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
2021-12-29 10:07:36	ga_ls8c_ard_3-2-1_098078_2021-12-29_final
2022-01-02 11:19:45	ga_ls8c_ard_3-2-1_110073_2022-01-02_final
2022-01-13 11:01:59	ga_ls8c_ard_3-2-1_107075_2022-01-13_final
2022-01-14 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-01-14_final
2022-01-21 11:52:59	ga_ls8c_ard_3-2-1_115079_2022-01-21_final
2022-01-29 09:22:37	ga_ls8c_ard_3-2-1_091074_2022-01-28_final
2022-01-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2022-01-30_final
2022-02-06 11:52:32	ga_ls8c_ard_3-2-1_115078_2022-02-06_final
2022-02-08 09:57:17	ga_ls8c_ard_3-2-1_097068_2022-02-08_final
2022-02-12 09:33:44	ga_ls8c_ard_3-2-1_093071_2022-02-12_final
2022-02-13 10:20:11	ga_ls8c_ard_3-2-1_100079_2022-02-13_final
2022-02-16 09:12:11	ga_ls8c_ard_3-2-1_089079_2022-02-15_final
2022-02-16 10:46:41	ga_ls8c_ard_3-2-1_105068_2022-02-16_final
2022-02-16 10:49:52	ga_ls8c_ard_3-2-1_105076_2022-02-16_final
2022-02-16 10:52:40	ga_ls8c_ard_3-2-1_105083_2022-02-16_final
2022-02-24 10:03:35	ga_ls8c_ard_3-2-1_097084_2022-02-24_final
2022-03-02 09:22:54	ga_ls8c_ard_3-2-1_091075_2022-03-01_final
2022-03-03 10:09:21	ga_ls8c_ard_3-2-1_098083_2022-03-03_final
2022-03-04 09:14:31	ga_ls8c_ard_3-2-1_089085_2022-03-03_final
2022-03-11 09:21:52	ga_ls8c_ard_3-2-1_090088_2022-03-10_final
2022-03-18 10:59:40	ga_ls8c_ard_3-2-1_107070_2022-03-18_final
2022-03-20 09:13:59	ga_ls8c_ard_3-2-1_089084_2022-03-19_final
2022-03-25 09:34:04	ga_ls8c_ard_3-2-1_092088_2022-03-25_final
2022-03-30 09:46:32	ga_ls8c_ard_3-2-1_095073_2022-03-30_final
2022-04-04 10:03:30	ga_ls8c_ard_3-2-1_098069_2022-04-04_final
2022-04-07 10:35:38	ga_ls8c_ard_3-2-1_103072_2022-04-07_final
2022-04-11 10:09:21	ga_ls8c_ard_3-2-1_099068_2022-04-11_final
2022-04-27 11:51:46	ga_ls8c_ard_3-2-1_115077_2022-04-27_final
2022-04-27 11:52:58	ga_ls8c_ard_3-2-1_115080_2022-04-27_final
2022-04-30 09:06:30	ga_ls8c_ard_3-2-1_088081_2022-04-29_final
2022-05-04 10:21:07	ga_ls8c_ard_3-2-1_100082_2022-05-04_final
2022-05-06 10:03:12	ga_ls8c_ard_3-2-1_098068_2022-05-06_final
2022-05-09 10:35:44	ga_ls8c_ard_3-2-1_103072_2022-05-09_final
2022-05-14 09:20:13	ga_ls8c_ard_3-2-1_090084_2022-05-13_final
2022-05-22 10:02:54	ga_ls8c_ard_3-2-1_098067_2022-05-22_final
2022-05-22 10:03:41	ga_ls8c_ard_3-2-1_098069_2022-05-22_final
2022-06-03 10:32:53	ga_ls8c_ard_3-2-1_102080_2022-06-03_final
2022-06-04 09:34:29	ga_ls8c_ard_3-2-1_093073_2022-06-04_final
2022-06-15 09:21:40	ga_ls8c_ard_3-2-1_090087_2022-06-14_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-20 11:17:55	ga_ls8c_ard_3-2-1_109084_2022-06-20_final
2022-06-30 10:14:10	ga_ls8c_ard_3-2-1_099079_2022-06-30_final
2022-07-01 10:54:38	ga_ls8c_ard_3-2-1_106072_2022-07-01_final
2022-07-07 10:19:09	ga_ls8c_ard_3-2-1_100076_2022-07-07_final
2022-07-10 09:15:09	ga_ls8c_ard_3-2-1_089086_2022-07-09_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-07-29 11:21:06	ga_ls8c_ard_3-2-1_110076_2022-07-29_final
2022-08-02 10:58:01	ga_ls8c_ard_3-2-1_106080_2022-08-02_final
2022-08-09 09:22:10	ga_ls8c_ard_3-2-1_091072_2022-08-08_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-18 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-08-18_final
2022-08-25 09:27:48	ga_ls8c_ard_3-2-1_091086_2022-08-24_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-09-13 11:32:53	ga_ls8c_ard_3-2-1_112074_2022-09-13_final
2022-09-13 11:36:53	ga_ls8c_ard_3-2-1_112084_2022-09-13_final
2022-09-14 10:39:40	ga_ls8c_ard_3-2-1_103080_2022-09-14_final
2022-09-19 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-09-19_final
2022-09-22 11:30:44	ga_ls8c_ard_3-2-1_111084_2022-09-22_final
2022-09-24 11:15:10	ga_ls8c_ard_3-2-1_109076_2022-09-24_final
2022-09-28 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-09-28_final
2022-09-29 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-09-29_final
2022-09-29 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-09-29_final
2022-10-04 10:14:32	ga_ls8c_ard_3-2-1_099079_2022-10-04_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-08 11:26:16	ga_ls8c_ard_3-2-1_111073_2022-10-08_final
2022-10-11 10:17:26	ga_ls8c_ard_3-2-1_100071_2022-10-11_final
2022-10-13 10:05:03	ga_ls8c_ard_3-2-1_098071_2022-10-13_final
2022-10-14 09:12:36	ga_ls8c_ard_3-2-1_089079_2022-10-13_final
2022-10-14 10:52:41	ga_ls8c_ard_3-2-1_105082_2022-10-14_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-21 09:17:41	ga_ls8c_ard_3-2-1_090076_2022-10-20_final
2022-11-02 09:44:52	ga_ls8c_ard_3-2-1_094082_2022-11-02_final
2022-11-04 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-11-04_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-04 09:33:42	ga_ls8c_ard_3-2-1_092085_2022-11-04_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-19 10:28:24	ga_ls8c_ard_3-2-1_101083_2022-11-19_final
2022-11-24 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-11-23_final
2022-11-25 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-11-25_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-07 10:09:41	ga_ls8c_ard_3-2-1_099067_2022-12-07_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-15 09:22:10	ga_ls8c_ard_3-2-1_091072_2022-12-14_final
2022-12-23 11:53:11	ga_ls8c_ard_3-2-1_115079_2022-12-23_final
2023-01-08 11:53:12	ga_ls8c_ard_3-2-1_115079_2023-01-08_final
2023-01-09 10:54:23	ga_ls8c_ard_3-2-1_106071_2023-01-09_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-21 11:24:13	ga_ls8c_ard_3-2-1_110084_2023-01-21_final
2023-01-31 10:17:41	ga_ls8c_ard_3-2-1_100072_2023-01-31_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-12 10:45:31	ga_ls8c_ard_3-2-1_104080_2023-02-12_final
2023-02-27 11:38:30	ga_ls8c_ard_3-2-1_113074_2023-02-27_final
2023-03-03 09:33:41	ga_ls8c_ard_3-2-1_093071_2023-03-03_final
2023-03-06 10:03:22	ga_ls8c_ard_3-2-1_098068_2023-03-06_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