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
2014-03-24 09:52:44	ga_ls8c_ard_3-0-0_095087_2014-03-24_final
2015-07-17 09:51:33	ga_ls8c_ard_3-0-0_095086_2015-07-17_final
2016-11-08 09:52:43	ga_ls8c_ard_3-0-0_095087_2016-11-08_final
2017-02-12 09:51:32	ga_ls8c_ard_3-0-0_095085_2017-02-12_final
2018-07-25 09:51:13	ga_ls8c_ard_3-0-0_095086_2018-07-25_final
2021-03-23 11:53:01	ga_ls8c_ard_3-2-0_115080_2021-03-23_final
2021-03-25 11:35:27	ga_ls8c_ard_3-2-0_113067_2021-03-25_final
2021-03-27 11:25:29	ga_ls8c_ard_3-2-0_111073_2021-03-27_final
2021-03-31 10:59:33	ga_ls8c_ard_3-2-0_107070_2021-03-31_final
2021-04-02 10:49:10	ga_ls8c_ard_3-2-0_105075_2021-04-02_final
2021-04-12 11:25:00	ga_ls8c_ard_3-2-0_111072_2021-04-12_final
2021-04-30 09:39:35	ga_ls8c_ard_3-2-0_093087_2021-04-30_final
2021-04-30 11:16:52	ga_ls8c_ard_3-2-0_109083_2021-04-30_final
2021-05-18 09:27:41	ga_ls8c_ard_3-2-0_091088_2021-05-17_final
2021-05-19 10:08:58	ga_ls8c_ard_3-2-0_098083_2021-05-19_final
2021-06-01 09:40:10	ga_ls8c_ard_3-2-0_093088_2021-06-01_final
2021-07-09 10:35:45	ga_ls8c_ard_3-2-0_103072_2021-07-09_final
2021-07-10 09:46:07	ga_ls8c_ard_3-2-0_094087_2021-07-10_final
2021-07-12 11:09:51	ga_ls8c_ard_3-2-0_108080_2021-07-12_final
2021-07-15 11:35:34	ga_ls8c_ard_3-2-0_113067_2021-07-15_final
2021-07-17 11:25:36	ga_ls8c_ard_3-2-0_111073_2021-07-17_final
2021-07-24 09:57:22	ga_ls8c_ard_3-2-0_096084_2021-07-24_final
2021-07-24 11:30:40	ga_ls8c_ard_3-2-0_112070_2021-07-24_final
2021-08-27 09:38:26	ga_ls8c_ard_3-2-0_094067_2021-08-27_final
2021-09-03 09:46:14	ga_ls8c_ard_3-2-0_095071_2021-09-03_final
2021-10-03 09:57:32	ga_ls8c_ard_3-2-0_097068_2021-10-03_final
2021-10-07 09:34:50	ga_ls8c_ard_3-2-0_093073_2021-10-07_final
2021-10-25 09:28:06	ga_ls8c_ard_3-2-0_091087_2021-10-24_final
2021-11-01 09:29:29	ga_ls8c_ard_3-2-0_092075_2021-10-31_final
2021-11-03 09:22:42	ga_ls8c_ard_3-2-0_090089_2021-11-02_final
2021-11-06 09:46:25	ga_ls8c_ard_3-2-0_095071_2021-11-06_final
2021-11-08 09:40:02	ga_ls8c_ard_3-2-0_093086_2021-11-08_final
2021-11-12 09:13:41	ga_ls8c_ard_3-2-0_089082_2021-11-11_final
2021-12-12 09:22:50	ga_ls8c_ard_3-2-1_091074_2021-12-11_final
2022-01-01 10:36:05	ga_ls8c_ard_3-2-1_103072_2022-01-01_final
2022-01-10 10:29:30	ga_ls8c_ard_3-2-1_102071_2022-01-10_final
2022-01-13 11:00:24	ga_ls8c_ard_3-2-1_107071_2022-01-13_final
2022-01-24 10:42:35	ga_ls8c_ard_3-2-1_104073_2022-01-24_final
2022-01-25 11:25:03	ga_ls8c_ard_3-2-1_111071_2022-01-25_final
2022-02-14 09:23:22	ga_ls8c_ard_3-2-1_091076_2022-02-13_final
2022-03-04 09:12:55	ga_ls8c_ard_3-2-1_089081_2022-03-03_final
2022-03-18 10:59:40	ga_ls8c_ard_3-2-1_107070_2022-03-18_final
2022-03-19 10:09:13	ga_ls8c_ard_3-2-1_098083_2022-03-19_final
2022-03-25 11:07:45	ga_ls8c_ard_3-2-1_108075_2022-03-25_final
2022-04-07 10:34:02	ga_ls8c_ard_3-2-1_103068_2022-04-07_final
2022-04-08 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-08_final
2022-04-18 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-04-18_final
2022-05-05 11:05:12	ga_ls8c_ard_3-2-1_107084_2022-05-05_final
2022-05-10 11:18:12	ga_ls8c_ard_3-2-1_110070_2022-05-10_final
2022-05-13 10:09:27	ga_ls8c_ard_3-2-1_099068_2022-05-13_final
2022-05-24 11:32:12	ga_ls8c_ard_3-2-1_112074_2022-05-24_final
2022-06-11 11:20:26	ga_ls8c_ard_3-2-1_110075_2022-06-11_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_final
2022-07-15 09:34:04	ga_ls8c_ard_3-2-1_092087_2022-07-15_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-09-19 09:17:21	ga_ls8c_ard_3-2-1_090075_2022-09-18_final
2022-09-22 09:47:03	ga_ls8c_ard_3-2-1_095072_2022-09-22_final
2022-09-29 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-09-29_final
2022-10-31 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-10-31_final
2022-11-04 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-11-03_final
2022-11-04 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-11-04_final
2022-11-21 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-11-21_final
2022-11-21 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-11-21_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-29 11:00:44	ga_ls8c_ard_3-2-1_107071_2022-11-29_final
2022-12-08 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-12-07_final
2022-12-11 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-12-11_final
2022-12-14 10:19:48	ga_ls8c_ard_3-2-1_100077_2022-12-14_final
2022-12-16 10:03:49	ga_ls8c_ard_3-2-1_098068_2022-12-16_final
2022-12-20 11:24:43	ga_ls8c_ard_3-2-1_110085_2022-12-20_final
2022-12-23 11:52:47	ga_ls8c_ard_3-2-1_115078_2022-12-23_final
2022-12-24 09:19:52	ga_ls8c_ard_3-2-1_090082_2022-12-23_final
2022-12-26 09:06:44	ga_ls8c_ard_3-2-1_088080_2022-12-25_final
2022-12-31 09:27:17	ga_ls8c_ard_3-2-1_091085_2022-12-30_final
2023-01-07 11:05:57	ga_ls8c_ard_3-2-1_108069_2023-01-07_final
2023-01-09 10:53:35	ga_ls8c_ard_3-2-1_106069_2023-01-09_final
2023-01-15 10:20:01	ga_ls8c_ard_3-2-1_100078_2023-01-15_final
2023-01-26 09:57:56	ga_ls8c_ard_3-2-1_097069_2023-01-26_final
2023-01-31 10:17:41	ga_ls8c_ard_3-2-1_100072_2023-01-31_final
2023-02-12 09:07:02	ga_ls8c_ard_3-2-1_088081_2023-02-11_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-21 10:39:35	ga_ls8c_ard_3-2-1_103081_2023-02-21_final
2023-03-12 09:33:50	ga_ls8c_ard_3-2-1_092087_2023-03-12_final
2023-04-04 11:13:27	ga_ls8c_ard_3-2-1_109074_2023-04-04_final
2023-04-09 11:35:28	ga_ls8c_ard_3-2-1_112083_2023-04-09_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-16 10:08:48	ga_ls8c_ard_3-2-1_099068_2023-05-16_final
2023-06-13 10:33:42	ga_ls8c_ard_3-2-1_103068_2023-06-13_final
2023-06-19 10:03:01	ga_ls8c_ard_3-2-1_097084_2023-06-19_final
2023-07-07 11:24:10	ga_ls8c_ard_3-2-1_111070_2023-07-07_final
2023-07-09 09:40:07	ga_ls8c_ard_3-2-1_093088_2023-07-09_final
2023-07-21 09:57:40	ga_ls8c_ard_3-2-1_097070_2023-07-21_final
2023-08-08 11:25:09	ga_ls8c_ard_3-2-1_111072_2023-08-08_final
2023-08-12 09:27:56	ga_ls8c_ard_3-2-1_091088_2023-08-11_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-09 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-09-09_final
2023-09-10 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-09-10_final
2023-09-15 09:11:46	ga_ls8c_ard_3-2-1_089078_2023-09-14_nrt
2023-09-20 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-09-20_nrt

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