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
2019-04-07 09:47:31	ga_ls8c_ard_3-1-0_095076_2019-04-07_final
2019-07-12 09:48:20	ga_ls8c_ard_3-1-0_095077_2019-07-12_final
2019-07-12 09:50:20	ga_ls8c_ard_3-1-0_095082_2019-07-12_final
2019-07-28 09:47:37	ga_ls8c_ard_3-1-0_095075_2019-07-28_final
2019-08-13 09:46:55	ga_ls8c_ard_3-1-0_095073_2019-08-13_final
2019-08-13 09:48:07	ga_ls8c_ard_3-1-0_095076_2019-08-13_final
2019-09-14 09:47:04	ga_ls8c_ard_3-1-0_095073_2019-09-14_final
2019-09-14 09:50:40	ga_ls8c_ard_3-1-0_095082_2019-09-14_final
2019-09-30 09:48:21	ga_ls8c_ard_3-1-0_095076_2019-09-30_final
2019-09-30 09:50:45	ga_ls8c_ard_3-1-0_095082_2019-09-30_final
2019-11-01 09:47:59	ga_ls8c_ard_3-1-0_095075_2019-11-01_final
2019-11-17 09:50:44	ga_ls8c_ard_3-1-0_095082_2019-11-17_final
2019-12-03 09:48:19	ga_ls8c_ard_3-1-0_095076_2019-12-03_final
2019-12-03 09:49:07	ga_ls8c_ard_3-1-0_095078_2019-12-03_final
2020-01-04 09:48:12	ga_ls8c_ard_3-1-0_095076_2020-01-04_final
2020-01-20 09:48:09	ga_ls8c_ard_3-1-0_095076_2020-01-20_final
2020-02-21 09:46:49	ga_ls8c_ard_3-1-0_095073_2020-02-21_final
2020-02-21 09:47:37	ga_ls8c_ard_3-1-0_095075_2020-02-21_final
2020-03-08 09:49:07	ga_ls8c_ard_3-1-0_095079_2020-03-08_final
2020-03-24 09:48:35	ga_ls8c_ard_3-1-0_095078_2020-03-24_final
2020-04-09 09:47:14	ga_ls8c_ard_3-1-0_095075_2020-04-09_final
2020-04-09 09:50:02	ga_ls8c_ard_3-1-0_095082_2020-04-09_final
2020-04-25 09:49:31	ga_ls8c_ard_3-1-0_095081_2020-04-25_final
2022-03-29 10:40:35	ga_ls8c_ard_3-2-1_104069_2022-03-29_final
2022-03-30 09:49:20	ga_ls8c_ard_3-2-1_095080_2022-03-30_final
2022-04-01 09:36:34	ga_ls8c_ard_3-2-1_093079_2022-04-01_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_final
2022-04-04 10:09:29	ga_ls8c_ard_3-2-1_098084_2022-04-04_final
2022-04-05 10:45:58	ga_ls8c_ard_3-2-1_105067_2022-04-05_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 09:56:45	ga_ls8c_ard_3-2-1_096083_2022-04-06_final
2022-04-06 11:33:14	ga_ls8c_ard_3-2-1_112077_2022-04-06_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-08 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-08_final
2022-04-09 10:26:29	ga_ls8c_ard_3-2-1_101080_2022-04-09_final
2022-04-10 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-04-10_final
2022-04-10 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-04-10_final
2022-04-11 10:14:32	ga_ls8c_ard_3-2-1_099081_2022-04-11_final
2022-04-12 10:55:01	ga_ls8c_ard_3-2-1_106074_2022-04-12_final
2022-04-13 10:01:47	ga_ls8c_ard_3-2-1_097080_2022-04-13_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-17 09:36:16	ga_ls8c_ard_3-2-1_093078_2022-04-17_final
2022-04-17 09:39:04	ga_ls8c_ard_3-2-1_093085_2022-04-17_final
2022-04-19 09:25:30	ga_ls8c_ard_3-2-1_091082_2022-04-18_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-20 10:08:45	ga_ls8c_ard_3-2-1_098082_2022-04-20_final
2022-04-20 11:44:27	ga_ls8c_ard_3-2-1_114074_2022-04-20_final
2022-04-22 09:53:35	ga_ls8c_ard_3-2-1_096075_2022-04-22_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-25 10:22:52	ga_ls8c_ard_3-2-1_101071_2022-04-25_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-26 11:07:19	ga_ls8c_ard_3-2-1_108074_2022-04-26_final
2022-04-27 10:11:41	ga_ls8c_ard_3-2-1_099074_2022-04-27_final
2022-04-28 10:54:56	ga_ls8c_ard_3-2-1_106074_2022-04-28_final
2022-04-29 10:00:31	ga_ls8c_ard_3-2-1_097077_2022-04-29_final
2022-04-29 10:00:55	ga_ls8c_ard_3-2-1_097078_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:41:48	ga_ls8c_ard_3-2-1_104072_2022-04-30_final
2022-05-01 11:29:04	ga_ls8c_ard_3-2-1_111082_2022-05-01_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-02 10:32:39	ga_ls8c_ard_3-2-1_102080_2022-05-02_final
2022-05-03 09:36:15	ga_ls8c_ard_3-2-1_093078_2022-05-03_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-06 11:44:29	ga_ls8c_ard_3-2-1_114074_2022-05-06_final
2022-05-07 10:46:52	ga_ls8c_ard_3-2-1_105069_2022-05-07_final
2022-05-07 10:48:04	ga_ls8c_ard_3-2-1_105072_2022-05-07_final
2022-05-07 10:49:16	ga_ls8c_ard_3-2-1_105075_2022-05-07_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-10 11:23:47	ga_ls8c_ard_3-2-1_110084_2022-05-10_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-15 10:01:05	ga_ls8c_ard_3-2-1_097078_2022-05-15_final
2022-05-16 10:43:33	ga_ls8c_ard_3-2-1_104076_2022-05-16_final
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2022-05-17_final
2022-05-19 09:36:23	ga_ls8c_ard_3-2-1_093078_2022-05-19_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-20 10:20:26	ga_ls8c_ard_3-2-1_100080_2022-05-20_final
2022-05-20 10:22:02	ga_ls8c_ard_3-2-1_100084_2022-05-20_final
2022-05-24 11:33:00	ga_ls8c_ard_3-2-1_112076_2022-05-24_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-25 10:37:22	ga_ls8c_ard_3-2-1_103076_2022-05-25_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-26 11:19:26	ga_ls8c_ard_3-2-1_110073_2022-05-26_final
2022-05-31 10:01:08	ga_ls8c_ard_3-2-1_097078_2022-05-31_final
2022-06-02 11:26:30	ga_ls8c_ard_3-2-1_111075_2022-06-02_final
2022-06-02 11:28:29	ga_ls8c_ard_3-2-1_111080_2022-06-02_final
2022-06-03 10:32:05	ga_ls8c_ard_3-2-1_102078_2022-06-03_final
2022-06-06 09:23:21	ga_ls8c_ard_3-2-1_091076_2022-06-05_final
2022-06-13 09:30:24	ga_ls8c_ard_3-2-1_092078_2022-06-13_final
2022-06-17 10:41:01	ga_ls8c_ard_3-2-1_104069_2022-06-17_final
2022-06-17 10:41:49	ga_ls8c_ard_3-2-1_104071_2022-06-17_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_final
2022-06-21 10:21:07	ga_ls8c_ard_3-2-1_100081_2022-06-21_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