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 09:24:54	ga_ls8c_ard_3-1-0_091081_2019-03-09_final
2019-03-17 11:09:56	ga_ls8c_ard_3-1-0_108081_2019-03-17_final
2019-03-22 09:50:46	ga_ls8c_ard_3-1-0_095084_2019-03-22_final
2019-03-22 11:28:51	ga_ls8c_ard_3-1-0_111082_2019-03-22_final
2019-03-26 09:26:02	ga_ls8c_ard_3-1-0_091084_2019-03-25_final
2019-03-28 10:46:58	ga_ls8c_ard_3-1-0_105070_2019-03-28_final
2019-03-28 10:47:46	ga_ls8c_ard_3-1-0_105072_2019-03-28_final
2019-03-28 10:48:10	ga_ls8c_ard_3-1-0_105073_2019-03-28_final
2019-03-29 09:57:20	ga_ls8c_ard_3-1-0_096085_2019-03-29_final
2019-04-02 11:05:05	ga_ls8c_ard_3-1-0_108069_2019-04-02_final
2019-04-07 11:28:47	ga_ls8c_ard_3-1-0_111082_2019-04-07_final
2019-04-13 10:46:53	ga_ls8c_ard_3-1-0_105070_2019-04-13_final
2019-04-14 09:54:51	ga_ls8c_ard_3-1-0_096079_2019-04-14_final
2019-06-16 10:46:50	ga_ls8c_ard_3-1-0_105069_2019-06-16_final
2019-06-21 11:09:24	ga_ls8c_ard_3-1-0_108079_2019-06-21_final
2019-06-26 09:49:53	ga_ls8c_ard_3-1-0_095081_2019-06-26_final
2019-06-30 09:23:11	ga_ls8c_ard_3-1-0_091076_2019-06-29_final
2019-06-30 09:25:58	ga_ls8c_ard_3-1-0_091083_2019-06-29_final
2019-07-02 10:46:07	ga_ls8c_ard_3-1-0_105067_2019-07-02_final
2019-07-02 10:47:43	ga_ls8c_ard_3-1-0_105071_2019-07-02_final
2019-07-02 10:48:07	ga_ls8c_ard_3-1-0_105072_2019-07-02_final
2019-07-03 09:56:29	ga_ls8c_ard_3-1-0_096082_2019-07-03_final
2019-07-16 09:23:37	ga_ls8c_ard_3-1-0_091077_2019-07-15_final
2019-07-18 10:48:33	ga_ls8c_ard_3-1-0_105073_2019-07-18_final
2019-07-18 10:51:45	ga_ls8c_ard_3-1-0_105081_2019-07-18_final
2019-07-28 09:50:49	ga_ls8c_ard_3-1-0_095083_2019-07-28_final
2019-07-28 11:26:30	ga_ls8c_ard_3-1-0_111075_2019-07-28_final
2019-08-03 10:48:40	ga_ls8c_ard_3-1-0_105073_2019-08-03_final
2019-08-03 10:51:52	ga_ls8c_ard_3-1-0_105081_2019-08-03_final
2019-08-03 10:52:16	ga_ls8c_ard_3-1-0_105082_2019-08-03_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 10:47:58	ga_ls8c_ard_3-1-0_105071_2019-08-19_final
2019-09-02 09:25:05	ga_ls8c_ard_3-1-0_091080_2019-09-01_final
2019-09-05 09:52:48	ga_ls8c_ard_3-1-0_096072_2019-09-05_final
2019-09-14 09:51:04	ga_ls8c_ard_3-1-0_095083_2019-09-14_final
2019-09-14 11:29:09	ga_ls8c_ard_3-1-0_111081_2019-09-14_final
2019-09-20 10:47:43	ga_ls8c_ard_3-1-0_105070_2019-09-20_final
2019-09-20 10:50:54	ga_ls8c_ard_3-1-0_105078_2019-09-20_final
2019-09-21 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-09-21_final
2019-09-30 11:27:14	ga_ls8c_ard_3-1-0_111076_2019-09-30_final
2019-10-06 10:50:34	ga_ls8c_ard_3-1-0_105077_2019-10-06_final
2019-10-11 11:11:07	ga_ls8c_ard_3-1-0_108082_2019-10-11_final
2019-10-16 11:25:17	ga_ls8c_ard_3-1-0_111071_2019-10-16_final
2019-11-01 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-11-01_final
2019-11-02 10:33:15	ga_ls8c_ard_3-1-0_102080_2019-11-02_final
2019-11-08 09:56:57	ga_ls8c_ard_3-1-0_096082_2019-11-08_final
2019-11-12 11:08:42	ga_ls8c_ard_3-1-0_108076_2019-11-12_final
2019-11-18 10:33:11	ga_ls8c_ard_3-1-0_102080_2019-11-18_final
2019-11-21 09:25:12	ga_ls8c_ard_3-1-0_091080_2019-11-20_final
2019-11-28 11:08:40	ga_ls8c_ard_3-1-0_108076_2019-11-28_final
2019-12-07 09:24:23	ga_ls8c_ard_3-1-0_091078_2019-12-06_final
2019-12-07 09:25:11	ga_ls8c_ard_3-1-0_091080_2019-12-06_final
2019-12-10 09:53:17	ga_ls8c_ard_3-1-0_096073_2019-12-10_final
2019-12-23 09:24:21	ga_ls8c_ard_3-1-0_091078_2019-12-22_final
2019-12-26 09:56:26	ga_ls8c_ard_3-1-0_096081_2019-12-26_final
2019-12-26 09:56:50	ga_ls8c_ard_3-1-0_096082_2019-12-26_final
2020-01-15 11:10:07	ga_ls8c_ard_3-1-0_108080_2020-01-15_final
2020-01-31 11:10:02	ga_ls8c_ard_3-1-0_108080_2020-01-31_final
2020-02-05 09:48:27	ga_ls8c_ard_3-1-0_095077_2020-02-05_final
2020-02-12 09:56:37	ga_ls8c_ard_3-1-0_096082_2020-02-12_final
2020-02-21 09:51:12	ga_ls8c_ard_3-1-0_095084_2020-02-21_final
2020-02-21 11:28:53	ga_ls8c_ard_3-1-0_111081_2020-02-21_final
2020-02-25 09:24:28	ga_ls8c_ard_3-1-0_091079_2020-02-24_final
2020-02-28 09:56:33	ga_ls8c_ard_3-1-0_096082_2020-02-28_final
2020-03-15 09:56:50	ga_ls8c_ard_3-1-0_096083_2020-03-15_final
2020-04-04 11:05:37	ga_ls8c_ard_3-1-0_108070_2020-04-04_final
2020-04-20 11:05:07	ga_ls8c_ard_3-1-0_108069_2020-04-20_final
2020-04-20 11:05:31	ga_ls8c_ard_3-1-0_108070_2020-04-20_final
2020-04-25 09:49:31	ga_ls8c_ard_3-1-0_095081_2020-04-25_final
2022-03-29 10:41:22	ga_ls8c_ard_3-2-1_104071_2022-03-29_final
2022-03-31 10:29:24	ga_ls8c_ard_3-2-1_102072_2022-03-31_final
2022-04-10 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-04-10_final
2022-04-10 09:30:28	ga_ls8c_ard_3-2-1_092079_2022-04-10_final
2022-04-10 11:05:22	ga_ls8c_ard_3-2-1_108069_2022-04-10_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-19 11:03:35	ga_ls8c_ard_3-2-1_107080_2022-04-19_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-28 10:56:08	ga_ls8c_ard_3-2-1_106077_2022-04-28_final
2022-04-29 11:39:24	ga_ls8c_ard_3-2-1_113077_2022-04-29_final
2022-05-03 11:14:44	ga_ls8c_ard_3-2-1_109077_2022-05-03_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-06 10:05:12	ga_ls8c_ard_3-2-1_098073_2022-05-06_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-08 11:34:56	ga_ls8c_ard_3-2-1_112081_2022-05-08_final
2022-05-14 10:57:54	ga_ls8c_ard_3-2-1_106081_2022-05-14_final
2022-05-16 10:42:45	ga_ls8c_ard_3-2-1_104074_2022-05-16_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-05-25 10:34:59	ga_ls8c_ard_3-2-1_103070_2022-05-25_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-06-02 09:48:00	ga_ls8c_ard_3-2-1_095076_2022-06-02_final
2022-06-17 10:45:00	ga_ls8c_ard_3-2-1_104079_2022-06-17_final
2022-06-19 10:31:04	ga_ls8c_ard_3-2-1_102075_2022-06-19_final
2022-06-20 09:38:38	ga_ls8c_ard_3-2-1_093083_2022-06-20_final
2022-06-20 11:15:08	ga_ls8c_ard_3-2-1_109077_2022-06-20_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