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
2021-11-12 10:59:24	ga_ls9c_ard_3-2-1_106077_2021-11-12_final.stac-item
2021-11-18 10:05:33	ga_ls9c_ard_3-2-1_097083_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
2021-12-22 10:51:17	ga_ls9c_ard_3-2-1_105079_2021-12-22_final.stac-item
2021-12-27 11:10:14	ga_ls9c_ard_3-2-1_108080_2021-12-27_final.stac-item
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-14 10:58:12	ga_ls9c_ard_3-2-1_106081_2022-01-14_final.stac-item
2022-01-28 11:10:13	ga_ls9c_ard_3-2-1_108080_2022-01-28_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-01-30 10:58:15	ga_ls9c_ard_3-2-1_106081_2022-01-30_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-05-06 09:19:36	ga_ls9c_ard_3-2-1_090083_2022-05-05_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-07-07 11:10:11	ga_ls9c_ard_3-2-1_108081_2022-07-07_final.stac-item
2022-08-01 09:24:08	ga_ls9c_ard_3-2-1_091078_2022-07-31_final.stac-item
2022-08-03 10:48:42	ga_ls9c_ard_3-2-1_105073_2022-08-03_final.stac-item
2022-08-06 11:22:49	ga_ls9c_ard_3-2-1_110081_2022-08-06_final.stac-item
2022-08-12 10:43:48	ga_ls9c_ard_3-2-1_104076_2022-08-12_final.stac-item
2022-08-27 09:59:48	ga_ls9c_ard_3-2-1_097074_2022-08-27_final.stac-item
2022-09-27 10:57:32	ga_ls9c_ard_3-2-1_106079_2022-09-27_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-27 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-10-27_final.stac-item
2022-12-01 11:41:39	ga_ls9c_ard_3-2-1_113081_2022-12-01_final.stac-item
2022-12-08 10:08:59	ga_ls9c_ard_3-2-1_098081_2022-12-08_final.stac-item
2022-12-18 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-12-18_final.stac-item
2022-12-30 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-30_final.stac-item
2023-01-04 09:50:03	ga_ls9c_ard_3-2-1_095080_2023-01-04_final.stac-item
2023-01-12 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-12_final.stac-item
2023-01-15 09:30:39	ga_ls9c_ard_3-2-1_092078_2023-01-15_final.stac-item
2023-01-22 09:33:57	ga_ls9c_ard_3-2-1_093071_2023-01-22_final.stac-item
2023-01-27 09:55:47	ga_ls9c_ard_3-2-1_096079_2023-01-27_final.stac-item
2023-01-27 11:33:52	ga_ls9c_ard_3-2-1_112077_2023-01-27_final.stac-item
2023-02-05 09:50:06	ga_ls9c_ard_3-2-1_095080_2023-02-05_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-05 11:27:47	ga_ls9c_ard_3-2-1_111077_2023-02-05_final.stac-item
2023-02-07 09:39:20	ga_ls9c_ard_3-2-1_093084_2023-02-07_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-12 11:33:58	ga_ls9c_ard_3-2-1_112077_2023-02-12_final.stac-item
2023-02-14 09:42:42	ga_ls9c_ard_3-2-1_094077_2023-02-14_final.stac-item
2023-04-24 10:02:11	ga_ls9c_ard_3-2-1_097081_2023-04-24_final.stac-item
2023-04-25 10:44:14	ga_ls9c_ard_3-2-1_104078_2023-04-25_final.stac-item
2023-04-26 09:49:48	ga_ls9c_ard_3-2-1_095081_2023-04-26_final.stac-item
2023-04-26 09:50:36	ga_ls9c_ard_3-2-1_095083_2023-04-26_final.stac-item
2023-04-28 09:38:36	ga_ls9c_ard_3-2-1_093084_2023-04-28_final.stac-item
2023-04-28 11:14:42	ga_ls9c_ard_3-2-1_109077_2023-04-28_final.stac-item
2023-04-28 11:15:53	ga_ls9c_ard_3-2-1_109080_2023-04-28_final.stac-item
2023-04-30 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-04-30_final.stac-item
2023-04-30 11:04:18	ga_ls9c_ard_3-2-1_107082_2023-04-30_final.stac-item
2023-05-30 09:37:54	ga_ls9c_ard_3-2-1_093083_2023-05-30_final.stac-item
2023-07-15 11:29:41	ga_ls9c_ard_3-2-1_111084_2023-07-15_final.stac-item
2023-07-20 11:45:49	ga_ls9c_ard_3-2-1_114078_2023-07-20_final.stac-item
2023-07-21 10:47:48	ga_ls9c_ard_3-2-1_105072_2023-07-21_final.stac-item
2023-07-24 09:41:24	ga_ls9c_ard_3-2-1_094076_2023-07-24_final.stac-item
2023-07-24 09:42:36	ga_ls9c_ard_3-2-1_094079_2023-07-24_final.stac-item
2023-07-24 09:43:00	ga_ls9c_ard_3-2-1_094080_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
2023-07-26 09:31:03	ga_ls9c_ard_3-2-1_092081_2023-07-26_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-07-28 09:19:32	ga_ls9c_ard_3-2-1_090083_2023-07-27_final.stac-item
2023-08-02 11:15:02	ga_ls9c_ard_3-2-1_109078_2023-08-02_final.stac-item
2023-08-02 11:16:14	ga_ls9c_ard_3-2-1_109081_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
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-14 09:30:05	ga_ls9c_ard_3-2-1_092077_2023-10-14_final.stac-item
2023-10-14 09:32:04	ga_ls9c_ard_3-2-1_092082_2023-10-14_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-14 11:09:46	ga_ls9c_ard_3-2-1_108079_2023-10-14_final.stac-item
2023-10-15 10:14:57	ga_ls9c_ard_3-2-1_099081_2023-10-15_final.stac-item
2023-10-16 10:56:37	ga_ls9c_ard_3-2-1_106077_2023-10-16_final.stac-item
2023-10-17 09:59:24	ga_ls9c_ard_3-2-1_097073_2023-10-17_final.stac-item
2023-10-18 10:43:28	ga_ls9c_ard_3-2-1_104075_2023-10-18_final.stac-item
2023-10-19 11:27:56	ga_ls9c_ard_3-2-1_111078_2023-10-19_final.stac-item
2023-10-21 09:36:17	ga_ls9c_ard_3-2-1_093077_2023-10-21_final.stac-item
2023-10-21 09:38:17	ga_ls9c_ard_3-2-1_093082_2023-10-21_final.stac-item
2023-10-21 11:15:34	ga_ls9c_ard_3-2-1_109078_2023-10-21_final.stac-item
2023-10-22 10:18:45	ga_ls9c_ard_3-2-1_100075_2023-10-22_final.stac-item
2023-10-22 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-10-22_final.stac-item
2023-10-22 11:58:50	ga_ls9c_ard_3-2-1_116078_2023-10-22_final.stac-item
2023-10-23 09:25:55	ga_ls9c_ard_3-2-1_091082_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
2023-10-25 09:10:21	ga_ls9c_ard_3-2-1_089074_2023-10-24_final.stac-item
2023-10-25 10:51:38	ga_ls9c_ard_3-2-1_105080_2023-10-25_final.stac-item
2023-10-26 09:56:24	ga_ls9c_ard_3-2-1_096081_2023-10-26_final.stac-item
2023-10-26 11:33:17	ga_ls9c_ard_3-2-1_112076_2023-10-26_final.stac-item
2023-10-26 11:34:05	ga_ls9c_ard_3-2-1_112078_2023-10-26_final.stac-item
2023-10-30 11:11:19	ga_ls9c_ard_3-2-1_108083_2023-10-30_final.stac-item
2023-10-31 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-10-31_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_final.stac-item
2023-11-05 10:33:00	ga_ls9c_ard_3-2-1_102080_2023-11-05_final.stac-item
2023-11-15 09:32:01	ga_ls9c_ard_3-2-1_092082_2023-11-15_final.stac-item
2023-11-18 10:00:58	ga_ls9c_ard_3-2-1_097077_2023-11-18_final.stac-item
2023-11-18 11:40:15	ga_ls9c_ard_3-2-1_113078_2023-11-18_final.stac-item
2023-11-19 10:45:03	ga_ls9c_ard_3-2-1_104079_2023-11-19_final.stac-item
2023-11-20 09:48:38	ga_ls9c_ard_3-2-1_095077_2023-11-20_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-20 11:27:31	ga_ls9c_ard_3-2-1_111077_2023-11-20_final.stac-item
2023-11-21 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-11-21_final.stac-item
2023-11-21 10:32:19	ga_ls9c_ard_3-2-1_102078_2023-11-21_final.stac-item
2023-11-22 11:15:36	ga_ls9c_ard_3-2-1_109078_2023-11-22_final.stac-item
2023-11-22 11:16:47	ga_ls9c_ard_3-2-1_109081_2023-11-22_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