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 09:53:46	ga_ls9c_ard_3-2-1_096072_2021-11-03_final.stac-item
2021-11-10 09:40:17	ga_ls9c_ard_3-2-1_094079_2021-11-10_final.stac-item
2021-11-20 11:20:41	ga_ls9c_ard_3-2-1_110071_2021-11-20_final.stac-item
2021-12-09 11:22:39	ga_ls9c_ard_3-2-1_110080_2021-12-09_final.stac-item
2021-12-25 09:43:42	ga_ls9c_ard_3-2-1_094080_2021-12-25_final.stac-item
2022-01-05 09:24:21	ga_ls9c_ard_3-2-1_091078_2022-01-04_final.stac-item
2022-01-08 09:55:38	ga_ls9c_ard_3-2-1_096079_2022-01-08_final.stac-item
2022-01-12 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-01-12_final.stac-item
2022-01-13 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-01-13_final.stac-item
2022-01-18 10:31:55	ga_ls9c_ard_3-2-1_102077_2022-01-18_final.stac-item
2022-02-09 11:32:55	ga_ls9c_ard_3-2-1_112075_2022-02-09_final.stac-item
2022-02-11 11:22:32	ga_ls9c_ard_3-2-1_110080_2022-02-11_final.stac-item
2022-02-12 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-02-12_final.stac-item
2022-02-16 11:39:02	ga_ls9c_ard_3-2-1_113075_2022-02-16_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-03-09 11:57:49	ga_ls9c_ard_3-2-1_116076_2022-03-09_final.stac-item
2022-03-10 11:04:35	ga_ls9c_ard_3-2-1_107082_2022-03-10_final.stac-item
2022-03-26 09:26:01	ga_ls9c_ard_3-2-1_091083_2022-03-25_final.stac-item
2022-03-29 11:35:00	ga_ls9c_ard_3-2-1_112081_2022-03-29_final.stac-item
2022-03-31 09:46:09	ga_ls9c_ard_3-2-1_094087_2022-03-31_final.stac-item
2022-04-02 09:30:12	ga_ls9c_ard_3-2-1_092078_2022-04-02_final.stac-item
2022-04-04 10:56:19	ga_ls9c_ard_3-2-1_106077_2022-04-04_final.stac-item
2022-04-10 11:58:05	ga_ls9c_ard_3-2-1_116077_2022-04-10_final.stac-item
2022-04-20 09:18:28	ga_ls9c_ard_3-2-1_090080_2022-04-19_final.stac-item
2022-04-22 10:43:22	ga_ls9c_ard_3-2-1_104076_2022-04-22_final.stac-item
2022-04-25 09:39:23	ga_ls9c_ard_3-2-1_093086_2022-04-25_final.stac-item
2022-05-03 10:22:25	ga_ls9c_ard_3-2-1_101070_2022-05-03_final.stac-item
2022-05-30 10:06:04	ga_ls9c_ard_3-2-1_098076_2022-05-30_final.stac-item
2022-06-13 10:20:29	ga_ls9c_ard_3-2-1_100081_2022-06-13_final.stac-item
2022-06-26 09:49:53	ga_ls9c_ard_3-2-1_095081_2022-06-26_final.stac-item
2022-07-04 10:36:30	ga_ls9c_ard_3-2-1_103074_2022-07-04_final.stac-item
2022-07-06 10:24:56	ga_ls9c_ard_3-2-1_101076_2022-07-06_final.stac-item
2022-07-20 10:36:32	ga_ls9c_ard_3-2-1_103074_2022-07-20_final.stac-item
2022-08-07 10:24:49	ga_ls9c_ard_3-2-1_101075_2022-08-07_final.stac-item
2022-08-13 09:50:11	ga_ls9c_ard_3-2-1_095081_2022-08-13_final.stac-item
2022-08-19 09:13:08	ga_ls9c_ard_3-2-1_089081_2022-08-18_final.stac-item
2022-08-22 09:44:26	ga_ls9c_ard_3-2-1_094082_2022-08-22_final.stac-item
2022-08-24 11:10:58	ga_ls9c_ard_3-2-1_108082_2022-08-24_final.stac-item
2022-08-29 09:48:38	ga_ls9c_ard_3-2-1_095077_2022-08-29_final.stac-item
2022-08-29 09:50:14	ga_ls9c_ard_3-2-1_095081_2022-08-29_final.stac-item
2022-09-19 10:06:52	ga_ls9c_ard_3-2-1_098076_2022-09-19_final.stac-item
2022-09-27 09:18:39	ga_ls9c_ard_3-2-1_090079_2022-09-26_final.stac-item
2022-10-05 10:06:53	ga_ls9c_ard_3-2-1_098076_2022-10-05_final.stac-item
2022-10-08 10:39:24	ga_ls9c_ard_3-2-1_103080_2022-10-08_final.stac-item
2022-10-19 10:18:09	ga_ls9c_ard_3-2-1_100073_2022-10-19_final.stac-item
2022-10-24 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-10-24_final.stac-item
2022-10-24 10:39:30	ga_ls9c_ard_3-2-1_103080_2022-10-24_final.stac-item
2022-10-25 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-10-25_final.stac-item
2022-10-25 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-10-25_final.stac-item
2022-11-11 10:25:09	ga_ls9c_ard_3-2-1_101075_2022-11-11_final.stac-item
2022-11-15 11:42:07	ga_ls9c_ard_3-2-1_113082_2022-11-15_final.stac-item
2022-11-28 11:09:10	ga_ls9c_ard_3-2-1_108077_2022-11-28_final.stac-item
2022-12-05 09:36:04	ga_ls9c_ard_3-2-1_093076_2022-12-05_final.stac-item
2022-12-07 11:03:48	ga_ls9c_ard_3-2-1_107079_2022-12-07_final.stac-item
2022-12-10 09:56:37	ga_ls9c_ard_3-2-1_096081_2022-12-10_final.stac-item
2022-12-10 11:32:19	ga_ls9c_ard_3-2-1_112073_2022-12-10_final.stac-item
2022-12-15 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-15_final.stac-item
2022-12-17 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-12-17_final.stac-item
2022-12-23 09:24:52	ga_ls9c_ard_3-2-1_091079_2022-12-22_final.stac-item
2022-12-23 11:03:45	ga_ls9c_ard_3-2-1_107079_2022-12-23_final.stac-item
2023-01-08 11:03:48	ga_ls9c_ard_3-2-1_107079_2023-01-08_final.stac-item
2023-01-10 10:50:38	ga_ls9c_ard_3-2-1_105077_2023-01-10_final.stac-item
2023-01-10 10:51:50	ga_ls9c_ard_3-2-1_105080_2023-01-10_final.stac-item
2023-02-01 10:15:11	ga_ls9c_ard_3-2-1_099081_2023-02-01_final.stac-item
2023-02-11 09:13:01	ga_ls9c_ard_3-2-1_089080_2023-02-10_final.stac-item
2023-03-02 11:22:33	ga_ls9c_ard_3-2-1_110080_2023-03-02_final.stac-item
2023-03-17 10:38:23	ga_ls9c_ard_3-2-1_103078_2023-03-17_final.stac-item
2023-03-30 10:05:41	ga_ls9c_ard_3-2-1_098074_2023-03-30_final.stac-item
2023-04-08 10:00:41	ga_ls9c_ard_3-2-1_097077_2023-04-08_final.stac-item
2023-04-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2023-04-23_final.stac-item
2023-05-01 11:45:56	ga_ls9c_ard_3-2-1_114078_2023-05-01_final.stac-item
2023-05-03 09:53:04	ga_ls9c_ard_3-2-1_096074_2023-05-03_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 09:47:14	ga_ls9c_ard_3-2-1_095075_2023-05-12_final.stac-item
2023-05-13 10:32:29	ga_ls9c_ard_3-2-1_102080_2023-05-13_final.stac-item
2023-05-17 11:45:25	ga_ls9c_ard_3-2-1_114077_2023-05-17_final.stac-item
2023-05-19 11:31:26	ga_ls9c_ard_3-2-1_112073_2023-05-19_final.stac-item
2023-05-28 11:25:58	ga_ls9c_ard_3-2-1_111075_2023-05-28_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-05-31 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-05-31_final.stac-item
2023-06-22 11:20:26	ga_ls9c_ard_3-2-1_110077_2023-06-22_final.stac-item
2023-06-24 09:31:10	ga_ls9c_ard_3-2-1_092082_2023-06-24_final.stac-item
2023-07-01 11:14:47	ga_ls9c_ard_3-2-1_109078_2023-07-01_final.stac-item
2023-07-15 09:50:00	ga_ls9c_ard_3-2-1_095082_2023-07-15_final.stac-item
2023-07-17 09:35:15	ga_ls9c_ard_3-2-1_093076_2023-07-17_final.stac-item
2023-07-30 10:41:18	ga_ls9c_ard_3-2-1_104071_2023-07-30_final.stac-item
2023-08-02 09:35:21	ga_ls9c_ard_3-2-1_093076_2023-08-02_final.stac-item
2023-08-06 10:49:57	ga_ls9c_ard_3-2-1_105077_2023-08-06_final.stac-item
2023-08-06 10:52:21	ga_ls9c_ard_3-2-1_105083_2023-08-06_final.stac-item
2023-08-11 09:30:26	ga_ls9c_ard_3-2-1_092079_2023-08-11_final.stac-item
2023-08-12 10:11:18	ga_ls9c_ard_3-2-1_099073_2023-08-12_final.stac-item
2023-08-13 09:18:04	ga_ls9c_ard_3-2-1_090079_2023-08-12_final.stac-item
2023-08-15 10:43:47	ga_ls9c_ard_3-2-1_104077_2023-08-15_final.stac-item
2023-10-15 11:53:26	ga_ls9c_ard_3-2-1_115080_2023-10-15_final.stac-item
2023-10-16 09:19:44	ga_ls9c_ard_3-2-1_090082_2023-10-15_final.stac-item
2023-10-21 09:38:41	ga_ls9c_ard_3-2-1_093083_2023-10-21_final.stac-item
2023-10-22 10:18:21	ga_ls9c_ard_3-2-1_100074_2023-10-22_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-14 10:24:27	ga_ls9c_ard_3-2-1_101074_2023-11-14_final.stac-item
2023-11-16 10:12:06	ga_ls9c_ard_3-2-1_099074_2023-11-16_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