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
2022-07-26 10:52:57	ga_ls8c_ard_3-2-1_105083_2022-07-26_final
2022-07-29 09:45:00	ga_ls8c_ard_3-2-1_094083_2022-07-29_final
2022-08-02 09:19:56	ga_ls8c_ard_3-2-1_090082_2022-08-01_final
2022-08-02 10:58:25	ga_ls8c_ard_3-2-1_106081_2022-08-02_final
2022-08-05 09:50:27	ga_ls8c_ard_3-2-1_095081_2022-08-05_final
2022-08-16 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-08-15_final
2022-08-21 11:29:25	ga_ls8c_ard_3-2-1_111081_2022-08-21_final
2022-08-29 10:37:11	ga_ls8c_ard_3-2-1_103074_2022-08-29_final
2022-08-30 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-08-30_final
2022-08-30 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-08-30_final
2022-08-30 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-08-30_final
2022-09-01 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-09-01_final
2022-09-04 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-09-04_final
2022-09-04 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-09-04_final
2022-09-07 10:34:13	ga_ls8c_ard_3-2-1_102082_2022-09-07_final
2022-09-10 11:01:10	ga_ls8c_ard_3-2-1_107072_2022-09-10_final
2022-09-11 10:05:57	ga_ls8c_ard_3-2-1_098073_2022-09-11_final
2022-09-11 11:46:50	ga_ls8c_ard_3-2-1_114078_2022-09-11_final
2022-09-13 11:35:17	ga_ls8c_ard_3-2-1_112080_2022-09-13_final
2022-09-15 11:21:44	ga_ls8c_ard_3-2-1_110077_2022-09-15_final
2022-09-23 10:31:31	ga_ls8c_ard_3-2-1_102075_2022-09-23_final
2022-09-26 11:01:13	ga_ls8c_ard_3-2-1_107072_2022-09-26_final
2022-09-30 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-09-30_final
2022-10-10 09:36:59	ga_ls8c_ard_3-2-1_093078_2022-10-10_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-12 11:04:40	ga_ls8c_ard_3-2-1_107081_2022-10-12_final
2022-10-13 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-10-13_final
2022-10-16 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-10-16_final
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-19 11:11:18	ga_ls8c_ard_3-2-1_108082_2022-10-19_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-23 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-23_final
2022-10-24 09:48:12	ga_ls8c_ard_3-2-1_095075_2022-10-24_final
2022-10-25 10:31:05	ga_ls8c_ard_3-2-1_102074_2022-10-25_final
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-10-28 11:04:23	ga_ls8c_ard_3-2-1_107080_2022-10-28_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-10-31 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-10-31_final
2022-11-02 11:22:57	ga_ls8c_ard_3-2-1_110080_2022-11-02_final
2022-11-04 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-11-04_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-12 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-11-12_final
2022-11-14 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-14_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-21 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-11-21_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-11-30 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-30_final
2022-12-02 09:57:08	ga_ls8c_ard_3-2-1_096082_2022-12-02_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-04 11:22:52	ga_ls8c_ard_3-2-1_110080_2022-12-04_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-09 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-12-09_final
2022-12-19 10:37:52	ga_ls8c_ard_3-2-1_103076_2022-12-19_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-20 11:22:43	ga_ls8c_ard_3-2-1_110080_2022-12-20_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-21 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-12-21_final
2022-12-21 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-12-21_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2022-12-28 10:32:28	ga_ls8c_ard_3-2-1_102078_2022-12-28_final
2022-12-31 11:04:58	ga_ls8c_ard_3-2-1_107082_2022-12-31_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-12 09:51:09	ga_ls8c_ard_3-2-1_095083_2023-01-12_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-13 10:34:00	ga_ls8c_ard_3-2-1_102082_2023-01-13_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-14 11:15:15	ga_ls8c_ard_3-2-1_109077_2023-01-14_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-02-01 09:26:03	ga_ls8c_ard_3-2-1_091082_2023-01-31_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-02-06 11:22:40	ga_ls8c_ard_3-2-1_110080_2023-02-06_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-08 09:33:00	ga_ls8c_ard_3-2-1_092084_2023-02-08_final
2023-02-08 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-02-08_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-15 09:36:18	ga_ls8c_ard_3-2-1_093077_2023-02-15_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-20 09:57:09	ga_ls8c_ard_3-2-1_096083_2023-02-20_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-25 10:14:46	ga_ls8c_ard_3-2-1_099081_2023-02-25_final
2023-03-01 09:47:39	ga_ls8c_ard_3-2-1_095075_2023-03-01_final
2023-03-01 11:28:32	ga_ls8c_ard_3-2-1_111080_2023-03-01_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-05 09:25:18	ga_ls8c_ard_3-2-1_091081_2023-03-04_final
2023-03-10 11:21:05	ga_ls8c_ard_3-2-1_110077_2023-03-10_final
2023-03-11 10:27:03	ga_ls8c_ard_3-2-1_101081_2023-03-11_final
2023-03-15 09:59:08	ga_ls8c_ard_3-2-1_097073_2023-03-15_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