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
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2021-11-19 09:06:03	ga_ls9c_ard_3-2-1_088081_2021-11-18_final.stac-item
2021-11-22 09:24:52	ga_ls9c_ard_3-2-1_091075_2021-11-21_final.stac-item
2021-12-04 09:24:29	ga_ls9c_ard_3-2-1_091078_2021-12-03_final.stac-item
2021-12-09 11:23:51	ga_ls9c_ard_3-2-1_110083_2021-12-09_final.stac-item
2021-12-25 09:41:19	ga_ls9c_ard_3-2-1_094074_2021-12-25_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2021-12-29 10:58:16	ga_ls9c_ard_3-2-1_106081_2021-12-29_final.stac-item
2022-01-04 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-01-04_final.stac-item
2022-01-30 10:58:15	ga_ls9c_ard_3-2-1_106081_2022-01-30_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-22 09:25:00	ga_ls9c_ard_3-2-1_091080_2022-02-21_final.stac-item
2022-02-23 10:10:15	ga_ls9c_ard_3-2-1_098085_2022-02-23_final.stac-item
2022-04-03 10:13:04	ga_ls9c_ard_3-2-1_099077_2022-04-03_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-16 09:40:51	ga_ls9c_ard_3-2-1_094074_2022-04-16_final.stac-item
2022-04-20 09:18:52	ga_ls9c_ard_3-2-1_090081_2022-04-19_final.stac-item
2022-04-28 10:05:06	ga_ls9c_ard_3-2-1_098073_2022-04-28_final.stac-item
2022-05-14 10:04:57	ga_ls9c_ard_3-2-1_098073_2022-05-14_final.stac-item
2022-05-27 09:36:20	ga_ls9c_ard_3-2-1_093079_2022-05-27_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-06-06 10:13:03	ga_ls9c_ard_3-2-1_099078_2022-06-06_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-25 09:19:52	ga_ls9c_ard_3-2-1_090083_2022-07-24_final.stac-item
2022-09-19 10:07:16	ga_ls9c_ard_3-2-1_098077_2022-09-19_final.stac-item
2022-10-09 09:43:47	ga_ls9c_ard_3-2-1_094080_2022-10-09_final.stac-item
2022-10-14 11:41:40	ga_ls9c_ard_3-2-1_113081_2022-10-14_final.stac-item
2022-10-15 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-15_final.stac-item
2022-10-16 09:48:02	ga_ls9c_ard_3-2-1_095075_2022-10-16_final.stac-item
2022-10-17 10:33:42	ga_ls9c_ard_3-2-1_102081_2022-10-17_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-20 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-10-20_final.stac-item
2022-10-26 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-10-26_final.stac-item
2022-10-27 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-10-27_final.stac-item
2022-10-31 10:41:39	ga_ls9c_ard_3-2-1_104070_2022-10-31_final.stac-item
2022-11-19 09:35:19	ga_ls9c_ard_3-2-1_093074_2022-11-19_final.stac-item
2022-12-01 09:59:58	ga_ls9c_ard_3-2-1_097074_2022-12-01_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_final.stac-item
2022-12-08 10:06:11	ga_ls9c_ard_3-2-1_098074_2022-12-08_final.stac-item
2022-12-08 10:07:23	ga_ls9c_ard_3-2-1_098077_2022-12-08_final.stac-item
2022-12-17 10:03:12	ga_ls9c_ard_3-2-1_097082_2022-12-17_final.stac-item
2022-12-19 11:30:06	ga_ls9c_ard_3-2-1_111083_2022-12-19_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2022-12-23 11:04:57	ga_ls9c_ard_3-2-1_107082_2022-12-23_final.stac-item
2022-12-30 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-30_final.stac-item
2023-01-01 09:19:33	ga_ls9c_ard_3-2-1_090081_2022-12-31_final.stac-item
2023-01-05 10:29:19	ga_ls9c_ard_3-2-1_102070_2023-01-05_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final.stac-item
2023-01-11 09:53:49	ga_ls9c_ard_3-2-1_096074_2023-01-11_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-27 09:56:59	ga_ls9c_ard_3-2-1_096082_2023-01-27_final.stac-item
2023-02-03 10:00:27	ga_ls9c_ard_3-2-1_097075_2023-02-03_final.stac-item
2023-02-11 09:15:25	ga_ls9c_ard_3-2-1_089086_2023-02-10_final.stac-item
2023-02-12 09:57:52	ga_ls9c_ard_3-2-1_096084_2023-02-12_final.stac-item
2023-04-26 11:26:17	ga_ls9c_ard_3-2-1_111075_2023-04-26_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-01 10:06:40	ga_ls9c_ard_3-2-1_098077_2023-05-01_final.stac-item
2023-05-01 10:07:51	ga_ls9c_ard_3-2-1_098080_2023-05-01_final.stac-item
2023-05-01 10:09:51	ga_ls9c_ard_3-2-1_098085_2023-05-01_final.stac-item
2023-05-03 09:52:16	ga_ls9c_ard_3-2-1_096072_2023-05-03_final.stac-item
2023-05-05 09:45:03	ga_ls9c_ard_3-2-1_094085_2023-05-05_final.stac-item
2023-05-05 11:20:21	ga_ls9c_ard_3-2-1_110076_2023-05-05_final.stac-item
2023-05-28 09:47:05	ga_ls9c_ard_3-2-1_095075_2023-05-28_final.stac-item
2023-06-01 09:26:20	ga_ls9c_ard_3-2-1_091085_2023-05-31_final.stac-item
2023-06-20 09:51:55	ga_ls9c_ard_3-2-1_096072_2023-06-20_final.stac-item
2023-06-21 10:33:59	ga_ls9c_ard_3-2-1_103069_2023-06-21_final.stac-item
2023-06-26 10:57:18	ga_ls9c_ard_3-2-1_106081_2023-06-26_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_final.stac-item
2023-07-06 09:52:07	ga_ls9c_ard_3-2-1_096072_2023-07-06_final.stac-item
2023-07-16 10:28:04	ga_ls9c_ard_3-2-1_102069_2023-07-16_final.stac-item
2023-07-19 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-07-18_final.stac-item
2023-07-20 10:04:33	ga_ls9c_ard_3-2-1_098072_2023-07-20_final.stac-item
2023-07-21 09:11:19	ga_ls9c_ard_3-2-1_089078_2023-07-20_final.stac-item
2023-07-21 09:13:43	ga_ls9c_ard_3-2-1_089084_2023-07-20_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-28 10:54:25	ga_ls9c_ard_3-2-1_106073_2023-07-28_final.stac-item
2023-08-02 09:34:57	ga_ls9c_ard_3-2-1_093075_2023-08-02_final.stac-item
2023-08-02 09:37:45	ga_ls9c_ard_3-2-1_093082_2023-08-02_final.stac-item
2023-10-16 10:54:13	ga_ls9c_ard_3-2-1_106071_2023-10-16_final.stac-item
2023-10-21 09:38:41	ga_ls9c_ard_3-2-1_093083_2023-10-21_final.stac-item
2023-10-26 09:56:48	ga_ls9c_ard_3-2-1_096082_2023-10-26_final.stac-item
2023-10-27 10:34:52	ga_ls9c_ard_3-2-1_103069_2023-10-27_final.stac-item
2023-10-28 09:44:01	ga_ls9c_ard_3-2-1_094081_2023-10-28_final.stac-item
2023-10-31 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-10-31_final.stac-item
2023-11-02 11:41:46	ga_ls9c_ard_3-2-1_113082_2023-11-02_final.stac-item
2023-11-03 10:42:08	ga_ls9c_ard_3-2-1_104072_2023-11-03_final.stac-item
2023-11-15 09:32:49	ga_ls9c_ard_3-2-1_092084_2023-11-15_final.stac-item
2023-11-18 11:41:27	ga_ls9c_ard_3-2-1_113081_2023-11-18_final.stac-item
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_final.stac-item
2023-11-20 11:30:19	ga_ls9c_ard_3-2-1_111084_2023-11-20_final.stac-item
2023-11-21 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-11-21_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years