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
2021-11-16 10:24:42	ga_ls9c_ard_3-2-1_100084_2021-11-16_final.stac-item
2021-11-19 09:06:51	ga_ls9c_ard_3-2-1_088083_2021-11-18_final.stac-item
2021-12-11 09:32:59	ga_ls9c_ard_3-2-1_092084_2021-12-11_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-27 09:32:57	ga_ls9c_ard_3-2-1_092084_2021-12-27_final.stac-item
2021-12-31 09:07:49	ga_ls9c_ard_3-2-1_088083_2021-12-30_final.stac-item
2022-01-05 11:05:38	ga_ls9c_ard_3-2-1_107084_2022-01-05_final.stac-item
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-17 11:30:19	ga_ls9c_ard_3-2-1_111084_2022-01-17_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-02-01 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-01-31_final.stac-item
2022-02-02 11:30:21	ga_ls9c_ard_3-2-1_111084_2022-02-02_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-02-18 11:30:15	ga_ls9c_ard_3-2-1_111084_2022-02-18_final.stac-item
2022-02-22 09:26:36	ga_ls9c_ard_3-2-1_091084_2022-02-21_final.stac-item
2022-02-22 11:05:29	ga_ls9c_ard_3-2-1_107084_2022-02-22_final.stac-item
2022-03-01 09:32:41	ga_ls9c_ard_3-2-1_092084_2022-03-01_final.stac-item
2022-03-01 11:11:34	ga_ls9c_ard_3-2-1_108084_2022-03-01_final.stac-item
2022-03-05 09:07:33	ga_ls9c_ard_3-2-1_088083_2022-03-04_final.stac-item
2022-03-10 11:05:23	ga_ls9c_ard_3-2-1_107084_2022-03-10_final.stac-item
2022-03-21 09:07:31	ga_ls9c_ard_3-2-1_088083_2022-03-20_final.stac-item
2022-03-24 11:17:41	ga_ls9c_ard_3-2-1_109084_2022-03-24_final.stac-item
2022-03-29 11:36:12	ga_ls9c_ard_3-2-1_112084_2022-03-29_final.stac-item
2022-04-02 09:32:36	ga_ls9c_ard_3-2-1_092084_2022-04-02_final.stac-item
2022-04-02 11:11:29	ga_ls9c_ard_3-2-1_108084_2022-04-02_final.stac-item
2022-04-11 09:26:22	ga_ls9c_ard_3-2-1_091084_2022-04-10_final.stac-item
2022-04-11 11:05:15	ga_ls9c_ard_3-2-1_107084_2022-04-11_final.stac-item
2022-04-18 11:11:20	ga_ls9c_ard_3-2-1_108084_2022-04-18_final.stac-item
2022-04-22 09:07:17	ga_ls9c_ard_3-2-1_088083_2022-04-21_final.stac-item
2022-04-25 11:17:28	ga_ls9c_ard_3-2-1_109084_2022-04-25_final.stac-item
2022-04-29 09:13:28	ga_ls9c_ard_3-2-1_089083_2022-04-28_final.stac-item
2022-05-04 11:11:15	ga_ls9c_ard_3-2-1_108084_2022-05-04_final.stac-item
2022-05-13 09:26:06	ga_ls9c_ard_3-2-1_091084_2022-05-12_final.stac-item
2022-05-15 09:13:18	ga_ls9c_ard_3-2-1_089083_2022-05-14_final.stac-item
2022-05-20 09:32:09	ga_ls9c_ard_3-2-1_092084_2022-05-20_final.stac-item
2022-05-20 11:11:03	ga_ls9c_ard_3-2-1_108084_2022-05-20_final.stac-item
2022-05-24 09:07:02	ga_ls9c_ard_3-2-1_088083_2022-05-23_final.stac-item
2022-05-29 09:25:59	ga_ls9c_ard_3-2-1_091084_2022-05-28_final.stac-item
2022-06-05 09:32:11	ga_ls9c_ard_3-2-1_092084_2022-06-05_final.stac-item
2022-06-05 11:11:04	ga_ls9c_ard_3-2-1_108084_2022-06-05_final.stac-item
2022-06-21 09:32:25	ga_ls9c_ard_3-2-1_092084_2022-06-21_final.stac-item
2022-06-30 09:26:21	ga_ls9c_ard_3-2-1_091084_2022-06-29_final.stac-item
2022-07-07 11:11:23	ga_ls9c_ard_3-2-1_108084_2022-07-07_final.stac-item
2022-07-11 09:07:21	ga_ls9c_ard_3-2-1_088083_2022-07-10_final.stac-item
2022-07-23 11:11:29	ga_ls9c_ard_3-2-1_108084_2022-07-23_final.stac-item
2022-08-01 11:05:25	ga_ls9c_ard_3-2-1_107084_2022-08-01_final.stac-item
2022-08-12 09:07:42	ga_ls9c_ard_3-2-1_088083_2022-08-11_final.stac-item
2022-08-17 11:05:34	ga_ls9c_ard_3-2-1_107084_2022-08-17_final.stac-item
2022-08-24 09:32:53	ga_ls9c_ard_3-2-1_092084_2022-08-24_final.stac-item
2022-09-02 11:05:35	ga_ls9c_ard_3-2-1_107084_2022-09-02_final.stac-item
2022-09-09 09:32:52	ga_ls9c_ard_3-2-1_092084_2022-09-09_final.stac-item
2022-09-09 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-09-09_final.stac-item
2022-09-20 09:14:02	ga_ls9c_ard_3-2-1_089083_2022-09-19_final.stac-item
2022-09-25 11:11:53	ga_ls9c_ard_3-2-1_108084_2022-09-25_final.stac-item
2022-09-29 09:07:54	ga_ls9c_ard_3-2-1_088083_2022-09-28_final.stac-item
2022-10-04 11:05:43	ga_ls9c_ard_3-2-1_107084_2022-10-04_final.stac-item
2022-10-06 09:14:03	ga_ls9c_ard_3-2-1_089083_2022-10-05_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-11 11:11:56	ga_ls9c_ard_3-2-1_108084_2022-10-11_final.stac-item
2022-10-15 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-10-14_final.stac-item
2022-10-22 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-10-21_final.stac-item
2022-10-27 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-10-27_final.stac-item
2022-10-31 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-10-30_final.stac-item
2022-11-05 11:05:46	ga_ls9c_ard_3-2-1_107084_2022-11-05_final.stac-item
2022-11-28 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-11-28_final.stac-item
2022-11-28 11:11:58	ga_ls9c_ard_3-2-1_108084_2022-11-28_final.stac-item
2022-12-02 09:07:56	ga_ls9c_ard_3-2-1_088083_2022-12-01_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_final.stac-item
2022-12-09 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-12-08_final.stac-item
2022-12-14 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-14_final.stac-item
2022-12-18 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-12-17_final.stac-item
2022-12-23 11:05:45	ga_ls9c_ard_3-2-1_107084_2022-12-23_final.stac-item
2022-12-25 09:14:07	ga_ls9c_ard_3-2-1_089083_2022-12-24_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-10 09:14:09	ga_ls9c_ard_3-2-1_089083_2023-01-09_final.stac-item
2023-01-19 09:07:51	ga_ls9c_ard_3-2-1_088083_2023-01-18_final.stac-item
2023-01-24 11:05:42	ga_ls9c_ard_3-2-1_107084_2023-01-24_final.stac-item
2023-01-26 09:14:06	ga_ls9c_ard_3-2-1_089083_2023-01-25_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-02-09 11:05:52	ga_ls9c_ard_3-2-1_107084_2023-02-09_final.stac-item
2023-02-11 09:14:13	ga_ls9c_ard_3-2-1_089083_2023-02-10_final.stac-item
2023-02-16 11:11:59	ga_ls9c_ard_3-2-1_108084_2023-02-16_final.stac-item
2023-03-04 11:11:46	ga_ls9c_ard_3-2-1_108084_2023-03-04_final.stac-item
2023-03-13 11:05:30	ga_ls9c_ard_3-2-1_107084_2023-03-13_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_final.stac-item
2023-04-14 11:05:12	ga_ls9c_ard_3-2-1_107084_2023-04-14_final.stac-item
2023-04-16 09:13:34	ga_ls9c_ard_3-2-1_089083_2023-04-15_final.stac-item
2023-04-25 09:07:21	ga_ls9c_ard_3-2-1_088083_2023-04-24_final.stac-item
2023-04-30 11:05:06	ga_ls9c_ard_3-2-1_107084_2023-04-30_final.stac-item
2023-05-02 09:13:25	ga_ls9c_ard_3-2-1_089083_2023-05-01_final.stac-item
2023-05-11 09:07:11	ga_ls9c_ard_3-2-1_088083_2023-05-10_final.stac-item
2023-05-18 09:13:18	ga_ls9c_ard_3-2-1_089083_2023-05-17_final.stac-item
2023-05-27 09:07:00	ga_ls9c_ard_3-2-1_088083_2023-05-26_final.stac-item
2023-06-03 09:13:10	ga_ls9c_ard_3-2-1_089083_2023-06-02_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-06-19 09:13:02	ga_ls9c_ard_3-2-1_089083_2023-06-18_final.stac-item
2023-06-28 09:06:55	ga_ls9c_ard_3-2-1_088083_2023-06-27_final.stac-item
2023-07-05 09:13:14	ga_ls9c_ard_3-2-1_089083_2023-07-04_final.stac-item
2024-04-16 09:26:21	ga_ls9c_ard_3-2-1_091084_2024-04-15_final.stac-item
2024-04-23 09:32:18	ga_ls9c_ard_3-2-1_092084_2024-04-23_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