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
2021-12-04 11:03:22	ga_ls9c_ard_3-2-1_107078_2021-12-04_final.stac-item
2021-12-11 11:08:41	ga_ls9c_ard_3-2-1_108076_2021-12-11_final.stac-item
2021-12-27 11:09:26	ga_ls9c_ard_3-2-1_108078_2021-12-27_final.stac-item
2022-01-12 11:08:35	ga_ls9c_ard_3-2-1_108076_2022-01-12_final.stac-item
2022-01-12 11:09:23	ga_ls9c_ard_3-2-1_108078_2022-01-12_final.stac-item
2022-01-28 11:08:37	ga_ls9c_ard_3-2-1_108076_2022-01-28_final.stac-item
2022-01-28 11:10:13	ga_ls9c_ard_3-2-1_108080_2022-01-28_final.stac-item
2022-02-13 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-02-13_final.stac-item
2022-02-13 11:09:21	ga_ls9c_ard_3-2-1_108078_2022-02-13_final.stac-item
2022-03-01 11:08:22	ga_ls9c_ard_3-2-1_108076_2022-03-01_final.stac-item
2022-03-01 11:09:10	ga_ls9c_ard_3-2-1_108078_2022-03-01_final.stac-item
2022-04-02 11:08:17	ga_ls9c_ard_3-2-1_108076_2022-04-02_final.stac-item
2022-04-02 11:09:05	ga_ls9c_ard_3-2-1_108078_2022-04-02_final.stac-item
2022-04-16 11:17:45	ga_ls9c_ard_3-2-1_110069_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
2022-05-04 11:08:04	ga_ls9c_ard_3-2-1_108076_2022-05-04_final.stac-item
2022-05-04 11:08:52	ga_ls9c_ard_3-2-1_108078_2022-05-04_final.stac-item
2022-05-18 11:17:27	ga_ls9c_ard_3-2-1_110069_2022-05-18_final.stac-item
2022-05-20 11:07:51	ga_ls9c_ard_3-2-1_108076_2022-05-20_final.stac-item
2022-05-20 11:08:39	ga_ls9c_ard_3-2-1_108078_2022-05-20_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-05 11:07:53	ga_ls9c_ard_3-2-1_108076_2022-06-05_final.stac-item
2022-06-05 11:08:40	ga_ls9c_ard_3-2-1_108078_2022-06-05_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-21 11:08:06	ga_ls9c_ard_3-2-1_108076_2022-06-21_final.stac-item
2022-06-30 11:02:50	ga_ls9c_ard_3-2-1_107078_2022-06-30_final.stac-item
2022-07-07 11:08:11	ga_ls9c_ard_3-2-1_108076_2022-07-07_final.stac-item
2022-07-07 11:08:59	ga_ls9c_ard_3-2-1_108078_2022-07-07_final.stac-item
2022-07-23 11:08:17	ga_ls9c_ard_3-2-1_108076_2022-07-23_final.stac-item
2022-07-23 11:09:05	ga_ls9c_ard_3-2-1_108078_2022-07-23_final.stac-item
2022-08-01 11:03:01	ga_ls9c_ard_3-2-1_107078_2022-08-01_final.stac-item
2022-08-08 11:08:29	ga_ls9c_ard_3-2-1_108076_2022-08-08_final.stac-item
2022-08-08 11:09:17	ga_ls9c_ard_3-2-1_108078_2022-08-08_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-08-24 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-08-24_final.stac-item
2022-08-24 11:09:22	ga_ls9c_ard_3-2-1_108078_2022-08-24_final.stac-item
2022-09-09 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-09-09_final.stac-item
2022-09-09 11:09:22	ga_ls9c_ard_3-2-1_108078_2022-09-09_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-09-25 11:08:42	ga_ls9c_ard_3-2-1_108076_2022-09-25_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 11:10:17	ga_ls9c_ard_3-2-1_108080_2022-09-25_final.stac-item
2022-10-11 11:09:32	ga_ls9c_ard_3-2-1_108078_2022-10-11_final.stac-item
2022-10-20 11:03:25	ga_ls9c_ard_3-2-1_107078_2022-10-20_final.stac-item
2022-10-27 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-10-27_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-21 11:03:26	ga_ls9c_ard_3-2-1_107078_2022-11-21_final.stac-item
2022-11-28 11:08:46	ga_ls9c_ard_3-2-1_108076_2022-11-28_final.stac-item
2022-11-28 11:09:34	ga_ls9c_ard_3-2-1_108078_2022-11-28_final.stac-item
2022-12-14 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-12-14_final.stac-item
2022-12-14 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-14_final.stac-item
2022-12-28 11:18:20	ga_ls9c_ard_3-2-1_110069_2022-12-28_final.stac-item
2022-12-30 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-30_final.stac-item
2023-01-13 11:18:19	ga_ls9c_ard_3-2-1_110069_2023-01-13_final.stac-item
2023-01-15 11:08:44	ga_ls9c_ard_3-2-1_108076_2023-01-15_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-31 11:08:48	ga_ls9c_ard_3-2-1_108076_2023-01-31_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 11:12:14	ga_ls9c_ard_3-2-1_109069_2023-02-07_final.stac-item
2023-02-09 11:03:28	ga_ls9c_ard_3-2-1_107078_2023-02-09_final.stac-item
2023-02-16 11:08:47	ga_ls9c_ard_3-2-1_108076_2023-02-16_final.stac-item
2023-02-16 11:09:35	ga_ls9c_ard_3-2-1_108078_2023-02-16_final.stac-item
2023-02-25 11:04:01	ga_ls9c_ard_3-2-1_107080_2023-02-25_final.stac-item
2023-03-04 11:08:35	ga_ls9c_ard_3-2-1_108076_2023-03-04_final.stac-item
2023-03-04 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-03-04_final.stac-item
2023-03-04 11:10:10	ga_ls9c_ard_3-2-1_108080_2023-03-04_final.stac-item
2023-03-18 11:18:03	ga_ls9c_ard_3-2-1_110069_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
2023-03-29 11:03:43	ga_ls9c_ard_3-2-1_107080_2023-03-29_final.stac-item
2023-04-03 11:17:52	ga_ls9c_ard_3-2-1_110069_2023-04-03_final.stac-item
2023-04-05 11:08:18	ga_ls9c_ard_3-2-1_108076_2023-04-05_final.stac-item
2023-04-05 11:09:53	ga_ls9c_ard_3-2-1_108080_2023-04-05_final.stac-item
2023-04-19 11:17:46	ga_ls9c_ard_3-2-1_110069_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
2023-05-07 11:08:47	ga_ls9c_ard_3-2-1_108078_2023-05-07_final.stac-item
2023-05-23 11:07:50	ga_ls9c_ard_3-2-1_108076_2023-05-23_final.stac-item
2023-05-23 11:08:38	ga_ls9c_ard_3-2-1_108078_2023-05-23_final.stac-item
2023-06-01 11:02:26	ga_ls9c_ard_3-2-1_107078_2023-06-01_final.stac-item
2023-06-08 11:07:46	ga_ls9c_ard_3-2-1_108076_2023-06-08_final.stac-item
2023-06-08 11:08:34	ga_ls9c_ard_3-2-1_108078_2023-06-08_final.stac-item
2023-06-08 11:09:22	ga_ls9c_ard_3-2-1_108080_2023-06-08_final.stac-item
2023-06-17 11:02:17	ga_ls9c_ard_3-2-1_107078_2023-06-17_final.stac-item
2023-06-24 11:08:28	ga_ls9c_ard_3-2-1_108078_2023-06-24_final.stac-item
2023-07-03 11:02:28	ga_ls9c_ard_3-2-1_107078_2023-07-03_final.stac-item
2023-07-10 11:08:43	ga_ls9c_ard_3-2-1_108078_2023-07-10_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-08-11 11:08:07	ga_ls9c_ard_3-2-1_108076_2023-08-11_final.stac-item
2023-08-27 11:08:15	ga_ls9c_ard_3-2-1_108076_2023-08-27_final.stac-item
2023-08-27 11:09:03	ga_ls9c_ard_3-2-1_108078_2023-08-27_final.stac-item
2023-09-05 11:02:57	ga_ls9c_ard_3-2-1_107078_2023-09-05_final.stac-item
2023-09-12 11:08:24	ga_ls9c_ard_3-2-1_108076_2023-09-12_final.stac-item
2023-09-12 11:10:00	ga_ls9c_ard_3-2-1_108080_2023-09-12_final.stac-item
2023-09-21 11:03:50	ga_ls9c_ard_3-2-1_107080_2023-09-21_final.stac-item
2023-09-26 11:17:56	ga_ls9c_ard_3-2-1_110069_2023-09-26_final.stac-item
2023-09-28 11:09:56	ga_ls9c_ard_3-2-1_108080_2023-09-28_final.stac-item
2023-10-07 11:03:53	ga_ls9c_ard_3-2-1_107080_2023-10-07_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2024-02-10 11:12:02	ga_ls9c_ard_3-2-1_109069_2024-02-10_final.stac-item
2024-03-13 11:11:54	ga_ls9c_ard_3-2-1_109069_2024-03-13_final.stac-item
2024-04-21 11:17:38	ga_ls9c_ard_3-2-1_110069_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