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
2021-11-05 09:39:00	ga_ls9c_ard_3-2-1_093082_2021-11-05_final.stac-item
2021-11-10 11:20:32	ga_ls9c_ard_3-2-1_110083_2021-11-10_final.stac-item
2021-11-12 09:21:56	ga_ls9c_ard_3-2-1_091080_2021-11-11_final.stac-item
2022-02-09 11:34:06	ga_ls9c_ard_3-2-1_112078_2022-02-09_final.stac-item
2022-02-10 10:38:53	ga_ls9c_ard_3-2-1_103079_2022-02-10_final.stac-item
2022-02-24 10:51:06	ga_ls9c_ard_3-2-1_105079_2022-02-24_final.stac-item
2022-02-25 11:34:21	ga_ls9c_ard_3-2-1_112079_2022-02-25_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
2022-03-28 10:50:56	ga_ls9c_ard_3-2-1_105079_2022-03-28_final.stac-item
2022-03-31 09:44:34	ga_ls9c_ard_3-2-1_094083_2022-03-31_final.stac-item
2022-04-06 10:44:21	ga_ls9c_ard_3-2-1_104078_2022-04-06_final.stac-item
2022-05-06 10:56:29	ga_ls9c_ard_3-2-1_106078_2022-05-06_final.stac-item
2022-05-15 10:50:59	ga_ls9c_ard_3-2-1_105080_2022-05-15_final.stac-item
2022-05-24 10:41:32	ga_ls9c_ard_3-2-1_104072_2022-05-24_final.stac-item
2022-06-01 11:32:35	ga_ls9c_ard_3-2-1_112076_2022-06-01_final.stac-item
2022-06-09 10:41:34	ga_ls9c_ard_3-2-1_104072_2022-06-09_final.stac-item
2022-06-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2022-06-23_final.stac-item
2022-06-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-06-23_final.stac-item
2022-06-28 11:11:37	ga_ls9c_ard_3-2-1_109069_2022-06-28_final.stac-item
2022-07-10 10:02:59	ga_ls9c_ard_3-2-1_097083_2022-07-10_final.stac-item
2022-07-16 09:23:54	ga_ls9c_ard_3-2-1_091078_2022-07-15_final.stac-item
2022-07-25 10:57:09	ga_ls9c_ard_3-2-1_106079_2022-07-25_final.stac-item
2022-08-03 10:51:29	ga_ls9c_ard_3-2-1_105080_2022-08-03_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-12 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-08-12_final.stac-item
2022-08-28 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-08-28_final.stac-item
2022-09-18 11:04:52	ga_ls9c_ard_3-2-1_107082_2022-09-18_final.stac-item
2022-09-24 10:23:02	ga_ls9c_ard_3-2-1_101070_2022-09-24_final.stac-item
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final.stac-item
2022-10-14 11:39:40	ga_ls9c_ard_3-2-1_113076_2022-10-14_final.stac-item
2022-11-07 10:49:02	ga_ls9c_ard_3-2-1_105073_2022-11-07_final.stac-item
2022-11-09 10:39:05	ga_ls9c_ard_3-2-1_103079_2022-11-09_final.stac-item
2022-11-15 10:00:26	ga_ls9c_ard_3-2-1_097075_2022-11-15_final.stac-item
2022-11-17 09:49:40	ga_ls9c_ard_3-2-1_095079_2022-11-17_final.stac-item
2022-12-03 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-03_final.stac-item
2022-12-03 09:50:00	ga_ls9c_ard_3-2-1_095080_2022-12-03_final.stac-item
2022-12-03 11:28:30	ga_ls9c_ard_3-2-1_111079_2022-12-03_final.stac-item
2022-12-10 09:55:02	ga_ls9c_ard_3-2-1_096077_2022-12-10_final.stac-item
2022-12-10 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-12-10_final.stac-item
2022-12-11 10:39:05	ga_ls9c_ard_3-2-1_103079_2022-12-11_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-18 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-12-18_final.stac-item
2022-12-19 11:28:07	ga_ls9c_ard_3-2-1_111078_2022-12-19_final.stac-item
2022-12-21 09:38:27	ga_ls9c_ard_3-2-1_093082_2022-12-21_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-04 11:28:32	ga_ls9c_ard_3-2-1_111079_2023-01-04_final.stac-item
2023-01-20 09:48:41	ga_ls9c_ard_3-2-1_095077_2023-01-20_final.stac-item
2023-01-20 11:28:22	ga_ls9c_ard_3-2-1_111079_2023-01-20_final.stac-item
2023-01-21 10:33:09	ga_ls9c_ard_3-2-1_102080_2023-01-21_final.stac-item
2023-01-27 09:56:59	ga_ls9c_ard_3-2-1_096082_2023-01-27_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-05 09:48:54	ga_ls9c_ard_3-2-1_095077_2023-02-05_final.stac-item
2023-02-05 11:28:35	ga_ls9c_ard_3-2-1_111079_2023-02-05_final.stac-item
2023-03-11 11:16:15	ga_ls9c_ard_3-2-1_109080_2023-03-11_final.stac-item
2023-04-30 11:04:18	ga_ls9c_ard_3-2-1_107082_2023-04-30_final.stac-item
2023-05-02 10:51:06	ga_ls9c_ard_3-2-1_105080_2023-05-02_final.stac-item
2023-05-05 09:43:04	ga_ls9c_ard_3-2-1_094080_2023-05-05_final.stac-item
2023-05-11 10:43:40	ga_ls9c_ard_3-2-1_104077_2023-05-11_final.stac-item
2023-05-11 10:44:52	ga_ls9c_ard_3-2-1_104080_2023-05-11_final.stac-item
2023-05-12 09:49:14	ga_ls9c_ard_3-2-1_095080_2023-05-12_final.stac-item
2023-05-19 09:52:33	ga_ls9c_ard_3-2-1_096073_2023-05-19_final.stac-item
2023-06-01 09:23:33	ga_ls9c_ard_3-2-1_091078_2023-05-31_final.stac-item
2023-06-21 10:35:58	ga_ls9c_ard_3-2-1_103074_2023-06-21_final.stac-item
2023-06-22 09:41:57	ga_ls9c_ard_3-2-1_094078_2023-06-22_final.stac-item
2023-06-23 10:22:01	ga_ls9c_ard_3-2-1_101070_2023-06-23_final.stac-item
2023-06-29 11:26:42	ga_ls9c_ard_3-2-1_111077_2023-06-29_final.stac-item
2023-06-29 11:27:54	ga_ls9c_ard_3-2-1_111080_2023-06-29_final.stac-item
2023-07-05 10:47:20	ga_ls9c_ard_3-2-1_105071_2023-07-05_final.stac-item
2023-07-17 11:15:20	ga_ls9c_ard_3-2-1_109079_2023-07-17_final.stac-item
2023-07-18 10:18:06	ga_ls9c_ard_3-2-1_100075_2023-07-18_final.stac-item
2023-07-21 10:47:24	ga_ls9c_ard_3-2-1_105071_2023-07-21_final.stac-item
2023-07-21 10:49:48	ga_ls9c_ard_3-2-1_105077_2023-07-21_final.stac-item
2023-07-22 09:52:35	ga_ls9c_ard_3-2-1_096073_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
2023-07-24 11:21:29	ga_ls9c_ard_3-2-1_110079_2023-07-24_final.stac-item
2023-07-24 11:22:17	ga_ls9c_ard_3-2-1_110081_2023-07-24_final.stac-item
2023-07-25 10:26:15	ga_ls9c_ard_3-2-1_101080_2023-07-25_final.stac-item
2023-07-28 10:58:25	ga_ls9c_ard_3-2-1_106083_2023-07-28_final.stac-item
2023-07-30 10:41:42	ga_ls9c_ard_3-2-1_104072_2023-07-30_final.stac-item
2023-07-30 10:44:05	ga_ls9c_ard_3-2-1_104078_2023-07-30_final.stac-item
2023-07-31 09:49:17	ga_ls9c_ard_3-2-1_095080_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
2023-08-02 09:35:45	ga_ls9c_ard_3-2-1_093077_2023-08-02_final.stac-item
2023-08-02 11:15:26	ga_ls9c_ard_3-2-1_109079_2023-08-02_final.stac-item
2023-08-05 10:06:17	ga_ls9c_ard_3-2-1_098076_2023-08-05_final.stac-item
2023-08-11 09:30:02	ga_ls9c_ard_3-2-1_092078_2023-08-11_final.stac-item
2023-10-18 10:41:52	ga_ls9c_ard_3-2-1_104071_2023-10-18_final.stac-item
2023-10-19 09:48:15	ga_ls9c_ard_3-2-1_095076_2023-10-19_final.stac-item
2023-10-19 11:28:20	ga_ls9c_ard_3-2-1_111079_2023-10-19_final.stac-item
2023-10-21 09:37:05	ga_ls9c_ard_3-2-1_093079_2023-10-21_final.stac-item
2023-10-21 09:37:53	ga_ls9c_ard_3-2-1_093081_2023-10-21_final.stac-item
2023-10-24 10:06:47	ga_ls9c_ard_3-2-1_098076_2023-10-24_final.stac-item
2023-10-26 09:57:12	ga_ls9c_ard_3-2-1_096083_2023-10-26_final.stac-item
2023-10-28 11:23:42	ga_ls9c_ard_3-2-1_110083_2023-10-28_final.stac-item
2023-11-14 10:22:52	ga_ls9c_ard_3-2-1_101070_2023-11-14_final.stac-item
2023-11-18 10:00:34	ga_ls9c_ard_3-2-1_097076_2023-11-18_final.stac-item
2023-11-20 11:29:55	ga_ls9c_ard_3-2-1_111083_2023-11-20_final.stac-item
2023-11-21 10:33:07	ga_ls9c_ard_3-2-1_102080_2023-11-21_final.stac-item
2023-11-26 10:52:06	ga_ls9c_ard_3-2-1_105081_2023-11-26_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