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
2021-11-02 10:56:03	ga_ls9c_ard_3-2-1_106081_2021-11-02_final.stac-item
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-03-06 09:47:38	ga_ls9c_ard_3-2-1_095075_2022-03-06_final.stac-item
2022-03-11 10:08:10	ga_ls9c_ard_3-2-1_098080_2022-03-11_final.stac-item
2022-04-18 09:31:40	ga_ls9c_ard_3-2-1_092082_2022-04-18_final.stac-item
2022-05-06 10:54:29	ga_ls9c_ard_3-2-1_106073_2022-05-06_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-05-23 11:40:45	ga_ls9c_ard_3-2-1_113081_2022-05-23_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-05-31 10:48:08	ga_ls9c_ard_3-2-1_105073_2022-05-31_final.stac-item
2022-06-12 11:11:42	ga_ls9c_ard_3-2-1_109070_2022-06-12_final.stac-item
2022-06-23 09:19:43	ga_ls9c_ard_3-2-1_090083_2022-06-22_final.stac-item
2022-06-25 10:44:18	ga_ls9c_ard_3-2-1_104078_2022-06-25_final.stac-item
2022-07-04 10:34:31	ga_ls9c_ard_3-2-1_103069_2022-07-04_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-08-05 10:34:45	ga_ls9c_ard_3-2-1_103069_2022-08-05_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-13 09:47:47	ga_ls9c_ard_3-2-1_095075_2022-08-13_final.stac-item
2022-08-31 11:13:10	ga_ls9c_ard_3-2-1_109072_2022-08-31_final.stac-item
2022-09-29 10:43:59	ga_ls9c_ard_3-2-1_104076_2022-09-29_final.stac-item
2022-10-05 10:08:05	ga_ls9c_ard_3-2-1_098079_2022-10-05_final.stac-item
2022-10-12 11:51:13	ga_ls9c_ard_3-2-1_115074_2022-10-12_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-11-13 10:11:59	ga_ls9c_ard_3-2-1_099073_2022-11-13_final.stac-item
2022-11-25 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-25_final.stac-item
2022-12-01 11:41:39	ga_ls9c_ard_3-2-1_113081_2022-12-01_final.stac-item
2022-12-04 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-04_final.stac-item
2022-12-14 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-14_final.stac-item
2022-12-17 10:00:00	ga_ls9c_ard_3-2-1_097074_2022-12-17_final.stac-item
2022-12-19 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-12-19_final.stac-item
2022-12-23 11:04:09	ga_ls9c_ard_3-2-1_107080_2022-12-23_final.stac-item
2023-01-01 10:57:38	ga_ls9c_ard_3-2-1_106079_2023-01-01_final.stac-item
2023-01-02 10:00:01	ga_ls9c_ard_3-2-1_097074_2023-01-02_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-24 11:01:19	ga_ls9c_ard_3-2-1_107073_2023-01-24_final.stac-item
2023-01-28 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-28_final.stac-item
2023-01-29 11:24:44	ga_ls9c_ard_3-2-1_110085_2023-01-29_final.stac-item
2023-01-31 11:10:00	ga_ls9c_ard_3-2-1_108079_2023-01-31_final.stac-item
2023-02-02 10:57:15	ga_ls9c_ard_3-2-1_106078_2023-02-02_final.stac-item
2023-02-07 09:38:56	ga_ls9c_ard_3-2-1_093083_2023-02-07_final.stac-item
2023-02-11 09:13:25	ga_ls9c_ard_3-2-1_089081_2023-02-10_final.stac-item
2023-02-12 09:56:40	ga_ls9c_ard_3-2-1_096081_2023-02-12_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-04-25 10:41:27	ga_ls9c_ard_3-2-1_104071_2023-04-25_final.stac-item
2023-04-26 11:28:17	ga_ls9c_ard_3-2-1_111080_2023-04-26_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-07-20 10:05:21	ga_ls9c_ard_3-2-1_098074_2023-07-20_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-24 11:20:41	ga_ls9c_ard_3-2-1_110077_2023-07-24_final.stac-item
2023-07-25 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-25_final.stac-item
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-08-02 11:12:38	ga_ls9c_ard_3-2-1_109072_2023-08-02_final.stac-item
2023-08-03 10:21:49	ga_ls9c_ard_3-2-1_100084_2023-08-03_final.stac-item
2023-08-04 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-08-04_final.stac-item
2023-08-04 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-08-04_final.stac-item
2023-08-05 11:46:46	ga_ls9c_ard_3-2-1_114080_2023-08-05_final.stac-item
2023-10-14 09:31:16	ga_ls9c_ard_3-2-1_092080_2023-10-14_final.stac-item
2023-10-14 11:10:33	ga_ls9c_ard_3-2-1_108081_2023-10-14_final.stac-item
2023-10-14 11:10:57	ga_ls9c_ard_3-2-1_108082_2023-10-14_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-16 10:57:01	ga_ls9c_ard_3-2-1_106078_2023-10-16_final.stac-item
2023-10-17 11:41:29	ga_ls9c_ard_3-2-1_113081_2023-10-17_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-19 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-10-19_final.stac-item
2023-10-22 10:17:57	ga_ls9c_ard_3-2-1_100073_2023-10-22_final.stac-item
2023-10-23 09:24:19	ga_ls9c_ard_3-2-1_091078_2023-10-22_final.stac-item
2023-10-23 11:03:12	ga_ls9c_ard_3-2-1_107078_2023-10-23_final.stac-item
2023-10-26 09:55:36	ga_ls9c_ard_3-2-1_096079_2023-10-26_final.stac-item
2023-10-26 11:34:53	ga_ls9c_ard_3-2-1_112080_2023-10-26_final.stac-item
2023-10-27 10:35:16	ga_ls9c_ard_3-2-1_103070_2023-10-27_final.stac-item
2023-10-27 10:38:27	ga_ls9c_ard_3-2-1_103078_2023-10-27_final.stac-item
2023-10-29 10:25:16	ga_ls9c_ard_3-2-1_101076_2023-10-29_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-11-01 10:56:55	ga_ls9c_ard_3-2-1_106078_2023-11-01_final.stac-item
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final.stac-item
2023-11-02 11:41:22	ga_ls9c_ard_3-2-1_113081_2023-11-02_final.stac-item
2023-11-03 10:45:20	ga_ls9c_ard_3-2-1_104080_2023-11-03_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-04 11:29:01	ga_ls9c_ard_3-2-1_111081_2023-11-04_final.stac-item
2023-11-14 10:24:27	ga_ls9c_ard_3-2-1_101074_2023-11-14_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-18 09:58:58	ga_ls9c_ard_3-2-1_097072_2023-11-18_final.stac-item
2023-11-18 09:59:22	ga_ls9c_ard_3-2-1_097073_2023-11-18_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-11-24 11:03:15	ga_ls9c_ard_3-2-1_107078_2023-11-24_final.stac-item
2023-11-24 11:04:03	ga_ls9c_ard_3-2-1_107080_2023-11-24_final.stac-item
2024-02-16 10:39:16	ga_ls9c_ard_3-2-1_103080_2024-02-16_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