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 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-10 09:39:05	ga_ls9c_ard_3-2-1_094076_2021-11-10_final.stac-item
2021-11-25 09:46:28	ga_ls9c_ard_3-2-1_095076_2021-11-25_final.stac-item
2021-12-09 11:21:04	ga_ls9c_ard_3-2-1_110076_2021-12-09_final.stac-item
2021-12-11 09:29:48	ga_ls9c_ard_3-2-1_092076_2021-12-10_final.stac-item
2021-12-25 09:42:07	ga_ls9c_ard_3-2-1_094076_2021-12-25_final.stac-item
2021-12-27 09:29:45	ga_ls9c_ard_3-2-1_092076_2021-12-26_final.stac-item
2022-01-01 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-01-01_final.stac-item
2022-01-03 11:14:48	ga_ls9c_ard_3-2-1_109076_2022-01-03_final.stac-item
2022-01-04 11:58:04	ga_ls9c_ard_3-2-1_116076_2022-01-04_final.stac-item
2022-01-10 11:20:57	ga_ls9c_ard_3-2-1_110076_2022-01-10_final.stac-item
2022-01-17 11:27:08	ga_ls9c_ard_3-2-1_111076_2022-01-17_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-01-20 11:58:03	ga_ls9c_ard_3-2-1_116076_2022-01-20_final.stac-item
2022-01-26 09:42:06	ga_ls9c_ard_3-2-1_094076_2022-01-26_final.stac-item
2022-01-26 11:20:59	ga_ls9c_ard_3-2-1_110076_2022-01-26_final.stac-item
2022-01-28 09:29:44	ga_ls9c_ard_3-2-1_092076_2022-01-27_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-02-04 11:14:47	ga_ls9c_ard_3-2-1_109076_2022-02-04_final.stac-item
2022-02-05 11:58:03	ga_ls9c_ard_3-2-1_116076_2022-02-05_final.stac-item
2022-02-18 11:27:03	ga_ls9c_ard_3-2-1_111076_2022-02-18_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-02-20 11:14:40	ga_ls9c_ard_3-2-1_109076_2022-02-20_final.stac-item
2022-02-21 11:57:55	ga_ls9c_ard_3-2-1_116076_2022-02-21_final.stac-item
2022-02-27 09:41:53	ga_ls9c_ard_3-2-1_094076_2022-02-27_final.stac-item
2022-03-08 11:14:33	ga_ls9c_ard_3-2-1_109076_2022-03-08_final.stac-item
2022-03-09 11:57:49	ga_ls9c_ard_3-2-1_116076_2022-03-09_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-03-24 11:14:29	ga_ls9c_ard_3-2-1_109076_2022-03-24_final.stac-item
2022-03-25 11:57:45	ga_ls9c_ard_3-2-1_116076_2022-03-25_final.stac-item
2022-03-31 11:20:39	ga_ls9c_ard_3-2-1_110076_2022-03-31_final.stac-item
2022-04-07 11:26:48	ga_ls9c_ard_3-2-1_111076_2022-04-07_final.stac-item
2022-04-09 09:35:33	ga_ls9c_ard_3-2-1_093076_2022-04-09_final.stac-item
2022-04-10 11:57:41	ga_ls9c_ard_3-2-1_116076_2022-04-10_final.stac-item
2022-04-16 09:41:39	ga_ls9c_ard_3-2-1_094076_2022-04-16_final.stac-item
2022-04-23 11:26:38	ga_ls9c_ard_3-2-1_111076_2022-04-23_final.stac-item
2022-04-25 09:35:24	ga_ls9c_ard_3-2-1_093076_2022-04-25_final.stac-item
2022-04-25 11:14:17	ga_ls9c_ard_3-2-1_109076_2022-04-25_final.stac-item
2022-04-26 11:57:32	ga_ls9c_ard_3-2-1_116076_2022-04-26_final.stac-item
2022-05-09 11:26:33	ga_ls9c_ard_3-2-1_111076_2022-05-09_final.stac-item
2022-05-11 09:35:17	ga_ls9c_ard_3-2-1_093076_2022-05-11_final.stac-item
2022-05-11 11:14:10	ga_ls9c_ard_3-2-1_109076_2022-05-11_final.stac-item
2022-05-12 11:57:25	ga_ls9c_ard_3-2-1_116076_2022-05-12_final.stac-item
2022-05-18 09:41:22	ga_ls9c_ard_3-2-1_094076_2022-05-18_final.stac-item
2022-05-18 11:20:15	ga_ls9c_ard_3-2-1_110076_2022-05-18_final.stac-item
2022-05-27 11:14:02	ga_ls9c_ard_3-2-1_109076_2022-05-27_final.stac-item
2022-05-28 11:57:18	ga_ls9c_ard_3-2-1_116076_2022-05-28_final.stac-item
2022-06-03 09:41:21	ga_ls9c_ard_3-2-1_094076_2022-06-03_final.stac-item
2022-06-13 11:57:23	ga_ls9c_ard_3-2-1_116076_2022-06-13_final.stac-item
2022-06-19 09:41:31	ga_ls9c_ard_3-2-1_094076_2022-06-19_final.stac-item
2022-06-21 09:29:13	ga_ls9c_ard_3-2-1_092076_2022-06-20_final.stac-item
2022-06-28 09:35:31	ga_ls9c_ard_3-2-1_093076_2022-06-28_final.stac-item
2022-06-28 11:14:24	ga_ls9c_ard_3-2-1_109076_2022-06-28_final.stac-item
2022-06-29 11:57:40	ga_ls9c_ard_3-2-1_116076_2022-06-29_final.stac-item
2022-07-05 09:41:41	ga_ls9c_ard_3-2-1_094076_2022-07-05_final.stac-item
2022-07-05 11:20:34	ga_ls9c_ard_3-2-1_110076_2022-07-05_final.stac-item
2022-07-07 09:29:18	ga_ls9c_ard_3-2-1_092076_2022-07-06_final.stac-item
2022-07-15 11:57:35	ga_ls9c_ard_3-2-1_116076_2022-07-15_final.stac-item
2022-07-21 11:20:37	ga_ls9c_ard_3-2-1_110076_2022-07-21_final.stac-item
2022-07-23 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-07-22_final.stac-item
2022-07-31 11:57:50	ga_ls9c_ard_3-2-1_116076_2022-07-31_final.stac-item
2022-08-15 11:14:43	ga_ls9c_ard_3-2-1_109076_2022-08-15_final.stac-item
2022-08-16 11:57:59	ga_ls9c_ard_3-2-1_116076_2022-08-16_final.stac-item
2022-08-22 09:42:03	ga_ls9c_ard_3-2-1_094076_2022-08-22_final.stac-item
2022-08-31 11:14:46	ga_ls9c_ard_3-2-1_109076_2022-08-31_final.stac-item
2022-09-01 11:58:01	ga_ls9c_ard_3-2-1_116076_2022-09-01_final.stac-item
2022-09-07 11:20:55	ga_ls9c_ard_3-2-1_110076_2022-09-07_final.stac-item
2022-09-14 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-09-14_final.stac-item
2022-09-17 11:58:05	ga_ls9c_ard_3-2-1_116076_2022-09-17_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-03 11:58:09	ga_ls9c_ard_3-2-1_116076_2022-10-03_final.stac-item
2022-10-04 09:23:38	ga_ls9c_ard_3-2-1_091076_2022-10-03_final.stac-item
2022-10-11 09:29:52	ga_ls9c_ard_3-2-1_092076_2022-10-10_final.stac-item
2022-10-16 11:27:19	ga_ls9c_ard_3-2-1_111076_2022-10-16_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-20 09:23:44	ga_ls9c_ard_3-2-1_091076_2022-10-19_final.stac-item
2022-11-01 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-11-01_final.stac-item
2022-11-04 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-11-04_final.stac-item
2022-11-12 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-11-11_final.stac-item
2022-11-20 11:58:15	ga_ls9c_ard_3-2-1_116076_2022-11-20_final.stac-item
2022-11-21 09:23:45	ga_ls9c_ard_3-2-1_091076_2022-11-20_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-14 09:29:54	ga_ls9c_ard_3-2-1_092076_2022-12-13_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-23 09:23:40	ga_ls9c_ard_3-2-1_091076_2022-12-22_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-08 09:23:44	ga_ls9c_ard_3-2-1_091076_2023-01-07_final.stac-item
2023-01-23 11:58:07	ga_ls9c_ard_3-2-1_116076_2023-01-23_final.stac-item
2023-01-24 09:23:38	ga_ls9c_ard_3-2-1_091076_2023-01-23_final.stac-item
2023-02-08 11:58:18	ga_ls9c_ard_3-2-1_116076_2023-02-08_final.stac-item
2023-02-24 11:58:03	ga_ls9c_ard_3-2-1_116076_2023-02-24_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-28 11:57:46	ga_ls9c_ard_3-2-1_116076_2023-03-28_final.stac-item
2023-04-13 11:57:39	ga_ls9c_ard_3-2-1_116076_2023-04-13_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-05-15 11:57:24	ga_ls9c_ard_3-2-1_116076_2023-05-15_final.stac-item
2023-05-31 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-05-31_final.stac-item
2023-06-16 11:57:06	ga_ls9c_ard_3-2-1_116076_2023-06-16_final.stac-item
2023-07-02 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-07-02_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