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
2015-11-21 09:06:53	ga_ls8c_ard_3-1-0_088081_2015-11-20_final
2017-02-11 09:06:41	ga_ls8c_ard_3-1-0_088081_2017-02-10_final
2017-08-17 10:23:32	ga_ls8c_ard_3-1-0_101072_2017-08-17_final
2019-03-10 09:27:42	ga_ls8c_ard_3-1-0_091088_2019-03-09_final
2019-03-13 11:33:04	ga_ls8c_ard_3-1-0_112077_2019-03-13_final
2019-03-25 11:58:09	ga_ls8c_ard_3-1-0_116078_2019-03-25_final
2019-03-29 11:35:25	ga_ls8c_ard_3-1-0_112083_2019-03-29_final
2019-04-04 10:57:54	ga_ls8c_ard_3-1-0_106082_2019-04-04_final
2019-04-07 09:51:30	ga_ls8c_ard_3-1-0_095086_2019-04-07_final
2019-04-10 11:58:05	ga_ls8c_ard_3-1-0_116078_2019-04-10_final
2019-04-11 09:26:46	ga_ls8c_ard_3-1-0_091086_2019-04-10_final
2019-06-14 09:21:30	ga_ls8c_ard_3-1-0_091072_2019-06-13_final
2019-06-15 10:02:46	ga_ls8c_ard_3-1-0_098067_2019-06-15_final
2019-07-01 10:02:51	ga_ls8c_ard_3-1-0_098067_2019-07-01_final
2019-07-23 11:06:20	ga_ls8c_ard_3-1-0_108071_2019-07-23_final
2019-07-28 11:25:43	ga_ls8c_ard_3-1-0_111073_2019-07-28_final
2019-08-03 10:52:40	ga_ls8c_ard_3-1-0_105083_2019-08-03_final
2019-08-04 09:57:27	ga_ls8c_ard_3-1-0_096084_2019-08-04_final
2019-08-04 11:35:32	ga_ls8c_ard_3-1-0_112082_2019-08-04_final
2019-08-08 11:11:38	ga_ls8c_ard_3-1-0_108084_2019-08-08_final
2019-08-10 10:54:53	ga_ls8c_ard_3-1-0_106073_2019-08-10_final
2019-08-12 09:07:15	ga_ls8c_ard_3-1-0_088082_2019-08-11_final
2019-08-16 11:57:31	ga_ls8c_ard_3-1-0_116075_2019-08-16_final
2019-08-16 11:57:55	ga_ls8c_ard_3-1-0_116076_2019-08-16_final
2019-08-18 10:03:06	ga_ls8c_ard_3-1-0_098067_2019-08-18_final
2019-08-24 09:33:13	ga_ls8c_ard_3-1-0_092085_2019-08-24_final
2019-08-26 10:54:58	ga_ls8c_ard_3-1-0_106073_2019-08-26_final
2019-08-29 11:24:41	ga_ls8c_ard_3-1-0_111070_2019-08-29_final
2019-08-29 11:26:17	ga_ls8c_ard_3-1-0_111074_2019-08-29_final
2019-09-08 10:28:06	ga_ls8c_ard_3-1-0_101083_2019-09-08_final
2019-09-09 09:32:53	ga_ls8c_ard_3-1-0_092084_2019-09-09_final
2019-09-14 09:51:52	ga_ls8c_ard_3-1-0_095085_2019-09-14_final
2019-09-18 09:25:10	ga_ls8c_ard_3-1-0_091080_2019-09-17_final
2019-09-24 10:27:24	ga_ls8c_ard_3-1-0_101081_2019-09-24_final
2019-09-27 10:55:07	ga_ls8c_ard_3-1-0_106073_2019-09-27_final
2019-10-11 09:30:14	ga_ls8c_ard_3-1-0_092077_2019-10-11_final
2019-10-13 10:57:10	ga_ls8c_ard_3-1-0_106078_2019-10-13_final
2019-10-21 10:07:44	ga_ls8c_ard_3-1-0_098078_2019-10-21_final
2019-10-23 11:31:04	ga_ls8c_ard_3-1-0_112070_2019-10-23_final
2019-10-23 11:36:15	ga_ls8c_ard_3-1-0_112083_2019-10-23_final
2019-10-29 10:54:47	ga_ls8c_ard_3-1-0_106072_2019-10-29_final
2019-11-01 09:47:11	ga_ls8c_ard_3-1-0_095073_2019-11-01_final
2019-11-06 10:09:43	ga_ls8c_ard_3-1-0_098083_2019-11-06_final
2019-11-07 10:49:47	ga_ls8c_ard_3-1-0_105075_2019-11-07_final
2019-11-23 10:48:31	ga_ls8c_ard_3-1-0_105072_2019-11-23_final
2019-11-24 09:52:30	ga_ls8c_ard_3-1-0_096071_2019-11-24_final
2019-11-24 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-11-24_final
2019-11-28 11:06:16	ga_ls8c_ard_3-1-0_108070_2019-11-28_final
2019-12-10 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-12-10_final
2019-12-24 10:07:36	ga_ls8c_ard_3-1-0_098078_2019-12-24_final
2019-12-25 10:50:27	ga_ls8c_ard_3-1-0_105077_2019-12-25_final
2019-12-26 11:33:43	ga_ls8c_ard_3-1-0_112077_2019-12-26_final
2019-12-26 11:36:31	ga_ls8c_ard_3-1-0_112084_2019-12-26_final
2020-01-27 09:54:42	ga_ls8c_ard_3-1-0_096077_2020-01-27_final
2020-01-30 10:26:23	ga_ls8c_ard_3-1-0_101079_2020-01-30_final
2020-02-05 11:30:08	ga_ls8c_ard_3-1-0_111084_2020-02-05_final
2020-02-09 09:24:08	ga_ls8c_ard_3-1-0_091078_2020-02-08_final
2020-02-12 09:52:14	ga_ls8c_ard_3-1-0_096071_2020-02-12_final
2020-02-16 11:09:58	ga_ls8c_ard_3-1-0_108080_2020-02-16_final
2020-02-24 11:57:23	ga_ls8c_ard_3-1-0_116075_2020-02-24_final
2020-02-26 10:03:44	ga_ls8c_ard_3-1-0_098069_2020-02-26_final
2020-03-09 10:32:46	ga_ls8c_ard_3-1-0_102080_2020-03-09_final
2020-03-09 10:33:34	ga_ls8c_ard_3-1-0_102082_2020-03-09_final
2020-03-14 10:48:28	ga_ls8c_ard_3-1-0_105073_2020-03-14_final
2020-03-29 10:06:16	ga_ls8c_ard_3-1-0_098076_2020-03-29_final
2020-03-30 10:46:20	ga_ls8c_ard_3-1-0_105068_2020-03-30_final
2020-03-31 11:31:34	ga_ls8c_ard_3-1-0_112073_2020-03-31_final
2020-04-10 10:32:29	ga_ls8c_ard_3-1-0_102080_2020-04-10_final
2020-04-16 09:51:23	ga_ls8c_ard_3-1-0_096070_2020-04-16_final
2020-04-25 11:24:01	ga_ls8c_ard_3-1-0_111070_2020-04-25_final
2020-04-29 09:27:09	ga_ls8c_ard_3-1-0_091087_2020-04-28_final
2022-04-01 09:39:46	ga_ls8c_ard_3-2-1_093087_2022-04-01_final
2022-04-02 10:21:50	ga_ls8c_ard_3-2-1_100084_2022-04-02_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-04 11:44:23	ga_ls8c_ard_3-2-1_114074_2022-04-04_final
2022-04-04 11:44:46	ga_ls8c_ard_3-2-1_114075_2022-04-04_final
2022-04-04 11:45:34	ga_ls8c_ard_3-2-1_114077_2022-04-04_final
2022-04-07 10:35:38	ga_ls8c_ard_3-2-1_103072_2022-04-07_final
2022-04-11 11:52:13	ga_ls8c_ard_3-2-1_115078_2022-04-11_final
2022-04-17 09:40:16	ga_ls8c_ard_3-2-1_093088_2022-04-17_final
2022-04-20 10:07:34	ga_ls8c_ard_3-2-1_098079_2022-04-20_final
2022-04-22 11:36:04	ga_ls8c_ard_3-2-1_112084_2022-04-22_final
2022-04-26 11:05:20	ga_ls8c_ard_3-2-1_108069_2022-04-26_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-06 10:07:35	ga_ls8c_ard_3-2-1_098079_2022-05-06_final
2022-05-07 09:12:22	ga_ls8c_ard_3-2-1_089080_2022-05-06_final
2022-05-14 10:52:43	ga_ls8c_ard_3-2-1_106068_2022-05-14_final
2022-05-14 10:58:18	ga_ls8c_ard_3-2-1_106082_2022-05-14_final
2022-05-16 10:45:57	ga_ls8c_ard_3-2-1_104082_2022-05-16_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-24 09:52:55	ga_ls8c_ard_3-2-1_096073_2022-05-24_final
2022-05-31 09:59:32	ga_ls8c_ard_3-2-1_097074_2022-05-31_final
2022-06-04 11:12:34	ga_ls8c_ard_3-2-1_109071_2022-06-04_final
2022-06-05 10:17:21	ga_ls8c_ard_3-2-1_100072_2022-06-05_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_final
2022-06-20 11:12:20	ga_ls8c_ard_3-2-1_109070_2022-06-20_final
2022-06-22 09:25:06	ga_ls8c_ard_3-2-1_091080_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