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
2022-08-23 11:17:03	ga_ls8c_ard_3-2-1_109081_2022-08-23_final
2022-09-14 10:36:04	ga_ls8c_ard_3-2-1_103071_2022-09-14_final
2022-09-15 09:42:51	ga_ls8c_ard_3-2-1_094077_2022-09-15_final
2022-09-15 09:43:15	ga_ls8c_ard_3-2-1_094078_2022-09-15_final
2022-09-17 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-09-17_final
2022-09-18 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-09-18_final
2022-09-19 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-09-19_final
2022-09-22 09:49:51	ga_ls8c_ard_3-2-1_095079_2022-09-22_final
2022-09-22 11:27:08	ga_ls8c_ard_3-2-1_111075_2022-09-22_final
2022-09-24 09:36:41	ga_ls8c_ard_3-2-1_093077_2022-09-24_final
2022-09-24 11:17:10	ga_ls8c_ard_3-2-1_109081_2022-09-24_final
2022-09-26 09:24:44	ga_ls8c_ard_3-2-1_091078_2022-09-25_final
2022-09-27 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-09-27_final
2022-10-15 09:53:29	ga_ls8c_ard_3-2-1_096073_2022-10-15_final
2022-10-15 11:35:58	ga_ls8c_ard_3-2-1_112082_2022-10-15_final
2022-10-17 09:43:33	ga_ls8c_ard_3-2-1_094079_2022-10-17_final
2022-10-17 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-10-17_final
2022-10-18 10:26:49	ga_ls8c_ard_3-2-1_101079_2022-10-18_final
2022-10-21 10:56:58	ga_ls8c_ard_3-2-1_106077_2022-10-21_final
2022-10-26 11:15:57	ga_ls8c_ard_3-2-1_109078_2022-10-26_final
2022-11-04 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-11-04_final
2022-11-04 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-11-04_final
2022-11-04 09:34:54	ga_ls8c_ard_3-2-1_092088_2022-11-04_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-07 10:01:23	ga_ls8c_ard_3-2-1_097077_2022-11-07_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-09 09:51:49	ga_ls8c_ard_3-2-1_095084_2022-11-09_final
2022-11-11 09:37:26	ga_ls8c_ard_3-2-1_093079_2022-11-11_final
2022-11-11 11:15:31	ga_ls8c_ard_3-2-1_109077_2022-11-11_final
2022-11-11 11:15:55	ga_ls8c_ard_3-2-1_109078_2022-11-11_final
2022-11-12 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-11-12_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-23 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-11-23_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-27 11:15:53	ga_ls8c_ard_3-2-1_109078_2022-11-27_final
2022-11-30 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-30_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-11 11:27:48	ga_ls8c_ard_3-2-1_111077_2022-12-11_final
2022-12-13 09:40:32	ga_ls8c_ard_3-2-1_093087_2022-12-13_final
2022-12-14 10:18:36	ga_ls8c_ard_3-2-1_100074_2022-12-14_final
2022-12-16 10:09:01	ga_ls8c_ard_3-2-1_098081_2022-12-16_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2023-01-12 09:47:34	ga_ls8c_ard_3-2-1_095074_2023-01-12_final
2023-01-12 11:27:39	ga_ls8c_ard_3-2-1_111077_2023-01-12_final
2023-01-19 11:35:21	ga_ls8c_ard_3-2-1_112081_2023-01-19_final
2023-01-21 09:43:20	ga_ls8c_ard_3-2-1_094079_2023-01-21_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-06 09:44:11	ga_ls8c_ard_3-2-1_094081_2023-02-06_final
2023-02-09 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-02-09_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-11 11:39:34	ga_ls8c_ard_3-2-1_113076_2023-02-11_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-15 09:36:18	ga_ls8c_ard_3-2-1_093077_2023-02-15_final
2023-02-15 09:39:06	ga_ls8c_ard_3-2-1_093084_2023-02-15_final
2023-02-15 11:15:11	ga_ls8c_ard_3-2-1_109077_2023-02-15_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-21 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-02-21_final
2023-02-22 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-02-22_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-24 09:30:44	ga_ls8c_ard_3-2-1_092079_2023-02-24_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-02-25 10:14:46	ga_ls8c_ard_3-2-1_099081_2023-02-25_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-02-28 10:44:05	ga_ls8c_ard_3-2-1_104077_2023-02-28_final
2023-03-03 09:37:41	ga_ls8c_ard_3-2-1_093081_2023-03-03_final
2023-03-03 09:38:29	ga_ls8c_ard_3-2-1_093083_2023-03-03_final
2023-03-03 11:15:22	ga_ls8c_ard_3-2-1_109078_2023-03-03_final
2023-03-05 09:24:30	ga_ls8c_ard_3-2-1_091079_2023-03-04_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-09 10:39:01	ga_ls8c_ard_3-2-1_103080_2023-03-09_final
2023-03-10 09:45:47	ga_ls8c_ard_3-2-1_094086_2023-03-10_final
2023-03-16 10:42:47	ga_ls8c_ard_3-2-1_104074_2023-03-16_final
2023-03-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2023-03-17_final
2023-03-28 11:06:34	ga_ls8c_ard_3-2-1_108072_2023-03-28_final
2023-03-28 11:08:57	ga_ls8c_ard_3-2-1_108078_2023-03-28_final
2023-03-28 11:09:45	ga_ls8c_ard_3-2-1_108080_2023-03-28_final
2023-03-29 10:11:44	ga_ls8c_ard_3-2-1_099074_2023-03-29_final
2023-03-31 11:38:38	ga_ls8c_ard_3-2-1_113075_2023-03-31_final
2023-04-10 10:38:37	ga_ls8c_ard_3-2-1_103080_2023-04-10_final
2023-04-15 09:19:03	ga_ls8c_ard_3-2-1_090082_2023-04-14_final
2023-04-17 10:42:45	ga_ls8c_ard_3-2-1_104075_2023-04-17_final
2023-04-20 11:12:26	ga_ls8c_ard_3-2-1_109072_2023-04-20_final
2023-04-26 10:35:45	ga_ls8c_ard_3-2-1_103073_2023-04-26_final
2023-04-29 11:09:50	ga_ls8c_ard_3-2-1_108081_2023-04-29_final
2023-05-01 10:56:15	ga_ls8c_ard_3-2-1_106078_2023-05-01_final
2023-05-02 10:02:37	ga_ls8c_ard_3-2-1_097083_2023-05-02_final
2023-05-11 09:55:29	ga_ls8c_ard_3-2-1_096081_2023-05-11_final
2023-05-17 09:18:45	ga_ls8c_ard_3-2-1_090082_2023-05-16_final
2023-05-19 10:40:06	ga_ls8c_ard_3-2-1_104069_2023-05-19_final
2023-05-22 11:11:25	ga_ls8c_ard_3-2-1_109070_2023-05-22_final
2023-05-29 09:43:55	ga_ls8c_ard_3-2-1_094083_2023-05-29_nrt
2023-06-02 09:19:12	ga_ls8c_ard_3-2-1_090083_2023-06-01_nrt
2023-06-02 10:57:17	ga_ls8c_ard_3-2-1_106081_2023-06-02_nrt
2023-06-03 11:38:58	ga_ls8c_ard_3-2-1_113077_2023-06-03_nrt

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