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
2018-05-27 10:03:24	ga_ls8c_ard_3-0-0_098071_2018-05-27_final
2018-05-28 10:46:39	ga_ls8c_ard_3-0-0_105071_2018-05-28_final
2018-06-12 10:03:24	ga_ls8c_ard_3-0-0_098071_2018-06-12_final
2018-06-12 10:03:48	ga_ls8c_ard_3-0-0_098072_2018-06-12_final
2018-06-13 10:46:40	ga_ls8c_ard_3-0-0_105071_2018-06-13_final
2018-06-18 09:26:23	ga_ls8c_ard_3-0-0_092071_2018-06-17_final
2018-06-18 09:26:47	ga_ls8c_ard_3-0-0_092072_2018-06-17_final
2018-06-18 11:05:16	ga_ls8c_ard_3-0-0_108071_2018-06-18_final
2018-06-18 11:05:40	ga_ls8c_ard_3-0-0_108072_2018-06-18_final
2018-06-19 10:09:40	ga_ls8c_ard_3-0-0_099071_2018-06-19_final
2018-06-19 10:10:03	ga_ls8c_ard_3-0-0_099072_2018-06-19_final
2018-06-27 09:20:42	ga_ls8c_ard_3-0-0_091072_2018-06-26_final
2018-06-27 10:59:11	ga_ls8c_ard_3-0-0_107071_2018-06-27_final
2018-06-28 10:03:34	ga_ls8c_ard_3-1-0_098071_2018-06-28_final
2018-06-28 10:03:58	ga_ls8c_ard_3-0-0_098072_2018-06-28_final
2018-06-29 10:46:51	ga_ls8c_ard_3-0-0_105071_2018-06-29_final
2018-06-30 09:51:14	ga_ls8c_ard_3-0-0_096071_2018-06-30_final
2018-06-30 09:51:38	ga_ls8c_ard_3-0-0_096072_2018-06-30_final
2018-06-30 11:30:07	ga_ls8c_ard_3-0-0_112071_2018-06-30_final
2018-07-01 10:34:30	ga_ls8c_ard_3-0-0_103071_2018-07-01_final
2018-07-01 10:34:54	ga_ls8c_ard_3-0-0_103072_2018-07-01_final
2018-07-02 09:38:53	ga_ls8c_ard_3-0-0_094071_2018-07-02_final
2018-07-02 09:39:17	ga_ls8c_ard_3-0-0_094072_2018-07-02_final
2018-07-02 11:17:46	ga_ls8c_ard_3-0-0_110071_2018-07-02_final
2018-07-02 11:18:10	ga_ls8c_ard_3-0-0_110072_2018-07-02_final
2018-07-03 10:22:09	ga_ls8c_ard_3-0-0_101071_2018-07-03_final
2018-07-03 10:22:33	ga_ls8c_ard_3-0-0_101072_2018-07-03_final
2018-07-14 10:03:42	ga_ls8c_ard_3-1-0_098071_2018-07-14_final
2018-07-14 10:04:06	ga_ls8c_ard_3-1-0_098072_2018-07-14_final
2018-07-15 10:46:58	ga_ls8c_ard_3-0-0_105071_2018-07-15_final
2018-07-15 10:47:22	ga_ls8c_ard_3-0-0_105072_2018-07-15_final
2018-07-29 10:59:26	ga_ls8c_ard_3-0-0_107071_2018-07-29_final
2018-07-30 10:03:49	ga_ls8c_ard_3-0-0_098071_2018-07-30_final
2018-07-30 10:04:13	ga_ls8c_ard_3-0-0_098072_2018-07-30_final
2018-07-31 10:47:06	ga_ls8c_ard_3-0-0_105071_2018-07-31_final
2018-08-31 10:04:06	ga_ls8c_ard_3-0-0_098071_2018-08-31_final
2018-08-31 10:04:29	ga_ls8c_ard_3-0-0_098072_2018-08-31_final
2018-09-01 10:47:22	ga_ls8c_ard_3-0-0_105071_2018-09-01_final
2018-09-01 10:47:45	ga_ls8c_ard_3-0-0_105072_2018-09-01_final
2018-09-04 09:39:24	ga_ls8c_ard_3-0-0_094071_2018-09-04_final
2018-09-04 09:39:48	ga_ls8c_ard_3-0-0_094072_2018-09-04_final
2018-09-04 11:18:17	ga_ls8c_ard_3-0-0_110071_2018-09-04_final
2018-09-04 11:18:41	ga_ls8c_ard_3-0-0_110072_2018-09-04_final
2018-09-05 10:22:40	ga_ls8c_ard_3-0-0_101071_2018-09-05_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_2018-09-16_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_final
2018-12-07 09:52:05	ga_ls8c_ard_3-0-0_096071_2018-12-07_final
2018-12-07 09:52:29	ga_ls8c_ard_3-0-0_096072_2018-12-07_final
2018-12-07 11:30:58	ga_ls8c_ard_3-0-0_112071_2018-12-07_final
2018-12-08 10:35:20	ga_ls8c_ard_3-0-0_103071_2018-12-08_final
2018-12-09 09:39:43	ga_ls8c_ard_3-0-0_094071_2018-12-09_final
2018-12-09 11:18:36	ga_ls8c_ard_3-0-0_110071_2018-12-09_final
2018-12-09 11:19:00	ga_ls8c_ard_3-0-0_110072_2018-12-09_final
2018-12-10 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-10_final
2018-12-10 10:23:22	ga_ls8c_ard_3-0-0_101072_2018-12-10_final
2018-12-16 09:45:52	ga_ls8c_ard_3-0-0_095071_2018-12-16_final
2018-12-16 09:46:16	ga_ls8c_ard_3-0-0_095072_2018-12-16_final
2018-12-16 11:24:45	ga_ls8c_ard_3-0-0_111071_2018-12-16_final
2018-12-16 11:25:09	ga_ls8c_ard_3-0-0_111072_2018-12-16_final
2018-12-17 10:29:08	ga_ls8c_ard_3-0-0_102071_2018-12-17_final
2018-12-17 10:29:32	ga_ls8c_ard_3-0-0_102072_2018-12-17_final
2018-12-18 09:33:31	ga_ls8c_ard_3-0-0_093071_2018-12-18_final
2018-12-18 11:12:24	ga_ls8c_ard_3-0-0_109071_2018-12-18_final
2018-12-19 10:16:47	ga_ls8c_ard_3-0-0_100071_2018-12-19_final
2018-12-19 10:17:11	ga_ls8c_ard_3-0-0_100072_2018-12-19_final
2018-12-23 09:52:04	ga_ls8c_ard_3-0-0_096071_2018-12-23_final
2018-12-23 09:52:28	ga_ls8c_ard_3-0-0_096072_2018-12-23_final
2018-12-23 11:30:57	ga_ls8c_ard_3-0-0_112071_2018-12-23_final
2018-12-24 10:35:19	ga_ls8c_ard_3-0-0_103071_2018-12-24_final
2018-12-24 10:35:43	ga_ls8c_ard_3-0-0_103072_2018-12-24_final
2018-12-25 09:39:42	ga_ls8c_ard_3-0-0_094071_2018-12-25_final
2018-12-25 11:18:35	ga_ls8c_ard_3-0-0_110071_2018-12-25_final
2018-12-26 10:22:58	ga_ls8c_ard_3-0-0_101071_2018-12-26_final
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-06 10:04:48	ga_ls8c_ard_3-0-0_098072_2019-01-06_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2019-01-07 10:48:04	ga_ls8c_ard_3-0-0_105072_2019-01-07_final
2019-01-08 09:52:03	ga_ls8c_ard_3-0-0_096071_2019-01-08_final
2019-01-08 11:30:56	ga_ls8c_ard_3-0-0_112071_2019-01-08_final
2019-01-09 10:35:18	ga_ls8c_ard_3-0-0_103071_2019-01-09_final
2019-01-10 09:39:41	ga_ls8c_ard_3-0-0_094071_2019-01-10_final
2019-01-10 11:18:34	ga_ls8c_ard_3-0-0_110071_2019-01-10_final
2019-01-10 11:18:58	ga_ls8c_ard_3-0-0_110072_2019-01-10_final
2019-01-11 10:22:56	ga_ls8c_ard_3-0-0_101071_2019-01-11_final
2023-08-25 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-08-25_final
2023-08-25 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-08-25_final
2023-08-26 09:33:39	ga_ls8c_ard_3-2-1_093071_2023-08-26_final
2023-08-26 09:34:02	ga_ls8c_ard_3-2-1_093072_2023-08-26_final
2023-08-26 11:12:32	ga_ls8c_ard_3-2-1_109071_2023-08-26_final
2023-08-26 11:12:56	ga_ls8c_ard_3-2-1_109072_2023-08-26_final
2023-08-27 10:16:54	ga_ls8c_ard_3-2-1_100071_2023-08-27_final
2023-08-27 10:17:18	ga_ls8c_ard_3-2-1_100072_2023-08-27_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-30 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-08-30_final
2023-08-31 09:52:11	ga_ls8c_ard_3-2-1_096071_2023-08-31_final
2023-08-31 11:31:28	ga_ls8c_ard_3-2-1_112072_2023-08-31_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