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
2021-10-31 11:10:48	ga_ls9c_ard_3-2-1_109071_2021-10-31_final.stac-item
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-23 10:03:38	ga_ls9c_ard_3-2-1_098072_2021-11-23_final.stac-item
2021-11-25 09:48:03	ga_ls9c_ard_3-2-1_095080_2021-11-25_final.stac-item
2021-12-09 09:45:22	ga_ls9c_ard_3-2-1_094084_2021-12-09_final.stac-item
2021-12-11 09:30:36	ga_ls9c_ard_3-2-1_092078_2021-12-11_final.stac-item
2021-12-11 11:09:52	ga_ls9c_ard_3-2-1_108079_2021-12-11_final.stac-item
2021-12-21 10:06:02	ga_ls9c_ard_3-2-1_098074_2021-12-21_final.stac-item
2021-12-23 09:54:52	ga_ls9c_ard_3-2-1_096077_2021-12-23_final.stac-item
2021-12-27 09:32:09	ga_ls9c_ard_3-2-1_092082_2021-12-27_final.stac-item
2022-01-22 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-22_final.stac-item
2022-02-13 09:29:41	ga_ls9c_ard_3-2-1_092076_2022-02-12_final.stac-item
2022-02-16 10:00:57	ga_ls9c_ard_3-2-1_097077_2022-02-16_final.stac-item
2022-02-24 10:47:30	ga_ls9c_ard_3-2-1_105070_2022-02-24_final.stac-item
2022-03-10 09:24:30	ga_ls9c_ard_3-2-1_091079_2022-03-09_final.stac-item
2022-04-05 09:57:30	ga_ls9c_ard_3-2-1_097069_2022-04-05_final.stac-item
2022-04-27 11:00:43	ga_ls9c_ard_3-2-1_107073_2022-04-27_final.stac-item
2022-05-14 10:05:45	ga_ls9c_ard_3-2-1_098075_2022-05-14_final.stac-item
2022-05-25 09:49:30	ga_ls9c_ard_3-2-1_095081_2022-05-25_final.stac-item
2022-06-01 11:34:59	ga_ls9c_ard_3-2-1_112082_2022-06-01_final.stac-item
2022-06-20 10:24:49	ga_ls9c_ard_3-2-1_101076_2022-06-20_final.stac-item
2022-06-23 09:18:55	ga_ls9c_ard_3-2-1_090081_2022-06-22_final.stac-item
2022-06-28 09:37:31	ga_ls9c_ard_3-2-1_093081_2022-06-28_final.stac-item
2022-07-07 09:31:18	ga_ls9c_ard_3-2-1_092081_2022-07-07_final.stac-item
2022-07-15 10:18:18	ga_ls9c_ard_3-2-1_100075_2022-07-15_final.stac-item
2022-07-16 11:00:47	ga_ls9c_ard_3-2-1_107073_2022-07-16_final.stac-item
2022-07-19 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-19_final.stac-item
2022-07-20 10:36:32	ga_ls9c_ard_3-2-1_103074_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
2022-07-31 10:17:45	ga_ls9c_ard_3-2-1_100073_2022-07-31_final.stac-item
2022-08-08 11:06:29	ga_ls9c_ard_3-2-1_108071_2022-08-08_final.stac-item
2022-08-12 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-08-12_final.stac-item
2022-08-18 10:08:21	ga_ls9c_ard_3-2-1_098080_2022-08-18_final.stac-item
2022-08-26 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-08-25_final.stac-item
2022-08-28 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-08-28_final.stac-item
2022-09-01 10:20:44	ga_ls9c_ard_3-2-1_100080_2022-09-01_final.stac-item
2022-09-02 09:25:54	ga_ls9c_ard_3-2-1_091082_2022-09-01_final.stac-item
2022-09-28 10:01:07	ga_ls9c_ard_3-2-1_097077_2022-09-28_final.stac-item
2022-10-07 11:34:36	ga_ls9c_ard_3-2-1_112079_2022-10-07_final.stac-item
2022-10-10 10:23:52	ga_ls9c_ard_3-2-1_101072_2022-10-10_final.stac-item
2022-10-14 11:41:40	ga_ls9c_ard_3-2-1_113081_2022-10-14_final.stac-item
2022-10-20 11:03:25	ga_ls9c_ard_3-2-1_107078_2022-10-20_final.stac-item
2022-10-23 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-10-23_final.stac-item
2022-10-23 11:34:43	ga_ls9c_ard_3-2-1_112079_2022-10-23_final.stac-item
2022-11-01 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-11-01_final.stac-item
2022-11-03 11:15:19	ga_ls9c_ard_3-2-1_109077_2022-11-03_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-20 11:58:15	ga_ls9c_ard_3-2-1_116076_2022-11-20_final.stac-item
2022-12-09 10:49:03	ga_ls9c_ard_3-2-1_105073_2022-12-09_final.stac-item
2022-12-26 09:55:23	ga_ls9c_ard_3-2-1_096078_2022-12-26_final.stac-item
2023-01-03 10:44:28	ga_ls9c_ard_3-2-1_104077_2023-01-03_final.stac-item
2023-01-04 09:48:03	ga_ls9c_ard_3-2-1_095075_2023-01-04_final.stac-item
2023-01-06 11:15:47	ga_ls9c_ard_3-2-1_109078_2023-01-06_final.stac-item
2023-01-18 11:37:59	ga_ls9c_ard_3-2-1_113072_2023-01-18_final.stac-item
2023-01-22 09:35:09	ga_ls9c_ard_3-2-1_093074_2023-01-22_final.stac-item
2023-01-29 11:19:08	ga_ls9c_ard_3-2-1_110071_2023-01-29_final.stac-item
2023-02-01 11:51:16	ga_ls9c_ard_3-2-1_115074_2023-02-01_final.stac-item
2023-02-01 11:52:28	ga_ls9c_ard_3-2-1_115077_2023-02-01_final.stac-item
2023-02-05 11:28:59	ga_ls9c_ard_3-2-1_111080_2023-02-05_final.stac-item
2023-03-09 09:51:20	ga_ls9c_ard_3-2-1_095084_2023-03-09_final.stac-item
2023-03-11 09:38:58	ga_ls9c_ard_3-2-1_093084_2023-03-11_final.stac-item
2023-03-14 10:05:54	ga_ls9c_ard_3-2-1_098074_2023-03-14_final.stac-item
2023-03-25 11:27:44	ga_ls9c_ard_3-2-1_111078_2023-03-25_final.stac-item
2023-03-27 11:14:56	ga_ls9c_ard_3-2-1_109077_2023-03-27_final.stac-item
2023-04-03 09:46:10	ga_ls9c_ard_3-2-1_094087_2023-04-03_final.stac-item
2023-04-13 11:58:03	ga_ls9c_ard_3-2-1_116077_2023-04-13_final.stac-item
2023-04-16 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-04-15_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-26 11:29:29	ga_ls9c_ard_3-2-1_111083_2023-04-26_final.stac-item
2023-05-03 09:51:28	ga_ls9c_ard_3-2-1_096070_2023-05-03_final.stac-item
2023-05-03 09:53:04	ga_ls9c_ard_3-2-1_096074_2023-05-03_final.stac-item
2023-05-06 10:25:32	ga_ls9c_ard_3-2-1_101078_2023-05-06_final.stac-item
2023-05-15 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-05-15_final.stac-item
2023-05-21 09:44:33	ga_ls9c_ard_3-2-1_094084_2023-05-21_final.stac-item
2023-05-30 11:12:24	ga_ls9c_ard_3-2-1_109072_2023-05-30_final.stac-item
2023-06-03 10:49:40	ga_ls9c_ard_3-2-1_105077_2023-06-03_final.stac-item
2023-06-19 09:12:14	ga_ls9c_ard_3-2-1_089081_2023-06-18_final.stac-item
2023-06-20 09:51:31	ga_ls9c_ard_3-2-1_096071_2023-06-20_final.stac-item
2023-06-28 10:40:37	ga_ls9c_ard_3-2-1_104070_2023-06-28_final.stac-item
2023-06-29 09:50:37	ga_ls9c_ard_3-2-1_095084_2023-06-29_final.stac-item
2023-07-07 10:34:12	ga_ls9c_ard_3-2-1_103069_2023-07-07_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-07-23 10:34:38	ga_ls9c_ard_3-2-1_103070_2023-07-23_final.stac-item
2023-07-26 11:05:57	ga_ls9c_ard_3-2-1_108071_2023-07-26_final.stac-item
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-07-31 09:49:41	ga_ls9c_ard_3-2-1_095081_2023-07-31_final.stac-item
2023-07-31 09:51:17	ga_ls9c_ard_3-2-1_095085_2023-07-31_final.stac-item
2023-08-06 10:50:45	ga_ls9c_ard_3-2-1_105079_2023-08-06_final.stac-item
2023-08-09 11:18:29	ga_ls9c_ard_3-2-1_110071_2023-08-09_final.stac-item
2023-10-14 11:09:46	ga_ls9c_ard_3-2-1_108079_2023-10-14_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-25 09:12:45	ga_ls9c_ard_3-2-1_089080_2023-10-24_final.stac-item
2023-10-25 09:13:09	ga_ls9c_ard_3-2-1_089081_2023-10-24_final.stac-item
2023-10-28 09:43:13	ga_ls9c_ard_3-2-1_094079_2023-10-28_final.stac-item
2023-10-29 10:23:41	ga_ls9c_ard_3-2-1_101072_2023-10-29_final.stac-item
2023-11-03 10:41:20	ga_ls9c_ard_3-2-1_104070_2023-11-03_final.stac-item
2023-11-15 11:10:30	ga_ls9c_ard_3-2-1_108081_2023-11-15_final.stac-item
2023-11-23 10:18:23	ga_ls9c_ard_3-2-1_100074_2023-11-23_final.stac-item
2023-11-24 09:29:10	ga_ls9c_ard_3-2-1_091090_2023-11-23_final.stac-item
2023-11-24 11:04:03	ga_ls9c_ard_3-2-1_107080_2023-11-24_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