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 10:20:43	ga_ls9c_ard_3-2-1_100074_2021-11-16_final.stac-item
2021-12-17 10:29:08	ga_ls9c_ard_3-2-1_102070_2021-12-17_final.stac-item
2021-12-26 10:24:10	ga_ls9c_ard_3-2-1_101073_2021-12-26_final.stac-item
2022-01-04 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-01-04_final.stac-item
2022-01-18 10:29:07	ga_ls9c_ard_3-2-1_102070_2022-01-18_final.stac-item
2022-01-20 10:20:21	ga_ls9c_ard_3-2-1_100079_2022-01-20_final.stac-item
2022-02-19 10:29:02	ga_ls9c_ard_3-2-1_102070_2022-02-19_final.stac-item
2022-02-21 10:20:14	ga_ls9c_ard_3-2-1_100079_2022-02-21_final.stac-item
2022-03-07 10:28:54	ga_ls9c_ard_3-2-1_102070_2022-03-07_final.stac-item
2022-03-09 10:20:08	ga_ls9c_ard_3-2-1_100079_2022-03-09_final.stac-item
2022-03-23 10:28:50	ga_ls9c_ard_3-2-1_102070_2022-03-23_final.stac-item
2022-04-17 10:23:42	ga_ls9c_ard_3-2-1_101073_2022-04-17_final.stac-item
2022-04-26 10:19:51	ga_ls9c_ard_3-2-1_100079_2022-04-26_final.stac-item
2022-05-03 10:23:37	ga_ls9c_ard_3-2-1_101073_2022-05-03_final.stac-item
2022-05-10 10:28:32	ga_ls9c_ard_3-2-1_102070_2022-05-10_final.stac-item
2022-05-12 10:19:44	ga_ls9c_ard_3-2-1_100079_2022-05-12_final.stac-item
2022-05-19 10:23:24	ga_ls9c_ard_3-2-1_101073_2022-05-19_final.stac-item
2022-05-26 10:28:22	ga_ls9c_ard_3-2-1_102070_2022-05-26_final.stac-item
2022-06-04 10:23:25	ga_ls9c_ard_3-2-1_101073_2022-06-04_final.stac-item
2022-06-11 10:27:38	ga_ls9c_ard_3-2-1_102068_2022-06-11_final.stac-item
2022-06-20 10:23:37	ga_ls9c_ard_3-2-1_101073_2022-06-20_final.stac-item
2022-06-29 10:19:59	ga_ls9c_ard_3-2-1_100079_2022-06-29_final.stac-item
2022-07-06 10:23:44	ga_ls9c_ard_3-2-1_101073_2022-07-06_final.stac-item
2022-07-13 10:28:16	ga_ls9c_ard_3-2-1_102069_2022-07-13_final.stac-item
2022-07-22 10:23:49	ga_ls9c_ard_3-2-1_101073_2022-07-22_final.stac-item
2022-07-29 10:28:06	ga_ls9c_ard_3-2-1_102068_2022-07-29_final.stac-item
2022-07-29 10:28:54	ga_ls9c_ard_3-2-1_102070_2022-07-29_final.stac-item
2022-08-07 10:24:01	ga_ls9c_ard_3-2-1_101073_2022-08-07_final.stac-item
2022-08-14 10:29:03	ga_ls9c_ard_3-2-1_102070_2022-08-14_final.stac-item
2022-09-01 10:20:20	ga_ls9c_ard_3-2-1_100079_2022-09-01_final.stac-item
2022-09-15 10:29:09	ga_ls9c_ard_3-2-1_102070_2022-09-15_final.stac-item
2022-09-17 10:20:24	ga_ls9c_ard_3-2-1_100079_2022-09-17_final.stac-item
2022-10-01 10:28:50	ga_ls9c_ard_3-2-1_102069_2022-10-01_final.stac-item
2022-10-01 10:29:14	ga_ls9c_ard_3-2-1_102070_2022-10-01_final.stac-item
2022-10-03 10:20:27	ga_ls9c_ard_3-2-1_100079_2022-10-03_final.stac-item
2022-10-17 10:29:19	ga_ls9c_ard_3-2-1_102070_2022-10-17_final.stac-item
2022-11-02 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-11-02_final.stac-item
2022-11-02 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-11-02_final.stac-item
2022-11-11 10:24:21	ga_ls9c_ard_3-2-1_101073_2022-11-11_final.stac-item
2022-12-04 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-12-04_final.stac-item
2022-12-06 10:20:32	ga_ls9c_ard_3-2-1_100079_2022-12-06_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-20 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-12-20_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2023-01-05 10:29:19	ga_ls9c_ard_3-2-1_102070_2023-01-05_final.stac-item
2023-01-14 10:24:17	ga_ls9c_ard_3-2-1_101073_2023-01-14_final.stac-item
2023-01-21 10:28:45	ga_ls9c_ard_3-2-1_102069_2023-01-21_final.stac-item
2023-01-30 10:24:20	ga_ls9c_ard_3-2-1_101073_2023-01-30_final.stac-item
2023-02-06 10:29:22	ga_ls9c_ard_3-2-1_102070_2023-02-06_final.stac-item
2023-02-15 10:24:21	ga_ls9c_ard_3-2-1_101073_2023-02-15_final.stac-item
2023-02-22 10:28:23	ga_ls9c_ard_3-2-1_102068_2023-02-22_final.stac-item
2023-02-22 10:28:47	ga_ls9c_ard_3-2-1_102069_2023-02-22_final.stac-item
2023-03-03 10:24:08	ga_ls9c_ard_3-2-1_101073_2023-03-03_final.stac-item
2023-03-10 10:28:36	ga_ls9c_ard_3-2-1_102069_2023-03-10_final.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-19 10:24:01	ga_ls9c_ard_3-2-1_101073_2023-03-19_final.stac-item
2023-04-04 10:23:50	ga_ls9c_ard_3-2-1_101073_2023-04-04_final.stac-item
2023-04-11 10:28:22	ga_ls9c_ard_3-2-1_102069_2023-04-11_final.stac-item
2023-04-11 10:28:46	ga_ls9c_ard_3-2-1_102070_2023-04-11_final.stac-item
2023-04-13 10:19:58	ga_ls9c_ard_3-2-1_100079_2023-04-13_final.stac-item
2023-04-20 10:23:44	ga_ls9c_ard_3-2-1_101073_2023-04-20_final.stac-item
2023-04-27 10:28:39	ga_ls9c_ard_3-2-1_102070_2023-04-27_final.stac-item
2023-05-06 10:23:32	ga_ls9c_ard_3-2-1_101073_2023-05-06_final.stac-item
2023-05-13 10:28:30	ga_ls9c_ard_3-2-1_102070_2023-05-13_final.stac-item
2023-05-22 10:23:24	ga_ls9c_ard_3-2-1_101073_2023-05-22_final.stac-item
2023-05-29 10:27:57	ga_ls9c_ard_3-2-1_102069_2023-05-29_final.stac-item
2023-06-07 10:23:19	ga_ls9c_ard_3-2-1_101073_2023-06-07_final.stac-item
2023-06-14 10:28:12	ga_ls9c_ard_3-2-1_102070_2023-06-14_final.stac-item
2023-06-16 10:19:25	ga_ls9c_ard_3-2-1_100079_2023-06-16_final.stac-item
2023-06-23 10:23:12	ga_ls9c_ard_3-2-1_101073_2023-06-23_final.stac-item
2023-06-30 10:28:19	ga_ls9c_ard_3-2-1_102070_2023-06-30_final.stac-item
2023-07-02 10:19:35	ga_ls9c_ard_3-2-1_100079_2023-07-02_final.stac-item
2023-07-09 10:23:27	ga_ls9c_ard_3-2-1_101073_2023-07-09_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-25 10:23:28	ga_ls9c_ard_3-2-1_101073_2023-07-25_final.stac-item
2023-08-01 10:27:46	ga_ls9c_ard_3-2-1_102068_2023-08-01_final.stac-item
2023-08-10 10:23:39	ga_ls9c_ard_3-2-1_101073_2023-08-10_final.stac-item
2023-08-26 10:23:46	ga_ls9c_ard_3-2-1_101073_2023-08-26_final.stac-item
2023-09-02 10:28:01	ga_ls9c_ard_3-2-1_102068_2023-09-02_final.stac-item
2023-09-11 10:23:56	ga_ls9c_ard_3-2-1_101073_2023-09-11_final.stac-item
2023-09-18 10:28:09	ga_ls9c_ard_3-2-1_102068_2023-09-18_final.stac-item
2023-09-27 10:23:53	ga_ls9c_ard_3-2-1_101073_2023-09-27_final.stac-item
2023-10-13 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-13_final.stac-item
2023-10-20 10:28:19	ga_ls9c_ard_3-2-1_102068_2023-10-20_final.stac-item
2023-10-29 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-29_final.stac-item
2023-11-14 10:24:03	ga_ls9c_ard_3-2-1_101073_2023-11-14_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_final.stac-item
2023-11-30 10:24:12	ga_ls9c_ard_3-2-1_101073_2023-11-30_final.stac-item
2023-12-16 10:24:12	ga_ls9c_ard_3-2-1_101073_2023-12-16_final.stac-item
2023-12-23 10:28:25	ga_ls9c_ard_3-2-1_102068_2023-12-23_final.stac-item
2024-01-01 10:24:10	ga_ls9c_ard_3-2-1_101073_2024-01-01_final.stac-item
2024-01-17 10:24:10	ga_ls9c_ard_3-2-1_101073_2024-01-17_final.stac-item
2024-02-02 10:24:11	ga_ls9c_ard_3-2-1_101073_2024-02-02_final.stac-item
2024-02-09 10:28:23	ga_ls9c_ard_3-2-1_102068_2024-02-09_final.stac-item
2024-02-18 10:24:04	ga_ls9c_ard_3-2-1_101073_2024-02-18_final.stac-item
2024-03-05 10:24:04	ga_ls9c_ard_3-2-1_101073_2024-03-05_final.stac-item
2024-03-12 10:28:14	ga_ls9c_ard_3-2-1_102068_2024-03-12_final.stac-item
2024-03-21 10:24:01	ga_ls9c_ard_3-2-1_101073_2024-03-21_final.stac-item
2024-03-28 10:28:06	ga_ls9c_ard_3-2-1_102068_2024-03-28_final.stac-item
2024-04-06 10:23:53	ga_ls9c_ard_3-2-1_101073_2024-04-06_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