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
2018-12-04 09:27:11	ga_ls8c_ard_3-1-0_091086_2018-12-03_final
2019-03-13 09:52:11	ga_ls8c_ard_3-1-0_096072_2019-03-13_final
2019-03-13 09:52:59	ga_ls8c_ard_3-1-0_096074_2019-03-13_final
2019-03-26 09:25:38	ga_ls8c_ard_3-1-0_091083_2019-03-25_final
2019-03-26 09:26:26	ga_ls8c_ard_3-1-0_091085_2019-03-25_final
2019-06-14 09:23:30	ga_ls8c_ard_3-1-0_091077_2019-06-13_final
2019-06-14 09:24:18	ga_ls8c_ard_3-1-0_091079_2019-06-13_final
2019-06-30 09:24:46	ga_ls8c_ard_3-1-0_091080_2019-06-29_final
2019-06-30 09:25:34	ga_ls8c_ard_3-1-0_091082_2019-06-29_final
2019-07-12 09:50:44	ga_ls8c_ard_3-1-0_095083_2019-07-12_final
2019-07-28 09:51:37	ga_ls8c_ard_3-1-0_095085_2019-07-28_final
2019-08-01 09:24:56	ga_ls8c_ard_3-1-0_091080_2019-07-31_final
2019-08-01 09:25:43	ga_ls8c_ard_3-1-0_091082_2019-07-31_final
2019-08-13 09:46:55	ga_ls8c_ard_3-1-0_095073_2019-08-13_final
2019-08-13 09:50:31	ga_ls8c_ard_3-1-0_095082_2019-08-13_final
2019-08-24 11:10:31	ga_ls8c_ard_3-1-0_108081_2019-08-24_final
2019-09-02 09:26:16	ga_ls8c_ard_3-1-0_091083_2019-09-01_final
2019-09-02 09:27:04	ga_ls8c_ard_3-1-0_091085_2019-09-01_final
2019-09-14 09:51:28	ga_ls8c_ard_3-1-0_095084_2019-09-14_final
2019-09-18 09:25:10	ga_ls8c_ard_3-1-0_091080_2019-09-17_final
2019-09-30 09:51:33	ga_ls8c_ard_3-1-0_095084_2019-09-30_final
2019-10-04 09:24:02	ga_ls8c_ard_3-1-0_091077_2019-10-03_final
2019-10-04 09:26:26	ga_ls8c_ard_3-1-0_091083_2019-10-03_final
2019-10-16 09:48:00	ga_ls8c_ard_3-1-0_095075_2019-10-16_final
2019-10-20 09:24:04	ga_ls8c_ard_3-1-0_091077_2019-10-19_final
2019-10-20 09:26:28	ga_ls8c_ard_3-1-0_091083_2019-10-19_final
2019-10-23 09:52:59	ga_ls8c_ard_3-1-0_096072_2019-10-23_final
2019-10-23 09:53:47	ga_ls8c_ard_3-1-0_096074_2019-10-23_final
2019-11-01 09:47:59	ga_ls8c_ard_3-1-0_095075_2019-11-01_final
2019-11-05 09:26:03	ga_ls8c_ard_3-1-0_091082_2019-11-04_final
2019-11-05 09:26:27	ga_ls8c_ard_3-1-0_091083_2019-11-04_final
2019-11-24 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-11-24_final
2019-12-03 09:47:55	ga_ls8c_ard_3-1-0_095075_2019-12-03_final
2019-12-03 09:50:19	ga_ls8c_ard_3-1-0_095081_2019-12-03_final
2019-12-07 09:27:35	ga_ls8c_ard_3-1-0_091086_2019-12-06_final
2019-12-26 09:53:38	ga_ls8c_ard_3-1-0_096074_2019-12-26_final
2019-12-26 09:58:01	ga_ls8c_ard_3-1-0_096085_2019-12-26_final
2020-01-08 09:25:28	ga_ls8c_ard_3-1-0_091081_2020-01-07_final
2020-01-11 09:53:34	ga_ls8c_ard_3-1-0_096074_2020-01-11_final
2020-02-05 09:48:27	ga_ls8c_ard_3-1-0_095077_2020-02-05_final
2020-03-08 09:49:54	ga_ls8c_ard_3-1-0_095081_2020-03-08_final
2020-03-08 09:50:42	ga_ls8c_ard_3-1-0_095083_2020-03-08_final
2020-04-09 09:47:14	ga_ls8c_ard_3-1-0_095075_2020-04-09_final
2020-04-16 09:56:34	ga_ls8c_ard_3-1-0_096083_2020-04-16_final
2020-05-02 09:56:02	ga_ls8c_ard_3-1-0_096082_2020-05-02_final
2022-03-30 09:47:20	ga_ls8c_ard_3-2-1_095075_2022-03-30_final
2022-03-30 11:27:25	ga_ls8c_ard_3-2-1_111078_2022-03-30_final
2022-04-01 09:35:22	ga_ls8c_ard_3-2-1_093076_2022-04-01_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-09 10:25:41	ga_ls8c_ard_3-2-1_101078_2022-04-09_final
2022-04-09 10:27:41	ga_ls8c_ard_3-2-1_101083_2022-04-09_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-10 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-04-10_final
2022-04-10 11:05:22	ga_ls8c_ard_3-2-1_108069_2022-04-10_final
2022-04-10 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-04-10_final
2022-04-10 11:11:21	ga_ls8c_ard_3-2-1_108084_2022-04-10_final
2022-04-11 10:12:32	ga_ls8c_ard_3-2-1_099076_2022-04-11_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-14 10:41:04	ga_ls8c_ard_3-2-1_104070_2022-04-14_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-17 09:34:41	ga_ls8c_ard_3-2-1_093074_2022-04-17_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-19 09:25:54	ga_ls8c_ard_3-2-1_091083_2022-04-18_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-24 09:44:49	ga_ls8c_ard_3-2-1_094084_2022-04-24_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-28 10:54:09	ga_ls8c_ard_3-2-1_106072_2022-04-28_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-05 09:25:55	ga_ls8c_ard_3-2-1_091083_2022-05-04_final
2022-05-07 10:52:03	ga_ls8c_ard_3-2-1_105082_2022-05-07_final
2022-05-12 11:05:27	ga_ls8c_ard_3-2-1_108069_2022-05-12_final
2022-05-16 10:43:33	ga_ls8c_ard_3-2-1_104076_2022-05-16_final
2022-05-18 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-05-18_final
2022-05-20 10:20:26	ga_ls8c_ard_3-2-1_100080_2022-05-20_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-24 09:53:19	ga_ls8c_ard_3-2-1_096074_2022-05-24_final
2022-05-26 09:43:21	ga_ls8c_ard_3-2-1_094080_2022-05-26_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-30 10:55:09	ga_ls8c_ard_3-2-1_106074_2022-05-30_final
2022-05-30 10:56:44	ga_ls8c_ard_3-2-1_106078_2022-05-30_final
2022-05-30 10:58:20	ga_ls8c_ard_3-2-1_106082_2022-05-30_final
2022-05-31 09:56:45	ga_ls8c_ard_3-2-1_097067_2022-05-31_final
2022-05-31 11:40:49	ga_ls8c_ard_3-2-1_113080_2022-05-31_final
2022-06-02 09:47:36	ga_ls8c_ard_3-2-1_095075_2022-06-02_final
2022-06-02 11:26:53	ga_ls8c_ard_3-2-1_111076_2022-06-02_final
2022-06-04 11:17:21	ga_ls8c_ard_3-2-1_109083_2022-06-04_final
2022-06-05 10:17:45	ga_ls8c_ard_3-2-1_100073_2022-06-05_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-07 10:10:13	ga_ls8c_ard_3-2-1_098085_2022-06-07_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_2022-06-20_final
2022-06-21 10:20:19	ga_ls8c_ard_3-2-1_100079_2022-06-21_final
2022-06-22 09:26:17	ga_ls8c_ard_3-2-1_091083_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