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
2021-12-17 10:31:32	ga_ls9c_ard_3-2-1_102076_2021-12-17_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2022-01-02 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-01-02_final.stac-item
2022-01-02 10:32:20	ga_ls9c_ard_3-2-1_102078_2022-01-02_final.stac-item
2022-01-18 10:32:19	ga_ls9c_ard_3-2-1_102078_2022-01-18_final.stac-item
2022-01-25 10:37:43	ga_ls9c_ard_3-2-1_103076_2022-01-25_final.stac-item
2022-02-03 10:31:32	ga_ls9c_ard_3-2-1_102076_2022-02-03_final.stac-item
2022-02-19 10:31:25	ga_ls9c_ard_3-2-1_102076_2022-02-19_final.stac-item
2022-02-19 10:32:13	ga_ls9c_ard_3-2-1_102078_2022-02-19_final.stac-item
2022-03-07 10:31:17	ga_ls9c_ard_3-2-1_102076_2022-03-07_final.stac-item
2022-03-07 10:32:05	ga_ls9c_ard_3-2-1_102078_2022-03-07_final.stac-item
2022-03-23 10:31:14	ga_ls9c_ard_3-2-1_102076_2022-03-23_final.stac-item
2022-03-23 10:32:02	ga_ls9c_ard_3-2-1_102078_2022-03-23_final.stac-item
2022-04-08 10:31:11	ga_ls9c_ard_3-2-1_102076_2022-04-08_final.stac-item
2022-04-08 10:31:59	ga_ls9c_ard_3-2-1_102078_2022-04-08_final.stac-item
2022-04-15 10:37:17	ga_ls9c_ard_3-2-1_103076_2022-04-15_final.stac-item
2022-04-24 10:31:01	ga_ls9c_ard_3-2-1_102076_2022-04-24_final.stac-item
2022-04-24 10:31:49	ga_ls9c_ard_3-2-1_102078_2022-04-24_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-05-17 10:37:00	ga_ls9c_ard_3-2-1_103076_2022-05-17_final.stac-item
2022-05-26 10:31:34	ga_ls9c_ard_3-2-1_102078_2022-05-26_final.stac-item
2022-06-02 10:36:58	ga_ls9c_ard_3-2-1_103076_2022-06-02_final.stac-item
2022-06-11 10:30:49	ga_ls9c_ard_3-2-1_102076_2022-06-11_final.stac-item
2022-06-18 10:37:06	ga_ls9c_ard_3-2-1_103076_2022-06-18_final.stac-item
2022-06-27 10:31:09	ga_ls9c_ard_3-2-1_102076_2022-06-27_final.stac-item
2022-07-13 10:31:04	ga_ls9c_ard_3-2-1_102076_2022-07-13_final.stac-item
2022-07-29 10:31:17	ga_ls9c_ard_3-2-1_102076_2022-07-29_final.stac-item
2022-07-29 10:32:53	ga_ls9c_ard_3-2-1_102080_2022-07-29_final.stac-item
2022-08-14 10:31:27	ga_ls9c_ard_3-2-1_102076_2022-08-14_final.stac-item
2022-08-30 10:31:30	ga_ls9c_ard_3-2-1_102076_2022-08-30_final.stac-item
2022-08-30 10:32:18	ga_ls9c_ard_3-2-1_102078_2022-08-30_final.stac-item
2022-09-15 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-09-15_final.stac-item
2022-09-15 10:32:21	ga_ls9c_ard_3-2-1_102078_2022-09-15_final.stac-item
2022-10-01 10:32:25	ga_ls9c_ard_3-2-1_102078_2022-10-01_final.stac-item
2022-10-08 10:37:48	ga_ls9c_ard_3-2-1_103076_2022-10-08_final.stac-item
2022-10-17 10:31:42	ga_ls9c_ard_3-2-1_102076_2022-10-17_final.stac-item
2022-10-17 10:32:30	ga_ls9c_ard_3-2-1_102078_2022-10-17_final.stac-item
2022-10-24 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-10-24_final.stac-item
2022-11-02 10:31:40	ga_ls9c_ard_3-2-1_102076_2022-11-02_final.stac-item
2022-11-09 10:37:53	ga_ls9c_ard_3-2-1_103076_2022-11-09_final.stac-item
2022-11-18 10:31:44	ga_ls9c_ard_3-2-1_102076_2022-11-18_final.stac-item
2022-11-18 10:32:32	ga_ls9c_ard_3-2-1_102078_2022-11-18_final.stac-item
2022-11-25 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-11-25_final.stac-item
2022-12-04 10:31:41	ga_ls9c_ard_3-2-1_102076_2022-12-04_final.stac-item
2022-12-04 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-04_final.stac-item
2022-12-11 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-12-11_final.stac-item
2022-12-20 10:31:41	ga_ls9c_ard_3-2-1_102076_2022-12-20_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-20_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2023-01-05 10:31:43	ga_ls9c_ard_3-2-1_102076_2023-01-05_final.stac-item
2023-01-05 10:32:31	ga_ls9c_ard_3-2-1_102078_2023-01-05_final.stac-item
2023-01-12 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-12_final.stac-item
2023-01-21 10:31:33	ga_ls9c_ard_3-2-1_102076_2023-01-21_final.stac-item
2023-01-21 10:32:21	ga_ls9c_ard_3-2-1_102078_2023-01-21_final.stac-item
2023-01-28 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-28_final.stac-item
2023-02-06 10:31:46	ga_ls9c_ard_3-2-1_102076_2023-02-06_final.stac-item
2023-02-06 10:32:34	ga_ls9c_ard_3-2-1_102078_2023-02-06_final.stac-item
2023-02-13 10:37:56	ga_ls9c_ard_3-2-1_103076_2023-02-13_final.stac-item
2023-02-22 10:31:34	ga_ls9c_ard_3-2-1_102076_2023-02-22_final.stac-item
2023-02-22 10:32:22	ga_ls9c_ard_3-2-1_102078_2023-02-22_final.stac-item
2023-03-01 10:37:42	ga_ls9c_ard_3-2-1_103076_2023-03-01_final.stac-item
2023-03-03 10:26:55	ga_ls9c_ard_3-2-1_101080_2023-03-03_final.stac-item
2023-03-10 10:32:11	ga_ls9c_ard_3-2-1_102078_2023-03-10_final.stac-item
2023-03-26 10:31:18	ga_ls9c_ard_3-2-1_102076_2023-03-26_final.stac-item
2023-03-26 10:32:05	ga_ls9c_ard_3-2-1_102078_2023-03-26_final.stac-item
2023-04-02 10:37:24	ga_ls9c_ard_3-2-1_103076_2023-04-02_final.stac-item
2023-04-04 10:26:38	ga_ls9c_ard_3-2-1_101080_2023-04-04_final.stac-item
2023-04-11 10:31:09	ga_ls9c_ard_3-2-1_102076_2023-04-11_final.stac-item
2023-04-11 10:31:57	ga_ls9c_ard_3-2-1_102078_2023-04-11_final.stac-item
2023-04-18 10:37:18	ga_ls9c_ard_3-2-1_103076_2023-04-18_final.stac-item
2023-04-27 10:31:03	ga_ls9c_ard_3-2-1_102076_2023-04-27_final.stac-item
2023-04-27 10:31:51	ga_ls9c_ard_3-2-1_102078_2023-04-27_final.stac-item
2023-05-04 10:37:06	ga_ls9c_ard_3-2-1_103076_2023-05-04_final.stac-item
2023-05-13 10:30:54	ga_ls9c_ard_3-2-1_102076_2023-05-13_final.stac-item
2023-05-13 10:31:41	ga_ls9c_ard_3-2-1_102078_2023-05-13_final.stac-item
2023-05-20 10:37:00	ga_ls9c_ard_3-2-1_103076_2023-05-20_final.stac-item
2023-05-29 10:30:44	ga_ls9c_ard_3-2-1_102076_2023-05-29_final.stac-item
2023-05-29 10:31:32	ga_ls9c_ard_3-2-1_102078_2023-05-29_final.stac-item
2023-06-05 10:36:53	ga_ls9c_ard_3-2-1_103076_2023-06-05_final.stac-item
2023-06-14 10:30:36	ga_ls9c_ard_3-2-1_102076_2023-06-14_final.stac-item
2023-06-14 10:31:24	ga_ls9c_ard_3-2-1_102078_2023-06-14_final.stac-item
2023-06-14 10:32:12	ga_ls9c_ard_3-2-1_102080_2023-06-14_final.stac-item
2023-06-21 10:36:46	ga_ls9c_ard_3-2-1_103076_2023-06-21_final.stac-item
2023-06-30 10:30:43	ga_ls9c_ard_3-2-1_102076_2023-06-30_final.stac-item
2023-06-30 10:31:30	ga_ls9c_ard_3-2-1_102078_2023-06-30_final.stac-item
2023-07-07 10:36:59	ga_ls9c_ard_3-2-1_103076_2023-07-07_final.stac-item
2023-07-16 10:30:52	ga_ls9c_ard_3-2-1_102076_2023-07-16_final.stac-item
2023-08-01 10:30:58	ga_ls9c_ard_3-2-1_102076_2023-08-01_final.stac-item
2023-08-08 10:37:12	ga_ls9c_ard_3-2-1_103076_2023-08-08_final.stac-item
2023-08-17 10:31:01	ga_ls9c_ard_3-2-1_102076_2023-08-17_final.stac-item
2023-09-02 10:31:13	ga_ls9c_ard_3-2-1_102076_2023-09-02_final.stac-item
2023-09-09 10:37:29	ga_ls9c_ard_3-2-1_103076_2023-09-09_final.stac-item
2023-09-11 10:26:44	ga_ls9c_ard_3-2-1_101080_2023-09-11_final.stac-item
2023-09-18 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-09-18_final.stac-item
2023-09-18 10:32:56	ga_ls9c_ard_3-2-1_102080_2023-09-18_final.stac-item
2023-09-25 10:37:28	ga_ls9c_ard_3-2-1_103076_2023-09-25_final.stac-item
2023-10-04 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-10-04_final.stac-item
2023-10-11 10:37:37	ga_ls9c_ard_3-2-1_103076_2023-10-11_final.stac-item
2023-10-20 10:31:31	ga_ls9c_ard_3-2-1_102076_2023-10-20_final.stac-item
2024-02-09 10:31:34	ga_ls9c_ard_3-2-1_102076_2024-02-09_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