093071_2015-11-08_final
2015-11-08 09:34:09	ga_ls8c_ard_3-0-0_093072_2015-11-08_final
2015-11-08 09:34:33	ga_ls8c_ard_3-0-0_093073_2015-11-08_final
2015-11-08 09:34:57	ga_ls8c_ard_3-0-0_093074_2015-11-08_final
2015-11-08 09:35:21	ga_ls8c_ard_3-0-0_093075_2015-11-08_final
2015-11-08 09:35:45	ga_ls8c_ard_3-0-0_093076_2015-11-08_final
2015-11-08 09:36:09	ga_ls8c_ard_3-0-0_093077_2015-11-08_final
2018-02-15 09:44:13	ga_ls8c_ard_3-0-0_095067_2018-02-15_final
2018-02-17 09:33:26	ga_ls8c_ard_3-0-0_093071_2018-02-17_final
2018-02-17 09:33:50	ga_ls8c_ard_3-0-0_093072_2018-02-17_final
2018-02-17 09:34:14	ga_ls8c_ard_3-0-0_093073_2018-02-17_final
2018-02-17 09:34:38	ga_ls8c_ard_3-0-0_093074_2018-02-17_final
2018-02-17 09:35:02	ga_ls8c_ard_3-0-0_093075_2018-02-17_final
2018-02-17 09:35:26	ga_ls8c_ard_3-0-0_093076_2018-02-17_final
2018-02-17 09:35:50	ga_ls8c_ard_3-0-0_093077_2018-02-17_final
2018-04-20 09:43:40	ga_ls8c_ard_3-0-0_095067_2018-04-20_final
2018-05-19 09:19:15	ga_ls8c_ard_3-0-0_090084_2018-05-18_final
2018-05-19 09:19:39	ga_ls8c_ard_3-0-0_090085_2018-05-18_final
2018-05-19 09:20:03	ga_ls8c_ard_3-0-0_090086_2018-05-18_final
2018-05-19 09:20:27	ga_ls8c_ard_3-0-0_090087_2018-05-18_final
2018-05-19 09:20:51	ga_ls8c_ard_3-0-0_090088_2018-05-18_final
2018-05-19 09:21:15	ga_ls8c_ard_3-0-0_090089_2018-05-18_final
2018-05-22 09:43:20	ga_ls8c_ard_3-0-0_095067_2018-05-22_final
2018-06-04 09:19:04	ga_ls8c_ard_3-0-0_090084_2018-06-03_final
2018-06-04 09:19:28	ga_ls8c_ard_3-0-0_090085_2018-06-03_final
2018-06-04 09:19:52	ga_ls8c_ard_3-0-0_090086_2018-06-03_final
2018-06-04 09:20:16	ga_ls8c_ard_3-0-0_090087_2018-06-03_final
2018-06-04 09:20:40	ga_ls8c_ard_3-0-0_090088_2018-06-03_final
2018-06-04 09:21:04	ga_ls8c_ard_3-0-0_090089_2018-06-03_final
2018-06-07 09:43:12	ga_ls8c_ard_3-0-0_095067_2018-06-07_final
2022-02-21 09:29:29	ga_ls8c_ard_3-2-1_092076_2022-02-20_final
2022-02-21 09:29:53	ga_ls8c_ard_3-2-1_092077_2022-02-20_final
2022-02-21 09:30:17	ga_ls8c_ard_3-2-1_092078_2022-02-21_final
2022-02-21 09:30:41	ga_ls8c_ard_3-2-1_092079_2022-02-21_final
2022-02-21 09:31:05	ga_ls8c_ard_3-2-1_092080_2022-02-21_final
2022-02-21 09:31:29	ga_ls8c_ard_3-2-1_092081_2022-02-21_final
2022-02-23 09:20:19	ga_ls8c_ard_3-2-1_090084_2022-02-22_final
2022-05-03 09:33:27	ga_ls8c_ard_3-2-1_093071_2022-05-03_final
2022-05-03 09:33:51	ga_ls8c_ard_3-2-1_093072_2022-05-03_final
2022-05-03 09:34:15	ga_ls8c_ard_3-2-1_093073_2022-05-03_final
2022-05-03 09:34:39	ga_ls8c_ard_3-2-1_093074_2022-05-03_final
2022-05-03 09:35:03	ga_ls8c_ard_3-2-1_093075_2022-05-03_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-05 09:24:43	ga_ls8c_ard_3-2-1_091080_2022-05-04_final
2022-05-05 09:25:07	ga_ls8c_ard_3-2-1_091081_2022-05-04_final
2022-05-05 09:25:31	ga_ls8c_ard_3-2-1_091082_2022-05-04_final
2022-05-05 09:25:55	ga_ls8c_ard_3-2-1_091083_2022-05-04_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-07 09:15:34	ga_ls8c_ard_3-2-1_089088_2022-05-06_final
2022-05-07 09:15:58	ga_ls8c_ard_3-2-1_089089_2022-05-06_final
2022-05-07 09:16:22	ga_ls8c_ard_3-2-1_089090_2022-05-06_final
2023-06-09 09:24:17	ga_ls8c_ard_3-2-1_091080_2023-06-08_final
2023-06-09 09:24:41	ga_ls8c_ard_3-2-1_091081_2023-06-08_final
2023-06-09 09:25:05	ga_ls8c_ard_3-2-1_091082_2023-06-08_final
2023-06-09 09:25:29	ga_ls8c_ard_3-2-1_091083_2023-06-08_final
2023-06-09 09:25:53	ga_ls8c_ard_3-2-1_091084_2023-06-08_final
2023-06-09 09:26:17	ga_ls8c_ard_3-2-1_091085_2023-06-08_final
2023-06-11 09:15:08	ga_ls8c_ard_3-2-1_089088_2023-06-10_final
2023-06-11 09:15:32	ga_ls8c_ard_3-2-1_089089_2023-06-10_final
2023-06-11 09:15:56	ga_ls8c_ard_3-2-1_089090_2023-06-10_final
2023-06-14 09:39:17	ga_ls8c_ard_3-2-1_094071_2023-06-14_final
2023-06-14 09:39:41	ga_ls8c_ard_3-2-1_094072_2023-06-14_final
2023-06-16 09:28:31	ga_ls8c_ard_3-2-1_092075_2023-06-15_final
2023-06-16 09:28:55	ga_ls8c_ard_3-2-1_092076_2023-06-15_final
2023-06-16 09:29:19	ga_ls8c_ard_3-2-1_092077_2023-06-15_final
2023-06-16 09:29:43	ga_ls8c_ard_3-2-1_092078_2023-06-15_final
2023-06-16 09:30:07	ga_ls8c_ard_3-2-1_092079_2023-06-16_final
2023-06-16 09:30:31	ga_ls8c_ard_3-2-1_092080_2023-06-16_final
2023-06-16 09:30:55	ga_ls8c_ard_3-2-1_092081_2023-06-16_final
2023-06-18 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-06-17_final
2023-06-18 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-06-17_final
2023-06-18 09:20:33	ga_ls8c_ard_3-2-1_090086_2023-06-17_final
2023-06-18 09:20:57	ga_ls8c_ard_3-2-1_090087_2023-06-17_final
2023-06-18 09:21:21	ga_ls8c_ard_3-2-1_090088_2023-06-17_final
2023-06-18 09:21:45	ga_ls8c_ard_3-2-1_090089_2023-06-17_final
2023-06-25 09:24:23	ga_ls8c_ard_3-2-1_091080_2023-06-24_final
2023-06-25 09:24:47	ga_ls8c_ard_3-2-1_091081_2023-06-24_final
2023-06-25 09:25:11	ga_ls8c_ard_3-2-1_091082_2023-06-24_final
2023-06-25 09:25:35	ga_ls8c_ard_3-2-1_091083_2023-06-24_final
2023-06-25 09:25:59	ga_ls8c_ard_3-2-1_091084_2023-06-24_final
2023-06-25 09:26:23	ga_ls8c_ard_3-2-1_091085_2023-06-24_final
2023-06-27 09:15:15	ga_ls8c_ard_3-2-1_089088_2023-06-26_final
2023-06-27 09:15:39	ga_ls8c_ard_3-2-1_089089_2023-06-26_final
2023-06-27 09:16:03	ga_ls8c_ard_3-2-1_089090_2023-06-26_final
2023-07-02 09:28:41	ga_ls8c_ard_3-2-1_092075_2023-07-01_final
2023-07-02 09:29:05	ga_ls8c_ard_3-2-1_092076_2023-07-01_final
2023-07-02 09:29:29	ga_ls8c_ard_3-2-1_092077_2023-07-01_final
2023-07-02 09:29:53	ga_ls8c_ard_3-2-1_092078_2023-07-01_final
2023-07-02 09:30:16	ga_ls8c_ard_3-2-1_092079_2023-07-02_final
2023-07-02 09:30:40	ga_ls8c_ard_3-2-1_092080_2023-07-02_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