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
2021-11-05 09:35:01	ga_ls9c_ard_3-2-1_093072_2021-11-05_final.stac-item
2021-11-10 09:37:30	ga_ls9c_ard_3-2-1_094072_2021-11-10_final.stac-item
2021-11-19 10:41:08	ga_ls9c_ard_3-2-1_104072_2021-11-19_final.stac-item
2021-11-25 09:44:52	ga_ls9c_ard_3-2-1_095072_2021-11-25_final.stac-item
2021-12-16 09:46:41	ga_ls9c_ard_3-2-1_095072_2021-12-16_final.stac-item
2021-12-24 10:36:08	ga_ls9c_ard_3-2-1_103072_2021-12-24_final.stac-item
2022-01-03 09:34:19	ga_ls9c_ard_3-2-1_093072_2022-01-03_final.stac-item
2022-01-09 10:35:42	ga_ls9c_ard_3-2-1_103071_2022-01-09_final.stac-item
2022-01-10 09:40:28	ga_ls9c_ard_3-2-1_094072_2022-01-10_final.stac-item
2022-01-18 10:29:31	ga_ls9c_ard_3-2-1_102071_2022-01-18_final.stac-item
2022-01-19 11:12:47	ga_ls9c_ard_3-2-1_109071_2022-01-19_final.stac-item
2022-01-26 09:40:30	ga_ls9c_ard_3-2-1_094072_2022-01-26_final.stac-item
2022-02-02 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-02-02_final.stac-item
2022-02-03 10:29:32	ga_ls9c_ard_3-2-1_102071_2022-02-03_final.stac-item
2022-02-10 10:35:41	ga_ls9c_ard_3-2-1_103071_2022-02-10_final.stac-item
2022-02-15 10:54:35	ga_ls9c_ard_3-2-1_106072_2022-02-15_final.stac-item
2022-02-19 10:29:25	ga_ls9c_ard_3-2-1_102071_2022-02-19_final.stac-item
2022-02-20 11:12:40	ga_ls9c_ard_3-2-1_109071_2022-02-20_final.stac-item
2022-02-26 10:35:31	ga_ls9c_ard_3-2-1_103071_2022-02-26_final.stac-item
2022-03-05 10:42:03	ga_ls9c_ard_3-2-1_104072_2022-03-05_final.stac-item
2022-03-06 09:46:26	ga_ls9c_ard_3-2-1_095072_2022-03-06_final.stac-item
2022-03-24 11:12:30	ga_ls9c_ard_3-2-1_109071_2022-03-24_final.stac-item
2022-03-30 10:35:23	ga_ls9c_ard_3-2-1_103071_2022-03-30_final.stac-item
2022-04-25 11:12:17	ga_ls9c_ard_3-2-1_109071_2022-04-25_final.stac-item
2022-05-26 10:28:46	ga_ls9c_ard_3-2-1_102071_2022-05-26_final.stac-item
2022-06-02 10:34:58	ga_ls9c_ard_3-2-1_103071_2022-06-02_final.stac-item
2022-06-03 09:39:45	ga_ls9c_ard_3-2-1_094072_2022-06-03_final.stac-item
2022-06-07 10:53:55	ga_ls9c_ard_3-2-1_106072_2022-06-07_final.stac-item
2022-06-09 10:41:34	ga_ls9c_ard_3-2-1_104072_2022-06-09_final.stac-item
2022-06-10 09:45:57	ga_ls9c_ard_3-2-1_095072_2022-06-10_final.stac-item
2022-06-12 11:12:06	ga_ls9c_ard_3-2-1_109071_2022-06-12_final.stac-item
2022-06-18 10:35:30	ga_ls9c_ard_3-2-1_103072_2022-06-18_final.stac-item
2022-06-26 09:46:17	ga_ls9c_ard_3-2-1_095072_2022-06-26_final.stac-item
2022-06-28 09:33:55	ga_ls9c_ard_3-2-1_093072_2022-06-28_final.stac-item
2022-06-28 11:12:25	ga_ls9c_ard_3-2-1_109071_2022-06-28_final.stac-item
2022-07-04 10:35:43	ga_ls9c_ard_3-2-1_103072_2022-07-04_final.stac-item
2022-07-11 10:41:51	ga_ls9c_ard_3-2-1_104072_2022-07-11_final.stac-item
2022-07-12 09:46:13	ga_ls9c_ard_3-2-1_095072_2022-07-12_final.stac-item
2022-07-13 10:29:04	ga_ls9c_ard_3-2-1_102071_2022-07-13_final.stac-item
2022-07-13 10:29:28	ga_ls9c_ard_3-2-1_102072_2022-07-13_final.stac-item
2022-07-20 10:35:44	ga_ls9c_ard_3-2-1_103072_2022-07-20_final.stac-item
2022-07-21 09:40:08	ga_ls9c_ard_3-2-1_094072_2022-07-21_final.stac-item
2022-07-25 10:54:21	ga_ls9c_ard_3-2-1_106072_2022-07-25_final.stac-item
2022-07-28 09:46:25	ga_ls9c_ard_3-2-1_095072_2022-07-28_final.stac-item
2022-07-29 10:29:41	ga_ls9c_ard_3-2-1_102072_2022-07-29_final.stac-item
2022-07-30 11:12:34	ga_ls9c_ard_3-2-1_109071_2022-07-30_final.stac-item
2022-08-03 10:48:18	ga_ls9c_ard_3-2-1_105072_2022-08-03_final.stac-item
2022-08-06 09:40:21	ga_ls9c_ard_3-2-1_094072_2022-08-06_final.stac-item
2022-08-13 09:46:35	ga_ls9c_ard_3-2-1_095072_2022-08-13_final.stac-item
2022-08-14 10:29:27	ga_ls9c_ard_3-2-1_102071_2022-08-14_final.stac-item
2022-08-14 10:29:51	ga_ls9c_ard_3-2-1_102072_2022-08-14_final.stac-item
2022-08-15 09:34:14	ga_ls9c_ard_3-2-1_093072_2022-08-15_final.stac-item
2022-08-22 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-08-22_final.stac-item
2022-08-26 10:54:37	ga_ls9c_ard_3-2-1_106072_2022-08-26_final.stac-item
2022-08-28 10:42:16	ga_ls9c_ard_3-2-1_104072_2022-08-28_final.stac-item
2022-08-30 10:29:54	ga_ls9c_ard_3-2-1_102072_2022-08-30_final.stac-item
2022-08-31 09:34:17	ga_ls9c_ard_3-2-1_093072_2022-08-31_final.stac-item
2022-09-11 10:54:38	ga_ls9c_ard_3-2-1_106072_2022-09-11_final.stac-item
2022-09-13 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-09-13_final.stac-item
2022-09-14 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-09-14_final.stac-item
2022-09-15 10:29:57	ga_ls9c_ard_3-2-1_102072_2022-09-15_final.stac-item
2022-09-23 09:40:34	ga_ls9c_ard_3-2-1_094072_2022-09-23_final.stac-item
2022-10-01 10:29:38	ga_ls9c_ard_3-2-1_102071_2022-10-01_final.stac-item
2022-10-02 11:12:53	ga_ls9c_ard_3-2-1_109071_2022-10-02_final.stac-item
2022-10-08 10:35:49	ga_ls9c_ard_3-2-1_103071_2022-10-08_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-10-16 09:46:51	ga_ls9c_ard_3-2-1_095072_2022-10-16_final.stac-item
2022-10-18 11:12:59	ga_ls9c_ard_3-2-1_109071_2022-10-18_final.stac-item
2022-10-25 09:40:41	ga_ls9c_ard_3-2-1_094072_2022-10-25_final.stac-item
2022-11-01 09:46:50	ga_ls9c_ard_3-2-1_095072_2022-11-01_final.stac-item
2022-11-03 09:34:27	ga_ls9c_ard_3-2-1_093072_2022-11-03_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-11-19 09:34:31	ga_ls9c_ard_3-2-1_093072_2022-11-19_final.stac-item
2022-11-19 11:13:00	ga_ls9c_ard_3-2-1_109071_2022-11-19_final.stac-item
2022-11-25 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-11-25_final.stac-item
2022-11-26 09:40:40	ga_ls9c_ard_3-2-1_094072_2022-11-26_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-05 09:34:28	ga_ls9c_ard_3-2-1_093072_2022-12-05_final.stac-item
2022-12-20 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-20_final.stac-item
2022-12-27 10:35:52	ga_ls9c_ard_3-2-1_103071_2022-12-27_final.stac-item
2022-12-28 09:40:39	ga_ls9c_ard_3-2-1_094072_2022-12-28_final.stac-item
2023-01-05 10:29:43	ga_ls9c_ard_3-2-1_102071_2023-01-05_final.stac-item
2023-01-28 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-28_final.stac-item
2023-02-07 09:34:33	ga_ls9c_ard_3-2-1_093072_2023-02-07_final.stac-item
2023-02-21 09:46:44	ga_ls9c_ard_3-2-1_095072_2023-02-21_final.stac-item
2023-03-01 10:35:42	ga_ls9c_ard_3-2-1_103071_2023-03-01_final.stac-item
2023-03-17 10:35:35	ga_ls9c_ard_3-2-1_103071_2023-03-17_final.stac-item
2023-04-11 10:29:10	ga_ls9c_ard_3-2-1_102071_2023-04-11_final.stac-item
2023-04-12 11:12:25	ga_ls9c_ard_3-2-1_109071_2023-04-12_final.stac-item
2023-04-27 10:29:03	ga_ls9c_ard_3-2-1_102071_2023-04-27_final.stac-item
2023-04-28 11:12:18	ga_ls9c_ard_3-2-1_109071_2023-04-28_final.stac-item
2023-05-04 10:35:06	ga_ls9c_ard_3-2-1_103071_2023-05-04_final.stac-item
2023-05-13 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-14 11:12:09	ga_ls9c_ard_3-2-1_109071_2023-05-14_final.stac-item
2023-05-29 10:28:45	ga_ls9c_ard_3-2-1_102071_2023-05-29_final.stac-item
2023-06-15 11:11:51	ga_ls9c_ard_3-2-1_109071_2023-06-15_final.stac-item
2023-06-22 09:39:33	ga_ls9c_ard_3-2-1_094072_2023-06-22_final.stac-item
2023-06-29 09:45:49	ga_ls9c_ard_3-2-1_095072_2023-06-29_final.stac-item
2023-07-01 11:12:00	ga_ls9c_ard_3-2-1_109071_2023-07-01_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years