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
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-11-25 09:46:04	ga_ls9c_ard_3-2-1_095075_2021-11-25_final.stac-item
2021-12-30 10:03:26	ga_ls9c_ard_3-2-1_097083_2021-12-30_final.stac-item
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-16 10:41:28	ga_ls9c_ard_3-2-1_104070_2022-01-16_final.stac-item
2022-02-04 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-02-04_final.stac-item
2022-02-11 09:43:15	ga_ls9c_ard_3-2-1_094079_2022-02-11_final.stac-item
2022-02-15 09:20:06	ga_ls9c_ard_3-2-1_090083_2022-02-14_final.stac-item
2022-04-18 09:31:40	ga_ls9c_ard_3-2-1_092082_2022-04-18_final.stac-item
2022-06-12 09:35:13	ga_ls9c_ard_3-2-1_093076_2022-06-12_final.stac-item
2022-06-18 10:34:18	ga_ls9c_ard_3-2-1_103069_2022-06-18_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-07-20 10:38:08	ga_ls9c_ard_3-2-1_103078_2022-07-20_final.stac-item
2022-07-26 09:59:33	ga_ls9c_ard_3-2-1_097074_2022-07-26_final.stac-item
2022-09-01 10:18:20	ga_ls9c_ard_3-2-1_100074_2022-09-01_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-12 11:51:13	ga_ls9c_ard_3-2-1_115074_2022-10-12_final.stac-item
2022-10-19 10:18:57	ga_ls9c_ard_3-2-1_100075_2022-10-19_final.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-12-14 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-14_final.stac-item
2022-12-17 10:00:00	ga_ls9c_ard_3-2-1_097074_2022-12-17_final.stac-item
2022-12-20 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-20_final.stac-item
2022-12-31 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-12-31_final.stac-item
2023-01-02 10:03:36	ga_ls9c_ard_3-2-1_097083_2023-01-02_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-11 11:35:53	ga_ls9c_ard_3-2-1_112082_2023-01-11_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-16 10:15:29	ga_ls9c_ard_3-2-1_099082_2023-01-16_final.stac-item
2023-01-24 11:04:07	ga_ls9c_ard_3-2-1_107080_2023-01-24_final.stac-item
2023-01-25 10:09:18	ga_ls9c_ard_3-2-1_098082_2023-01-25_final.stac-item
2023-01-31 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-01-31_final.stac-item
2023-02-03 10:00:27	ga_ls9c_ard_3-2-1_097075_2023-02-03_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-02-12 09:56:40	ga_ls9c_ard_3-2-1_096081_2023-02-12_final.stac-item
2023-02-14 11:22:23	ga_ls9c_ard_3-2-1_110079_2023-02-14_final.stac-item
2023-04-23 09:19:20	ga_ls9c_ard_3-2-1_090082_2023-04-22_final.stac-item
2023-04-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2023-04-23_final.stac-item
2023-04-23 10:58:13	ga_ls9c_ard_3-2-1_106082_2023-04-23_final.stac-item
2023-04-24 09:58:59	ga_ls9c_ard_3-2-1_097073_2023-04-24_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-27 10:29:27	ga_ls9c_ard_3-2-1_102072_2023-04-27_final.stac-item
2023-04-30 11:03:54	ga_ls9c_ard_3-2-1_107081_2023-04-30_final.stac-item
2023-05-30 09:38:18	ga_ls9c_ard_3-2-1_093084_2023-05-30_final.stac-item
2023-07-16 10:33:16	ga_ls9c_ard_3-2-1_102082_2023-07-16_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-07-19 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-07-19_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-21 10:46:36	ga_ls9c_ard_3-2-1_105069_2023-07-21_final.stac-item
2023-07-26 09:30:39	ga_ls9c_ard_3-2-1_092080_2023-07-26_final.stac-item
2023-07-28 10:54:01	ga_ls9c_ard_3-2-1_106072_2023-07-28_final.stac-item
2023-07-28 10:57:37	ga_ls9c_ard_3-2-1_106081_2023-07-28_final.stac-item
2023-07-29 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-07-29_final.stac-item
2023-07-29 10:00:25	ga_ls9c_ard_3-2-1_097077_2023-07-29_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-05 11:46:22	ga_ls9c_ard_3-2-1_114079_2023-08-05_final.stac-item
2023-08-06 09:12:16	ga_ls9c_ard_3-2-1_089080_2023-08-05_final.stac-item
2023-10-14 09:31:16	ga_ls9c_ard_3-2-1_092080_2023-10-14_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-14 11:05:46	ga_ls9c_ard_3-2-1_108069_2023-10-14_final.stac-item
2023-10-14 11:06:58	ga_ls9c_ard_3-2-1_108072_2023-10-14_final.stac-item
2023-10-15 10:12:57	ga_ls9c_ard_3-2-1_099076_2023-10-15_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-16 10:57:01	ga_ls9c_ard_3-2-1_106078_2023-10-16_final.stac-item
2023-10-16 10:57:25	ga_ls9c_ard_3-2-1_106079_2023-10-16_final.stac-item
2023-10-17 09:59:48	ga_ls9c_ard_3-2-1_097074_2023-10-17_final.stac-item
2023-10-17 11:41:53	ga_ls9c_ard_3-2-1_113082_2023-10-17_final.stac-item
2023-10-19 09:50:39	ga_ls9c_ard_3-2-1_095082_2023-10-19_final.stac-item
2023-10-19 09:51:03	ga_ls9c_ard_3-2-1_095083_2023-10-19_final.stac-item
2023-10-19 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-10-19_final.stac-item
2023-10-19 11:28:44	ga_ls9c_ard_3-2-1_111080_2023-10-19_final.stac-item
2023-10-20 10:31:07	ga_ls9c_ard_3-2-1_102075_2023-10-20_final.stac-item
2023-10-21 09:38:41	ga_ls9c_ard_3-2-1_093083_2023-10-21_final.stac-item
2023-10-23 09:24:19	ga_ls9c_ard_3-2-1_091078_2023-10-22_final.stac-item
2023-10-24 10:05:59	ga_ls9c_ard_3-2-1_098074_2023-10-24_final.stac-item
2023-10-25 10:47:38	ga_ls9c_ard_3-2-1_105070_2023-10-25_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-10-27 10:35:40	ga_ls9c_ard_3-2-1_103071_2023-10-27_final.stac-item
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_2023-10-27_final.stac-item
2023-10-30 09:30:50	ga_ls9c_ard_3-2-1_092079_2023-10-30_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-10-30 09:31:38	ga_ls9c_ard_3-2-1_092081_2023-10-30_final.stac-item
2023-10-30 11:09:43	ga_ls9c_ard_3-2-1_108079_2023-10-30_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-10-31 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-10-31_final.stac-item
2023-11-02 10:02:29	ga_ls9c_ard_3-2-1_097081_2023-11-02_final.stac-item
2023-11-02 10:02:53	ga_ls9c_ard_3-2-1_097082_2023-11-02_final.stac-item
2023-11-02 11:39:22	ga_ls9c_ard_3-2-1_113076_2023-11-02_final.stac-item
2023-11-03 10:44:08	ga_ls9c_ard_3-2-1_104077_2023-11-03_final.stac-item
2023-11-04 09:50:55	ga_ls9c_ard_3-2-1_095083_2023-11-04_final.stac-item
2023-11-14 10:24:27	ga_ls9c_ard_3-2-1_101074_2023-11-14_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-16 10:11:42	ga_ls9c_ard_3-2-1_099073_2023-11-16_final.stac-item
2023-11-20 09:49:02	ga_ls9c_ard_3-2-1_095078_2023-11-20_final.stac-item
2023-11-20 11:27:55	ga_ls9c_ard_3-2-1_111078_2023-11-20_final.stac-item
2023-11-22 11:15:12	ga_ls9c_ard_3-2-1_109077_2023-11-22_final.stac-item
2023-11-23 10:20:47	ga_ls9c_ard_3-2-1_100080_2023-11-23_final.stac-item
2023-11-24 11:04:03	ga_ls9c_ard_3-2-1_107080_2023-11-24_final.stac-item
2023-11-26 10:51:42	ga_ls9c_ard_3-2-1_105080_2023-11-26_final.stac-item
2024-02-16 10:36:52	ga_ls9c_ard_3-2-1_103074_2024-02-16_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