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
2021-11-08 11:38:29	ga_ls9c_ard_3-2-1_113081_2021-11-08_final.stac-item
2021-11-08 11:38:53	ga_ls9c_ard_3-2-1_113082_2021-11-08_final.stac-item
2021-11-12 10:57:49	ga_ls9c_ard_3-2-1_106073_2021-11-12_final.stac-item
2021-12-10 10:26:37	ga_ls9c_ard_3-2-1_101079_2021-12-10_final.stac-item
2021-12-12 11:52:20	ga_ls9c_ard_3-2-1_115077_2021-12-12_final.stac-item
2021-12-21 11:46:54	ga_ls9c_ard_3-2-1_114079_2021-12-21_final.stac-item
2022-01-01 09:51:05	ga_ls9c_ard_3-2-1_095083_2022-01-01_final.stac-item
2022-01-08 11:33:19	ga_ls9c_ard_3-2-1_112076_2022-01-08_final.stac-item
2022-01-24 11:32:56	ga_ls9c_ard_3-2-1_112075_2022-01-24_final.stac-item
2022-02-05 10:20:46	ga_ls9c_ard_3-2-1_100080_2022-02-05_final.stac-item
2022-02-05 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-02-05_final.stac-item
2022-02-08 09:12:46	ga_ls9c_ard_3-2-1_089080_2022-02-07_final.stac-item
2022-02-09 09:53:38	ga_ls9c_ard_3-2-1_096074_2022-02-09_final.stac-item
2022-02-28 10:22:44	ga_ls9c_ard_3-2-1_101070_2022-02-28_final.stac-item
2022-04-05 10:01:30	ga_ls9c_ard_3-2-1_097079_2022-04-05_final.stac-item
2022-04-11 09:24:22	ga_ls9c_ard_3-2-1_091079_2022-04-10_final.stac-item
2022-05-04 09:29:11	ga_ls9c_ard_3-2-1_092076_2022-05-03_final.stac-item
2022-05-04 09:31:34	ga_ls9c_ard_3-2-1_092082_2022-05-04_final.stac-item
2022-05-29 11:00:53	ga_ls9c_ard_3-2-1_107074_2022-05-29_final.stac-item
2022-06-08 10:03:05	ga_ls9c_ard_3-2-1_097084_2022-06-08_final.stac-item
2022-06-12 11:11:18	ga_ls9c_ard_3-2-1_109069_2022-06-12_final.stac-item
2022-06-14 11:03:22	ga_ls9c_ard_3-2-1_107080_2022-06-14_final.stac-item
2022-06-15 11:44:39	ga_ls9c_ard_3-2-1_114075_2022-06-15_final.stac-item
2022-07-03 11:35:20	ga_ls9c_ard_3-2-1_112082_2022-07-03_final.stac-item
2022-07-13 10:30:16	ga_ls9c_ard_3-2-1_102074_2022-07-13_final.stac-item
2022-07-21 11:18:37	ga_ls9c_ard_3-2-1_110071_2022-07-21_final.stac-item
2022-07-26 09:58:45	ga_ls9c_ard_3-2-1_097072_2022-07-26_final.stac-item
2022-07-30 11:12:34	ga_ls9c_ard_3-2-1_109071_2022-07-30_final.stac-item
2022-08-09 10:16:04	ga_ls9c_ard_3-2-1_099084_2022-08-09_final.stac-item
2022-09-05 09:57:12	ga_ls9c_ard_3-2-1_096083_2022-09-05_final.stac-item
2022-09-16 11:15:13	ga_ls9c_ard_3-2-1_109077_2022-09-16_final.stac-item
2022-10-05 10:10:29	ga_ls9c_ard_3-2-1_098085_2022-10-05_final.stac-item
2022-10-06 10:48:33	ga_ls9c_ard_3-2-1_105072_2022-10-06_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-24 10:39:30	ga_ls9c_ard_3-2-1_103080_2022-10-24_final.stac-item
2022-10-31 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-10-31_final.stac-item
2022-11-04 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-11-04_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-06 11:45:51	ga_ls9c_ard_3-2-1_114076_2022-11-06_final.stac-item
2022-11-24 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-24_final.stac-item
2022-11-25 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-11-25_final.stac-item
2022-11-28 09:31:29	ga_ls9c_ard_3-2-1_092080_2022-11-28_final.stac-item
2022-12-01 11:39:15	ga_ls9c_ard_3-2-1_113075_2022-12-01_final.stac-item
2022-12-11 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-12-11_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2022-12-12 11:19:57	ga_ls9c_ard_3-2-1_110073_2022-12-12_final.stac-item
2022-12-17 10:00:00	ga_ls9c_ard_3-2-1_097074_2022-12-17_final.stac-item
2022-12-26 09:55:47	ga_ls9c_ard_3-2-1_096079_2022-12-26_final.stac-item
2023-01-04 09:52:03	ga_ls9c_ard_3-2-1_095085_2023-01-04_final.stac-item
2023-01-05 10:34:07	ga_ls9c_ard_3-2-1_102082_2023-01-05_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-12 10:37:04	ga_ls9c_ard_3-2-1_103074_2023-01-12_final.stac-item
2023-01-20 09:51:29	ga_ls9c_ard_3-2-1_095084_2023-01-20_final.stac-item
2023-01-25 10:08:30	ga_ls9c_ard_3-2-1_098080_2023-01-25_final.stac-item
2023-01-28 10:36:40	ga_ls9c_ard_3-2-1_103073_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
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-07 11:13:02	ga_ls9c_ard_3-2-1_109071_2023-02-07_final.stac-item
2023-02-10 11:47:32	ga_ls9c_ard_3-2-1_114080_2023-02-10_final.stac-item
2023-02-11 09:13:01	ga_ls9c_ard_3-2-1_089080_2023-02-10_final.stac-item
2023-02-11 10:48:19	ga_ls9c_ard_3-2-1_105071_2023-02-11_final.stac-item
2023-02-16 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-02-16_final.stac-item
2023-02-19 10:01:33	ga_ls9c_ard_3-2-1_097078_2023-02-19_final.stac-item
2023-02-25 09:28:44	ga_ls9c_ard_3-2-1_091089_2023-02-24_final.stac-item
2023-03-15 09:12:40	ga_ls9c_ard_3-2-1_089080_2023-03-14_final.stac-item
2023-03-20 09:31:59	ga_ls9c_ard_3-2-1_092082_2023-03-20_final.stac-item
2023-03-23 11:40:56	ga_ls9c_ard_3-2-1_113080_2023-03-23_final.stac-item
2023-03-24 10:45:17	ga_ls9c_ard_3-2-1_104080_2023-03-24_final.stac-item
2023-04-02 10:39:00	ga_ls9c_ard_3-2-1_103080_2023-04-02_final.stac-item
2023-04-09 10:41:09	ga_ls9c_ard_3-2-1_104070_2023-04-09_final.stac-item
2023-04-14 09:25:08	ga_ls9c_ard_3-2-1_091081_2023-04-13_final.stac-item
2023-04-15 10:06:23	ga_ls9c_ard_3-2-1_098076_2023-04-15_final.stac-item
2023-05-09 09:17:57	ga_ls9c_ard_3-2-1_090079_2023-05-08_final.stac-item
2023-05-09 10:53:38	ga_ls9c_ard_3-2-1_106071_2023-05-09_final.stac-item
2023-05-13 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-15 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-05-15_final.stac-item
2023-05-15 10:21:18	ga_ls9c_ard_3-2-1_100083_2023-05-15_final.stac-item
2023-05-16 11:04:57	ga_ls9c_ard_3-2-1_107084_2023-05-16_final.stac-item
2023-06-26 09:17:13	ga_ls9c_ard_3-2-1_090078_2023-06-25_final.stac-item
2023-06-27 10:00:31	ga_ls9c_ard_3-2-1_097078_2023-06-27_final.stac-item
2023-06-28 10:40:37	ga_ls9c_ard_3-2-1_104070_2023-06-28_final.stac-item
2023-07-03 09:21:11	ga_ls9c_ard_3-2-1_091072_2023-07-02_final.stac-item
2023-07-04 11:44:08	ga_ls9c_ard_3-2-1_114074_2023-07-04_final.stac-item
2023-07-04 11:46:08	ga_ls9c_ard_3-2-1_114079_2023-07-04_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-11 11:52:23	ga_ls9c_ard_3-2-1_115079_2023-07-11_final.stac-item
2023-09-06 10:08:08	ga_ls9c_ard_3-2-1_098080_2023-09-06_final.stac-item
2023-09-08 11:35:53	ga_ls9c_ard_3-2-1_112083_2023-09-08_final.stac-item
2023-09-10 09:45:03	ga_ls9c_ard_3-2-1_094084_2023-09-10_final.stac-item
2023-09-17 11:30:09	ga_ls9c_ard_3-2-1_111084_2023-09-17_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-09-23 09:11:22	ga_ls9c_ard_3-2-1_089077_2023-09-22_final.stac-item
2023-09-23 10:51:03	ga_ls9c_ard_3-2-1_105079_2023-09-23_final.stac-item
2023-10-05 11:17:02	ga_ls9c_ard_3-2-1_109082_2023-10-05_final.stac-item
2023-10-07 09:28:35	ga_ls9c_ard_3-2-1_091089_2023-10-06_final.stac-item
2023-10-10 09:57:56	ga_ls9c_ard_3-2-1_096085_2023-10-10_final.stac-item
2023-10-11 10:35:37	ga_ls9c_ard_3-2-1_103071_2023-10-11_final.stac-item
2023-10-13 10:23:18	ga_ls9c_ard_3-2-1_101071_2023-10-13_final.stac-item
2023-10-13 10:23:41	ga_ls9c_ard_3-2-1_101072_2023-10-13_final.stac-item
2023-10-15 11:52:14	ga_ls9c_ard_3-2-1_115077_2023-10-15_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