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 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-10 11:16:10	ga_ls9c_ard_3-2-1_110072_2021-11-10_final.stac-item
2021-11-15 11:18:38	ga_ls9c_ard_3-2-1_110072_2021-11-15_final.stac-item
2021-12-09 11:19:28	ga_ls9c_ard_3-2-1_110072_2021-12-09_final.stac-item
2021-12-18 11:13:12	ga_ls9c_ard_3-2-1_109072_2021-12-18_final.stac-item
2021-12-25 11:19:24	ga_ls9c_ard_3-2-1_110072_2021-12-25_final.stac-item
2022-01-03 11:13:12	ga_ls9c_ard_3-2-1_109072_2022-01-03_final.stac-item
2022-01-10 11:19:21	ga_ls9c_ard_3-2-1_110072_2022-01-10_final.stac-item
2022-01-12 11:09:23	ga_ls9c_ard_3-2-1_108078_2022-01-12_final.stac-item
2022-01-12 11:09:47	ga_ls9c_ard_3-2-1_108079_2022-01-12_final.stac-item
2022-01-19 11:13:11	ga_ls9c_ard_3-2-1_109072_2022-01-19_final.stac-item
2022-01-19 11:13:59	ga_ls9c_ard_3-2-1_109074_2022-01-19_final.stac-item
2022-01-26 11:19:23	ga_ls9c_ard_3-2-1_110072_2022-01-26_final.stac-item
2022-02-13 11:09:21	ga_ls9c_ard_3-2-1_108078_2022-02-13_final.stac-item
2022-02-20 11:13:04	ga_ls9c_ard_3-2-1_109072_2022-02-20_final.stac-item
2022-03-01 11:09:10	ga_ls9c_ard_3-2-1_108078_2022-03-01_final.stac-item
2022-03-08 11:12:57	ga_ls9c_ard_3-2-1_109072_2022-03-08_final.stac-item
2022-03-31 11:19:03	ga_ls9c_ard_3-2-1_110072_2022-03-31_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-16 11:18:56	ga_ls9c_ard_3-2-1_110072_2022-04-16_final.stac-item
2022-04-18 11:08:57	ga_ls9c_ard_3-2-1_108078_2022-04-18_final.stac-item
2022-04-18 11:09:21	ga_ls9c_ard_3-2-1_108079_2022-04-18_final.stac-item
2022-04-25 11:12:41	ga_ls9c_ard_3-2-1_109072_2022-04-25_final.stac-item
2022-04-25 11:13:29	ga_ls9c_ard_3-2-1_109074_2022-04-25_final.stac-item
2022-05-27 11:12:26	ga_ls9c_ard_3-2-1_109072_2022-05-27_final.stac-item
2022-05-27 11:13:14	ga_ls9c_ard_3-2-1_109074_2022-05-27_final.stac-item
2022-06-05 11:08:40	ga_ls9c_ard_3-2-1_108078_2022-06-05_final.stac-item
2022-06-05 11:09:04	ga_ls9c_ard_3-2-1_108079_2022-06-05_final.stac-item
2022-06-12 11:13:18	ga_ls9c_ard_3-2-1_109074_2022-06-12_final.stac-item
2022-06-19 11:18:48	ga_ls9c_ard_3-2-1_110072_2022-06-19_final.stac-item
2022-06-28 11:13:36	ga_ls9c_ard_3-2-1_109074_2022-06-28_final.stac-item
2022-07-05 11:18:58	ga_ls9c_ard_3-2-1_110072_2022-07-05_final.stac-item
2022-07-07 11:08:59	ga_ls9c_ard_3-2-1_108078_2022-07-07_final.stac-item
2022-07-14 11:12:43	ga_ls9c_ard_3-2-1_109072_2022-07-14_final.stac-item
2022-07-21 11:19:01	ga_ls9c_ard_3-2-1_110072_2022-07-21_final.stac-item
2022-07-30 11:13:46	ga_ls9c_ard_3-2-1_109074_2022-07-30_final.stac-item
2022-08-08 11:09:41	ga_ls9c_ard_3-2-1_108079_2022-08-08_final.stac-item
2022-08-15 11:13:55	ga_ls9c_ard_3-2-1_109074_2022-08-15_final.stac-item
2022-08-24 11:09:46	ga_ls9c_ard_3-2-1_108079_2022-08-24_final.stac-item
2022-08-31 11:13:10	ga_ls9c_ard_3-2-1_109072_2022-08-31_final.stac-item
2022-08-31 11:13:58	ga_ls9c_ard_3-2-1_109074_2022-08-31_final.stac-item
2022-09-07 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-09-07_final.stac-item
2022-09-16 11:14:01	ga_ls9c_ard_3-2-1_109074_2022-09-16_final.stac-item
2022-09-25 11:09:30	ga_ls9c_ard_3-2-1_108078_2022-09-25_final.stac-item
2022-09-25 11:09:54	ga_ls9c_ard_3-2-1_108079_2022-09-25_final.stac-item
2022-10-02 11:13:17	ga_ls9c_ard_3-2-1_109072_2022-10-02_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-18 11:14:10	ga_ls9c_ard_3-2-1_109074_2022-10-18_final.stac-item
2022-11-03 11:13:20	ga_ls9c_ard_3-2-1_109072_2022-11-03_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-10 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-11-10_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-19 11:13:24	ga_ls9c_ard_3-2-1_109072_2022-11-19_final.stac-item
2022-11-26 11:19:33	ga_ls9c_ard_3-2-1_110072_2022-11-26_final.stac-item
2022-12-05 11:13:21	ga_ls9c_ard_3-2-1_109072_2022-12-05_final.stac-item
2022-12-05 11:14:09	ga_ls9c_ard_3-2-1_109074_2022-12-05_final.stac-item
2022-12-21 11:13:20	ga_ls9c_ard_3-2-1_109072_2022-12-21_final.stac-item
2023-01-13 11:19:31	ga_ls9c_ard_3-2-1_110072_2023-01-13_final.stac-item
2023-01-22 11:13:14	ga_ls9c_ard_3-2-1_109072_2023-01-22_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-07 11:14:14	ga_ls9c_ard_3-2-1_109074_2023-02-07_final.stac-item
2023-02-16 11:09:35	ga_ls9c_ard_3-2-1_108078_2023-02-16_final.stac-item
2023-02-23 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-02-23_final.stac-item
2023-03-04 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-03-04_final.stac-item
2023-03-18 11:19:15	ga_ls9c_ard_3-2-1_110072_2023-03-18_final.stac-item
2023-03-20 11:09:16	ga_ls9c_ard_3-2-1_108078_2023-03-20_final.stac-item
2023-04-03 11:19:04	ga_ls9c_ard_3-2-1_110072_2023-04-03_final.stac-item
2023-04-19 11:18:58	ga_ls9c_ard_3-2-1_110072_2023-04-19_final.stac-item
2023-04-21 11:08:59	ga_ls9c_ard_3-2-1_108078_2023-04-21_final.stac-item
2023-04-28 11:12:42	ga_ls9c_ard_3-2-1_109072_2023-04-28_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-05-05 11:18:45	ga_ls9c_ard_3-2-1_110072_2023-05-05_final.stac-item
2023-05-07 11:08:47	ga_ls9c_ard_3-2-1_108078_2023-05-07_final.stac-item
2023-05-14 11:12:33	ga_ls9c_ard_3-2-1_109072_2023-05-14_final.stac-item
2023-05-14 11:13:21	ga_ls9c_ard_3-2-1_109074_2023-05-14_final.stac-item
2023-05-23 11:08:38	ga_ls9c_ard_3-2-1_108078_2023-05-23_final.stac-item
2023-05-30 11:13:12	ga_ls9c_ard_3-2-1_109074_2023-05-30_final.stac-item
2023-06-15 11:12:15	ga_ls9c_ard_3-2-1_109072_2023-06-15_final.stac-item
2023-06-15 11:13:03	ga_ls9c_ard_3-2-1_109074_2023-06-15_final.stac-item
2023-06-24 11:08:28	ga_ls9c_ard_3-2-1_108078_2023-06-24_final.stac-item
2023-07-01 11:12:24	ga_ls9c_ard_3-2-1_109072_2023-07-01_final.stac-item
2023-07-01 11:13:12	ga_ls9c_ard_3-2-1_109074_2023-07-01_final.stac-item
2023-07-08 11:18:40	ga_ls9c_ard_3-2-1_110072_2023-07-08_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-24 11:18:41	ga_ls9c_ard_3-2-1_110072_2023-07-24_final.stac-item
2023-08-02 11:12:38	ga_ls9c_ard_3-2-1_109072_2023-08-02_final.stac-item
2023-09-19 11:13:48	ga_ls9c_ard_3-2-1_109074_2023-09-19_final.stac-item
2023-10-05 11:13:50	ga_ls9c_ard_3-2-1_109074_2023-10-05_final.stac-item
2023-10-21 11:13:58	ga_ls9c_ard_3-2-1_109074_2023-10-21_final.stac-item
2023-11-06 11:13:53	ga_ls9c_ard_3-2-1_109074_2023-11-06_final.stac-item
2023-11-22 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-11-22_final.stac-item
2023-12-08 11:13:57	ga_ls9c_ard_3-2-1_109074_2023-12-08_final.stac-item
2023-12-24 11:14:04	ga_ls9c_ard_3-2-1_109074_2023-12-24_final.stac-item
2024-01-09 11:13:59	ga_ls9c_ard_3-2-1_109074_2024-01-09_final.stac-item
2024-01-25 11:13:56	ga_ls9c_ard_3-2-1_109074_2024-01-25_final.stac-item
2024-01-25 11:13:56	ga_ls9c_ard_3-2-1_109074_2024-01-25_nrt.stac-item
2024-02-10 11:13:38	ga_ls9c_ard_3-2-1_109073_2024-02-10_final.stac-item
2024-02-17 11:19:43	ga_ls9c_ard_3-2-1_110073_2024-02-17_final.stac-item
2024-03-29 11:13:20	ga_ls9c_ard_3-2-1_109073_2024-03-29_final.stac-item
2024-04-21 11:19:14	ga_ls9c_ard_3-2-1_110073_2024-04-21_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