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
2021-12-08 10:34:37	ga_ls9c_ard_3-2-1_103068_2021-12-08_final.stac-item
2021-12-17 10:28:44	ga_ls9c_ard_3-2-1_102069_2021-12-17_final.stac-item
2021-12-17 10:29:32	ga_ls9c_ard_3-2-1_102071_2021-12-17_final.stac-item
2021-12-24 10:34:32	ga_ls9c_ard_3-2-1_103068_2021-12-24_final.stac-item
2021-12-24 10:34:56	ga_ls9c_ard_3-2-1_103069_2021-12-24_final.stac-item
2022-01-02 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-01-02_final.stac-item
2022-01-04 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-01-04_final.stac-item
2022-01-09 10:34:30	ga_ls9c_ard_3-2-1_103068_2022-01-09_final.stac-item
2022-01-09 10:34:54	ga_ls9c_ard_3-2-1_103069_2022-01-09_final.stac-item
2022-01-18 10:29:31	ga_ls9c_ard_3-2-1_102071_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
2022-01-25 10:34:31	ga_ls9c_ard_3-2-1_103068_2022-01-25_final.stac-item
2022-01-25 10:34:55	ga_ls9c_ard_3-2-1_103069_2022-01-25_final.stac-item
2022-02-03 10:28:44	ga_ls9c_ard_3-2-1_102069_2022-02-03_final.stac-item
2022-02-03 10:29:32	ga_ls9c_ard_3-2-1_102071_2022-02-03_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-19 10:29:25	ga_ls9c_ard_3-2-1_102071_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
2022-02-26 10:34:19	ga_ls9c_ard_3-2-1_103068_2022-02-26_final.stac-item
2022-03-07 10:29:18	ga_ls9c_ard_3-2-1_102071_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 10:28:27	ga_ls9c_ard_3-2-1_102069_2022-03-23_final.stac-item
2022-03-23 10:29:14	ga_ls9c_ard_3-2-1_102071_2022-03-23_final.stac-item
2022-03-30 10:34:12	ga_ls9c_ard_3-2-1_103068_2022-03-30_final.stac-item
2022-04-08 10:29:11	ga_ls9c_ard_3-2-1_102071_2022-04-08_final.stac-item
2022-04-15 10:34:06	ga_ls9c_ard_3-2-1_103068_2022-04-15_final.stac-item
2022-04-24 10:28:13	ga_ls9c_ard_3-2-1_102069_2022-04-24_final.stac-item
2022-04-24 10:29:01	ga_ls9c_ard_3-2-1_102071_2022-04-24_final.stac-item
2022-04-26 10:19:51	ga_ls9c_ard_3-2-1_100079_2022-04-26_final.stac-item
2022-05-01 10:33:59	ga_ls9c_ard_3-2-1_103068_2022-05-01_final.stac-item
2022-05-10 10:28:08	ga_ls9c_ard_3-2-1_102069_2022-05-10_final.stac-item
2022-05-10 10:28:56	ga_ls9c_ard_3-2-1_102071_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
2022-05-17 10:33:49	ga_ls9c_ard_3-2-1_103068_2022-05-17_final.stac-item
2022-05-26 10:27:58	ga_ls9c_ard_3-2-1_102069_2022-05-26_final.stac-item
2022-05-26 10:28:46	ga_ls9c_ard_3-2-1_102071_2022-05-26_final.stac-item
2022-06-11 10:28:50	ga_ls9c_ard_3-2-1_102071_2022-06-11_final.stac-item
2022-06-27 10:27:57	ga_ls9c_ard_3-2-1_102068_2022-06-27_final.stac-item
2022-06-27 10:29:09	ga_ls9c_ard_3-2-1_102071_2022-06-27_final.stac-item
2022-06-29 10:19:59	ga_ls9c_ard_3-2-1_100079_2022-06-29_final.stac-item
2022-07-13 10:29:04	ga_ls9c_ard_3-2-1_102071_2022-07-13_final.stac-item
2022-07-20 10:34:08	ga_ls9c_ard_3-2-1_103068_2022-07-20_final.stac-item
2022-07-29 10:29:18	ga_ls9c_ard_3-2-1_102071_2022-07-29_final.stac-item
2022-08-05 10:34:22	ga_ls9c_ard_3-2-1_103068_2022-08-05_final.stac-item
2022-08-14 10:28:16	ga_ls9c_ard_3-2-1_102068_2022-08-14_final.stac-item
2022-08-14 10:29:27	ga_ls9c_ard_3-2-1_102071_2022-08-14_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-08-30 10:28:42	ga_ls9c_ard_3-2-1_102069_2022-08-30_final.stac-item
2022-08-30 10:29:30	ga_ls9c_ard_3-2-1_102071_2022-08-30_final.stac-item
2022-09-01 10:20:20	ga_ls9c_ard_3-2-1_100079_2022-09-01_final.stac-item
2022-09-06 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-09-06_final.stac-item
2022-09-15 10:29:33	ga_ls9c_ard_3-2-1_102071_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
2022-09-22 10:34:35	ga_ls9c_ard_3-2-1_103068_2022-09-22_final.stac-item
2022-10-01 10:29:38	ga_ls9c_ard_3-2-1_102071_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
2022-10-08 10:34:37	ga_ls9c_ard_3-2-1_103068_2022-10-08_final.stac-item
2022-10-17 10:28:55	ga_ls9c_ard_3-2-1_102069_2022-10-17_final.stac-item
2022-10-17 10:29:43	ga_ls9c_ard_3-2-1_102071_2022-10-17_final.stac-item
2022-10-24 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-10-24_final.stac-item
2022-11-02 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-11-02_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-18 10:29:44	ga_ls9c_ard_3-2-1_102071_2022-11-18_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_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
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-20 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-20_final.stac-item
2022-12-27 10:34:40	ga_ls9c_ard_3-2-1_103068_2022-12-27_final.stac-item
2023-01-05 10:29:43	ga_ls9c_ard_3-2-1_102071_2023-01-05_final.stac-item
2023-01-12 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-12_final.stac-item
2023-01-21 10:29:33	ga_ls9c_ard_3-2-1_102071_2023-01-21_final.stac-item
2023-01-28 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-28_final.stac-item
2023-02-06 10:28:34	ga_ls9c_ard_3-2-1_102068_2023-02-06_final.stac-item
2023-02-06 10:29:46	ga_ls9c_ard_3-2-1_102071_2023-02-06_final.stac-item
2023-02-13 10:34:44	ga_ls9c_ard_3-2-1_103068_2023-02-13_final.stac-item
2023-03-01 10:34:31	ga_ls9c_ard_3-2-1_103068_2023-03-01_final.stac-item
2023-03-19 10:24:01	ga_ls9c_ard_3-2-1_101073_2023-03-19_final.stac-item
2023-03-26 10:29:18	ga_ls9c_ard_3-2-1_102071_2023-03-26_final.stac-item
2023-04-02 10:34:12	ga_ls9c_ard_3-2-1_103068_2023-04-02_final.stac-item
2023-04-11 10:29:10	ga_ls9c_ard_3-2-1_102071_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
2023-04-18 10:34:06	ga_ls9c_ard_3-2-1_103068_2023-04-18_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 10:29:03	ga_ls9c_ard_3-2-1_102071_2023-04-27_final.stac-item
2023-05-04 10:33:54	ga_ls9c_ard_3-2-1_103068_2023-05-04_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 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-20 10:33:48	ga_ls9c_ard_3-2-1_103068_2023-05-20_final.stac-item
2023-05-29 10:28:45	ga_ls9c_ard_3-2-1_102071_2023-05-29_final.stac-item
2023-06-14 10:28:36	ga_ls9c_ard_3-2-1_102071_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
2023-06-21 10:33:35	ga_ls9c_ard_3-2-1_103068_2023-06-21_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 10:28:43	ga_ls9c_ard_3-2-1_102071_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
2023-07-07 10:33:48	ga_ls9c_ard_3-2-1_103068_2023-07-07_final.stac-item
2024-04-29 10:28:05	ga_ls9c_ard_3-2-1_102069_2024-04-29_final.stac-item
2024-04-29 10:28:53	ga_ls9c_ard_3-2-1_102071_2024-04-29_final.stac-item
2024-05-15 10:27:59	ga_ls9c_ard_3-2-1_102069_2024-05-15_nrt.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