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 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-15 11:19:25	ga_ls9c_ard_3-2-1_110074_2021-11-15_final.stac-item
2021-12-19 10:17:59	ga_ls9c_ard_3-2-1_100073_2021-12-19_final.stac-item
2021-12-19 10:19:35	ga_ls9c_ard_3-2-1_100077_2021-12-19_final.stac-item
2022-01-19 11:13:35	ga_ls9c_ard_3-2-1_109073_2022-01-19_final.stac-item
2022-01-22 11:44:54	ga_ls9c_ard_3-2-1_114074_2022-01-22_final.stac-item
2022-01-30 09:18:58	ga_ls9c_ard_3-2-1_090080_2022-01-29_final.stac-item
2022-02-04 11:15:11	ga_ls9c_ard_3-2-1_109077_2022-02-04_final.stac-item
2022-02-05 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-02-05_final.stac-item
2022-02-06 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-02-06_final.stac-item
2022-03-20 10:00:45	ga_ls9c_ard_3-2-1_097077_2022-03-20_final.stac-item
2022-03-31 11:18:15	ga_ls9c_ard_3-2-1_110070_2022-03-31_final.stac-item
2022-04-03 10:09:52	ga_ls9c_ard_3-2-1_099069_2022-04-03_final.stac-item
2022-04-15 10:39:17	ga_ls9c_ard_3-2-1_103081_2022-04-15_final.stac-item
2022-04-16 11:19:44	ga_ls9c_ard_3-2-1_110074_2022-04-16_final.stac-item
2022-04-19 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-04-19_final.stac-item
2022-05-01 10:33:59	ga_ls9c_ard_3-2-1_103068_2022-05-01_final.stac-item
2022-05-11 11:14:34	ga_ls9c_ard_3-2-1_109077_2022-05-11_final.stac-item
2022-05-16 11:31:03	ga_ls9c_ard_3-2-1_112072_2022-05-16_final.stac-item
2022-06-01 09:57:18	ga_ls9c_ard_3-2-1_096085_2022-06-01_final.stac-item
2022-09-01 11:58:01	ga_ls9c_ard_3-2-1_116076_2022-09-01_final.stac-item
2022-09-02 09:29:06	ga_ls9c_ard_3-2-1_091090_2022-09-01_final.stac-item
2022-09-05 11:33:18	ga_ls9c_ard_3-2-1_112076_2022-09-05_final.stac-item
2022-09-18 11:02:52	ga_ls9c_ard_3-2-1_107077_2022-09-18_final.stac-item
2022-10-07 09:58:07	ga_ls9c_ard_3-2-1_096085_2022-10-07_final.stac-item
2022-10-09 11:20:41	ga_ls9c_ard_3-2-1_110075_2022-10-09_final.stac-item
2022-10-13 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-10-13_final.stac-item
2022-10-18 11:14:34	ga_ls9c_ard_3-2-1_109075_2022-10-18_final.stac-item
2022-10-20 11:03:01	ga_ls9c_ard_3-2-1_107077_2022-10-20_final.stac-item
2022-10-21 10:10:35	ga_ls9c_ard_3-2-1_098085_2022-10-21_final.stac-item
2022-10-25 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-10-25_final.stac-item
2022-10-27 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-10-26_final.stac-item
2022-10-27 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-10-27_final.stac-item
2022-10-29 10:56:49	ga_ls9c_ard_3-2-1_106077_2022-10-29_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-12 11:07:37	ga_ls9c_ard_3-2-1_108073_2022-11-12_final.stac-item
2022-11-12 11:10:48	ga_ls9c_ard_3-2-1_108081_2022-11-12_final.stac-item
2022-11-14 10:54:27	ga_ls9c_ard_3-2-1_106071_2022-11-14_final.stac-item
2022-11-18 10:28:33	ga_ls9c_ard_3-2-1_102068_2022-11-18_final.stac-item
2022-11-19 11:18:11	ga_ls9c_ard_3-2-1_109084_2022-11-19_final.stac-item
2022-11-23 10:51:51	ga_ls9c_ard_3-2-1_105080_2022-11-23_final.stac-item
2022-11-25 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-25_final.stac-item
2022-11-30 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-11-30_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2022-12-07 11:03:24	ga_ls9c_ard_3-2-1_107078_2022-12-07_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_final.stac-item
2022-12-12 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-12-12_final.stac-item
2022-12-12 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-12-12_final.stac-item
2022-12-18 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-12-18_final.stac-item
2022-12-18 10:44:27	ga_ls9c_ard_3-2-1_104077_2022-12-18_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-23 09:28:28	ga_ls9c_ard_3-2-1_091088_2022-12-22_final.stac-item
2022-12-26 11:33:28	ga_ls9c_ard_3-2-1_112076_2022-12-26_final.stac-item
2022-12-30 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-12-30_final.stac-item
2023-01-02 11:39:18	ga_ls9c_ard_3-2-1_113075_2023-01-02_final.stac-item
2023-01-04 09:50:51	ga_ls9c_ard_3-2-1_095082_2023-01-04_final.stac-item
2023-01-04 09:52:03	ga_ls9c_ard_3-2-1_095085_2023-01-04_final.stac-item
2023-01-06 09:36:30	ga_ls9c_ard_3-2-1_093077_2023-01-06_final.stac-item
2023-01-07 10:22:09	ga_ls9c_ard_3-2-1_100083_2023-01-07_final.stac-item
2023-01-12 10:39:28	ga_ls9c_ard_3-2-1_103080_2023-01-12_final.stac-item
2023-01-15 11:10:43	ga_ls9c_ard_3-2-1_108081_2023-01-15_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-01-21 10:33:56	ga_ls9c_ard_3-2-1_102082_2023-01-21_final.stac-item
2023-01-31 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-01-31_final.stac-item
2023-01-31 11:10:48	ga_ls9c_ard_3-2-1_108081_2023-01-31_final.stac-item
2023-02-01 11:53:16	ga_ls9c_ard_3-2-1_115079_2023-02-01_final.stac-item
2023-02-18 10:58:23	ga_ls9c_ard_3-2-1_106081_2023-02-18_final.stac-item
2023-02-20 10:45:59	ga_ls9c_ard_3-2-1_104081_2023-02-20_final.stac-item
2023-02-23 11:14:24	ga_ls9c_ard_3-2-1_109075_2023-02-23_final.stac-item
2023-04-12 09:33:56	ga_ls9c_ard_3-2-1_093072_2023-04-12_final.stac-item
2023-04-13 10:21:58	ga_ls9c_ard_3-2-1_100084_2023-04-13_final.stac-item
2023-04-14 09:28:19	ga_ls9c_ard_3-2-1_091089_2023-04-13_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-05-11 10:44:28	ga_ls9c_ard_3-2-1_104079_2023-05-11_final.stac-item
2023-05-12 11:25:20	ga_ls9c_ard_3-2-1_111073_2023-05-12_final.stac-item
2023-05-14 09:37:39	ga_ls9c_ard_3-2-1_093082_2023-05-14_final.stac-item
2023-05-15 10:16:31	ga_ls9c_ard_3-2-1_100071_2023-05-15_final.stac-item
2023-05-15 11:58:12	ga_ls9c_ard_3-2-1_116078_2023-05-15_final.stac-item
2023-05-27 10:45:06	ga_ls9c_ard_3-2-1_104081_2023-05-27_final.stac-item
2023-06-03 10:45:40	ga_ls9c_ard_3-2-1_105067_2023-06-03_final.stac-item
2023-06-24 11:06:28	ga_ls9c_ard_3-2-1_108073_2023-06-24_final.stac-item
2023-06-29 11:24:42	ga_ls9c_ard_3-2-1_111072_2023-06-29_final.stac-item
2023-06-30 10:27:55	ga_ls9c_ard_3-2-1_102069_2023-06-30_final.stac-item
2023-06-30 10:33:06	ga_ls9c_ard_3-2-1_102082_2023-06-30_final.stac-item
2023-07-02 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-07-02_final.stac-item
2023-07-08 11:19:28	ga_ls9c_ard_3-2-1_110074_2023-07-08_final.stac-item
2023-07-11 10:10:19	ga_ls9c_ard_3-2-1_099071_2023-07-11_final.stac-item
2023-07-11 10:15:54	ga_ls9c_ard_3-2-1_099085_2023-07-11_final.stac-item
2023-09-05 11:02:57	ga_ls9c_ard_3-2-1_107078_2023-09-05_final.stac-item
2023-09-07 09:11:44	ga_ls9c_ard_3-2-1_089078_2023-09-06_final.stac-item
2023-09-08 09:52:12	ga_ls9c_ard_3-2-1_096071_2023-09-08_final.stac-item
2023-09-09 10:34:17	ga_ls9c_ard_3-2-1_103068_2023-09-09_final.stac-item
2023-09-10 09:44:16	ga_ls9c_ard_3-2-1_094082_2023-09-10_final.stac-item
2023-09-14 10:58:51	ga_ls9c_ard_3-2-1_106083_2023-09-14_final.stac-item
2023-09-21 11:02:38	ga_ls9c_ard_3-2-1_107077_2023-09-21_final.stac-item
2023-10-03 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-10-03_final.stac-item
2023-10-05 11:14:38	ga_ls9c_ard_3-2-1_109076_2023-10-05_final.stac-item
2023-10-09 10:46:45	ga_ls9c_ard_3-2-1_105068_2023-10-09_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