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
2019-03-22 09:51:10	ga_ls8c_ard_3-1-0_095085_2019-03-22_final
2019-04-11 09:27:09	ga_ls8c_ard_3-1-0_091087_2019-04-10_final
2019-06-26 09:50:17	ga_ls8c_ard_3-1-0_095082_2019-06-26_final
2019-06-26 09:50:40	ga_ls8c_ard_3-1-0_095083_2019-06-26_final
2019-07-12 09:47:08	ga_ls8c_ard_3-1-0_095074_2019-07-12_final
2019-07-28 09:50:25	ga_ls8c_ard_3-1-0_095082_2019-07-28_final
2019-08-29 09:46:12	ga_ls8c_ard_3-1-0_095071_2019-08-29_final
2019-09-02 09:23:29	ga_ls8c_ard_3-1-0_091076_2019-09-01_final
2019-09-02 09:26:40	ga_ls8c_ard_3-1-0_091084_2019-09-01_final
2019-09-30 09:45:57	ga_ls8c_ard_3-1-0_095070_2019-09-30_final
2019-09-30 09:52:20	ga_ls8c_ard_3-1-0_095086_2019-09-30_final
2019-10-16 09:47:12	ga_ls8c_ard_3-1-0_095073_2019-10-16_final
2019-10-20 09:25:16	ga_ls8c_ard_3-1-0_091080_2019-10-19_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-17 09:50:20	ga_ls8c_ard_3-1-0_095081_2019-11-17_final
2019-12-03 09:46:43	ga_ls8c_ard_3-1-0_095072_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
2020-01-04 09:44:37	ga_ls8c_ard_3-1-0_095067_2020-01-04_final
2020-01-20 09:46:10	ga_ls8c_ard_3-1-0_095071_2020-01-20_final
2020-02-05 09:50:51	ga_ls8c_ard_3-1-0_095083_2020-02-05_final
2020-03-08 09:49:54	ga_ls8c_ard_3-1-0_095081_2020-03-08_final
2020-04-09 09:49:38	ga_ls8c_ard_3-1-0_095081_2020-04-09_final
2020-04-25 09:50:19	ga_ls8c_ard_3-1-0_095083_2020-04-25_final
2020-04-25 09:50:43	ga_ls8c_ard_3-1-0_095084_2020-04-25_final
2020-04-25 09:51:07	ga_ls8c_ard_3-1-0_095085_2020-04-25_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-03-30 11:26:37	ga_ls8c_ard_3-2-1_111076_2022-03-30_final
2022-04-01 11:13:04	ga_ls8c_ard_3-2-1_109073_2022-04-01_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-05 09:12:16	ga_ls8c_ard_3-2-1_089080_2022-04-04_final
2022-04-05 09:13:04	ga_ls8c_ard_3-2-1_089082_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-14 10:42:16	ga_ls8c_ard_3-2-1_104073_2022-04-14_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-19 09:24:42	ga_ls8c_ard_3-2-1_091080_2022-04-18_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-04-21 10:46:50	ga_ls8c_ard_3-2-1_105069_2022-04-21_final
2022-04-22 11:35:16	ga_ls8c_ard_3-2-1_112082_2022-04-22_final
2022-04-23 10:39:38	ga_ls8c_ard_3-2-1_103082_2022-04-23_final
2022-04-24 09:39:37	ga_ls8c_ard_3-2-1_094071_2022-04-24_final
2022-04-24 09:43:13	ga_ls8c_ard_3-2-1_094080_2022-04-24_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-24 11:23:42	ga_ls8c_ard_3-2-1_110084_2022-04-24_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-03 09:34:39	ga_ls8c_ard_3-2-1_093074_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-06 10:04:24	ga_ls8c_ard_3-2-1_098071_2022-05-06_final
2022-05-06 10:04:48	ga_ls8c_ard_3-2-1_098072_2022-05-06_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-10 09:45:18	ga_ls8c_ard_3-2-1_094085_2022-05-10_final
2022-05-12 09:33:21	ga_ls8c_ard_3-2-1_092086_2022-05-12_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-14 10:53:54	ga_ls8c_ard_3-2-1_106071_2022-05-14_final
2022-05-14 10:56:18	ga_ls8c_ard_3-2-1_106077_2022-05-14_final
2022-05-14 10:58:42	ga_ls8c_ard_3-2-1_106083_2022-05-14_final
2022-05-15 09:57:54	ga_ls8c_ard_3-2-1_097070_2022-05-15_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-16 10:43:33	ga_ls8c_ard_3-2-1_104076_2022-05-16_final
2022-05-17 09:50:44	ga_ls8c_ard_3-2-1_095083_2022-05-17_final
2022-05-17 11:24:50	ga_ls8c_ard_3-2-1_111071_2022-05-17_final
2022-05-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2022-05-17_final
2022-05-19 09:37:59	ga_ls8c_ard_3-2-1_093082_2022-05-19_final
2022-05-19 11:16:52	ga_ls8c_ard_3-2-1_109082_2022-05-19_final
2022-05-24 09:52:55	ga_ls8c_ard_3-2-1_096073_2022-05-24_final
2022-05-24 09:56:55	ga_ls8c_ard_3-2-1_096083_2022-05-24_final
2022-05-24 11:35:00	ga_ls8c_ard_3-2-1_112081_2022-05-24_final
2022-05-25 10:39:46	ga_ls8c_ard_3-2-1_103082_2022-05-25_final
2022-05-26 09:46:08	ga_ls8c_ard_3-2-1_094087_2022-05-26_final
2022-05-30 10:55:33	ga_ls8c_ard_3-2-1_106075_2022-05-30_final
2022-05-31 11:40:49	ga_ls8c_ard_3-2-1_113080_2022-05-31_final
2022-06-02 11:23:42	ga_ls8c_ard_3-2-1_111068_2022-06-02_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-03 10:29:17	ga_ls8c_ard_3-2-1_102071_2022-06-03_final
2022-06-04 09:39:40	ga_ls8c_ard_3-2-1_093086_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-06 09:25:20	ga_ls8c_ard_3-2-1_091081_2022-06-05_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-07 11:45:54	ga_ls8c_ard_3-2-1_114077_2022-06-07_final
2022-06-08 10:51:53	ga_ls8c_ard_3-2-1_105081_2022-06-08_final
2022-06-13 09:30:48	ga_ls8c_ard_3-2-1_092079_2022-06-13_final
2022-06-13 11:06:30	ga_ls8c_ard_3-2-1_108071_2022-06-13_final
2022-06-17 10:41:25	ga_ls8c_ard_3-2-1_104070_2022-06-17_final
2022-06-18 09:47:48	ga_ls8c_ard_3-2-1_095075_2022-06-18_final
2022-06-20 09:35:51	ga_ls8c_ard_3-2-1_093076_2022-06-20_final
2022-06-20 11:17:08	ga_ls8c_ard_3-2-1_109082_2022-06-20_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_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