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
2022-09-13 11:36:29	ga_ls8c_ard_3-2-1_112083_2022-09-13_final
2022-09-17 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-09-17_final
2022-09-18 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-09-18_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-10 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-10-10_final
2022-10-10 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-10-10_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-13 10:05:27	ga_ls8c_ard_3-2-1_098072_2022-10-13_final
2022-10-24 09:51:00	ga_ls8c_ard_3-2-1_095082_2022-10-24_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-27 10:19:08	ga_ls8c_ard_3-2-1_100075_2022-10-27_final
2022-10-29 10:07:35	ga_ls8c_ard_3-2-1_098077_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-20 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-11-20_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-11-27 09:36:12	ga_ls8c_ard_3-2-1_093076_2022-11-27_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-11 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-12-11_final
2022-12-12 10:28:59	ga_ls8c_ard_3-2-1_102069_2022-12-12_final
2022-12-21 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-12-21_final
2022-12-21 10:28:16	ga_ls8c_ard_3-2-1_101083_2022-12-21_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-17 11:47:42	ga_ls8c_ard_3-2-1_114081_2023-01-17_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-30 09:40:01	ga_ls8c_ard_3-2-1_093086_2023-01-30_final
2023-02-01 09:28:51	ga_ls8c_ard_3-2-1_091089_2023-01-31_final
2023-02-02 11:47:24	ga_ls8c_ard_3-2-1_114080_2023-02-02_final
2023-02-08 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-02-08_final
2023-02-15 11:13:35	ga_ls8c_ard_3-2-1_109073_2023-02-15_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-05 11:01:23	ga_ls8c_ard_3-2-1_107074_2023-03-05_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-08 11:35:50	ga_ls8c_ard_3-2-1_112083_2023-03-08_final
2023-03-14 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-03-13_final
2023-03-16 10:40:23	ga_ls8c_ard_3-2-1_104068_2023-03-16_final
2023-03-17 09:50:20	ga_ls8c_ard_3-2-1_095082_2023-03-17_final
2023-03-21 09:23:34	ga_ls8c_ard_3-2-1_091077_2023-03-20_final
2023-03-24 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-03-24_final
2023-04-02 11:24:39	ga_ls8c_ard_3-2-1_111071_2023-04-02_final
2023-04-02 11:26:39	ga_ls8c_ard_3-2-1_111076_2023-04-02_final
2023-04-06 09:25:21	ga_ls8c_ard_3-2-1_091082_2023-04-05_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-07 11:46:41	ga_ls8c_ard_3-2-1_114080_2023-04-07_final
2023-04-12 10:25:02	ga_ls8c_ard_3-2-1_101077_2023-04-12_final
2023-04-16 09:58:19	ga_ls8c_ard_3-2-1_097072_2023-04-16_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-04-20 09:39:08	ga_ls8c_ard_3-2-1_093086_2023-04-20_final
2023-04-20 09:39:32	ga_ls8c_ard_3-2-1_093087_2023-04-20_final
2023-04-24 09:15:37	ga_ls8c_ard_3-2-1_089089_2023-04-23_final
2023-04-25 09:52:06	ga_ls8c_ard_3-2-1_096072_2023-04-25_final
2023-04-27 11:19:01	ga_ls8c_ard_3-2-1_110073_2023-04-27_final
2023-05-06 11:17:08	ga_ls8c_ard_3-2-1_109084_2023-05-06_final
2023-05-12 10:33:33	ga_ls8c_ard_3-2-1_103068_2023-05-12_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-15 09:32:20	ga_ls8c_ard_3-2-1_092085_2023-05-15_final
2023-06-06 10:28:38	ga_ls8c_ard_3-2-1_102071_2023-06-06_final
2023-06-08 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-06-08_final
2023-06-09 09:24:17	ga_ls8c_ard_3-2-1_091080_2023-06-08_final
2023-06-09 11:00:46	ga_ls8c_ard_3-2-1_107074_2023-06-09_final
2023-06-09 11:04:46	ga_ls8c_ard_3-2-1_107084_2023-06-09_final
2023-06-10 10:09:33	ga_ls8c_ard_3-2-1_098085_2023-06-10_final
2023-06-21 11:23:10	ga_ls8c_ard_3-2-1_111068_2023-06-21_final
2023-06-25 09:25:59	ga_ls8c_ard_3-2-1_091084_2023-06-24_final
2023-07-05 10:00:49	ga_ls8c_ard_3-2-1_097078_2023-07-05_final
2023-07-10 10:20:59	ga_ls8c_ard_3-2-1_100082_2023-07-10_final
2023-07-16 09:40:20	ga_ls8c_ard_3-2-1_094073_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-07-19 10:10:49	ga_ls8c_ard_3-2-1_099072_2023-07-19_final
2023-07-19 10:15:13	ga_ls8c_ard_3-2-1_099083_2023-07-19_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_2023-07-27_final
2023-08-01 11:19:21	ga_ls8c_ard_3-2-1_110073_2023-08-01_final
2023-08-21 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-08-20_final
2023-08-21 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-08-20_final
2023-08-30 09:16:30	ga_ls8c_ard_3-2-1_089090_2023-08-29_final
2023-09-07 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-09-07_final
2023-09-15 09:14:34	ga_ls8c_ard_3-2-1_089085_2023-09-14_final
2023-09-25 09:50:53	ga_ls8c_ard_3-2-1_095083_2023-09-25_final
2023-09-28 11:58:42	ga_ls8c_ard_3-2-1_116078_2023-09-28_final
2023-10-04 11:19:14	ga_ls8c_ard_3-2-1_110072_2023-10-04_final
2023-10-07 11:53:20	ga_ls8c_ard_3-2-1_115080_2023-10-07_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_final
2023-10-16 10:05:06	ga_ls8c_ard_3-2-1_098072_2023-10-16_final
2023-10-27 09:46:37	ga_ls8c_ard_3-2-1_095072_2023-10-27_final
2023-10-29 11:13:33	ga_ls8c_ard_3-2-1_109073_2023-10-29_final
2023-11-02 10:48:49	ga_ls8c_ard_3-2-1_105073_2023-11-02_final
2023-11-16 11:01:34	ga_ls8c_ard_3-2-1_107074_2023-11-16_final
2023-11-17 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-11-17_final
2023-11-23 09:32:30	ga_ls8c_ard_3-2-1_092083_2023-11-23_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