Search ga_ls9c_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
2021-11-03 09:54:34	ga_ls9c_ard_3-2-1_096074_2021-11-03_final.stac-item
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-10 11:17:45	ga_ls9c_ard_3-2-1_110076_2021-11-10_final.stac-item
2021-11-16 10:21:31	ga_ls9c_ard_3-2-1_100076_2021-11-16_final.stac-item
2021-11-17 09:23:16	ga_ls9c_ard_3-2-1_091077_2021-11-16_final.stac-item
2022-01-03 09:35:31	ga_ls9c_ard_3-2-1_093075_2022-01-03_final.stac-item
2022-01-13 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-01-13_final.stac-item
2022-01-13 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-01-13_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-17 09:46:39	ga_ls9c_ard_3-2-1_095072_2022-01-17_final.stac-item
2022-01-24 09:53:15	ga_ls9c_ard_3-2-1_096073_2022-01-24_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-13 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-02-13_final.stac-item
2022-02-27 11:23:09	ga_ls9c_ard_3-2-1_110082_2022-02-27_final.stac-item
2022-04-13 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-04-13_final.stac-item
2022-04-14 11:34:55	ga_ls9c_ard_3-2-1_112081_2022-04-14_final.stac-item
2022-04-21 10:00:55	ga_ls9c_ard_3-2-1_097078_2022-04-21_final.stac-item
2022-05-07 10:00:51	ga_ls9c_ard_3-2-1_097078_2022-05-07_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-05-30 10:07:39	ga_ls9c_ard_3-2-1_098080_2022-05-30_final.stac-item
2022-06-29 10:16:47	ga_ls9c_ard_3-2-1_100071_2022-06-29_final.stac-item
2022-07-08 10:09:22	ga_ls9c_ard_3-2-1_099068_2022-07-08_final.stac-item
2022-07-29 10:28:30	ga_ls9c_ard_3-2-1_102069_2022-07-29_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-19 09:12:44	ga_ls9c_ard_3-2-1_089080_2022-08-18_final.stac-item
2022-08-22 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-08-22_final.stac-item
2022-09-01 10:21:56	ga_ls9c_ard_3-2-1_100083_2022-09-01_final.stac-item
2022-09-16 09:35:08	ga_ls9c_ard_3-2-1_093074_2022-09-16_final.stac-item
2022-09-28 09:58:20	ga_ls9c_ard_3-2-1_097070_2022-09-28_final.stac-item
2022-10-02 09:35:36	ga_ls9c_ard_3-2-1_093075_2022-10-02_final.stac-item
2022-10-02 09:40:23	ga_ls9c_ard_3-2-1_093087_2022-10-02_final.stac-item
2022-11-02 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-11-02_final.stac-item
2022-11-05 11:02:34	ga_ls9c_ard_3-2-1_107076_2022-11-05_final.stac-item
2022-11-17 09:48:04	ga_ls9c_ard_3-2-1_095075_2022-11-17_final.stac-item
2022-11-17 11:30:33	ga_ls9c_ard_3-2-1_111084_2022-11-17_final.stac-item
2022-11-24 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-24_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-11-29 11:52:02	ga_ls9c_ard_3-2-1_115076_2022-11-29_final.stac-item
2022-12-02 10:45:37	ga_ls9c_ard_3-2-1_104080_2022-12-02_final.stac-item
2022-12-07 09:25:19	ga_ls9c_ard_3-2-1_091080_2022-12-06_final.stac-item
2022-12-07 09:27:43	ga_ls9c_ard_3-2-1_091086_2022-12-06_final.stac-item
2022-12-11 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-12-11_final.stac-item
2022-12-13 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-12-13_final.stac-item
2022-12-15 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-12-15_final.stac-item
2022-12-25 09:16:30	ga_ls9c_ard_3-2-1_089089_2022-12-24_final.stac-item
2022-12-30 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-12-29_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-04 09:46:52	ga_ls9c_ard_3-2-1_095072_2023-01-04_final.stac-item
2023-01-08 11:02:37	ga_ls9c_ard_3-2-1_107076_2023-01-08_final.stac-item
2023-01-11 09:56:36	ga_ls9c_ard_3-2-1_096081_2023-01-11_final.stac-item
2023-02-03 10:02:50	ga_ls9c_ard_3-2-1_097081_2023-02-03_final.stac-item
2023-02-08 10:19:25	ga_ls9c_ard_3-2-1_100076_2023-02-08_final.stac-item
2023-03-01 10:39:42	ga_ls9c_ard_3-2-1_103081_2023-03-01_final.stac-item
2023-03-09 09:46:33	ga_ls9c_ard_3-2-1_095072_2023-03-09_final.stac-item
2023-03-14 10:05:54	ga_ls9c_ard_3-2-1_098074_2023-03-14_final.stac-item
2023-03-16 11:36:00	ga_ls9c_ard_3-2-1_112083_2023-03-16_final.stac-item
2023-04-01 09:56:56	ga_ls9c_ard_3-2-1_096083_2023-04-01_final.stac-item
2023-04-23 09:19:44	ga_ls9c_ard_3-2-1_090083_2023-04-22_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-01 11:45:09	ga_ls9c_ard_3-2-1_114076_2023-05-01_final.stac-item
2023-05-02 09:13:01	ga_ls9c_ard_3-2-1_089082_2023-05-01_final.stac-item
2023-05-02 09:16:12	ga_ls9c_ard_3-2-1_089090_2023-05-01_final.stac-item
2023-05-05 09:40:16	ga_ls9c_ard_3-2-1_094073_2023-05-05_final.stac-item
2023-05-05 09:43:52	ga_ls9c_ard_3-2-1_094082_2023-05-05_final.stac-item
2023-05-09 09:21:56	ga_ls9c_ard_3-2-1_090089_2023-05-08_final.stac-item
2023-05-14 11:16:08	ga_ls9c_ard_3-2-1_109081_2023-05-14_final.stac-item
2023-05-15 10:16:31	ga_ls9c_ard_3-2-1_100071_2023-05-15_final.stac-item
2023-05-16 09:26:05	ga_ls9c_ard_3-2-1_091084_2023-05-15_final.stac-item
2023-05-18 10:48:59	ga_ls9c_ard_3-2-1_105075_2023-05-18_final.stac-item
2023-05-19 09:51:21	ga_ls9c_ard_3-2-1_096070_2023-05-19_final.stac-item
2023-05-21 11:22:38	ga_ls9c_ard_3-2-1_110082_2023-05-21_final.stac-item
2023-05-29 10:29:32	ga_ls9c_ard_3-2-1_102073_2023-05-29_final.stac-item
2023-06-01 11:03:38	ga_ls9c_ard_3-2-1_107081_2023-06-01_final.stac-item
2023-06-27 09:56:31	ga_ls9c_ard_3-2-1_097068_2023-06-27_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-06-27 11:41:00	ga_ls9c_ard_3-2-1_113082_2023-06-27_final.stac-item
2023-06-29 09:49:25	ga_ls9c_ard_3-2-1_095081_2023-06-29_final.stac-item
2023-07-15 11:29:17	ga_ls9c_ard_3-2-1_111083_2023-07-15_final.stac-item
2023-07-17 09:34:51	ga_ls9c_ard_3-2-1_093075_2023-07-17_final.stac-item
2023-07-18 11:57:23	ga_ls9c_ard_3-2-1_116076_2023-07-18_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-22 11:31:52	ga_ls9c_ard_3-2-1_112074_2023-07-22_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_2023-07-27_final.stac-item
2023-07-27 11:52:25	ga_ls9c_ard_3-2-1_115079_2023-07-27_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-10 10:22:27	ga_ls9c_ard_3-2-1_101070_2023-08-10_final.stac-item
2023-08-10 10:26:51	ga_ls9c_ard_3-2-1_101081_2023-08-10_final.stac-item
2023-10-14 11:06:34	ga_ls9c_ard_3-2-1_108071_2023-10-14_final.stac-item
2023-10-15 11:52:14	ga_ls9c_ard_3-2-1_115077_2023-10-15_final.stac-item
2023-10-18 10:41:04	ga_ls9c_ard_3-2-1_104069_2023-10-18_final.stac-item
2023-10-23 09:27:55	ga_ls9c_ard_3-2-1_091087_2023-10-22_final.stac-item
2023-10-31 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-10-31_final.stac-item
2023-11-03 10:43:20	ga_ls9c_ard_3-2-1_104075_2023-11-03_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-14 10:22:52	ga_ls9c_ard_3-2-1_101070_2023-11-14_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-17 10:53:23	ga_ls9c_ard_3-2-1_106069_2023-11-17_final.stac-item
2023-11-20 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-11-20_final.stac-item
2023-11-23 11:58:52	ga_ls9c_ard_3-2-1_116078_2023-11-23_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 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