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 09:56:09	ga_ls9c_ard_3-2-1_096078_2021-11-03_final.stac-item
2021-11-08 09:58:38	ga_ls9c_ard_3-2-1_097078_2021-11-08_final.stac-item
2021-11-25 09:47:16	ga_ls9c_ard_3-2-1_095078_2021-11-25_final.stac-item
2021-12-07 09:55:21	ga_ls9c_ard_3-2-1_096078_2021-12-07_final.stac-item
2021-12-16 09:49:04	ga_ls9c_ard_3-2-1_095078_2021-12-16_final.stac-item
2021-12-23 09:55:16	ga_ls9c_ard_3-2-1_096078_2021-12-23_final.stac-item
2022-01-04 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-01-04_final.stac-item
2022-01-08 09:55:14	ga_ls9c_ard_3-2-1_096078_2022-01-08_final.stac-item
2022-01-11 10:26:07	ga_ls9c_ard_3-2-1_101078_2022-01-11_final.stac-item
2022-01-15 10:01:24	ga_ls9c_ard_3-2-1_097078_2022-01-15_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-01-20 10:19:57	ga_ls9c_ard_3-2-1_100078_2022-01-20_final.stac-item
2022-01-31 10:01:26	ga_ls9c_ard_3-2-1_097078_2022-01-31_final.stac-item
2022-02-05 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-02-05_final.stac-item
2022-02-12 10:26:06	ga_ls9c_ard_3-2-1_101078_2022-02-12_final.stac-item
2022-02-16 10:01:21	ga_ls9c_ard_3-2-1_097078_2022-02-16_final.stac-item
2022-02-18 09:48:58	ga_ls9c_ard_3-2-1_095078_2022-02-18_final.stac-item
2022-02-28 10:25:55	ga_ls9c_ard_3-2-1_101078_2022-02-28_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_2022-03-09_final.stac-item
2022-03-22 09:48:47	ga_ls9c_ard_3-2-1_095078_2022-03-22_final.stac-item
2022-03-29 09:54:55	ga_ls9c_ard_3-2-1_096078_2022-03-29_final.stac-item
2022-04-07 09:48:43	ga_ls9c_ard_3-2-1_095078_2022-04-07_final.stac-item
2022-04-10 10:19:36	ga_ls9c_ard_3-2-1_100078_2022-04-10_final.stac-item
2022-04-14 09:54:50	ga_ls9c_ard_3-2-1_096078_2022-04-14_final.stac-item
2022-04-23 09:48:33	ga_ls9c_ard_3-2-1_095078_2022-04-23_final.stac-item
2022-04-26 10:19:27	ga_ls9c_ard_3-2-1_100078_2022-04-26_final.stac-item
2022-05-09 09:48:28	ga_ls9c_ard_3-2-1_095078_2022-05-09_final.stac-item
2022-05-12 10:19:20	ga_ls9c_ard_3-2-1_100078_2022-05-12_final.stac-item
2022-05-16 09:54:33	ga_ls9c_ard_3-2-1_096078_2022-05-16_final.stac-item
2022-05-23 10:00:40	ga_ls9c_ard_3-2-1_097078_2022-05-23_final.stac-item
2022-05-28 10:19:12	ga_ls9c_ard_3-2-1_100078_2022-05-28_final.stac-item
2022-06-04 10:25:25	ga_ls9c_ard_3-2-1_101078_2022-06-04_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-13 10:19:17	ga_ls9c_ard_3-2-1_100078_2022-06-13_final.stac-item
2022-06-17 09:54:37	ga_ls9c_ard_3-2-1_096078_2022-06-17_final.stac-item
2022-06-26 09:48:41	ga_ls9c_ard_3-2-1_095078_2022-06-26_final.stac-item
2022-07-03 09:54:51	ga_ls9c_ard_3-2-1_096078_2022-07-03_final.stac-item
2022-07-06 10:25:44	ga_ls9c_ard_3-2-1_101078_2022-07-06_final.stac-item
2022-07-10 10:00:59	ga_ls9c_ard_3-2-1_097078_2022-07-10_final.stac-item
2022-07-12 09:48:37	ga_ls9c_ard_3-2-1_095078_2022-07-12_final.stac-item
2022-07-19 09:54:51	ga_ls9c_ard_3-2-1_096078_2022-07-19_final.stac-item
2022-07-26 10:01:09	ga_ls9c_ard_3-2-1_097078_2022-07-26_final.stac-item
2022-07-28 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-07-28_final.stac-item
2022-07-31 10:19:45	ga_ls9c_ard_3-2-1_100078_2022-07-31_final.stac-item
2022-08-11 10:01:19	ga_ls9c_ard_3-2-1_097078_2022-08-11_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_final.stac-item
2022-08-29 09:49:02	ga_ls9c_ard_3-2-1_095078_2022-08-29_final.stac-item
2022-09-08 10:26:06	ga_ls9c_ard_3-2-1_101078_2022-09-08_final.stac-item
2022-09-12 10:01:25	ga_ls9c_ard_3-2-1_097078_2022-09-12_final.stac-item
2022-09-17 10:20:00	ga_ls9c_ard_3-2-1_100078_2022-09-17_final.stac-item
2022-09-24 10:26:14	ga_ls9c_ard_3-2-1_101078_2022-09-24_final.stac-item
2022-09-28 10:01:31	ga_ls9c_ard_3-2-1_097078_2022-09-28_final.stac-item
2022-10-10 10:26:16	ga_ls9c_ard_3-2-1_101078_2022-10-10_final.stac-item
2022-10-14 10:01:35	ga_ls9c_ard_3-2-1_097078_2022-10-14_final.stac-item
2022-10-19 10:20:09	ga_ls9c_ard_3-2-1_100078_2022-10-19_final.stac-item
2022-10-23 09:55:26	ga_ls9c_ard_3-2-1_096078_2022-10-23_final.stac-item
2022-10-26 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-10-26_final.stac-item
2022-10-30 10:01:36	ga_ls9c_ard_3-2-1_097078_2022-10-30_final.stac-item
2022-11-11 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-11-11_final.stac-item
2022-11-27 10:26:19	ga_ls9c_ard_3-2-1_101078_2022-11-27_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_nrt.stac-item
2022-12-13 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-12-13_final.stac-item
2022-12-17 10:01:36	ga_ls9c_ard_3-2-1_097078_2022-12-17_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-29 10:26:19	ga_ls9c_ard_3-2-1_101078_2022-12-29_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-14 10:26:17	ga_ls9c_ard_3-2-1_101078_2023-01-14_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-23 10:20:02	ga_ls9c_ard_3-2-1_100078_2023-01-23_final.stac-item
2023-01-27 09:55:23	ga_ls9c_ard_3-2-1_096078_2023-01-27_final.stac-item
2023-01-30 10:26:19	ga_ls9c_ard_3-2-1_101078_2023-01-30_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-08 10:20:13	ga_ls9c_ard_3-2-1_100078_2023-02-08_final.stac-item
2023-02-19 10:01:33	ga_ls9c_ard_3-2-1_097078_2023-02-19_final.stac-item
2023-03-03 10:26:07	ga_ls9c_ard_3-2-1_101078_2023-03-03_final.stac-item
2023-03-07 10:01:21	ga_ls9c_ard_3-2-1_097078_2023-03-07_final.stac-item
2023-03-16 09:55:08	ga_ls9c_ard_3-2-1_096078_2023-03-16_final.stac-item
2023-03-18 09:42:45	ga_ls9c_ard_3-2-1_094078_2023-03-18_final.stac-item
2023-03-19 10:26:01	ga_ls9c_ard_3-2-1_101078_2023-03-19_final.stac-item
2023-03-23 10:01:15	ga_ls9c_ard_3-2-1_097078_2023-03-23_final.stac-item
2023-04-01 09:54:56	ga_ls9c_ard_3-2-1_096078_2023-04-01_final.stac-item
2023-04-04 10:25:50	ga_ls9c_ard_3-2-1_101078_2023-04-04_final.stac-item
2023-04-10 09:48:42	ga_ls9c_ard_3-2-1_095078_2023-04-10_final.stac-item
2023-04-13 10:19:34	ga_ls9c_ard_3-2-1_100078_2023-04-13_final.stac-item
2023-04-17 09:54:50	ga_ls9c_ard_3-2-1_096078_2023-04-17_final.stac-item
2023-04-19 09:42:28	ga_ls9c_ard_3-2-1_094078_2023-04-19_final.stac-item
2023-04-20 10:25:44	ga_ls9c_ard_3-2-1_101078_2023-04-20_final.stac-item
2023-04-26 09:48:36	ga_ls9c_ard_3-2-1_095078_2023-04-26_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-05-06 10:25:32	ga_ls9c_ard_3-2-1_101078_2023-05-06_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_2023-05-12_final.stac-item
2023-05-15 10:19:19	ga_ls9c_ard_3-2-1_100078_2023-05-15_final.stac-item
2023-05-21 09:42:09	ga_ls9c_ard_3-2-1_094078_2023-05-21_final.stac-item
2023-05-22 10:25:24	ga_ls9c_ard_3-2-1_101078_2023-05-22_final.stac-item
2023-05-28 09:48:16	ga_ls9c_ard_3-2-1_095078_2023-05-28_final.stac-item
2023-06-16 10:19:01	ga_ls9c_ard_3-2-1_100078_2023-06-16_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 10:25:12	ga_ls9c_ard_3-2-1_101078_2023-06-23_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