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
2021-10-31 11:15:11	ga_ls9c_ard_3-2-1_109082_2021-10-31_final.stac-item
2021-11-05 11:17:40	ga_ls9c_ard_3-2-1_109082_2021-11-05_final.stac-item
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2021-12-16 11:25:58	ga_ls9c_ard_3-2-1_111073_2021-12-16_final.stac-item
2021-12-18 11:17:11	ga_ls9c_ard_3-2-1_109082_2021-12-18_final.stac-item
2022-01-01 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-01-01_final.stac-item
2022-01-03 11:17:12	ga_ls9c_ard_3-2-1_109082_2022-01-03_final.stac-item
2022-01-19 11:17:10	ga_ls9c_ard_3-2-1_109082_2022-01-19_final.stac-item
2022-02-02 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-02-02_final.stac-item
2022-02-04 11:17:11	ga_ls9c_ard_3-2-1_109082_2022-02-04_final.stac-item
2022-02-11 11:20:56	ga_ls9c_ard_3-2-1_110076_2022-02-11_final.stac-item
2022-02-18 11:25:51	ga_ls9c_ard_3-2-1_111073_2022-02-18_final.stac-item
2022-02-20 11:17:04	ga_ls9c_ard_3-2-1_109082_2022-02-20_final.stac-item
2022-02-27 11:20:46	ga_ls9c_ard_3-2-1_110076_2022-02-27_final.stac-item
2022-03-06 11:25:43	ga_ls9c_ard_3-2-1_111073_2022-03-06_final.stac-item
2022-03-08 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-03-08_final.stac-item
2022-03-22 11:25:40	ga_ls9c_ard_3-2-1_111073_2022-03-22_final.stac-item
2022-03-24 11:16:53	ga_ls9c_ard_3-2-1_109082_2022-03-24_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 11:25:13	ga_ls9c_ard_3-2-1_111072_2022-04-07_final.stac-item
2022-04-07 11:25:37	ga_ls9c_ard_3-2-1_111073_2022-04-07_final.stac-item
2022-04-09 11:16:50	ga_ls9c_ard_3-2-1_109082_2022-04-09_final.stac-item
2022-04-16 11:20:32	ga_ls9c_ard_3-2-1_110076_2022-04-16_final.stac-item
2022-04-23 11:25:26	ga_ls9c_ard_3-2-1_111073_2022-04-23_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-02 11:20:26	ga_ls9c_ard_3-2-1_110076_2022-05-02_final.stac-item
2022-05-09 11:25:21	ga_ls9c_ard_3-2-1_111073_2022-05-09_final.stac-item
2022-05-11 11:16:34	ga_ls9c_ard_3-2-1_109082_2022-05-11_final.stac-item
2022-05-25 11:24:48	ga_ls9c_ard_3-2-1_111072_2022-05-25_final.stac-item
2022-05-25 11:25:12	ga_ls9c_ard_3-2-1_111073_2022-05-25_final.stac-item
2022-05-27 11:16:25	ga_ls9c_ard_3-2-1_109082_2022-05-27_final.stac-item
2022-06-03 11:20:14	ga_ls9c_ard_3-2-1_110076_2022-06-03_final.stac-item
2022-06-10 11:24:50	ga_ls9c_ard_3-2-1_111072_2022-06-10_final.stac-item
2022-06-12 11:16:30	ga_ls9c_ard_3-2-1_109082_2022-06-12_final.stac-item
2022-06-19 11:20:24	ga_ls9c_ard_3-2-1_110076_2022-06-19_final.stac-item
2022-06-26 11:25:10	ga_ls9c_ard_3-2-1_111072_2022-06-26_final.stac-item
2022-06-28 11:16:48	ga_ls9c_ard_3-2-1_109082_2022-06-28_final.stac-item
2022-07-12 11:25:30	ga_ls9c_ard_3-2-1_111073_2022-07-12_final.stac-item
2022-07-14 11:16:43	ga_ls9c_ard_3-2-1_109082_2022-07-14_final.stac-item
2022-07-30 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-07-30_final.stac-item
2022-08-13 11:25:28	ga_ls9c_ard_3-2-1_111072_2022-08-13_final.stac-item
2022-08-15 11:17:07	ga_ls9c_ard_3-2-1_109082_2022-08-15_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-23 11:21:03	ga_ls9c_ard_3-2-1_110076_2022-09-23_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-02 11:17:17	ga_ls9c_ard_3-2-1_109082_2022-10-02_final.stac-item
2022-10-09 11:21:05	ga_ls9c_ard_3-2-1_110076_2022-10-09_final.stac-item
2022-10-16 11:25:44	ga_ls9c_ard_3-2-1_111072_2022-10-16_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-11-01 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-11-01_final.stac-item
2022-11-03 11:17:19	ga_ls9c_ard_3-2-1_109082_2022-11-03_final.stac-item
2022-11-17 11:26:10	ga_ls9c_ard_3-2-1_111073_2022-11-17_final.stac-item
2022-11-19 11:17:23	ga_ls9c_ard_3-2-1_109082_2022-11-19_final.stac-item
2022-11-26 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-11-26_final.stac-item
2022-12-03 11:25:42	ga_ls9c_ard_3-2-1_111072_2022-12-03_final.stac-item
2022-12-03 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-12-03_final.stac-item
2022-12-05 11:17:21	ga_ls9c_ard_3-2-1_109082_2022-12-05_final.stac-item
2022-12-12 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-12-12_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-21 11:17:20	ga_ls9c_ard_3-2-1_109082_2022-12-21_final.stac-item
2022-12-28 11:21:08	ga_ls9c_ard_3-2-1_110076_2022-12-28_final.stac-item
2023-01-04 11:26:09	ga_ls9c_ard_3-2-1_111073_2023-01-04_final.stac-item
2023-01-06 11:17:22	ga_ls9c_ard_3-2-1_109082_2023-01-06_final.stac-item
2023-01-13 11:21:07	ga_ls9c_ard_3-2-1_110076_2023-01-13_final.stac-item
2023-01-20 11:25:58	ga_ls9c_ard_3-2-1_111073_2023-01-20_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-02-05 11:25:47	ga_ls9c_ard_3-2-1_111072_2023-02-05_final.stac-item
2023-02-05 11:26:11	ga_ls9c_ard_3-2-1_111073_2023-02-05_final.stac-item
2023-02-07 11:17:26	ga_ls9c_ard_3-2-1_109082_2023-02-07_final.stac-item
2023-02-14 11:21:11	ga_ls9c_ard_3-2-1_110076_2023-02-14_final.stac-item
2023-02-21 11:26:01	ga_ls9c_ard_3-2-1_111073_2023-02-21_final.stac-item
2023-02-23 11:17:12	ga_ls9c_ard_3-2-1_109082_2023-02-23_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-04-10 11:25:36	ga_ls9c_ard_3-2-1_111073_2023-04-10_final.stac-item
2023-04-12 11:16:48	ga_ls9c_ard_3-2-1_109082_2023-04-12_final.stac-item
2023-04-26 11:25:05	ga_ls9c_ard_3-2-1_111072_2023-04-26_final.stac-item
2023-04-26 11:25:29	ga_ls9c_ard_3-2-1_111073_2023-04-26_final.stac-item
2023-04-28 11:16:41	ga_ls9c_ard_3-2-1_109082_2023-04-28_final.stac-item
2023-05-12 11:25:20	ga_ls9c_ard_3-2-1_111073_2023-05-12_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-05-28 11:24:46	ga_ls9c_ard_3-2-1_111072_2023-05-28_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-05-30 11:16:24	ga_ls9c_ard_3-2-1_109082_2023-05-30_final.stac-item
2023-06-13 11:25:02	ga_ls9c_ard_3-2-1_111073_2023-06-13_final.stac-item
2023-06-29 11:24:42	ga_ls9c_ard_3-2-1_111072_2023-06-29_final.stac-item
2023-06-29 11:25:06	ga_ls9c_ard_3-2-1_111073_2023-06-29_final.stac-item
2023-07-01 11:16:23	ga_ls9c_ard_3-2-1_109082_2023-07-01_final.stac-item
2023-07-31 11:25:22	ga_ls9c_ard_3-2-1_111073_2023-07-31_final.stac-item
2023-08-16 11:25:27	ga_ls9c_ard_3-2-1_111073_2023-08-16_final.stac-item
2023-09-17 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-09-17_final.stac-item
2023-09-17 11:25:46	ga_ls9c_ard_3-2-1_111073_2023-09-17_final.stac-item
2023-10-03 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-10-03_final.stac-item
2023-10-19 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-10-19_final.stac-item
2023-11-04 11:25:25	ga_ls9c_ard_3-2-1_111072_2023-11-04_final.stac-item
2023-11-20 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-11-20_final.stac-item
2023-12-06 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-12-06_final.stac-item
2023-12-22 11:25:38	ga_ls9c_ard_3-2-1_111072_2023-12-22_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