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
2022-01-05 10:15:46	ga_ls8c_ard_3-2-1_099083_2022-01-05_final
2022-01-08 10:46:15	ga_ls8c_ard_3-2-1_104082_2022-01-08_final
2022-01-13 09:22:43	ga_ls8c_ard_3-2-1_091074_2022-01-12_final
2022-01-22 09:20:52	ga_ls8c_ard_3-2-1_090085_2022-01-21_final
2022-01-25 11:25:03	ga_ls8c_ard_3-2-1_111071_2022-01-25_final
2022-02-06 10:14:03	ga_ls8c_ard_3-2-1_099079_2022-02-06_final
2022-02-09 09:07:15	ga_ls8c_ard_3-2-1_088082_2022-02-08_final
2022-02-12 09:33:44	ga_ls8c_ard_3-2-1_093071_2022-02-12_final
2022-02-14 09:23:22	ga_ls8c_ard_3-2-1_091076_2022-02-13_final
2022-02-23 09:21:55	ga_ls8c_ard_3-2-1_090088_2022-02-22_final
2022-03-02 09:23:18	ga_ls8c_ard_3-2-1_091076_2022-03-01_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_2022-03-03_final
2022-03-12 10:03:31	ga_ls8c_ard_3-2-1_097084_2022-03-12_final
2022-03-14 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-03-14_final
2022-03-15 10:30:00	ga_ls8c_ard_3-2-1_102073_2022-03-15_final
2022-03-18 09:23:11	ga_ls8c_ard_3-2-1_091076_2022-03-17_final
2022-03-27 09:21:40	ga_ls8c_ard_3-2-1_090088_2022-03-26_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-13 09:56:36	ga_ls8c_ard_3-2-1_097067_2022-04-13_final
2022-04-30 09:06:54	ga_ls8c_ard_3-2-1_088082_2022-04-29_final
2022-05-05 09:25:31	ga_ls8c_ard_3-2-1_091082_2022-05-04_final
2022-05-27 10:23:00	ga_ls8c_ard_3-2-1_101071_2022-05-27_final
2022-06-13 11:11:17	ga_ls8c_ard_3-2-1_108083_2022-06-13_final
2022-06-23 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-06-23_final
2022-07-06 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-07-06_final
2022-07-07 10:22:20	ga_ls8c_ard_3-2-1_100084_2022-07-07_final
2022-07-09 11:44:52	ga_ls8c_ard_3-2-1_114074_2022-07-09_final
2022-07-12 10:36:04	ga_ls8c_ard_3-2-1_103072_2022-07-12_final
2022-07-13 11:20:08	ga_ls8c_ard_3-2-1_110074_2022-07-13_final
2022-07-20 09:51:28	ga_ls8c_ard_3-2-1_095084_2022-07-20_final
2022-07-20 11:24:46	ga_ls8c_ard_3-2-1_111070_2022-07-20_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-28 10:36:14	ga_ls8c_ard_3-2-1_103072_2022-07-28_final
2022-08-09 09:28:34	ga_ls8c_ard_3-2-1_091088_2022-08-08_final
2022-08-13 10:36:21	ga_ls8c_ard_3-2-1_103072_2022-08-13_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-17 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-08-17_final
2022-08-23 09:34:59	ga_ls8c_ard_3-2-1_093073_2022-08-23_final
2022-09-20 11:42:17	ga_ls8c_ard_3-2-1_113082_2022-09-20_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-09-26 11:00:25	ga_ls8c_ard_3-2-1_107070_2022-09-26_final
2022-09-26 11:02:01	ga_ls8c_ard_3-2-1_107074_2022-09-26_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-10-06 09:57:46	ga_ls8c_ard_3-2-1_097068_2022-10-06_final
2022-10-06 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-06_final
2022-10-08 11:26:16	ga_ls8c_ard_3-2-1_111073_2022-10-08_final
2022-10-10 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-10-10_final
2022-10-15 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-10-15_final
2022-10-21 09:17:41	ga_ls8c_ard_3-2-1_090076_2022-10-20_final
2022-10-28 09:27:30	ga_ls8c_ard_3-2-1_091085_2022-10-27_final
2022-11-07 09:58:12	ga_ls8c_ard_3-2-1_097069_2022-11-07_final
2022-11-21 10:16:27	ga_ls8c_ard_3-2-1_099084_2022-11-21_final
2022-12-07 11:51:45	ga_ls8c_ard_3-2-1_115075_2022-12-07_final
2022-12-08 09:18:03	ga_ls8c_ard_3-2-1_090077_2022-12-07_final
2022-12-12 10:28:59	ga_ls8c_ard_3-2-1_102069_2022-12-12_final
2023-01-07 09:34:15	ga_ls8c_ard_3-2-1_092087_2023-01-07_final
2023-01-18 10:48:05	ga_ls8c_ard_3-2-1_105071_2023-01-18_final
2023-01-25 10:58:44	ga_ls8c_ard_3-2-1_106082_2023-01-25_final
2023-01-30 09:40:25	ga_ls8c_ard_3-2-1_093087_2023-01-30_final
2023-01-30 11:13:19	ga_ls8c_ard_3-2-1_109072_2023-01-30_final
2023-02-02 10:07:43	ga_ls8c_ard_3-2-1_098078_2023-02-02_final
2023-02-18 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-02-18_final
2023-02-20 09:52:45	ga_ls8c_ard_3-2-1_096072_2023-02-20_final
2023-02-23 10:23:11	ga_ls8c_ard_3-2-1_101071_2023-02-23_final
2023-02-27 09:57:14	ga_ls8c_ard_3-2-1_097068_2023-02-27_final
2023-03-14 10:55:57	ga_ls8c_ard_3-2-1_106076_2023-03-14_final
2023-03-17 09:52:20	ga_ls8c_ard_3-2-1_095087_2023-03-17_final
2023-03-29 11:53:01	ga_ls8c_ard_3-2-1_115080_2023-03-29_final
2023-04-05 10:16:37	ga_ls8c_ard_3-2-1_100071_2023-04-05_final
2023-04-18 11:25:13	ga_ls8c_ard_3-2-1_111073_2023-04-18_final
2023-04-29 09:27:21	ga_ls8c_ard_3-2-1_092072_2023-04-28_final
2023-05-15 11:09:13	ga_ls8c_ard_3-2-1_108080_2023-05-15_final
2023-05-16 10:08:48	ga_ls8c_ard_3-2-1_099068_2023-05-16_final
2023-06-01 10:09:14	ga_ls8c_ard_3-2-1_099069_2023-06-01_final
2023-06-09 10:59:11	ga_ls8c_ard_3-2-1_107070_2023-06-09_final
2023-06-12 09:57:37	ga_ls8c_ard_3-2-1_096086_2023-06-12_final
2023-06-16 09:27:19	ga_ls8c_ard_3-2-1_092072_2023-06-15_final
2023-06-16 11:11:00	ga_ls8c_ard_3-2-1_108084_2023-06-16_final
2023-06-18 09:16:10	ga_ls8c_ard_3-2-1_090075_2023-06-17_final
2023-06-27 09:10:04	ga_ls8c_ard_3-2-1_089075_2023-06-26_final
2023-07-05 09:57:13	ga_ls8c_ard_3-2-1_097069_2023-07-05_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-15 10:39:09	ga_ls8c_ard_3-2-1_103081_2023-07-15_final
2023-07-16 11:19:37	ga_ls8c_ard_3-2-1_110074_2023-07-16_final
2023-07-20 09:16:24	ga_ls8c_ard_3-2-1_090075_2023-07-19_final
2023-07-21 09:56:28	ga_ls8c_ard_3-2-1_097067_2023-07-21_final
2023-08-03 11:07:24	ga_ls8c_ard_3-2-1_108074_2023-08-03_final
2023-08-05 09:22:33	ga_ls8c_ard_3-2-1_090090_2023-08-04_final
2023-08-08 11:25:33	ga_ls8c_ard_3-2-1_111073_2023-08-08_final
2023-08-10 09:33:54	ga_ls8c_ard_3-2-1_093072_2023-08-10_final
2023-08-14 09:11:13	ga_ls8c_ard_3-2-1_089077_2023-08-13_final
2023-08-21 09:22:16	ga_ls8c_ard_3-2-1_090089_2023-08-20_final
2023-08-28 09:22:05	ga_ls8c_ard_3-2-1_091073_2023-08-27_final
2023-08-28 09:22:29	ga_ls8c_ard_3-2-1_091074_2023-08-27_final
2023-08-30 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-08-30_final
2023-08-30 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-08-30_final
2023-09-04 11:07:55	ga_ls8c_ard_3-2-1_108075_2023-09-04_final
2023-09-06 09:21:27	ga_ls8c_ard_3-2-1_090087_2023-09-05_final
2023-09-06 10:55:09	ga_ls8c_ard_3-2-1_106074_2023-09-06_final
2023-09-09 11:24:53	ga_ls8c_ard_3-2-1_111071_2023-09-09_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