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
2013-05-23 09:08:46	ga_ls8c_ard_3-1-0_088081_2013-05-22_final
2016-06-18 10:31:22	ga_ls8c_ard_3-1-0_102077_2016-06-18_final
2016-07-02 09:06:35	ga_ls8c_ard_3-1-0_088081_2016-07-01_final
2017-07-21 09:06:37	ga_ls8c_ard_3-1-0_088081_2017-07-20_final
2019-03-11 10:03:46	ga_ls8c_ard_3-1-0_098070_2019-03-11_final
2019-04-01 10:23:26	ga_ls8c_ard_3-1-0_101073_2019-04-01_final
2019-04-02 11:05:53	ga_ls8c_ard_3-1-0_108071_2019-04-02_final
2019-06-17 11:35:18	ga_ls8c_ard_3-1-0_112082_2019-06-17_final
2019-06-20 10:24:32	ga_ls8c_ard_3-1-0_101075_2019-06-20_final
2019-06-21 11:06:12	ga_ls8c_ard_3-1-0_108071_2019-06-21_final
2019-07-03 09:57:41	ga_ls8c_ard_3-1-0_096085_2019-07-03_final
2019-07-06 10:23:48	ga_ls8c_ard_3-1-0_101073_2019-07-06_final
2019-07-12 09:46:20	ga_ls8c_ard_3-1-0_095072_2019-07-12_final
2019-07-12 11:26:49	ga_ls8c_ard_3-1-0_111076_2019-07-12_final
2019-07-12 11:29:13	ga_ls8c_ard_3-1-0_111082_2019-07-12_final
2019-07-15 11:58:32	ga_ls8c_ard_3-1-0_116078_2019-07-15_final
2019-07-17 10:04:30	ga_ls8c_ard_3-1-0_098071_2019-07-17_final
2019-07-17 10:04:53	ga_ls8c_ard_3-1-0_098072_2019-07-17_final
2019-07-22 10:23:52	ga_ls8c_ard_3-1-0_101073_2019-07-22_final
2019-07-22 10:27:51	ga_ls8c_ard_3-1-0_101083_2019-07-22_final
2019-07-27 09:07:33	ga_ls8c_ard_3-1-0_088083_2019-07-26_final
2019-07-29 10:29:18	ga_ls8c_ard_3-1-0_102071_2019-07-29_final
2019-08-02 10:03:00	ga_ls8c_ard_3-1-0_098067_2019-08-02_final
2019-08-04 11:36:20	ga_ls8c_ard_3-1-0_112084_2019-08-04_final
2019-08-07 10:23:11	ga_ls8c_ard_3-1-0_101071_2019-08-07_final
2019-08-10 10:54:06	ga_ls8c_ard_3-1-0_106071_2019-08-10_final
2019-08-20 09:57:32	ga_ls8c_ard_3-1-0_096084_2019-08-20_final
2019-08-23 10:26:03	ga_ls8c_ard_3-1-0_101078_2019-08-23_final
2019-08-26 10:54:34	ga_ls8c_ard_3-1-0_106072_2019-08-26_final
2019-09-02 09:23:29	ga_ls8c_ard_3-1-0_091076_2019-09-01_final
2019-09-03 10:03:09	ga_ls8c_ard_3-1-0_098067_2019-09-03_final
2019-09-04 10:52:24	ga_ls8c_ard_3-1-0_105082_2019-09-04_final
2019-09-17 11:58:04	ga_ls8c_ard_3-1-0_116076_2019-09-17_final
2019-09-18 09:23:34	ga_ls8c_ard_3-1-0_091076_2019-09-17_final
2019-09-19 10:07:14	ga_ls8c_ard_3-1-0_098077_2019-09-19_final
2019-09-19 10:08:50	ga_ls8c_ard_3-1-0_098081_2019-09-19_final
2019-09-24 10:24:36	ga_ls8c_ard_3-1-0_101074_2019-09-24_final
2019-09-25 11:10:40	ga_ls8c_ard_3-1-0_108081_2019-09-25_final
2019-09-30 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-09-30_final
2019-09-30 11:25:14	ga_ls8c_ard_3-1-0_111071_2019-09-30_final
2019-10-11 11:11:31	ga_ls8c_ard_3-1-0_108083_2019-10-11_final
2019-10-17 10:29:16	ga_ls8c_ard_3-1-0_102070_2019-10-17_final
2019-10-20 09:25:40	ga_ls8c_ard_3-1-0_091081_2019-10-19_final
2019-10-22 10:48:36	ga_ls8c_ard_3-1-0_105072_2019-10-22_final
2019-10-27 11:11:32	ga_ls8c_ard_3-1-0_108083_2019-10-27_final
2019-11-05 09:25:39	ga_ls8c_ard_3-1-0_091081_2019-11-04_final
2019-11-07 10:48:59	ga_ls8c_ard_3-1-0_105073_2019-11-07_final
2019-11-12 11:07:06	ga_ls8c_ard_3-1-0_108072_2019-11-12_final
2019-11-14 10:58:44	ga_ls8c_ard_3-1-0_106082_2019-11-14_final
2019-11-17 09:50:20	ga_ls8c_ard_3-1-0_095081_2019-11-17_final
2019-11-17 11:27:13	ga_ls8c_ard_3-1-0_111076_2019-11-17_final
2019-11-20 11:58:54	ga_ls8c_ard_3-1-0_116078_2019-11-20_final
2019-11-22 10:08:27	ga_ls8c_ard_3-1-0_098080_2019-11-22_final
2019-11-23 10:48:55	ga_ls8c_ard_3-1-0_105073_2019-11-23_final
2019-11-24 09:52:30	ga_ls8c_ard_3-1-0_096071_2019-11-24_final
2019-12-04 10:29:35	ga_ls8c_ard_3-1-0_102071_2019-12-04_final
2019-12-07 09:26:23	ga_ls8c_ard_3-1-0_091083_2019-12-06_final
2019-12-08 10:05:15	ga_ls8c_ard_3-1-0_098072_2019-12-08_final
2019-12-29 10:23:43	ga_ls8c_ard_3-1-0_101072_2019-12-29_final
2020-01-11 09:57:10	ga_ls8c_ard_3-1-0_096083_2020-01-11_final
2020-01-20 09:50:09	ga_ls8c_ard_3-1-0_095081_2020-01-20_final
2020-01-20 11:23:51	ga_ls8c_ard_3-1-0_111068_2020-01-20_final
2020-01-31 11:06:26	ga_ls8c_ard_3-1-0_108071_2020-01-31_final
2020-02-12 11:35:06	ga_ls8c_ard_3-1-0_112081_2020-02-12_final
2020-02-15 10:25:55	ga_ls8c_ard_3-1-0_101078_2020-02-15_final
2020-02-16 11:07:10	ga_ls8c_ard_3-1-0_108073_2020-02-16_final
2020-02-26 10:05:20	ga_ls8c_ard_3-1-0_098073_2020-02-26_final
2020-02-26 10:07:19	ga_ls8c_ard_3-1-0_098078_2020-02-26_final
2020-03-08 09:49:54	ga_ls8c_ard_3-1-0_095081_2020-03-08_final
2020-03-09 10:32:46	ga_ls8c_ard_3-1-0_102080_2020-03-09_final
2020-03-13 10:06:49	ga_ls8c_ard_3-1-0_098077_2020-03-13_final
2020-03-14 10:46:05	ga_ls8c_ard_3-1-0_105067_2020-03-14_final
2020-03-15 09:57:38	ga_ls8c_ard_3-1-0_096085_2020-03-15_final
2020-03-19 11:06:58	ga_ls8c_ard_3-1-0_108073_2020-03-19_final
2020-03-29 10:07:52	ga_ls8c_ard_3-1-0_098080_2020-03-29_final
2020-03-30 10:45:56	ga_ls8c_ard_3-1-0_105067_2020-03-30_final
2020-04-09 11:29:19	ga_ls8c_ard_3-1-0_111083_2020-04-09_final
2020-04-13 09:23:17	ga_ls8c_ard_3-1-0_091077_2020-04-12_final
2020-04-19 10:25:03	ga_ls8c_ard_3-1-0_101077_2020-04-19_final
2020-04-22 10:53:32	ga_ls8c_ard_3-1-0_106071_2020-04-22_final
2020-04-25 11:26:24	ga_ls8c_ard_3-1-0_111076_2020-04-25_final
2020-05-02 11:35:19	ga_ls8c_ard_3-1-0_112083_2020-05-02_final
2022-04-05 09:11:53	ga_ls8c_ard_3-2-1_089079_2022-04-04_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-15 11:28:43	ga_ls8c_ard_3-2-1_111081_2022-04-15_final
2022-04-17 09:35:04	ga_ls8c_ard_3-2-1_093075_2022-04-17_final
2022-04-22 11:35:16	ga_ls8c_ard_3-2-1_112082_2022-04-22_final
2022-04-27 10:15:17	ga_ls8c_ard_3-2-1_099083_2022-04-27_final
2022-04-29 10:01:19	ga_ls8c_ard_3-2-1_097079_2022-04-29_final
2022-05-09 10:34:32	ga_ls8c_ard_3-2-1_103069_2022-05-09_final
2022-05-13 11:51:31	ga_ls8c_ard_3-2-1_115076_2022-05-13_final
2022-05-14 10:55:06	ga_ls8c_ard_3-2-1_106074_2022-05-14_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-24 09:56:55	ga_ls8c_ard_3-2-1_096083_2022-05-24_final
2022-06-03 10:29:17	ga_ls8c_ard_3-2-1_102071_2022-06-03_final
2022-06-07 10:07:49	ga_ls8c_ard_3-2-1_098079_2022-06-07_final
2022-06-13 09:33:12	ga_ls8c_ard_3-2-1_092085_2022-06-13_final
2022-06-13 11:06:30	ga_ls8c_ard_3-2-1_108071_2022-06-13_final
2022-06-18 09:47:24	ga_ls8c_ard_3-2-1_095074_2022-06-18_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