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:

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First 100 results (query limit)

Time (local)	Label
2019-11-17 09:53:08	ga_ls8c_ard_3-1-0_095088_2019-11-17_final
2020-04-09 09:52:26	ga_ls8c_ard_3-1-0_095088_2020-04-09_final
2022-03-29 10:45:22	ga_ls8c_ard_3-2-1_104081_2022-03-29_final
2022-03-30 11:24:38	ga_ls8c_ard_3-2-1_111071_2022-03-30_final
2022-03-30 11:28:37	ga_ls8c_ard_3-2-1_111081_2022-03-30_final
2022-04-03 09:27:00	ga_ls8c_ard_3-2-1_091086_2022-04-02_final
2022-04-04 11:46:22	ga_ls8c_ard_3-2-1_114079_2022-04-04_final
2022-04-04 11:47:10	ga_ls8c_ard_3-2-1_114081_2022-04-04_final
2022-04-05 09:10:41	ga_ls8c_ard_3-2-1_089076_2022-04-04_final
2022-04-05 10:51:10	ga_ls8c_ard_3-2-1_105080_2022-04-05_final
2022-04-05 10:51:33	ga_ls8c_ard_3-2-1_105081_2022-04-05_final
2022-04-08 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-08_final
2022-04-10 09:27:16	ga_ls8c_ard_3-2-1_092071_2022-04-09_final
2022-04-10 09:28:04	ga_ls8c_ard_3-2-1_092073_2022-04-09_final
2022-04-11 10:16:08	ga_ls8c_ard_3-2-1_099085_2022-04-11_final
2022-04-12 09:16:07	ga_ls8c_ard_3-2-1_090074_2022-04-11_final
2022-04-13 09:57:24	ga_ls8c_ard_3-2-1_097069_2022-04-13_final
2022-04-13 11:37:53	ga_ls8c_ard_3-2-1_113073_2022-04-13_final
2022-04-15 09:45:51	ga_ls8c_ard_3-2-1_095071_2022-04-15_final
2022-04-15 11:24:44	ga_ls8c_ard_3-2-1_111071_2022-04-15_final
2022-04-17 11:14:45	ga_ls8c_ard_3-2-1_109077_2022-04-17_final
2022-04-17 11:17:33	ga_ls8c_ard_3-2-1_109084_2022-04-17_final
2022-04-18 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-04-18_final
2022-04-19 09:21:31	ga_ls8c_ard_3-2-1_091072_2022-04-18_final
2022-04-21 09:10:44	ga_ls8c_ard_3-2-1_089076_2022-04-20_final
2022-04-21 10:51:37	ga_ls8c_ard_3-2-1_105081_2022-04-21_final
2022-04-21 10:52:25	ga_ls8c_ard_3-2-1_105083_2022-04-21_final
2022-04-22 09:53:12	ga_ls8c_ard_3-2-1_096074_2022-04-22_final
2022-04-22 09:57:59	ga_ls8c_ard_3-2-1_096086_2022-04-22_final
2022-04-22 11:31:41	ga_ls8c_ard_3-2-1_112073_2022-04-22_final
2022-04-24 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-24_final
2022-04-25 10:22:28	ga_ls8c_ard_3-2-1_101070_2022-04-25_final
2022-04-25 10:24:52	ga_ls8c_ard_3-2-1_101076_2022-04-25_final
2022-04-25 10:25:16	ga_ls8c_ard_3-2-1_101077_2022-04-25_final
2022-04-25 10:26:52	ga_ls8c_ard_3-2-1_101081_2022-04-25_final
2022-04-26 09:27:15	ga_ls8c_ard_3-2-1_092071_2022-04-25_final
2022-04-26 09:27:39	ga_ls8c_ard_3-2-1_092072_2022-04-25_final
2022-04-26 09:28:02	ga_ls8c_ard_3-2-1_092073_2022-04-25_final
2022-04-26 09:30:02	ga_ls8c_ard_3-2-1_092078_2022-04-26_final
2022-04-26 09:30:26	ga_ls8c_ard_3-2-1_092079_2022-04-26_final
2022-04-26 09:30:50	ga_ls8c_ard_3-2-1_092080_2022-04-26_final
2022-04-27 10:16:05	ga_ls8c_ard_3-2-1_099085_2022-04-27_final
2022-04-28 09:16:04	ga_ls8c_ard_3-2-1_090074_2022-04-27_final
2022-04-29 10:02:06	ga_ls8c_ard_3-2-1_097081_2022-04-29_final
2022-04-29 11:37:48	ga_ls8c_ard_3-2-1_113073_2022-04-29_final
2022-05-01 11:26:40	ga_ls8c_ard_3-2-1_111076_2022-05-01_final
2022-05-05 09:25:07	ga_ls8c_ard_3-2-1_091081_2022-05-04_final
2022-05-07 09:09:59	ga_ls8c_ard_3-2-1_089074_2022-05-06_final
2022-05-07 09:10:47	ga_ls8c_ard_3-2-1_089076_2022-05-06_final
2022-05-07 09:11:59	ga_ls8c_ard_3-2-1_089079_2022-05-06_final
2022-05-09 10:37:19	ga_ls8c_ard_3-2-1_103076_2022-05-09_final
2022-05-09 10:37:43	ga_ls8c_ard_3-2-1_103077_2022-05-09_final
2022-05-10 09:40:31	ga_ls8c_ard_3-2-1_094073_2022-05-10_final
2022-05-10 09:41:43	ga_ls8c_ard_3-2-1_094076_2022-05-10_final
2022-05-10 09:42:06	ga_ls8c_ard_3-2-1_094077_2022-05-10_final
2022-05-10 09:42:30	ga_ls8c_ard_3-2-1_094078_2022-05-10_final
2022-05-10 09:42:54	ga_ls8c_ard_3-2-1_094079_2022-05-10_final
2022-05-10 09:43:18	ga_ls8c_ard_3-2-1_094080_2022-05-10_final
2022-05-10 09:43:42	ga_ls8c_ard_3-2-1_094081_2022-05-10_final
2022-05-11 10:22:35	ga_ls8c_ard_3-2-1_101070_2022-05-11_final
2022-05-12 09:27:22	ga_ls8c_ard_3-2-1_092071_2022-05-11_final
2022-05-12 09:27:46	ga_ls8c_ard_3-2-1_092072_2022-05-11_final
2022-05-12 09:28:10	ga_ls8c_ard_3-2-1_092073_2022-05-11_final
2022-05-12 09:29:22	ga_ls8c_ard_3-2-1_092076_2022-05-11_final
2022-05-12 09:29:46	ga_ls8c_ard_3-2-1_092077_2022-05-11_final
2022-05-12 09:30:10	ga_ls8c_ard_3-2-1_092078_2022-05-12_final
2022-05-12 09:30:34	ga_ls8c_ard_3-2-1_092079_2022-05-12_final
2022-05-12 09:30:58	ga_ls8c_ard_3-2-1_092080_2022-05-12_final
2022-05-12 09:32:10	ga_ls8c_ard_3-2-1_092083_2022-05-12_final
2022-05-12 09:34:57	ga_ls8c_ard_3-2-1_092090_2022-05-12_final
2022-05-14 09:16:13	ga_ls8c_ard_3-2-1_090074_2022-05-13_final
2022-05-14 09:17:49	ga_ls8c_ard_3-2-1_090078_2022-05-13_final
2022-05-15 11:37:59	ga_ls8c_ard_3-2-1_113073_2022-05-15_final
2022-05-17 11:26:49	ga_ls8c_ard_3-2-1_111076_2022-05-17_final
2022-05-17 11:27:13	ga_ls8c_ard_3-2-1_111077_2022-05-17_final
2022-05-18 10:32:00	ga_ls8c_ard_3-2-1_102078_2022-05-18_final
2022-05-18 10:32:24	ga_ls8c_ard_3-2-1_102079_2022-05-18_final
2022-05-19 09:40:22	ga_ls8c_ard_3-2-1_093088_2022-05-19_final
2022-05-21 09:24:01	ga_ls8c_ard_3-2-1_091078_2022-05-20_final
2022-05-24 11:31:48	ga_ls8c_ard_3-2-1_112073_2022-05-24_final
2022-05-30 10:58:44	ga_ls8c_ard_3-2-1_106083_2022-05-30_final
2022-05-31 11:38:01	ga_ls8c_ard_3-2-1_113073_2022-05-31_final
2022-05-31 11:38:49	ga_ls8c_ard_3-2-1_113075_2022-05-31_final
2022-05-31 11:39:13	ga_ls8c_ard_3-2-1_113076_2022-05-31_final
2022-06-01 10:42:25	ga_ls8c_ard_3-2-1_104073_2022-06-01_final
2022-06-01 10:42:49	ga_ls8c_ard_3-2-1_104074_2022-06-01_final
2022-06-01 10:45:37	ga_ls8c_ard_3-2-1_104081_2022-06-01_final
2022-06-04 09:35:41	ga_ls8c_ard_3-2-1_093076_2022-06-04_final
2022-06-04 09:36:28	ga_ls8c_ard_3-2-1_093078_2022-06-04_final
2022-06-05 11:57:50	ga_ls8c_ard_3-2-1_116076_2022-06-05_final
2022-06-06 09:22:09	ga_ls8c_ard_3-2-1_091073_2022-06-05_final
2022-06-06 09:23:45	ga_ls8c_ard_3-2-1_091077_2022-06-05_final
2022-06-06 09:26:08	ga_ls8c_ard_3-2-1_091083_2022-06-05_final
2022-06-08 09:10:13	ga_ls8c_ard_3-2-1_089074_2022-06-07_final
2022-06-08 09:11:01	ga_ls8c_ard_3-2-1_089076_2022-06-07_final
2022-06-13 09:32:00	ga_ls8c_ard_3-2-1_092082_2022-06-13_final
2022-06-13 09:35:12	ga_ls8c_ard_3-2-1_092090_2022-06-13_final
2022-06-16 11:38:14	ga_ls8c_ard_3-2-1_113073_2022-06-16_final
2022-06-18 09:46:12	ga_ls8c_ard_3-2-1_095071_2022-06-18_final
2022-06-19 10:32:16	ga_ls8c_ard_3-2-1_102078_2022-06-19_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