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
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-09 10:31:26	ga_ls8c_ard_3-2-1_102075_2022-10-09_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-12 11:01:29	ga_ls8c_ard_3-2-1_107073_2022-10-12_final
2022-10-12 11:03:05	ga_ls8c_ard_3-2-1_107077_2022-10-12_final
2022-10-13 11:47:31	ga_ls8c_ard_3-2-1_114080_2022-10-13_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-21 09:18:29	ga_ls8c_ard_3-2-1_090078_2022-10-20_final
2022-10-23 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-23_final
2022-10-24 09:48:36	ga_ls8c_ard_3-2-1_095076_2022-10-24_final
2022-10-26 11:16:20	ga_ls8c_ard_3-2-1_109079_2022-10-26_final
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-11-01 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-11-01_final
2022-11-02 09:43:40	ga_ls8c_ard_3-2-1_094079_2022-11-02_final
2022-11-03 10:25:20	ga_ls8c_ard_3-2-1_101075_2022-11-03_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-04 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-11-04_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-06 10:57:01	ga_ls8c_ard_3-2-1_106077_2022-11-06_final
2022-11-07 09:59:48	ga_ls8c_ard_3-2-1_097073_2022-11-07_final
2022-11-09 11:29:54	ga_ls8c_ard_3-2-1_111082_2022-11-09_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-10 10:31:04	ga_ls8c_ard_3-2-1_102074_2022-11-10_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-14 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-14_final
2022-11-15 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-11-15_final
2022-11-15 10:48:21	ga_ls8c_ard_3-2-1_105071_2022-11-15_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-23 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-11-23_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-25 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-11-25_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-11-28 11:58:21	ga_ls8c_ard_3-2-1_116076_2022-11-28_final
2022-11-30 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-30_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-11 11:29:24	ga_ls8c_ard_3-2-1_111081_2022-12-11_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-17 10:48:16	ga_ls8c_ard_3-2-1_105071_2022-12-17_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-20 09:43:50	ga_ls8c_ard_3-2-1_094080_2022-12-20_final
2022-12-21 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-12-21_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-25 10:02:21	ga_ls8c_ard_3-2-1_097080_2022-12-25_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-05 11:23:31	ga_ls8c_ard_3-2-1_110082_2023-01-05_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-06 10:25:29	ga_ls8c_ard_3-2-1_101076_2023-01-06_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-11 10:41:36	ga_ls8c_ard_3-2-1_104070_2023-01-11_final
2023-01-11 10:45:35	ga_ls8c_ard_3-2-1_104080_2023-01-11_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-19 09:56:28	ga_ls8c_ard_3-2-1_096081_2023-01-19_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-24 10:12:17	ga_ls8c_ard_3-2-1_099074_2023-01-24_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-01-30 09:36:25	ga_ls8c_ard_3-2-1_093077_2023-01-30_final
2023-01-30 09:36:49	ga_ls8c_ard_3-2-1_093078_2023-01-30_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-01 09:28:51	ga_ls8c_ard_3-2-1_091089_2023-01-31_final
2023-02-05 10:35:49	ga_ls8c_ard_3-2-1_103071_2023-02-05_final
2023-02-05 10:38:37	ga_ls8c_ard_3-2-1_103078_2023-02-05_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-13 09:50:17	ga_ls8c_ard_3-2-1_095081_2023-02-13_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-02-22 09:45:32	ga_ls8c_ard_3-2-1_094085_2023-02-22_final
2023-02-24 09:31:56	ga_ls8c_ard_3-2-1_092082_2023-02-24_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-02-25 10:12:22	ga_ls8c_ard_3-2-1_099075_2023-02-25_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_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