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
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-08 10:37:25	ga_ls9c_ard_3-2-1_103075_2021-12-08_final.stac-item
2021-12-10 10:25:02	ga_ls9c_ard_3-2-1_101075_2021-12-10_final.stac-item
2021-12-11 09:29:48	ga_ls9c_ard_3-2-1_092076_2021-12-10_final.stac-item
2021-12-17 10:31:08	ga_ls9c_ard_3-2-1_102075_2021-12-17_final.stac-item
2021-12-20 09:23:10	ga_ls9c_ard_3-2-1_091075_2021-12-19_final.stac-item
2021-12-26 10:24:58	ga_ls9c_ard_3-2-1_101075_2021-12-26_final.stac-item
2021-12-27 09:29:21	ga_ls9c_ard_3-2-1_092075_2021-12-26_final.stac-item
2021-12-27 09:29:45	ga_ls9c_ard_3-2-1_092076_2021-12-26_final.stac-item
2022-01-03 11:14:48	ga_ls9c_ard_3-2-1_109076_2022-01-03_final.stac-item
2022-01-09 10:37:18	ga_ls9c_ard_3-2-1_103075_2022-01-09_final.stac-item
2022-01-10 11:20:57	ga_ls9c_ard_3-2-1_110076_2022-01-10_final.stac-item
2022-01-12 09:29:18	ga_ls9c_ard_3-2-1_092075_2022-01-11_final.stac-item
2022-01-18 10:31:07	ga_ls9c_ard_3-2-1_102075_2022-01-18_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-02-03 10:31:08	ga_ls9c_ard_3-2-1_102075_2022-02-03_final.stac-item
2022-02-05 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-02-05_final.stac-item
2022-02-06 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-02-05_final.stac-item
2022-02-10 10:37:17	ga_ls9c_ard_3-2-1_103075_2022-02-10_final.stac-item
2022-02-22 09:23:00	ga_ls9c_ard_3-2-1_091075_2022-02-21_final.stac-item
2022-02-26 10:37:07	ga_ls9c_ard_3-2-1_103075_2022-02-26_final.stac-item
2022-03-07 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-03-07_final.stac-item
2022-03-10 09:22:55	ga_ls9c_ard_3-2-1_091075_2022-03-09_final.stac-item
2022-03-23 10:30:50	ga_ls9c_ard_3-2-1_102075_2022-03-23_final.stac-item
2022-03-26 09:22:50	ga_ls9c_ard_3-2-1_091075_2022-03-25_final.stac-item
2022-03-26 09:23:14	ga_ls9c_ard_3-2-1_091076_2022-03-25_final.stac-item
2022-03-30 10:36:59	ga_ls9c_ard_3-2-1_103075_2022-03-30_final.stac-item
2022-04-08 10:30:47	ga_ls9c_ard_3-2-1_102075_2022-04-08_final.stac-item
2022-04-17 10:24:30	ga_ls9c_ard_3-2-1_101075_2022-04-17_final.stac-item
2022-04-26 10:18:15	ga_ls9c_ard_3-2-1_100075_2022-04-26_final.stac-item
2022-04-27 09:22:38	ga_ls9c_ard_3-2-1_091075_2022-04-26_final.stac-item
2022-05-01 10:36:47	ga_ls9c_ard_3-2-1_103075_2022-05-01_final.stac-item
2022-05-17 10:36:36	ga_ls9c_ard_3-2-1_103075_2022-05-17_final.stac-item
2022-05-19 10:24:12	ga_ls9c_ard_3-2-1_101075_2022-05-19_final.stac-item
2022-05-20 09:28:34	ga_ls9c_ard_3-2-1_092075_2022-05-19_final.stac-item
2022-05-27 11:14:02	ga_ls9c_ard_3-2-1_109076_2022-05-27_final.stac-item
2022-05-29 09:22:24	ga_ls9c_ard_3-2-1_091075_2022-05-28_final.stac-item
2022-05-29 09:22:48	ga_ls9c_ard_3-2-1_091076_2022-05-28_final.stac-item
2022-05-31 09:10:03	ga_ls9c_ard_3-2-1_089075_2022-05-30_final.stac-item
2022-06-20 10:24:25	ga_ls9c_ard_3-2-1_101075_2022-06-20_final.stac-item
2022-06-21 09:29:13	ga_ls9c_ard_3-2-1_092076_2022-06-20_final.stac-item
2022-06-26 09:47:53	ga_ls9c_ard_3-2-1_095076_2022-06-26_final.stac-item
2022-06-28 11:14:24	ga_ls9c_ard_3-2-1_109076_2022-06-28_final.stac-item
2022-06-30 09:23:09	ga_ls9c_ard_3-2-1_091076_2022-06-29_final.stac-item
2022-07-02 09:10:23	ga_ls9c_ard_3-2-1_089075_2022-07-01_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 09:28:55	ga_ls9c_ard_3-2-1_092075_2022-07-06_final.stac-item
2022-07-07 09:29:18	ga_ls9c_ard_3-2-1_092076_2022-07-06_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
2022-07-28 09:48:01	ga_ls9c_ard_3-2-1_095076_2022-07-28_final.stac-item
2022-08-01 09:23:20	ga_ls9c_ard_3-2-1_091076_2022-07-31_final.stac-item
2022-08-14 10:31:03	ga_ls9c_ard_3-2-1_102075_2022-08-14_final.stac-item
2022-08-15 11:14:43	ga_ls9c_ard_3-2-1_109076_2022-08-15_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-09-15 10:31:09	ga_ls9c_ard_3-2-1_102075_2022-09-15_final.stac-item
2022-09-18 09:23:12	ga_ls9c_ard_3-2-1_091075_2022-09-17_final.stac-item
2022-09-22 10:37:23	ga_ls9c_ard_3-2-1_103075_2022-09-22_final.stac-item
2022-09-25 09:29:25	ga_ls9c_ard_3-2-1_092075_2022-09-24_final.stac-item
2022-10-04 09:23:38	ga_ls9c_ard_3-2-1_091076_2022-10-03_final.stac-item
2022-10-07 09:54:32	ga_ls9c_ard_3-2-1_096076_2022-10-07_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-11 09:29:28	ga_ls9c_ard_3-2-1_092075_2022-10-10_final.stac-item
2022-10-11 09:29:52	ga_ls9c_ard_3-2-1_092076_2022-10-10_final.stac-item
2022-10-23 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-10-23_final.stac-item
2022-10-27 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-10-26_final.stac-item
2022-11-05 09:23:17	ga_ls9c_ard_3-2-1_091075_2022-11-04_final.stac-item
2022-11-12 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-11-11_final.stac-item
2022-11-12 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-11-11_final.stac-item
2022-11-21 09:23:21	ga_ls9c_ard_3-2-1_091075_2022-11-20_final.stac-item
2022-11-28 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-11-27_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-22 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-12-22_final.stac-item
2023-01-08 09:23:44	ga_ls9c_ard_3-2-1_091076_2023-01-07_final.stac-item
2023-02-11 09:11:01	ga_ls9c_ard_3-2-1_089075_2023-02-10_final.stac-item
2023-03-22 09:16:48	ga_ls9c_ard_3-2-1_090075_2023-03-21_final.stac-item
2023-04-23 09:16:32	ga_ls9c_ard_3-2-1_090075_2023-04-22_final.stac-item
2023-05-09 09:16:21	ga_ls9c_ard_3-2-1_090075_2023-05-08_final.stac-item
2023-06-03 09:09:59	ga_ls9c_ard_3-2-1_089075_2023-06-02_final.stac-item
2023-06-20 09:53:30	ga_ls9c_ard_3-2-1_096076_2023-06-20_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-06-27 09:59:43	ga_ls9c_ard_3-2-1_097076_2023-06-27_final.stac-item
2023-06-29 09:47:25	ga_ls9c_ard_3-2-1_095076_2023-06-29_final.stac-item
2023-07-05 09:10:03	ga_ls9c_ard_3-2-1_089075_2023-07-04_final.stac-item
2023-07-06 09:53:43	ga_ls9c_ard_3-2-1_096076_2023-07-06_final.stac-item
2023-07-13 09:59:57	ga_ls9c_ard_3-2-1_097076_2023-07-13_final.stac-item
2023-07-20 10:06:08	ga_ls9c_ard_3-2-1_098076_2023-07-20_final.stac-item
2023-07-21 09:10:07	ga_ls9c_ard_3-2-1_089075_2023-07-20_final.stac-item
2023-07-22 09:53:46	ga_ls9c_ard_3-2-1_096076_2023-07-22_final.stac-item
2023-07-29 10:00:01	ga_ls9c_ard_3-2-1_097076_2023-07-29_final.stac-item
2023-08-06 09:10:16	ga_ls9c_ard_3-2-1_089075_2023-08-05_final.stac-item
2023-09-07 09:10:32	ga_ls9c_ard_3-2-1_089075_2023-09-06_final.stac-item
2023-10-25 09:10:45	ga_ls9c_ard_3-2-1_089075_2023-10-24_final.stac-item
2023-11-26 09:10:50	ga_ls9c_ard_3-2-1_089075_2023-11-25_final.stac-item
2023-12-28 09:10:51	ga_ls9c_ard_3-2-1_089075_2023-12-27_final.stac-item
2024-02-14 09:10:47	ga_ls9c_ard_3-2-1_089075_2024-02-13_final.stac-item
2024-03-17 09:10:41	ga_ls9c_ard_3-2-1_089075_2024-03-16_final.stac-item
2024-04-02 09:10:32	ga_ls9c_ard_3-2-1_089075_2024-04-01_final.stac-item
2024-04-18 09:10:21	ga_ls9c_ard_3-2-1_089075_2024-04-17_final.stac-item
2024-05-04 09:10:07	ga_ls9c_ard_3-2-1_089075_2024-05-03_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