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
2021-11-25 09:47:16	ga_ls9c_ard_3-2-1_095078_2021-11-25_final.stac-item
2021-12-04 11:03:22	ga_ls9c_ard_3-2-1_107078_2021-12-04_final.stac-item
2021-12-09 09:42:59	ga_ls9c_ard_3-2-1_094078_2021-12-09_final.stac-item
2021-12-16 09:49:04	ga_ls9c_ard_3-2-1_095078_2021-12-16_final.stac-item
2021-12-25 09:42:54	ga_ls9c_ard_3-2-1_094078_2021-12-25_final.stac-item
2022-01-12 11:09:23	ga_ls9c_ard_3-2-1_108078_2022-01-12_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-01-21 11:03:13	ga_ls9c_ard_3-2-1_107078_2022-01-21_final.stac-item
2022-01-26 09:42:53	ga_ls9c_ard_3-2-1_094078_2022-01-26_final.stac-item
2022-01-30 10:57:03	ga_ls9c_ard_3-2-1_106078_2022-01-30_final.stac-item
2022-02-11 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-02-11_final.stac-item
2022-02-13 11:09:21	ga_ls9c_ard_3-2-1_108078_2022-02-13_final.stac-item
2022-02-15 10:56:59	ga_ls9c_ard_3-2-1_106078_2022-02-15_final.stac-item
2022-02-18 09:48:58	ga_ls9c_ard_3-2-1_095078_2022-02-18_final.stac-item
2022-03-01 11:09:10	ga_ls9c_ard_3-2-1_108078_2022-03-01_final.stac-item
2022-03-19 10:56:47	ga_ls9c_ard_3-2-1_106078_2022-03-19_final.stac-item
2022-03-22 09:48:47	ga_ls9c_ard_3-2-1_095078_2022-03-22_final.stac-item
2022-03-26 11:02:55	ga_ls9c_ard_3-2-1_107078_2022-03-26_final.stac-item
2022-04-04 10:56:43	ga_ls9c_ard_3-2-1_106078_2022-04-04_final.stac-item
2022-04-07 09:48:43	ga_ls9c_ard_3-2-1_095078_2022-04-07_final.stac-item
2022-04-18 11:08:57	ga_ls9c_ard_3-2-1_108078_2022-04-18_final.stac-item
2022-04-23 09:48:33	ga_ls9c_ard_3-2-1_095078_2022-04-23_final.stac-item
2022-05-02 09:42:21	ga_ls9c_ard_3-2-1_094078_2022-05-02_final.stac-item
2022-05-09 09:48:28	ga_ls9c_ard_3-2-1_095078_2022-05-09_final.stac-item
2022-05-13 11:02:35	ga_ls9c_ard_3-2-1_107078_2022-05-13_final.stac-item
2022-05-18 09:42:10	ga_ls9c_ard_3-2-1_094078_2022-05-18_final.stac-item
2022-06-03 09:42:09	ga_ls9c_ard_3-2-1_094078_2022-06-03_final.stac-item
2022-06-05 11:08:40	ga_ls9c_ard_3-2-1_108078_2022-06-05_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-19 09:42:19	ga_ls9c_ard_3-2-1_094078_2022-06-19_final.stac-item
2022-06-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2022-06-23_final.stac-item
2022-06-26 09:48:41	ga_ls9c_ard_3-2-1_095078_2022-06-26_final.stac-item
2022-07-05 09:42:29	ga_ls9c_ard_3-2-1_094078_2022-07-05_final.stac-item
2022-07-07 11:08:59	ga_ls9c_ard_3-2-1_108078_2022-07-07_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 09:48:37	ga_ls9c_ard_3-2-1_095078_2022-07-12_final.stac-item
2022-07-21 09:42:32	ga_ls9c_ard_3-2-1_094078_2022-07-21_final.stac-item
2022-07-25 10:56:45	ga_ls9c_ard_3-2-1_106078_2022-07-25_final.stac-item
2022-07-28 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-07-28_final.stac-item
2022-08-10 10:56:56	ga_ls9c_ard_3-2-1_106078_2022-08-10_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_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 09:49:02	ga_ls9c_ard_3-2-1_095078_2022-08-29_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-09-23 09:42:58	ga_ls9c_ard_3-2-1_094078_2022-09-23_final.stac-item
2022-09-25 11:09:30	ga_ls9c_ard_3-2-1_108078_2022-09-25_final.stac-item
2022-09-27 10:57:08	ga_ls9c_ard_3-2-1_106078_2022-09-27_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-10-04 11:03:19	ga_ls9c_ard_3-2-1_107078_2022-10-04_final.stac-item
2022-10-13 10:57:12	ga_ls9c_ard_3-2-1_106078_2022-10-13_final.stac-item
2022-10-16 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-10-16_final.stac-item
2022-10-20 11:03:25	ga_ls9c_ard_3-2-1_107078_2022-10-20_final.stac-item
2022-10-29 10:57:13	ga_ls9c_ard_3-2-1_106078_2022-10-29_final.stac-item
2022-11-10 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-11-10_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-21 11:03:26	ga_ls9c_ard_3-2-1_107078_2022-11-21_final.stac-item
2022-12-03 09:49:13	ga_ls9c_ard_3-2-1_095078_2022-12-03_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_nrt.stac-item
2022-12-07 11:03:24	ga_ls9c_ard_3-2-1_107078_2022-12-07_nrt.stac-item
2022-12-12 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-12-12_final.stac-item
2022-12-16 10:57:13	ga_ls9c_ard_3-2-1_106078_2022-12-16_final.stac-item
2022-12-19 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-12-19_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-02 10:57:15	ga_ls9c_ard_3-2-1_106078_2023-02-02_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-02-16 11:09:35	ga_ls9c_ard_3-2-1_108078_2023-02-16_final.stac-item
2023-02-18 10:57:11	ga_ls9c_ard_3-2-1_106078_2023-02-18_final.stac-item
2023-02-25 11:03:14	ga_ls9c_ard_3-2-1_107078_2023-02-25_final.stac-item
2023-03-04 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-03-04_final.stac-item
2023-03-13 11:03:07	ga_ls9c_ard_3-2-1_107078_2023-03-13_final.stac-item
2023-03-18 09:42:45	ga_ls9c_ard_3-2-1_094078_2023-03-18_final.stac-item
2023-03-20 11:09:16	ga_ls9c_ard_3-2-1_108078_2023-03-20_final.stac-item
2023-03-22 10:56:53	ga_ls9c_ard_3-2-1_106078_2023-03-22_final.stac-item
2023-04-03 09:42:34	ga_ls9c_ard_3-2-1_094078_2023-04-03_final.stac-item
2023-04-07 10:56:43	ga_ls9c_ard_3-2-1_106078_2023-04-07_final.stac-item
2023-04-10 09:48:42	ga_ls9c_ard_3-2-1_095078_2023-04-10_final.stac-item
2023-04-14 11:02:49	ga_ls9c_ard_3-2-1_107078_2023-04-14_final.stac-item
2023-04-19 09:42:28	ga_ls9c_ard_3-2-1_094078_2023-04-19_final.stac-item
2023-04-21 11:08:59	ga_ls9c_ard_3-2-1_108078_2023-04-21_final.stac-item
2023-04-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2023-04-23_final.stac-item
2023-04-26 09:48:36	ga_ls9c_ard_3-2-1_095078_2023-04-26_final.stac-item
2023-04-30 11:02:42	ga_ls9c_ard_3-2-1_107078_2023-04-30_final.stac-item
2023-05-07 11:08:47	ga_ls9c_ard_3-2-1_108078_2023-05-07_final.stac-item
2023-05-09 10:56:26	ga_ls9c_ard_3-2-1_106078_2023-05-09_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_2023-05-12_final.stac-item
2023-05-16 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-05-16_final.stac-item
2023-05-21 09:42:09	ga_ls9c_ard_3-2-1_094078_2023-05-21_final.stac-item
2023-05-23 11:08:38	ga_ls9c_ard_3-2-1_108078_2023-05-23_final.stac-item
2023-05-25 10:56:15	ga_ls9c_ard_3-2-1_106078_2023-05-25_final.stac-item
2023-05-28 09:48:16	ga_ls9c_ard_3-2-1_095078_2023-05-28_final.stac-item
2023-06-01 11:02:26	ga_ls9c_ard_3-2-1_107078_2023-06-01_final.stac-item
2023-06-13 09:48:09	ga_ls9c_ard_3-2-1_095078_2023-06-13_final.stac-item
2023-06-22 09:41:57	ga_ls9c_ard_3-2-1_094078_2023-06-22_final.stac-item
2023-06-24 11:08:28	ga_ls9c_ard_3-2-1_108078_2023-06-24_final.stac-item
2023-06-26 10:56:06	ga_ls9c_ard_3-2-1_106078_2023-06-26_final.stac-item
2023-06-29 09:48:13	ga_ls9c_ard_3-2-1_095078_2023-06-29_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years