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
2017-07-18 10:15:22	ga_ls8c_ard_3-0-0_099083_2017-07-18_final
2017-07-18 10:15:46	ga_ls8c_ard_3-0-0_099084_2017-07-18_final
2017-07-18 10:16:10	ga_ls8c_ard_3-0-0_099085_2017-07-18_final
2017-07-27 10:10:27	ga_ls8c_ard_3-0-0_098086_2017-07-27_final
2021-05-15 10:28:27	ga_ls8c_ard_3-2-0_102070_2021-05-15_final
2021-05-15 10:28:51	ga_ls8c_ard_3-2-0_102071_2021-05-15_final
2021-05-15 10:29:15	ga_ls8c_ard_3-2-0_102072_2021-05-15_final
2021-05-15 10:29:39	ga_ls8c_ard_3-2-0_102073_2021-05-15_final
2021-05-15 10:30:03	ga_ls8c_ard_3-2-0_102074_2021-05-15_final
2021-05-15 10:30:27	ga_ls8c_ard_3-2-0_102075_2021-05-15_final
2021-05-19 10:10:09	ga_ls8c_ard_3-2-0_098086_2021-05-19_final
2021-05-31 10:28:36	ga_ls8c_ard_3-2-0_102070_2021-05-31_final
2021-05-31 10:29:00	ga_ls8c_ard_3-2-0_102071_2021-05-31_final
2021-05-31 10:29:24	ga_ls8c_ard_3-2-0_102072_2021-05-31_final
2021-05-31 10:29:48	ga_ls8c_ard_3-2-0_102073_2021-05-31_final
2021-05-31 10:30:12	ga_ls8c_ard_3-2-0_102074_2021-05-31_final
2021-05-31 10:30:36	ga_ls8c_ard_3-2-0_102075_2021-05-31_final
2021-09-24 10:10:50	ga_ls8c_ard_3-2-0_098086_2021-09-24_final
2021-09-27 10:34:11	ga_ls8c_ard_3-2-0_103067_2021-09-27_final
2021-09-27 10:34:35	ga_ls8c_ard_3-2-0_103068_2021-09-27_final
2021-09-27 10:34:59	ga_ls8c_ard_3-2-0_103069_2021-09-27_final
2021-09-27 10:35:23	ga_ls8c_ard_3-2-0_103070_2021-09-27_final
2021-09-27 10:35:46	ga_ls8c_ard_3-2-0_103071_2021-09-27_final
2021-09-29 10:24:38	ga_ls8c_ard_3-2-0_101074_2021-09-29_final
2021-09-29 10:25:01	ga_ls8c_ard_3-2-0_101075_2021-09-29_final
2021-09-29 10:25:25	ga_ls8c_ard_3-2-0_101076_2021-09-29_final
2021-09-29 10:25:49	ga_ls8c_ard_3-2-0_101077_2021-09-29_final
2021-09-29 10:26:13	ga_ls8c_ard_3-2-0_101078_2021-09-29_final
2021-09-29 10:26:37	ga_ls8c_ard_3-2-0_101079_2021-09-29_final
2021-09-29 10:27:01	ga_ls8c_ard_3-2-0_101080_2021-09-29_final
2021-10-10 10:10:56	ga_ls8c_ard_3-2-0_098086_2021-10-10_final
2021-10-13 10:34:16	ga_ls8c_ard_3-2-0_103067_2021-10-13_final
2021-10-13 10:34:40	ga_ls8c_ard_3-2-0_103068_2021-10-13_final
2021-10-13 10:35:04	ga_ls8c_ard_3-2-0_103069_2021-10-13_final
2021-10-13 10:35:28	ga_ls8c_ard_3-2-0_103070_2021-10-13_final
2021-10-13 10:35:52	ga_ls8c_ard_3-2-0_103071_2021-10-13_final
2021-10-15 10:24:42	ga_ls8c_ard_3-2-0_101074_2021-10-15_final
2021-10-15 10:25:06	ga_ls8c_ard_3-2-0_101075_2021-10-15_final
2021-10-15 10:25:30	ga_ls8c_ard_3-2-0_101076_2021-10-15_final
2021-10-15 10:25:54	ga_ls8c_ard_3-2-0_101077_2021-10-15_final
2021-10-15 10:26:18	ga_ls8c_ard_3-2-0_101078_2021-10-15_final
2021-10-15 10:26:42	ga_ls8c_ard_3-2-0_101079_2021-10-15_final
2021-10-15 10:27:06	ga_ls8c_ard_3-2-0_101080_2021-10-15_final
2023-06-24 10:19:35	ga_ls8c_ard_3-2-1_100079_2023-06-24_final
2023-06-24 10:19:59	ga_ls8c_ard_3-2-1_100080_2023-06-24_final
2023-06-24 10:20:23	ga_ls8c_ard_3-2-1_100081_2023-06-24_final
2023-06-24 10:20:47	ga_ls8c_ard_3-2-1_100082_2023-06-24_final
2023-06-24 10:21:11	ga_ls8c_ard_3-2-1_100083_2023-06-24_final
2023-06-24 10:21:35	ga_ls8c_ard_3-2-1_100084_2023-06-24_final
2023-07-01 10:25:05	ga_ls8c_ard_3-2-1_101077_2023-07-01_final
2023-07-01 10:25:29	ga_ls8c_ard_3-2-1_101078_2023-07-01_final
2023-07-01 10:25:53	ga_ls8c_ard_3-2-1_101079_2023-07-01_final
2023-07-03 10:15:09	ga_ls8c_ard_3-2-1_099083_2023-07-03_final
2023-07-03 10:15:33	ga_ls8c_ard_3-2-1_099084_2023-07-03_final
2023-07-03 10:15:57	ga_ls8c_ard_3-2-1_099085_2023-07-03_final
2023-07-15 10:33:57	ga_ls8c_ard_3-2-1_103068_2023-07-15_final
2023-07-15 10:34:21	ga_ls8c_ard_3-2-1_103069_2023-07-15_final
2023-07-15 10:34:45	ga_ls8c_ard_3-2-1_103070_2023-07-15_final
2023-07-15 10:35:09	ga_ls8c_ard_3-2-1_103071_2023-07-15_final
2023-07-24 10:28:37	ga_ls8c_ard_3-2-1_102070_2023-07-24_final
2023-07-24 10:29:01	ga_ls8c_ard_3-2-1_102071_2023-07-24_final
2023-07-24 10:29:25	ga_ls8c_ard_3-2-1_102072_2023-07-24_final
2023-07-24 10:29:49	ga_ls8c_ard_3-2-1_102073_2023-07-24_final
2023-07-24 10:30:13	ga_ls8c_ard_3-2-1_102074_2023-07-24_final
2023-07-24 10:30:37	ga_ls8c_ard_3-2-1_102075_2023-07-24_final
2023-07-26 10:19:53	ga_ls8c_ard_3-2-1_100079_2023-07-26_final
2023-07-26 10:20:17	ga_ls8c_ard_3-2-1_100080_2023-07-26_final
2023-07-26 10:20:41	ga_ls8c_ard_3-2-1_100081_2023-07-26_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-07-26 10:21:28	ga_ls8c_ard_3-2-1_100083_2023-07-26_final
2023-07-26 10:21:52	ga_ls8c_ard_3-2-1_100084_2023-07-26_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-10 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-09-10_final
2023-09-10 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-09-10_final
2023-09-10 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-09-10_final
2023-09-10 10:30:28	ga_ls8c_ard_3-2-1_102074_2023-09-10_final
2023-09-10 10:30:52	ga_ls8c_ard_3-2-1_102075_2023-09-10_final
2023-09-12 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-09-12_final
2023-09-12 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-09-12_final
2023-09-12 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-09-12_final
2023-09-12 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-09-12_final
2023-09-12 10:21:43	ga_ls8c_ard_3-2-1_100083_2023-09-12_final
2023-09-12 10:22:07	ga_ls8c_ard_3-2-1_100084_2023-09-12_final
2023-10-12 10:29:02	ga_ls8c_ard_3-2-1_102070_2023-10-12_final
2023-10-12 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-10-12_final
2023-10-12 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-10-12_final
2023-10-12 10:30:14	ga_ls8c_ard_3-2-1_102073_2023-10-12_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-12 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-10-12_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_nrt
2023-10-14 10:20:40	ga_ls8c_ard_3-2-1_100080_2023-10-14_final
2023-10-14 10:20:40	ga_ls8c_ard_3-2-1_100080_2023-10-14_nrt
2023-10-14 10:21:04	ga_ls8c_ard_3-2-1_100081_2023-10-14_final
2023-10-14 10:21:04	ga_ls8c_ard_3-2-1_100081_2023-10-14_nrt
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_final
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_nrt
2023-10-14 10:21:52	ga_ls8c_ard_3-2-1_100083_2023-10-14_final
2023-10-14 10:21:52	ga_ls8c_ard_3-2-1_100083_2023-10-14_nrt
2023-10-14 10:22:16	ga_ls8c_ard_3-2-1_100084_2023-10-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years