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
2021-11-12 09:25:07	ga_ls9c_ard_3-2-1_091088_2021-11-11_final.stac-item
2021-12-04 11:02:34	ga_ls9c_ard_3-2-1_107076_2021-12-04_final.stac-item
2021-12-06 10:47:48	ga_ls9c_ard_3-2-1_105070_2021-12-06_final.stac-item
2021-12-07 09:53:22	ga_ls9c_ard_3-2-1_096073_2021-12-07_final.stac-item
2021-12-14 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-14_final.stac-item
2021-12-15 10:41:07	ga_ls9c_ard_3-2-1_104069_2021-12-15_final.stac-item
2021-12-23 09:52:52	ga_ls9c_ard_3-2-1_096072_2021-12-23_final.stac-item
2021-12-25 09:45:18	ga_ls9c_ard_3-2-1_094084_2021-12-25_final.stac-item
2021-12-30 11:39:08	ga_ls9c_ard_3-2-1_113075_2021-12-30_final.stac-item
2022-01-03 09:35:07	ga_ls9c_ard_3-2-1_093074_2022-01-03_final.stac-item
2022-01-06 11:46:05	ga_ls9c_ard_3-2-1_114077_2022-01-06_final.stac-item
2022-01-18 10:31:07	ga_ls9c_ard_3-2-1_102075_2022-01-18_final.stac-item
2022-01-19 11:17:34	ga_ls9c_ard_3-2-1_109083_2022-01-19_final.stac-item
2022-01-20 10:20:21	ga_ls9c_ard_3-2-1_100079_2022-01-20_final.stac-item
2022-01-21 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-01-20_final.stac-item
2022-02-03 10:31:56	ga_ls9c_ard_3-2-1_102077_2022-02-03_final.stac-item
2022-02-20 09:40:11	ga_ls9c_ard_3-2-1_093087_2022-02-20_final.stac-item
2022-02-20 11:13:52	ga_ls9c_ard_3-2-1_109074_2022-02-20_final.stac-item
2022-02-21 11:58:43	ga_ls9c_ard_3-2-1_116078_2022-02-21_final.stac-item
2022-03-29 11:33:48	ga_ls9c_ard_3-2-1_112078_2022-03-29_final.stac-item
2022-03-30 10:37:47	ga_ls9c_ard_3-2-1_103077_2022-03-30_final.stac-item
2022-04-05 09:57:30	ga_ls9c_ard_3-2-1_097069_2022-04-05_final.stac-item
2022-04-19 11:52:59	ga_ls9c_ard_3-2-1_115080_2022-04-19_final.stac-item
2022-05-20 11:05:51	ga_ls9c_ard_3-2-1_108071_2022-05-20_final.stac-item
2022-05-21 11:52:19	ga_ls9c_ard_3-2-1_115079_2022-05-21_final.stac-item
2022-05-26 10:32:46	ga_ls9c_ard_3-2-1_102081_2022-05-26_final.stac-item
2022-06-05 11:09:04	ga_ls9c_ard_3-2-1_108079_2022-06-05_final.stac-item
2022-06-06 11:51:08	ga_ls9c_ard_3-2-1_115076_2022-06-06_final.stac-item
2022-06-07 10:53:31	ga_ls9c_ard_3-2-1_106071_2022-06-07_final.stac-item
2022-06-09 10:41:58	ga_ls9c_ard_3-2-1_104073_2022-06-09_final.stac-item
2022-06-12 09:35:37	ga_ls9c_ard_3-2-1_093077_2022-06-12_final.stac-item
2022-06-15 11:44:15	ga_ls9c_ard_3-2-1_114074_2022-06-15_final.stac-item
2022-06-20 10:24:49	ga_ls9c_ard_3-2-1_101076_2022-06-20_final.stac-item
2022-06-26 11:29:10	ga_ls9c_ard_3-2-1_111082_2022-06-26_final.stac-item
2022-07-05 11:18:34	ga_ls9c_ard_3-2-1_110071_2022-07-05_final.stac-item
2022-07-06 10:26:56	ga_ls9c_ard_3-2-1_101081_2022-07-06_final.stac-item
2022-07-17 11:46:51	ga_ls9c_ard_3-2-1_114080_2022-07-17_final.stac-item
2022-07-21 11:20:37	ga_ls9c_ard_3-2-1_110076_2022-07-21_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-07-26 10:01:32	ga_ls9c_ard_3-2-1_097079_2022-07-26_final.stac-item
2022-08-11 10:00:56	ga_ls9c_ard_3-2-1_097077_2022-08-11_final.stac-item
2022-08-18 10:03:57	ga_ls9c_ard_3-2-1_098069_2022-08-18_final.stac-item
2022-08-21 10:36:52	ga_ls9c_ard_3-2-1_103074_2022-08-21_final.stac-item
2022-08-24 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-08-24_final.stac-item
2022-08-26 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-08-26_final.stac-item
2022-08-31 09:33:53	ga_ls9c_ard_3-2-1_093071_2022-08-31_final.stac-item
2022-08-31 11:17:33	ga_ls9c_ard_3-2-1_109083_2022-08-31_final.stac-item
2022-10-04 09:29:13	ga_ls9c_ard_3-2-1_091090_2022-10-03_final.stac-item
2022-10-11 09:31:27	ga_ls9c_ard_3-2-1_092080_2022-10-11_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-25 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-10-25_final.stac-item
2022-10-29 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-10-29_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-11-07 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-11-06_final.stac-item
2022-11-07 10:50:38	ga_ls9c_ard_3-2-1_105077_2022-11-07_final.stac-item
2022-11-08 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-11-08_final.stac-item
2022-11-29 11:52:02	ga_ls9c_ard_3-2-1_115076_2022-11-29_final.stac-item
2022-12-01 10:01:10	ga_ls9c_ard_3-2-1_097077_2022-12-01_final.stac-item
2022-12-07 11:01:00	ga_ls9c_ard_3-2-1_107072_2022-12-07_final.stac-item
2022-12-12 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-12-12_final.stac-item
2022-12-20 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-20_final.stac-item
2022-12-25 10:52:36	ga_ls9c_ard_3-2-1_105082_2022-12-25_final.stac-item
2023-01-05 10:30:55	ga_ls9c_ard_3-2-1_102074_2023-01-05_final.stac-item
2023-01-08 09:24:32	ga_ls9c_ard_3-2-1_091078_2023-01-07_final.stac-item
2023-01-09 11:45:28	ga_ls9c_ard_3-2-1_114075_2023-01-09_final.stac-item
2023-01-14 10:23:53	ga_ls9c_ard_3-2-1_101072_2023-01-14_final.stac-item
2023-01-18 09:57:06	ga_ls9c_ard_3-2-1_097067_2023-01-18_final.stac-item
2023-01-21 10:30:45	ga_ls9c_ard_3-2-1_102074_2023-01-21_final.stac-item
2023-01-31 09:32:18	ga_ls9c_ard_3-2-1_092082_2023-01-31_final.stac-item
2023-02-03 11:42:07	ga_ls9c_ard_3-2-1_113082_2023-02-03_final.stac-item
2023-02-07 09:39:44	ga_ls9c_ard_3-2-1_093085_2023-02-07_final.stac-item
2023-02-11 09:14:13	ga_ls9c_ard_3-2-1_089083_2023-02-10_final.stac-item
2023-02-19 11:42:01	ga_ls9c_ard_3-2-1_113082_2023-02-19_final.stac-item
2023-02-21 09:47:56	ga_ls9c_ard_3-2-1_095075_2023-02-21_final.stac-item
2023-02-21 09:51:56	ga_ls9c_ard_3-2-1_095085_2023-02-21_final.stac-item
2023-03-01 10:34:55	ga_ls9c_ard_3-2-1_103069_2023-03-01_final.stac-item
2023-03-06 09:20:30	ga_ls9c_ard_3-2-1_090084_2023-03-05_final.stac-item
2023-03-11 11:16:39	ga_ls9c_ard_3-2-1_109081_2023-03-11_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-29 11:00:07	ga_ls9c_ard_3-2-1_107071_2023-03-29_final.stac-item
2023-04-05 11:06:18	ga_ls9c_ard_3-2-1_108071_2023-04-05_final.stac-item
2023-04-18 10:38:29	ga_ls9c_ard_3-2-1_103079_2023-04-18_final.stac-item
2023-04-30 11:05:06	ga_ls9c_ard_3-2-1_107084_2023-04-30_final.stac-item
2023-05-12 09:46:50	ga_ls9c_ard_3-2-1_095074_2023-05-12_final.stac-item
2023-05-19 11:35:25	ga_ls9c_ard_3-2-1_112083_2023-05-19_final.stac-item
2023-05-22 10:22:12	ga_ls9c_ard_3-2-1_101070_2023-05-22_final.stac-item
2023-06-01 11:01:38	ga_ls9c_ard_3-2-1_107076_2023-06-01_final.stac-item
2023-06-17 09:24:12	ga_ls9c_ard_3-2-1_091080_2023-06-16_final.stac-item
2023-07-01 11:17:11	ga_ls9c_ard_3-2-1_109084_2023-07-01_final.stac-item
2023-07-07 10:33:48	ga_ls9c_ard_3-2-1_103068_2023-07-07_final.stac-item
2023-07-11 11:51:35	ga_ls9c_ard_3-2-1_115077_2023-07-11_final.stac-item
2023-07-12 10:53:35	ga_ls9c_ard_3-2-1_106071_2023-07-12_final.stac-item
2023-07-19 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-07-18_final.stac-item
2023-07-19 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-07-19_final.stac-item
2023-07-26 11:05:09	ga_ls9c_ard_3-2-1_108069_2023-07-26_final.stac-item
2023-07-29 11:39:18	ga_ls9c_ard_3-2-1_113077_2023-07-29_final.stac-item
2023-10-15 10:12:09	ga_ls9c_ard_3-2-1_099074_2023-10-15_final.stac-item
2023-10-15 10:12:57	ga_ls9c_ard_3-2-1_099076_2023-10-15_final.stac-item
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-11-01 10:54:32	ga_ls9c_ard_3-2-1_106072_2023-11-01_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