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
2022-08-25 09:28:12	ga_ls8c_ard_3-2-1_091087_2022-08-24_final
2022-08-26 10:05:29	ga_ls8c_ard_3-2-1_098072_2022-08-26_final
2022-08-30 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-30_final
2022-09-01 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-09-01_final
2022-09-02 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-09-02_final
2022-09-18 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-09-18_final
2022-09-26 09:22:20	ga_ls8c_ard_3-2-1_091072_2022-09-25_final
2022-09-26 09:29:31	ga_ls8c_ard_3-2-1_091090_2022-09-25_final
2022-09-26 11:02:01	ga_ls8c_ard_3-2-1_107074_2022-09-26_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-10-06 09:58:10	ga_ls8c_ard_3-2-1_097069_2022-10-06_final
2022-10-11 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-10-11_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-14 10:49:54	ga_ls8c_ard_3-2-1_105075_2022-10-14_final
2022-10-17 09:45:57	ga_ls8c_ard_3-2-1_094085_2022-10-17_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-21 10:56:34	ga_ls8c_ard_3-2-1_106076_2022-10-21_final
2022-10-25 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-10-25_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-26 11:14:21	ga_ls8c_ard_3-2-1_109074_2022-10-26_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-11-01 10:36:29	ga_ls8c_ard_3-2-1_103072_2022-11-01_final
2022-11-02 11:20:57	ga_ls8c_ard_3-2-1_110075_2022-11-02_final
2022-11-03 10:28:31	ga_ls8c_ard_3-2-1_101083_2022-11-03_final
2022-11-09 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-11-09_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-27 09:34:12	ga_ls8c_ard_3-2-1_093071_2022-11-27_final
2022-12-22 11:09:55	ga_ls8c_ard_3-2-1_108079_2022-12-22_final
2022-12-27 11:25:17	ga_ls8c_ard_3-2-1_111071_2022-12-27_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2023-01-08 10:11:07	ga_ls8c_ard_3-2-1_099071_2023-01-08_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-15 10:19:37	ga_ls8c_ard_3-2-1_100077_2023-01-15_final
2023-01-16 11:00:04	ga_ls8c_ard_3-2-1_107070_2023-01-16_final
2023-01-17 10:03:38	ga_ls8c_ard_3-2-1_098068_2023-01-17_final
2023-01-29 10:30:03	ga_ls8c_ard_3-2-1_102072_2023-01-29_final
2023-01-30 09:39:13	ga_ls8c_ard_3-2-1_093084_2023-01-30_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-02-04 09:52:34	ga_ls8c_ard_3-2-1_096071_2023-02-04_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-03-05 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-03-04_final
2023-03-08 09:51:46	ga_ls8c_ard_3-2-1_096070_2023-03-08_final
2023-03-08 09:52:10	ga_ls8c_ard_3-2-1_096071_2023-03-08_final
2023-03-12 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-03-12_final
2023-03-14 09:21:51	ga_ls8c_ard_3-2-1_090088_2023-03-13_final
2023-03-23 10:47:15	ga_ls8c_ard_3-2-1_105070_2023-03-23_final
2023-03-25 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-03-25_final
2023-03-29 10:10:08	ga_ls8c_ard_3-2-1_099070_2023-03-29_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-04 11:16:14	ga_ls8c_ard_3-2-1_109081_2023-04-04_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-07 10:02:36	ga_ls8c_ard_3-2-1_098067_2023-04-07_final
2023-04-08 10:49:02	ga_ls8c_ard_3-2-1_105075_2023-04-08_final
2023-04-13 09:31:49	ga_ls8c_ard_3-2-1_092083_2023-04-13_final
2023-04-13 11:06:18	ga_ls8c_ard_3-2-1_108072_2023-04-13_final
2023-04-16 09:56:43	ga_ls8c_ard_3-2-1_097068_2023-04-16_final
2023-04-17 10:39:58	ga_ls8c_ard_3-2-1_104068_2023-04-17_final
2023-04-18 09:51:55	ga_ls8c_ard_3-2-1_095087_2023-04-18_final
2023-04-18 11:25:13	ga_ls8c_ard_3-2-1_111073_2023-04-18_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_final
2023-05-05 10:28:18	ga_ls8c_ard_3-2-1_102070_2023-05-05_final
2023-05-12 10:39:08	ga_ls8c_ard_3-2-1_103082_2023-05-12_final
2023-05-15 11:09:13	ga_ls8c_ard_3-2-1_108080_2023-05-15_final
2023-05-16 10:12:23	ga_ls8c_ard_3-2-1_099077_2023-05-16_final
2023-05-21 10:27:45	ga_ls8c_ard_3-2-1_102069_2023-05-21_final
2023-05-24 09:22:11	ga_ls8c_ard_3-2-1_091075_2023-05-23_final
2023-05-24 09:28:10	ga_ls8c_ard_3-2-1_091090_2023-05-23_final
2023-05-24 11:01:28	ga_ls8c_ard_3-2-1_107076_2023-05-24_final
2023-05-31 09:32:46	ga_ls8c_ard_3-2-1_092086_2023-05-31_final
2023-05-31 11:10:27	ga_ls8c_ard_3-2-1_108083_2023-05-31_final
2023-06-05 09:45:46	ga_ls8c_ard_3-2-1_095072_2023-06-05_final
2023-06-07 11:17:06	ga_ls8c_ard_3-2-1_109084_2023-06-07_final
2023-06-08 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-06-08_final
2023-06-09 10:59:11	ga_ls8c_ard_3-2-1_107070_2023-06-09_final
2023-06-14 11:19:45	ga_ls8c_ard_3-2-1_110075_2023-06-14_final
2023-06-21 09:45:52	ga_ls8c_ard_3-2-1_095072_2023-06-21_final
2023-06-30 11:23:29	ga_ls8c_ard_3-2-1_110084_2023-06-30_final
2023-07-01 10:27:05	ga_ls8c_ard_3-2-1_101082_2023-07-01_final
2023-07-02 11:05:34	ga_ls8c_ard_3-2-1_108070_2023-07-02_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-11 09:27:46	ga_ls8c_ard_3-2-1_091088_2023-07-10_final
2023-07-16 11:18:49	ga_ls8c_ard_3-2-1_110072_2023-07-16_final
2023-07-22 09:06:51	ga_ls8c_ard_3-2-1_088082_2023-07-21_final
2023-07-22 10:42:09	ga_ls8c_ard_3-2-1_104073_2023-07-22_final
2023-07-23 11:24:13	ga_ls8c_ard_3-2-1_111070_2023-07-23_final
2023-08-10 11:17:34	ga_ls8c_ard_3-2-1_109084_2023-08-10_final
2023-08-13 10:09:37	ga_ls8c_ard_3-2-1_098084_2023-08-13_final
2023-08-15 11:32:11	ga_ls8c_ard_3-2-1_112074_2023-08-15_final
2023-08-17 09:44:57	ga_ls8c_ard_3-2-1_094084_2023-08-17_final
2023-08-17 11:23:50	ga_ls8c_ard_3-2-1_110084_2023-08-17_final
2023-08-19 11:07:30	ga_ls8c_ard_3-2-1_108074_2023-08-19_final
2023-08-20 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-08-20_final
2023-08-22 11:38:26	ga_ls8c_ard_3-2-1_113074_2023-08-22_final
2023-08-24 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-08-24_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_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