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
2019-03-10 09:25:18	ga_ls8c_ard_3-1-0_091082_2019-03-09_final
2019-03-28 10:48:10	ga_ls8c_ard_3-1-0_105073_2019-03-28_final
2019-03-29 09:56:08	ga_ls8c_ard_3-1-0_096082_2019-03-29_final
2019-03-29 09:56:56	ga_ls8c_ard_3-1-0_096084_2019-03-29_final
2019-04-18 11:05:47	ga_ls8c_ard_3-1-0_108071_2019-04-18_final
2019-06-14 09:21:54	ga_ls8c_ard_3-1-0_091073_2019-06-13_final
2019-06-21 11:06:12	ga_ls8c_ard_3-1-0_108071_2019-06-21_final
2019-06-21 11:09:00	ga_ls8c_ard_3-1-0_108078_2019-06-21_final
2019-07-18 10:48:33	ga_ls8c_ard_3-1-0_105073_2019-07-18_final
2019-07-19 09:56:32	ga_ls8c_ard_3-1-0_096082_2019-07-19_final
2019-07-19 09:57:43	ga_ls8c_ard_3-1-0_096085_2019-07-19_final
2019-07-23 11:06:20	ga_ls8c_ard_3-1-0_108071_2019-07-23_final
2019-08-04 09:52:39	ga_ls8c_ard_3-1-0_096072_2019-08-04_final
2019-08-04 09:56:39	ga_ls8c_ard_3-1-0_096082_2019-08-04_final
2019-08-19 10:48:45	ga_ls8c_ard_3-1-0_105073_2019-08-19_final
2019-09-05 09:52:48	ga_ls8c_ard_3-1-0_096072_2019-09-05_final
2019-09-09 11:06:35	ga_ls8c_ard_3-1-0_108071_2019-09-09_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-18 09:23:34	ga_ls8c_ard_3-1-0_091076_2019-09-17_final
2019-09-18 09:25:58	ga_ls8c_ard_3-1-0_091082_2019-09-17_final
2019-09-18 09:29:10	ga_ls8c_ard_3-1-0_091090_2019-09-17_final
2019-09-20 10:48:30	ga_ls8c_ard_3-1-0_105072_2019-09-20_final
2019-10-04 09:28:50	ga_ls8c_ard_3-1-0_091089_2019-10-03_final
2019-10-06 10:48:58	ga_ls8c_ard_3-1-0_105073_2019-10-06_final
2019-10-16 09:48:00	ga_ls8c_ard_3-1-0_095075_2019-10-16_final
2019-10-20 09:22:05	ga_ls8c_ard_3-1-0_091072_2019-10-19_final
2019-10-22 10:48:36	ga_ls8c_ard_3-1-0_105072_2019-10-22_final
2019-10-23 09:56:58	ga_ls8c_ard_3-1-0_096082_2019-10-23_final
2019-10-23 09:57:22	ga_ls8c_ard_3-1-0_096083_2019-10-23_final
2019-11-01 09:46:48	ga_ls8c_ard_3-1-0_095072_2019-11-01_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-07 10:48:35	ga_ls8c_ard_3-1-0_105072_2019-11-07_final
2019-11-08 09:52:57	ga_ls8c_ard_3-1-0_096072_2019-11-08_final
2019-11-17 09:47:08	ga_ls8c_ard_3-1-0_095073_2019-11-17_final
2019-11-21 09:27:11	ga_ls8c_ard_3-1-0_091085_2019-11-20_final
2019-11-24 09:52:54	ga_ls8c_ard_3-1-0_096072_2019-11-24_final
2019-12-03 09:47:55	ga_ls8c_ard_3-1-0_095075_2019-12-03_final
2019-12-07 09:27:11	ga_ls8c_ard_3-1-0_091085_2019-12-06_final
2019-12-10 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-12-10_final
2019-12-25 10:48:28	ga_ls8c_ard_3-1-0_105072_2019-12-25_final
2020-01-15 11:08:31	ga_ls8c_ard_3-1-0_108076_2020-01-15_final
2020-01-20 09:48:09	ga_ls8c_ard_3-1-0_095076_2020-01-20_final
2020-01-20 09:50:57	ga_ls8c_ard_3-1-0_095083_2020-01-20_final
2020-02-11 10:51:27	ga_ls8c_ard_3-1-0_105080_2020-02-11_final
2020-02-12 09:56:37	ga_ls8c_ard_3-1-0_096082_2020-02-12_final
2020-02-28 09:56:33	ga_ls8c_ard_3-1-0_096082_2020-02-28_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-14 10:51:16	ga_ls8c_ard_3-1-0_105080_2020-03-14_final
2020-03-19 11:08:10	ga_ls8c_ard_3-1-0_108076_2020-03-19_final
2020-03-24 09:46:35	ga_ls8c_ard_3-1-0_095073_2020-03-24_final
2020-03-28 09:28:12	ga_ls8c_ard_3-1-0_091089_2020-03-27_final
2020-04-16 09:57:22	ga_ls8c_ard_3-1-0_096085_2020-04-16_final
2020-05-01 10:50:52	ga_ls8c_ard_3-1-0_105080_2020-05-01_final
2022-04-01 09:38:58	ga_ls8c_ard_3-2-1_093085_2022-04-01_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-04 10:09:29	ga_ls8c_ard_3-2-1_098084_2022-04-04_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-09 10:22:29	ga_ls8c_ard_3-2-1_101070_2022-04-09_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-10 09:34:27	ga_ls8c_ard_3-2-1_092089_2022-04-10_final
2022-04-11 10:13:20	ga_ls8c_ard_3-2-1_099078_2022-04-11_final
2022-04-12 09:20:31	ga_ls8c_ard_3-2-1_090085_2022-04-11_final
2022-04-12 10:55:01	ga_ls8c_ard_3-2-1_106074_2022-04-12_final
2022-04-12 10:55:48	ga_ls8c_ard_3-2-1_106076_2022-04-12_final
2022-04-15 09:47:02	ga_ls8c_ard_3-2-1_095074_2022-04-15_final
2022-04-15 11:29:31	ga_ls8c_ard_3-2-1_111083_2022-04-15_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-28 10:57:44	ga_ls8c_ard_3-2-1_106081_2022-04-28_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-05-01 09:46:35	ga_ls8c_ard_3-2-1_095073_2022-05-01_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-02 10:27:52	ga_ls8c_ard_3-2-1_102068_2022-05-02_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-05 11:04:00	ga_ls8c_ard_3-2-1_107081_2022-05-05_final
2022-05-15 09:58:18	ga_ls8c_ard_3-2-1_097071_2022-05-15_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-17 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-05-17_final
2022-05-19 09:37:59	ga_ls8c_ard_3-2-1_093082_2022-05-19_final
2022-05-19 11:17:40	ga_ls8c_ard_3-2-1_109084_2022-05-19_final
2022-05-20 10:22:02	ga_ls8c_ard_3-2-1_100084_2022-05-20_final
2022-05-20 11:57:44	ga_ls8c_ard_3-2-1_116076_2022-05-20_final
2022-05-26 09:40:57	ga_ls8c_ard_3-2-1_094074_2022-05-26_final
2022-05-26 11:22:14	ga_ls8c_ard_3-2-1_110080_2022-05-26_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-05-31 10:03:32	ga_ls8c_ard_3-2-1_097084_2022-05-31_final
2022-05-31 11:41:13	ga_ls8c_ard_3-2-1_113081_2022-05-31_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-03 10:33:41	ga_ls8c_ard_3-2-1_102082_2022-06-03_final
2022-06-04 09:38:04	ga_ls8c_ard_3-2-1_093082_2022-06-04_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-16 09:58:57	ga_ls8c_ard_3-2-1_097072_2022-06-16_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_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