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
2021-12-23 09:54:52	ga_ls9c_ard_3-2-1_096077_2021-12-23_final.stac-item
2021-12-25 09:43:18	ga_ls9c_ard_3-2-1_094079_2021-12-25_final.stac-item
2022-01-03 09:38:19	ga_ls9c_ard_3-2-1_093082_2022-01-03_final.stac-item
2022-01-08 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-01-08_final.stac-item
2022-01-25 10:38:55	ga_ls9c_ard_3-2-1_103079_2022-01-25_final.stac-item
2022-02-27 09:43:04	ga_ls9c_ard_3-2-1_094079_2022-02-27_final.stac-item
2022-03-05 10:41:15	ga_ls9c_ard_3-2-1_104070_2022-03-05_final.stac-item
2022-03-06 09:49:37	ga_ls9c_ard_3-2-1_095080_2022-03-06_final.stac-item
2022-03-22 09:47:59	ga_ls9c_ard_3-2-1_095076_2022-03-22_final.stac-item
2022-04-03 10:14:39	ga_ls9c_ard_3-2-1_099081_2022-04-03_final.stac-item
2022-04-30 09:53:55	ga_ls9c_ard_3-2-1_096076_2022-04-30_final.stac-item
2022-05-08 10:44:54	ga_ls9c_ard_3-2-1_104080_2022-05-08_final.stac-item
2022-06-24 11:38:43	ga_ls9c_ard_3-2-1_113075_2022-06-24_final.stac-item
2022-06-28 11:11:37	ga_ls9c_ard_3-2-1_109069_2022-06-28_final.stac-item
2022-07-03 09:54:51	ga_ls9c_ard_3-2-1_096078_2022-07-03_final.stac-item
2022-07-10 11:38:40	ga_ls9c_ard_3-2-1_113075_2022-07-10_final.stac-item
2022-07-11 10:43:27	ga_ls9c_ard_3-2-1_104076_2022-07-11_final.stac-item
2022-07-26 11:38:50	ga_ls9c_ard_3-2-1_113075_2022-07-26_final.stac-item
2022-08-04 09:53:53	ga_ls9c_ard_3-2-1_096075_2022-08-04_final.stac-item
2022-08-04 09:55:05	ga_ls9c_ard_3-2-1_096078_2022-08-04_final.stac-item
2022-08-05 10:38:21	ga_ls9c_ard_3-2-1_103078_2022-08-05_final.stac-item
2022-08-22 09:41:39	ga_ls9c_ard_3-2-1_094075_2022-08-22_final.stac-item
2022-09-23 09:43:22	ga_ls9c_ard_3-2-1_094079_2022-09-23_final.stac-item
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final.stac-item
2022-10-07 09:54:08	ga_ls9c_ard_3-2-1_096075_2022-10-07_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-14 11:40:52	ga_ls9c_ard_3-2-1_113079_2022-10-14_final.stac-item
2022-10-22 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-10-22_final.stac-item
2022-10-23 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-10-23_final.stac-item
2022-10-23 11:34:43	ga_ls9c_ard_3-2-1_112079_2022-10-23_final.stac-item
2022-11-08 11:33:54	ga_ls9c_ard_3-2-1_112077_2022-11-08_final.stac-item
2022-11-09 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-09_final.stac-item
2022-11-10 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-11-10_final.stac-item
2022-11-11 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-11-11_final.stac-item
2022-11-16 10:46:05	ga_ls9c_ard_3-2-1_104081_2022-11-16_final.stac-item
2022-11-26 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-11-26_final.stac-item
2022-12-03 11:28:06	ga_ls9c_ard_3-2-1_111078_2022-12-03_final.stac-item
2022-12-13 10:27:32	ga_ls9c_ard_3-2-1_101081_2022-12-13_final.stac-item
2022-12-19 11:28:07	ga_ls9c_ard_3-2-1_111078_2022-12-19_final.stac-item
2022-12-30 11:08:47	ga_ls9c_ard_3-2-1_108076_2022-12-30_final.stac-item
2023-01-20 09:48:41	ga_ls9c_ard_3-2-1_095077_2023-01-20_final.stac-item
2023-01-29 11:21:56	ga_ls9c_ard_3-2-1_110078_2023-01-29_final.stac-item
2023-01-29 11:22:20	ga_ls9c_ard_3-2-1_110079_2023-01-29_final.stac-item
2023-02-08 10:21:24	ga_ls9c_ard_3-2-1_100081_2023-02-08_final.stac-item
2023-02-14 11:22:23	ga_ls9c_ard_3-2-1_110079_2023-02-14_final.stac-item
2023-03-02 09:43:40	ga_ls9c_ard_3-2-1_094080_2023-03-02_final.stac-item
2023-03-02 09:44:52	ga_ls9c_ard_3-2-1_094083_2023-03-02_final.stac-item
2023-03-03 10:26:31	ga_ls9c_ard_3-2-1_101079_2023-03-03_final.stac-item
2023-03-11 09:38:10	ga_ls9c_ard_3-2-1_093082_2023-03-11_final.stac-item
2023-04-24 09:59:47	ga_ls9c_ard_3-2-1_097075_2023-04-24_final.stac-item
2023-04-24 10:00:11	ga_ls9c_ard_3-2-1_097076_2023-04-24_final.stac-item
2023-04-24 11:40:40	ga_ls9c_ard_3-2-1_113080_2023-04-24_final.stac-item
2023-04-25 10:43:26	ga_ls9c_ard_3-2-1_104076_2023-04-25_final.stac-item
2023-04-28 09:36:37	ga_ls9c_ard_3-2-1_093079_2023-04-28_final.stac-item
2023-04-30 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-04-29_final.stac-item
2023-05-03 11:32:21	ga_ls9c_ard_3-2-1_112075_2023-05-03_final.stac-item
2023-05-05 11:21:09	ga_ls9c_ard_3-2-1_110078_2023-05-05_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-09 10:56:26	ga_ls9c_ard_3-2-1_106078_2023-05-09_final.stac-item
2023-05-10 10:00:00	ga_ls9c_ard_3-2-1_097076_2023-05-10_final.stac-item
2023-05-10 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-05-10_final.stac-item
2023-05-11 10:43:40	ga_ls9c_ard_3-2-1_104077_2023-05-11_final.stac-item
2023-05-14 09:36:04	ga_ls9c_ard_3-2-1_093078_2023-05-14_final.stac-item
2023-05-19 09:54:57	ga_ls9c_ard_3-2-1_096079_2023-05-19_final.stac-item
2023-05-30 09:35:55	ga_ls9c_ard_3-2-1_093078_2023-05-30_final.stac-item
2023-06-01 09:23:33	ga_ls9c_ard_3-2-1_091078_2023-05-31_final.stac-item
2023-06-27 09:59:19	ga_ls9c_ard_3-2-1_097075_2023-06-27_final.stac-item
2023-06-27 11:39:24	ga_ls9c_ard_3-2-1_113078_2023-06-27_final.stac-item
2023-07-06 11:33:24	ga_ls9c_ard_3-2-1_112078_2023-07-06_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-22 09:53:22	ga_ls9c_ard_3-2-1_096075_2023-07-22_final.stac-item
2023-07-22 11:34:15	ga_ls9c_ard_3-2-1_112080_2023-07-22_final.stac-item
2023-07-23 10:36:38	ga_ls9c_ard_3-2-1_103075_2023-07-23_final.stac-item
2023-07-27 10:11:56	ga_ls9c_ard_3-2-1_099075_2023-07-27_final.stac-item
2023-07-29 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-07-29_final.stac-item
2023-07-29 11:40:06	ga_ls9c_ard_3-2-1_113079_2023-07-29_final.stac-item
2023-07-31 09:48:53	ga_ls9c_ard_3-2-1_095079_2023-07-31_final.stac-item
2023-07-31 09:49:41	ga_ls9c_ard_3-2-1_095081_2023-07-31_final.stac-item
2023-08-04 11:03:53	ga_ls9c_ard_3-2-1_107081_2023-08-04_final.stac-item
2023-08-05 10:08:17	ga_ls9c_ard_3-2-1_098081_2023-08-05_final.stac-item
2023-08-06 10:50:21	ga_ls9c_ard_3-2-1_105078_2023-08-06_final.stac-item
2023-08-11 09:30:02	ga_ls9c_ard_3-2-1_092078_2023-08-11_final.stac-item
2023-08-11 11:06:31	ga_ls9c_ard_3-2-1_108072_2023-08-11_final.stac-item
2023-08-17 10:31:49	ga_ls9c_ard_3-2-1_102078_2023-08-17_final.stac-item
2023-10-14 09:30:29	ga_ls9c_ard_3-2-1_092078_2023-10-14_final.stac-item
2023-10-16 10:58:13	ga_ls9c_ard_3-2-1_106081_2023-10-16_final.stac-item
2023-10-17 10:00:36	ga_ls9c_ard_3-2-1_097076_2023-10-17_final.stac-item
2023-10-17 10:03:00	ga_ls9c_ard_3-2-1_097082_2023-10-17_final.stac-item
2023-10-17 11:40:41	ga_ls9c_ard_3-2-1_113079_2023-10-17_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-21 09:37:29	ga_ls9c_ard_3-2-1_093080_2023-10-21_final.stac-item
2023-10-21 11:15:34	ga_ls9c_ard_3-2-1_109078_2023-10-21_final.stac-item
2023-10-21 11:15:58	ga_ls9c_ard_3-2-1_109079_2023-10-21_final.stac-item
2023-10-24 10:09:10	ga_ls9c_ard_3-2-1_098082_2023-10-24_final.stac-item
2023-10-28 09:43:13	ga_ls9c_ard_3-2-1_094079_2023-10-28_final.stac-item
2023-10-30 09:30:26	ga_ls9c_ard_3-2-1_092078_2023-10-30_final.stac-item
2023-11-02 10:00:05	ga_ls9c_ard_3-2-1_097075_2023-11-02_final.stac-item
2023-11-15 09:30:25	ga_ls9c_ard_3-2-1_092078_2023-11-15_final.stac-item
2023-11-20 09:48:38	ga_ls9c_ard_3-2-1_095077_2023-11-20_final.stac-item
2023-11-20 09:49:02	ga_ls9c_ard_3-2-1_095078_2023-11-20_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