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
2021-11-03 09:58:09	ga_ls9c_ard_3-2-1_096083_2021-11-03_final.stac-item
2021-12-07 09:56:57	ga_ls9c_ard_3-2-1_096082_2021-12-07_final.stac-item
2021-12-07 09:57:21	ga_ls9c_ard_3-2-1_096083_2021-12-07_final.stac-item
2021-12-23 09:57:16	ga_ls9c_ard_3-2-1_096083_2021-12-23_final.stac-item
2022-01-01 09:51:29	ga_ls9c_ard_3-2-1_095084_2022-01-01_final.stac-item
2022-01-08 09:56:50	ga_ls9c_ard_3-2-1_096082_2022-01-08_final.stac-item
2022-01-08 09:57:14	ga_ls9c_ard_3-2-1_096083_2022-01-08_final.stac-item
2022-01-24 09:57:15	ga_ls9c_ard_3-2-1_096083_2022-01-24_final.stac-item
2022-01-24 09:57:39	ga_ls9c_ard_3-2-1_096084_2022-01-24_final.stac-item
2022-02-09 09:57:13	ga_ls9c_ard_3-2-1_096083_2022-02-09_final.stac-item
2022-02-18 09:51:22	ga_ls9c_ard_3-2-1_095084_2022-02-18_final.stac-item
2022-02-25 09:57:03	ga_ls9c_ard_3-2-1_096083_2022-02-25_final.stac-item
2022-02-25 09:57:27	ga_ls9c_ard_3-2-1_096084_2022-02-25_final.stac-item
2022-03-29 09:56:55	ga_ls9c_ard_3-2-1_096083_2022-03-29_final.stac-item
2022-04-14 09:56:50	ga_ls9c_ard_3-2-1_096083_2022-04-14_final.stac-item
2022-04-14 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-04-14_final.stac-item
2022-04-23 09:50:57	ga_ls9c_ard_3-2-1_095084_2022-04-23_final.stac-item
2022-04-30 09:56:19	ga_ls9c_ard_3-2-1_096082_2022-04-30_final.stac-item
2022-04-30 09:56:43	ga_ls9c_ard_3-2-1_096083_2022-04-30_final.stac-item
2022-05-16 09:56:33	ga_ls9c_ard_3-2-1_096083_2022-05-16_final.stac-item
2022-05-25 09:50:42	ga_ls9c_ard_3-2-1_095084_2022-05-25_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-06-01 09:56:06	ga_ls9c_ard_3-2-1_096082_2022-06-01_final.stac-item
2022-06-01 09:56:30	ga_ls9c_ard_3-2-1_096083_2022-06-01_final.stac-item
2022-06-10 09:50:44	ga_ls9c_ard_3-2-1_095084_2022-06-10_final.stac-item
2022-06-17 09:56:13	ga_ls9c_ard_3-2-1_096082_2022-06-17_final.stac-item
2022-06-17 09:56:37	ga_ls9c_ard_3-2-1_096083_2022-06-17_final.stac-item
2022-06-17 09:57:01	ga_ls9c_ard_3-2-1_096084_2022-06-17_final.stac-item
2022-06-26 09:51:05	ga_ls9c_ard_3-2-1_095084_2022-06-26_final.stac-item
2022-07-03 09:56:26	ga_ls9c_ard_3-2-1_096082_2022-07-03_final.stac-item
2022-07-03 09:56:50	ga_ls9c_ard_3-2-1_096083_2022-07-03_final.stac-item
2022-07-03 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-07-03_final.stac-item
2022-07-12 09:51:00	ga_ls9c_ard_3-2-1_095084_2022-07-12_final.stac-item
2022-07-19 09:56:27	ga_ls9c_ard_3-2-1_096082_2022-07-19_final.stac-item
2022-07-19 09:56:51	ga_ls9c_ard_3-2-1_096083_2022-07-19_final.stac-item
2022-07-19 09:57:15	ga_ls9c_ard_3-2-1_096084_2022-07-19_final.stac-item
2022-07-28 09:51:12	ga_ls9c_ard_3-2-1_095084_2022-07-28_final.stac-item
2022-08-04 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-08-04_final.stac-item
2022-08-04 09:57:04	ga_ls9c_ard_3-2-1_096083_2022-08-04_final.stac-item
2022-08-20 09:57:12	ga_ls9c_ard_3-2-1_096083_2022-08-20_final.stac-item
2022-09-05 09:56:48	ga_ls9c_ard_3-2-1_096082_2022-09-05_final.stac-item
2022-09-05 09:57:12	ga_ls9c_ard_3-2-1_096083_2022-09-05_final.stac-item
2022-09-21 09:57:18	ga_ls9c_ard_3-2-1_096083_2022-09-21_final.stac-item
2022-10-07 09:56:55	ga_ls9c_ard_3-2-1_096082_2022-10-07_final.stac-item
2022-10-07 09:57:19	ga_ls9c_ard_3-2-1_096083_2022-10-07_final.stac-item
2022-10-07 09:57:43	ga_ls9c_ard_3-2-1_096084_2022-10-07_final.stac-item
2022-10-23 09:57:02	ga_ls9c_ard_3-2-1_096082_2022-10-23_final.stac-item
2022-10-23 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-10-23_final.stac-item
2022-11-08 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-11-08_final.stac-item
2022-11-17 09:51:40	ga_ls9c_ard_3-2-1_095084_2022-11-17_final.stac-item
2022-11-24 09:57:02	ga_ls9c_ard_3-2-1_096082_2022-11-24_final.stac-item
2022-11-24 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-11-24_final.stac-item
2022-12-03 09:51:36	ga_ls9c_ard_3-2-1_095084_2022-12-03_final.stac-item
2022-12-10 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-12-10_final.stac-item
2022-12-10 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-12-10_final.stac-item
2022-12-19 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-12-19_final.stac-item
2022-12-26 09:56:59	ga_ls9c_ard_3-2-1_096082_2022-12-26_final.stac-item
2022-12-26 09:57:23	ga_ls9c_ard_3-2-1_096083_2022-12-26_final.stac-item
2023-01-04 09:51:39	ga_ls9c_ard_3-2-1_095084_2023-01-04_final.stac-item
2023-01-11 09:57:00	ga_ls9c_ard_3-2-1_096082_2023-01-11_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-11 09:57:48	ga_ls9c_ard_3-2-1_096084_2023-01-11_final.stac-item
2023-01-27 09:57:23	ga_ls9c_ard_3-2-1_096083_2023-01-27_final.stac-item
2023-02-12 09:57:28	ga_ls9c_ard_3-2-1_096083_2023-02-12_final.stac-item
2023-02-12 09:57:52	ga_ls9c_ard_3-2-1_096084_2023-02-12_final.stac-item
2023-03-16 09:57:07	ga_ls9c_ard_3-2-1_096083_2023-03-16_final.stac-item
2023-03-16 09:57:31	ga_ls9c_ard_3-2-1_096084_2023-03-16_final.stac-item
2023-03-25 09:51:15	ga_ls9c_ard_3-2-1_095084_2023-03-25_final.stac-item
2023-04-01 09:56:56	ga_ls9c_ard_3-2-1_096083_2023-04-01_final.stac-item
2023-04-01 09:57:20	ga_ls9c_ard_3-2-1_096084_2023-04-01_final.stac-item
2023-04-17 09:56:49	ga_ls9c_ard_3-2-1_096083_2023-04-17_final.stac-item
2023-04-17 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-04-17_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-05-03 09:56:39	ga_ls9c_ard_3-2-1_096083_2023-05-03_final.stac-item
2023-05-12 09:50:50	ga_ls9c_ard_3-2-1_095084_2023-05-12_final.stac-item
2023-05-19 09:56:32	ga_ls9c_ard_3-2-1_096083_2023-05-19_final.stac-item
2023-05-28 09:50:40	ga_ls9c_ard_3-2-1_095084_2023-05-28_final.stac-item
2023-06-04 09:56:26	ga_ls9c_ard_3-2-1_096083_2023-06-04_final.stac-item
2023-06-20 09:56:18	ga_ls9c_ard_3-2-1_096083_2023-06-20_final.stac-item
2023-07-06 09:56:31	ga_ls9c_ard_3-2-1_096083_2023-07-06_final.stac-item
2023-07-22 09:56:34	ga_ls9c_ard_3-2-1_096083_2023-07-22_final.stac-item
2023-08-07 09:56:44	ga_ls9c_ard_3-2-1_096083_2023-08-07_final.stac-item
2023-08-23 09:56:49	ga_ls9c_ard_3-2-1_096083_2023-08-23_final.stac-item
2023-09-08 09:57:00	ga_ls9c_ard_3-2-1_096083_2023-09-08_final.stac-item
2023-09-24 09:57:01	ga_ls9c_ard_3-2-1_096083_2023-09-24_final.stac-item
2023-10-10 09:57:08	ga_ls9c_ard_3-2-1_096083_2023-10-10_final.stac-item
2023-10-26 09:57:12	ga_ls9c_ard_3-2-1_096083_2023-10-26_final.stac-item
2023-11-11 09:57:09	ga_ls9c_ard_3-2-1_096083_2023-11-11_final.stac-item
2023-11-27 09:57:17	ga_ls9c_ard_3-2-1_096083_2023-11-27_final.stac-item
2023-12-13 09:57:16	ga_ls9c_ard_3-2-1_096083_2023-12-13_final.stac-item
2023-12-29 09:57:18	ga_ls9c_ard_3-2-1_096083_2023-12-29_final.stac-item
2024-01-14 09:57:15	ga_ls9c_ard_3-2-1_096083_2024-01-14_final.stac-item
2024-01-30 09:57:15	ga_ls9c_ard_3-2-1_096083_2024-01-30_final.stac-item
2024-02-15 09:57:13	ga_ls9c_ard_3-2-1_096083_2024-02-15_final.stac-item
2024-03-02 09:57:08	ga_ls9c_ard_3-2-1_096083_2024-03-02_final.stac-item
2024-03-18 09:57:08	ga_ls9c_ard_3-2-1_096083_2024-03-18_final.stac-item
2024-04-03 09:56:59	ga_ls9c_ard_3-2-1_096083_2024-04-03_final.stac-item
2024-04-19 09:56:46	ga_ls9c_ard_3-2-1_096083_2024-04-19_final.stac-item
2024-05-05 09:56:35	ga_ls9c_ard_3-2-1_096083_2024-05-05_final.stac-item
2024-05-21 09:56:26	ga_ls9c_ard_3-2-1_096083_2024-05-21_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