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 11:10:24	ga_ls9c_ard_3-2-1_109070_2021-10-31_final.stac-item
2021-11-05 11:12:53	ga_ls9c_ard_3-2-1_109070_2021-11-05_final.stac-item
2021-12-11 11:06:17	ga_ls9c_ard_3-2-1_108070_2021-12-11_final.stac-item
2021-12-18 11:12:24	ga_ls9c_ard_3-2-1_109070_2021-12-18_final.stac-item
2021-12-27 11:06:14	ga_ls9c_ard_3-2-1_108070_2021-12-27_final.stac-item
2022-01-03 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-01-03_final.stac-item
2022-01-12 11:06:11	ga_ls9c_ard_3-2-1_108070_2022-01-12_final.stac-item
2022-01-19 11:12:23	ga_ls9c_ard_3-2-1_109070_2022-01-19_final.stac-item
2022-01-30 10:57:27	ga_ls9c_ard_3-2-1_106079_2022-01-30_final.stac-item
2022-02-04 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-02-04_final.stac-item
2022-02-13 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-02-13_final.stac-item
2022-02-20 11:12:17	ga_ls9c_ard_3-2-1_109070_2022-02-20_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-24 11:12:06	ga_ls9c_ard_3-2-1_109070_2022-03-24_final.stac-item
2022-03-26 11:03:18	ga_ls9c_ard_3-2-1_107079_2022-03-26_final.stac-item
2022-04-02 11:05:54	ga_ls9c_ard_3-2-1_108070_2022-04-02_final.stac-item
2022-04-09 11:12:02	ga_ls9c_ard_3-2-1_109070_2022-04-09_final.stac-item
2022-04-18 11:05:45	ga_ls9c_ard_3-2-1_108070_2022-04-18_final.stac-item
2022-04-25 11:11:53	ga_ls9c_ard_3-2-1_109070_2022-04-25_final.stac-item
2022-05-06 10:56:53	ga_ls9c_ard_3-2-1_106079_2022-05-06_final.stac-item
2022-05-11 11:11:47	ga_ls9c_ard_3-2-1_109070_2022-05-11_final.stac-item
2022-05-20 11:05:27	ga_ls9c_ard_3-2-1_108070_2022-05-20_final.stac-item
2022-05-22 10:56:41	ga_ls9c_ard_3-2-1_106079_2022-05-22_final.stac-item
2022-05-27 11:11:38	ga_ls9c_ard_3-2-1_109070_2022-05-27_final.stac-item
2022-06-05 11:05:29	ga_ls9c_ard_3-2-1_108070_2022-06-05_final.stac-item
2022-06-12 11:11:42	ga_ls9c_ard_3-2-1_109070_2022-06-12_final.stac-item
2022-06-21 11:05:43	ga_ls9c_ard_3-2-1_108070_2022-06-21_final.stac-item
2022-06-28 11:12:01	ga_ls9c_ard_3-2-1_109070_2022-06-28_final.stac-item
2022-07-14 11:11:56	ga_ls9c_ard_3-2-1_109070_2022-07-14_final.stac-item
2022-07-30 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-07-30_final.stac-item
2022-08-08 11:06:05	ga_ls9c_ard_3-2-1_108070_2022-08-08_final.stac-item
2022-08-15 11:12:19	ga_ls9c_ard_3-2-1_109070_2022-08-15_final.stac-item
2022-08-24 11:06:11	ga_ls9c_ard_3-2-1_108070_2022-08-24_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-09 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-09-09_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-25 11:06:18	ga_ls9c_ard_3-2-1_108070_2022-09-25_final.stac-item
2022-10-02 11:12:29	ga_ls9c_ard_3-2-1_109070_2022-10-02_final.stac-item
2022-10-11 11:06:21	ga_ls9c_ard_3-2-1_108070_2022-10-11_final.stac-item
2022-10-18 11:12:35	ga_ls9c_ard_3-2-1_109070_2022-10-18_final.stac-item
2022-10-27 11:06:24	ga_ls9c_ard_3-2-1_108070_2022-10-27_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-11-03_final.stac-item
2022-11-19 11:12:36	ga_ls9c_ard_3-2-1_109070_2022-11-19_final.stac-item
2022-12-05 11:12:33	ga_ls9c_ard_3-2-1_109070_2022-12-05_final.stac-item
2022-12-21 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-12-21_final.stac-item
2023-01-06 11:12:35	ga_ls9c_ard_3-2-1_109070_2023-01-06_final.stac-item
2023-01-22 11:12:26	ga_ls9c_ard_3-2-1_109070_2023-01-22_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-03-04 11:06:11	ga_ls9c_ard_3-2-1_108070_2023-03-04_final.stac-item
2023-03-11 11:12:16	ga_ls9c_ard_3-2-1_109070_2023-03-11_final.stac-item
2023-03-13 11:03:54	ga_ls9c_ard_3-2-1_107080_2023-03-13_final.stac-item
2023-03-20 11:06:04	ga_ls9c_ard_3-2-1_108070_2023-03-20_final.stac-item
2023-03-27 11:12:08	ga_ls9c_ard_3-2-1_109070_2023-03-27_final.stac-item
2023-04-12 11:12:01	ga_ls9c_ard_3-2-1_109070_2023-04-12_final.stac-item
2023-04-28 11:11:54	ga_ls9c_ard_3-2-1_109070_2023-04-28_final.stac-item
2023-05-14 11:11:45	ga_ls9c_ard_3-2-1_109070_2023-05-14_final.stac-item
2023-05-23 11:05:27	ga_ls9c_ard_3-2-1_108070_2023-05-23_final.stac-item
2023-05-30 11:11:36	ga_ls9c_ard_3-2-1_109070_2023-05-30_final.stac-item
2023-06-15 11:11:27	ga_ls9c_ard_3-2-1_109070_2023-06-15_final.stac-item
2023-06-24 11:05:16	ga_ls9c_ard_3-2-1_108070_2023-06-24_final.stac-item
2023-07-01 11:11:36	ga_ls9c_ard_3-2-1_109070_2023-07-01_final.stac-item
2023-07-10 11:05:32	ga_ls9c_ard_3-2-1_108070_2023-07-10_final.stac-item
2023-07-17 11:11:44	ga_ls9c_ard_3-2-1_109070_2023-07-17_final.stac-item
2023-07-26 11:05:33	ga_ls9c_ard_3-2-1_108070_2023-07-26_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-08-11 11:05:43	ga_ls9c_ard_3-2-1_108070_2023-08-11_final.stac-item
2023-08-18 11:11:53	ga_ls9c_ard_3-2-1_109070_2023-08-18_final.stac-item
2023-08-27 11:05:51	ga_ls9c_ard_3-2-1_108070_2023-08-27_final.stac-item
2023-09-03 11:12:05	ga_ls9c_ard_3-2-1_109070_2023-09-03_final.stac-item
2023-09-12 11:06:01	ga_ls9c_ard_3-2-1_108070_2023-09-12_final.stac-item
2023-09-19 11:12:12	ga_ls9c_ard_3-2-1_109070_2023-09-19_final.stac-item
2023-09-28 11:05:56	ga_ls9c_ard_3-2-1_108070_2023-09-28_final.stac-item
2023-10-05 11:12:14	ga_ls9c_ard_3-2-1_109070_2023-10-05_final.stac-item
2023-10-14 11:06:10	ga_ls9c_ard_3-2-1_108070_2023-10-14_final.stac-item
2023-10-21 11:12:23	ga_ls9c_ard_3-2-1_109070_2023-10-21_final.stac-item
2023-10-30 11:06:08	ga_ls9c_ard_3-2-1_108070_2023-10-30_final.stac-item
2023-11-06 11:12:17	ga_ls9c_ard_3-2-1_109070_2023-11-06_final.stac-item
2023-11-15 11:06:07	ga_ls9c_ard_3-2-1_108070_2023-11-15_final.stac-item
2023-11-22 11:12:24	ga_ls9c_ard_3-2-1_109070_2023-11-22_final.stac-item
2023-12-01 11:06:15	ga_ls9c_ard_3-2-1_108070_2023-12-01_final.stac-item
2023-12-08 11:12:21	ga_ls9c_ard_3-2-1_109070_2023-12-08_final.stac-item
2023-12-17 11:06:16	ga_ls9c_ard_3-2-1_108070_2023-12-17_final.stac-item
2023-12-24 11:12:28	ga_ls9c_ard_3-2-1_109070_2023-12-24_final.stac-item
2024-01-02 11:06:13	ga_ls9c_ard_3-2-1_108070_2024-01-02_final.stac-item
2024-01-09 11:12:23	ga_ls9c_ard_3-2-1_109070_2024-01-09_final.stac-item
2024-01-18 11:06:13	ga_ls9c_ard_3-2-1_108070_2024-01-18_final.stac-item
2024-01-25 11:12:21	ga_ls9c_ard_3-2-1_109070_2024-01-25_final.stac-item
2024-02-03 11:06:15	ga_ls9c_ard_3-2-1_108070_2024-02-03_final.stac-item
2024-02-10 11:12:26	ga_ls9c_ard_3-2-1_109070_2024-02-10_final.stac-item
2024-02-19 11:06:07	ga_ls9c_ard_3-2-1_108070_2024-02-19_final.stac-item
2024-02-26 11:12:15	ga_ls9c_ard_3-2-1_109070_2024-02-26_final.stac-item
2024-03-06 11:06:08	ga_ls9c_ard_3-2-1_108070_2024-03-06_final.stac-item
2024-03-13 11:12:17	ga_ls9c_ard_3-2-1_109070_2024-03-13_final.stac-item
2024-03-22 11:06:05	ga_ls9c_ard_3-2-1_108070_2024-03-22_final.stac-item
2024-03-29 11:12:08	ga_ls9c_ard_3-2-1_109070_2024-03-29_final.stac-item
2024-04-07 11:05:56	ga_ls9c_ard_3-2-1_108070_2024-04-07_final.stac-item
2024-04-14 11:12:02	ga_ls9c_ard_3-2-1_109070_2024-04-14_final.stac-item
2024-04-23 11:05:36	ga_ls9c_ard_3-2-1_108070_2024-04-23_final.stac-item
2024-04-30 11:11:45	ga_ls9c_ard_3-2-1_109070_2024-04-30_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