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
2021-11-15 09:42:21	ga_ls9c_ard_3-2-1_094078_2021-11-15_final.stac-item
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-12-18 09:38:18	ga_ls9c_ard_3-2-1_093082_2021-12-18_final.stac-item
2021-12-25 09:42:54	ga_ls9c_ard_3-2-1_094078_2021-12-25_final.stac-item
2022-01-04 10:21:10	ga_ls9c_ard_3-2-1_100081_2022-01-04_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_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 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-03-06_final.stac-item
2022-03-22 09:49:35	ga_ls9c_ard_3-2-1_095080_2022-03-22_final.stac-item
2022-04-16 09:42:27	ga_ls9c_ard_3-2-1_094078_2022-04-16_final.stac-item
2022-04-16 11:21:44	ga_ls9c_ard_3-2-1_110079_2022-04-16_final.stac-item
2022-04-21 09:59:43	ga_ls9c_ard_3-2-1_097075_2022-04-21_final.stac-item
2022-05-04 09:31:58	ga_ls9c_ard_3-2-1_092083_2022-05-04_final.stac-item
2022-05-17 10:38:36	ga_ls9c_ard_3-2-1_103080_2022-05-17_final.stac-item
2022-06-07 10:56:19	ga_ls9c_ard_3-2-1_106078_2022-06-07_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-16 10:49:50	ga_ls9c_ard_3-2-1_105077_2022-06-16_final.stac-item
2022-06-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2022-06-23_final.stac-item
2022-06-24 09:59:50	ga_ls9c_ard_3-2-1_097075_2022-06-24_final.stac-item
2022-06-26 09:49:05	ga_ls9c_ard_3-2-1_095079_2022-06-26_final.stac-item
2022-07-02 10:50:04	ga_ls9c_ard_3-2-1_105077_2022-07-02_final.stac-item
2022-07-04 10:34:55	ga_ls9c_ard_3-2-1_103070_2022-07-04_final.stac-item
2022-07-09 10:56:37	ga_ls9c_ard_3-2-1_106078_2022-07-09_final.stac-item
2022-07-12 09:49:01	ga_ls9c_ard_3-2-1_095079_2022-07-12_final.stac-item
2022-07-19 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-19_final.stac-item
2022-07-25 10:56:45	ga_ls9c_ard_3-2-1_106078_2022-07-25_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-15 11:16:19	ga_ls9c_ard_3-2-1_109080_2022-08-15_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-21 10:37:16	ga_ls9c_ard_3-2-1_103075_2022-08-21_final.stac-item
2022-08-21 10:39:16	ga_ls9c_ard_3-2-1_103080_2022-08-21_final.stac-item
2022-08-22 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-08-22_final.stac-item
2022-08-29 11:27:55	ga_ls9c_ard_3-2-1_111078_2022-08-29_final.stac-item
2022-08-31 11:16:21	ga_ls9c_ard_3-2-1_109080_2022-08-31_final.stac-item
2022-09-23 11:21:51	ga_ls9c_ard_3-2-1_110078_2022-09-23_final.stac-item
2022-09-29 10:45:59	ga_ls9c_ard_3-2-1_104081_2022-09-29_final.stac-item
2022-09-30 09:49:33	ga_ls9c_ard_3-2-1_095079_2022-09-30_final.stac-item
2022-10-07 09:54:32	ga_ls9c_ard_3-2-1_096076_2022-10-07_final.stac-item
2022-10-07 11:35:00	ga_ls9c_ard_3-2-1_112080_2022-10-07_final.stac-item
2022-10-10 10:27:04	ga_ls9c_ard_3-2-1_101080_2022-10-10_final.stac-item
2022-10-11 11:09:09	ga_ls9c_ard_3-2-1_108077_2022-10-11_final.stac-item
2022-10-14 10:00:23	ga_ls9c_ard_3-2-1_097075_2022-10-14_final.stac-item
2022-10-15 10:45:15	ga_ls9c_ard_3-2-1_104079_2022-10-15_final.stac-item
2022-10-16 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-10-16_final.stac-item
2022-10-25 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-10-25_final.stac-item
2022-11-05 09:27:17	ga_ls9c_ard_3-2-1_091085_2022-11-04_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-11-17 09:52:04	ga_ls9c_ard_3-2-1_095085_2022-11-17_final.stac-item
2022-12-02 10:46:01	ga_ls9c_ard_3-2-1_104081_2022-12-02_final.stac-item
2022-12-09 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-12-09_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-03-02 09:42:52	ga_ls9c_ard_3-2-1_094078_2023-03-02_final.stac-item
2023-03-07 10:02:56	ga_ls9c_ard_3-2-1_097082_2023-03-07_final.stac-item
2023-03-08 10:45:47	ga_ls9c_ard_3-2-1_104081_2023-03-08_final.stac-item
2023-03-09 11:27:49	ga_ls9c_ard_3-2-1_111078_2023-03-09_final.stac-item
2023-03-11 09:38:10	ga_ls9c_ard_3-2-1_093082_2023-03-11_final.stac-item
2023-03-25 09:49:15	ga_ls9c_ard_3-2-1_095079_2023-03-25_final.stac-item
2023-03-25 09:49:39	ga_ls9c_ard_3-2-1_095080_2023-03-25_final.stac-item
2023-03-27 11:14:56	ga_ls9c_ard_3-2-1_109077_2023-03-27_final.stac-item
2023-04-01 09:54:32	ga_ls9c_ard_3-2-1_096077_2023-04-01_final.stac-item
2023-04-22 11:50:39	ga_ls9c_ard_3-2-1_115074_2023-04-22_final.stac-item
2023-04-24 10:02:35	ga_ls9c_ard_3-2-1_097082_2023-04-24_final.stac-item
2023-04-26 09:49:00	ga_ls9c_ard_3-2-1_095079_2023-04-26_final.stac-item
2023-04-26 09:49:24	ga_ls9c_ard_3-2-1_095080_2023-04-26_final.stac-item
2023-04-28 11:15:30	ga_ls9c_ard_3-2-1_109079_2023-04-28_final.stac-item
2023-05-05 09:42:16	ga_ls9c_ard_3-2-1_094078_2023-05-05_final.stac-item
2023-05-05 11:21:33	ga_ls9c_ard_3-2-1_110079_2023-05-05_final.stac-item
2023-05-09 10:56:26	ga_ls9c_ard_3-2-1_106078_2023-05-09_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-11 10:44:04	ga_ls9c_ard_3-2-1_104078_2023-05-11_final.stac-item
2023-05-12 09:48:02	ga_ls9c_ard_3-2-1_095077_2023-05-12_final.stac-item
2023-05-12 09:49:14	ga_ls9c_ard_3-2-1_095080_2023-05-12_final.stac-item
2023-05-12 09:49:38	ga_ls9c_ard_3-2-1_095081_2023-05-12_final.stac-item
2023-05-14 09:36:28	ga_ls9c_ard_3-2-1_093079_2023-05-14_final.stac-item
2023-05-19 11:34:14	ga_ls9c_ard_3-2-1_112080_2023-05-19_final.stac-item
2023-05-21 11:21:02	ga_ls9c_ard_3-2-1_110078_2023-05-21_final.stac-item
2023-05-28 09:48:40	ga_ls9c_ard_3-2-1_095079_2023-05-28_final.stac-item
2023-05-30 09:36:19	ga_ls9c_ard_3-2-1_093079_2023-05-30_final.stac-item
2023-06-18 10:08:15	ga_ls9c_ard_3-2-1_098082_2023-06-18_final.stac-item
2023-06-22 11:20:50	ga_ls9c_ard_3-2-1_110078_2023-06-22_final.stac-item
2023-07-06 11:33:00	ga_ls9c_ard_3-2-1_112077_2023-07-06_final.stac-item
2023-07-17 11:14:56	ga_ls9c_ard_3-2-1_109078_2023-07-17_final.stac-item
2023-07-17 11:15:20	ga_ls9c_ard_3-2-1_109079_2023-07-17_final.stac-item
2023-07-19 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-07-19_final.stac-item
2023-07-22 09:56:10	ga_ls9c_ard_3-2-1_096082_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
2023-07-28 09:20:43	ga_ls9c_ard_3-2-1_090086_2023-07-27_final.stac-item
2023-08-06 10:49:57	ga_ls9c_ard_3-2-1_105077_2023-08-06_final.stac-item
2023-08-09 09:42:47	ga_ls9c_ard_3-2-1_094079_2023-08-09_final.stac-item
2023-10-17 10:00:12	ga_ls9c_ard_3-2-1_097075_2023-10-17_final.stac-item
2023-10-19 11:28:20	ga_ls9c_ard_3-2-1_111079_2023-10-19_final.stac-item
2023-10-28 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-28_final.stac-item
2023-10-29 10:26:52	ga_ls9c_ard_3-2-1_101080_2023-10-29_final.stac-item
2023-11-01 10:58:07	ga_ls9c_ard_3-2-1_106081_2023-11-01_final.stac-item
2023-11-03 10:45:44	ga_ls9c_ard_3-2-1_104081_2023-11-03_final.stac-item
2023-11-19 10:45:50	ga_ls9c_ard_3-2-1_104081_2023-11-19_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