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
2021-12-07 09:52:10	ga_ls9c_ard_3-2-1_096070_2021-12-07_final.stac-item
2021-12-07 09:52:58	ga_ls9c_ard_3-2-1_096072_2021-12-07_final.stac-item
2021-12-16 09:46:41	ga_ls9c_ard_3-2-1_095072_2021-12-16_final.stac-item
2021-12-23 09:52:04	ga_ls9c_ard_3-2-1_096070_2021-12-23_final.stac-item
2021-12-23 09:52:28	ga_ls9c_ard_3-2-1_096071_2021-12-23_final.stac-item
2021-12-23 09:52:52	ga_ls9c_ard_3-2-1_096072_2021-12-23_final.stac-item
2022-01-08 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-08_final.stac-item
2022-01-08 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-08_final.stac-item
2022-01-17 09:46:39	ga_ls9c_ard_3-2-1_095072_2022-01-17_final.stac-item
2022-01-24 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-24_final.stac-item
2022-01-24 09:52:27	ga_ls9c_ard_3-2-1_096071_2022-01-24_final.stac-item
2022-02-02 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-02-02_final.stac-item
2022-02-09 09:52:02	ga_ls9c_ard_3-2-1_096070_2022-02-09_final.stac-item
2022-02-18 09:46:34	ga_ls9c_ard_3-2-1_095072_2022-02-18_final.stac-item
2022-02-25 09:51:52	ga_ls9c_ard_3-2-1_096070_2022-02-25_final.stac-item
2022-02-25 09:52:16	ga_ls9c_ard_3-2-1_096071_2022-02-25_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-03-29 09:52:32	ga_ls9c_ard_3-2-1_096072_2022-03-29_final.stac-item
2022-04-14 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-04-14_final.stac-item
2022-04-30 09:51:32	ga_ls9c_ard_3-2-1_096070_2022-04-30_final.stac-item
2022-04-30 09:51:56	ga_ls9c_ard_3-2-1_096071_2022-04-30_final.stac-item
2022-04-30 09:52:20	ga_ls9c_ard_3-2-1_096072_2022-04-30_final.stac-item
2022-05-16 09:51:22	ga_ls9c_ard_3-2-1_096070_2022-05-16_final.stac-item
2022-05-16 09:51:46	ga_ls9c_ard_3-2-1_096071_2022-05-16_final.stac-item
2022-05-16 09:52:10	ga_ls9c_ard_3-2-1_096072_2022-05-16_final.stac-item
2022-06-01 09:51:19	ga_ls9c_ard_3-2-1_096070_2022-06-01_final.stac-item
2022-06-01 09:52:07	ga_ls9c_ard_3-2-1_096072_2022-06-01_final.stac-item
2022-06-10 09:45:57	ga_ls9c_ard_3-2-1_095072_2022-06-10_final.stac-item
2022-06-17 09:51:26	ga_ls9c_ard_3-2-1_096070_2022-06-17_final.stac-item
2022-06-17 09:51:50	ga_ls9c_ard_3-2-1_096071_2022-06-17_final.stac-item
2022-06-17 09:52:14	ga_ls9c_ard_3-2-1_096072_2022-06-17_final.stac-item
2022-06-26 09:46:17	ga_ls9c_ard_3-2-1_095072_2022-06-26_final.stac-item
2022-07-03 09:52:27	ga_ls9c_ard_3-2-1_096072_2022-07-03_final.stac-item
2022-07-19 09:52:27	ga_ls9c_ard_3-2-1_096072_2022-07-19_final.stac-item
2022-07-28 09:46:25	ga_ls9c_ard_3-2-1_095072_2022-07-28_final.stac-item
2022-08-04 09:51:53	ga_ls9c_ard_3-2-1_096070_2022-08-04_final.stac-item
2022-08-20 09:52:00	ga_ls9c_ard_3-2-1_096070_2022-08-20_final.stac-item
2022-09-14 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-09-14_final.stac-item
2022-09-21 09:52:07	ga_ls9c_ard_3-2-1_096070_2022-09-21_final.stac-item
2022-09-21 09:52:31	ga_ls9c_ard_3-2-1_096071_2022-09-21_final.stac-item
2022-10-07 09:52:08	ga_ls9c_ard_3-2-1_096070_2022-10-07_final.stac-item
2022-10-23 09:52:39	ga_ls9c_ard_3-2-1_096071_2022-10-23_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-08 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-11-08_final.stac-item
2022-11-08 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-08_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-11-24 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-24_final.stac-item
2022-11-24 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-11-24_final.stac-item
2022-11-24 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-24_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-10 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-12-10_final.stac-item
2022-12-19 09:46:50	ga_ls9c_ard_3-2-1_095072_2022-12-19_final.stac-item
2022-12-26 09:52:12	ga_ls9c_ard_3-2-1_096070_2022-12-26_final.stac-item
2022-12-26 09:53:00	ga_ls9c_ard_3-2-1_096072_2022-12-26_final.stac-item
2023-01-04 09:46:52	ga_ls9c_ard_3-2-1_095072_2023-01-04_final.stac-item
2023-01-11 09:52:37	ga_ls9c_ard_3-2-1_096071_2023-01-11_final.stac-item
2023-01-11 09:53:01	ga_ls9c_ard_3-2-1_096072_2023-01-11_final.stac-item
2023-01-20 09:46:41	ga_ls9c_ard_3-2-1_095072_2023-01-20_final.stac-item
2023-01-27 09:52:11	ga_ls9c_ard_3-2-1_096070_2023-01-27_final.stac-item
2023-01-27 09:52:35	ga_ls9c_ard_3-2-1_096071_2023-01-27_final.stac-item
2023-01-27 09:52:59	ga_ls9c_ard_3-2-1_096072_2023-01-27_final.stac-item
2023-02-05 09:46:54	ga_ls9c_ard_3-2-1_095072_2023-02-05_final.stac-item
2023-02-21 09:46:44	ga_ls9c_ard_3-2-1_095072_2023-02-21_final.stac-item
2023-03-09 09:46:33	ga_ls9c_ard_3-2-1_095072_2023-03-09_final.stac-item
2023-03-16 09:52:20	ga_ls9c_ard_3-2-1_096071_2023-03-16_final.stac-item
2023-03-16 09:52:44	ga_ls9c_ard_3-2-1_096072_2023-03-16_final.stac-item
2023-03-25 09:46:27	ga_ls9c_ard_3-2-1_095072_2023-03-25_final.stac-item
2023-04-01 09:51:45	ga_ls9c_ard_3-2-1_096070_2023-04-01_final.stac-item
2023-04-01 09:52:08	ga_ls9c_ard_3-2-1_096071_2023-04-01_final.stac-item
2023-04-01 09:52:32	ga_ls9c_ard_3-2-1_096072_2023-04-01_final.stac-item
2023-04-10 09:46:19	ga_ls9c_ard_3-2-1_095072_2023-04-10_final.stac-item
2023-04-17 09:51:38	ga_ls9c_ard_3-2-1_096070_2023-04-17_final.stac-item
2023-04-17 09:52:26	ga_ls9c_ard_3-2-1_096072_2023-04-17_final.stac-item
2023-05-03 09:51:28	ga_ls9c_ard_3-2-1_096070_2023-05-03_final.stac-item
2023-05-03 09:51:52	ga_ls9c_ard_3-2-1_096071_2023-05-03_final.stac-item
2023-05-03 09:52:16	ga_ls9c_ard_3-2-1_096072_2023-05-03_final.stac-item
2023-05-19 09:51:21	ga_ls9c_ard_3-2-1_096070_2023-05-19_final.stac-item
2023-05-19 09:52:09	ga_ls9c_ard_3-2-1_096072_2023-05-19_final.stac-item
2023-06-04 09:51:15	ga_ls9c_ard_3-2-1_096070_2023-06-04_final.stac-item
2023-06-04 09:51:38	ga_ls9c_ard_3-2-1_096071_2023-06-04_final.stac-item
2023-06-20 09:51:07	ga_ls9c_ard_3-2-1_096070_2023-06-20_final.stac-item
2023-06-20 09:51:31	ga_ls9c_ard_3-2-1_096071_2023-06-20_final.stac-item
2023-06-29 09:45:49	ga_ls9c_ard_3-2-1_095072_2023-06-29_final.stac-item
2023-07-06 09:51:19	ga_ls9c_ard_3-2-1_096070_2023-07-06_final.stac-item
2023-07-06 09:52:07	ga_ls9c_ard_3-2-1_096072_2023-07-06_final.stac-item
2023-07-22 09:51:47	ga_ls9c_ard_3-2-1_096071_2023-07-22_final.stac-item
2023-08-07 09:51:57	ga_ls9c_ard_3-2-1_096071_2023-08-07_final.stac-item
2023-09-08 09:51:49	ga_ls9c_ard_3-2-1_096070_2023-09-08_final.stac-item
2023-09-24 09:52:14	ga_ls9c_ard_3-2-1_096071_2023-09-24_final.stac-item
2023-10-10 09:52:21	ga_ls9c_ard_3-2-1_096071_2023-10-10_final.stac-item
2023-10-26 09:52:25	ga_ls9c_ard_3-2-1_096071_2023-10-26_final.stac-item
2023-11-11 09:52:22	ga_ls9c_ard_3-2-1_096071_2023-11-11_final.stac-item
2023-11-27 09:52:30	ga_ls9c_ard_3-2-1_096071_2023-11-27_final.stac-item
2023-12-13 09:52:28	ga_ls9c_ard_3-2-1_096071_2023-12-13_final.stac-item
2023-12-29 09:52:30	ga_ls9c_ard_3-2-1_096071_2023-12-29_final.stac-item
2024-01-14 09:52:28	ga_ls9c_ard_3-2-1_096071_2024-01-14_final.stac-item
2024-01-30 09:52:28	ga_ls9c_ard_3-2-1_096071_2024-01-30_final.stac-item
2024-02-15 09:52:26	ga_ls9c_ard_3-2-1_096071_2024-02-15_final.stac-item
2024-03-02 09:52:21	ga_ls9c_ard_3-2-1_096071_2024-03-02_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