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
2021-11-03 09:54:34	ga_ls9c_ard_3-2-1_096074_2021-11-03_final.stac-item
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-25 09:48:27	ga_ls9c_ard_3-2-1_095081_2021-11-25_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2022-01-29 10:15:23	ga_ls9c_ard_3-2-1_099082_2022-01-29_final.stac-item
2022-02-06 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-02-05_final.stac-item
2022-02-15 09:19:18	ga_ls9c_ard_3-2-1_090081_2022-02-14_final.stac-item
2022-02-27 09:44:16	ga_ls9c_ard_3-2-1_094082_2022-02-27_final.stac-item
2022-03-24 11:13:18	ga_ls9c_ard_3-2-1_109073_2022-03-24_final.stac-item
2022-04-11 09:25:58	ga_ls9c_ard_3-2-1_091083_2022-04-10_final.stac-item
2022-04-20 09:18:04	ga_ls9c_ard_3-2-1_090079_2022-04-19_final.stac-item
2022-04-21 09:58:31	ga_ls9c_ard_3-2-1_097072_2022-04-21_final.stac-item
2022-05-02 09:44:45	ga_ls9c_ard_3-2-1_094084_2022-05-02_final.stac-item
2022-06-10 09:46:45	ga_ls9c_ard_3-2-1_095074_2022-06-10_final.stac-item
2022-06-15 11:44:39	ga_ls9c_ard_3-2-1_114075_2022-06-15_final.stac-item
2022-06-24 09:58:14	ga_ls9c_ard_3-2-1_097071_2022-06-24_final.stac-item
2022-07-09 09:18:56	ga_ls9c_ard_3-2-1_090081_2022-07-08_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-09 10:16:04	ga_ls9c_ard_3-2-1_099084_2022-08-09_final.stac-item
2022-08-19 09:13:32	ga_ls9c_ard_3-2-1_089082_2022-08-18_final.stac-item
2022-08-22 11:20:56	ga_ls9c_ard_3-2-1_110076_2022-08-22_final.stac-item
2022-08-26 10:55:01	ga_ls9c_ard_3-2-1_106073_2022-08-26_final.stac-item
2022-09-16 11:13:37	ga_ls9c_ard_3-2-1_109073_2022-09-16_final.stac-item
2022-09-27 10:54:45	ga_ls9c_ard_3-2-1_106072_2022-09-27_final.stac-item
2022-09-28 11:42:24	ga_ls9c_ard_3-2-1_113083_2022-09-28_final.stac-item
2022-10-08 10:36:36	ga_ls9c_ard_3-2-1_103073_2022-10-08_final.stac-item
2022-10-18 09:35:17	ga_ls9c_ard_3-2-1_093074_2022-10-18_final.stac-item
2022-10-22 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-10-22_final.stac-item
2022-10-27 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-10-27_final.stac-item
2022-11-06 11:47:03	ga_ls9c_ard_3-2-1_114079_2022-11-06_final.stac-item
2022-11-12 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-11-12_final.stac-item
2022-11-13 10:12:23	ga_ls9c_ard_3-2-1_099074_2022-11-13_final.stac-item
2022-11-13 11:51:17	ga_ls9c_ard_3-2-1_115074_2022-11-13_final.stac-item
2022-11-19 09:38:06	ga_ls9c_ard_3-2-1_093081_2022-11-19_final.stac-item
2022-11-19 11:17:47	ga_ls9c_ard_3-2-1_109083_2022-11-19_final.stac-item
2022-11-27 10:24:43	ga_ls9c_ard_3-2-1_101074_2022-11-27_final.stac-item
2022-12-03 09:48:01	ga_ls9c_ard_3-2-1_095075_2022-12-03_final.stac-item
2022-12-09 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-12-09_final.stac-item
2022-12-16 09:18:44	ga_ls9c_ard_3-2-1_090079_2022-12-15_final.stac-item
2022-12-21 11:13:44	ga_ls9c_ard_3-2-1_109073_2022-12-21_final.stac-item
2022-12-21 11:17:20	ga_ls9c_ard_3-2-1_109082_2022-12-21_final.stac-item
2022-12-24 11:45:49	ga_ls9c_ard_3-2-1_114076_2022-12-24_final.stac-item
2022-12-31 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-31_final.stac-item
2023-01-14 10:25:05	ga_ls9c_ard_3-2-1_101075_2023-01-14_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_final.stac-item
2023-01-27 09:53:47	ga_ls9c_ard_3-2-1_096074_2023-01-27_final.stac-item
2023-01-31 09:32:18	ga_ls9c_ard_3-2-1_092082_2023-01-31_final.stac-item
2023-01-31 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-01-31_final.stac-item
2023-02-02 09:19:10	ga_ls9c_ard_3-2-1_090080_2023-02-01_final.stac-item
2023-02-02 10:56:04	ga_ls9c_ard_3-2-1_106075_2023-02-02_final.stac-item
2023-02-02 10:58:03	ga_ls9c_ard_3-2-1_106080_2023-02-02_final.stac-item
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-08 11:59:06	ga_ls9c_ard_3-2-1_116078_2023-02-08_final.stac-item
2023-02-10 11:45:32	ga_ls9c_ard_3-2-1_114075_2023-02-10_final.stac-item
2023-02-14 11:23:34	ga_ls9c_ard_3-2-1_110082_2023-02-14_final.stac-item
2023-04-06 10:15:51	ga_ls9c_ard_3-2-1_099084_2023-04-06_final.stac-item
2023-04-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2023-04-23_final.stac-item
2023-04-26 11:26:17	ga_ls9c_ard_3-2-1_111075_2023-04-26_final.stac-item
2023-04-27 10:29:03	ga_ls9c_ard_3-2-1_102071_2023-04-27_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-04-28_final.stac-item
2023-04-28 11:16:41	ga_ls9c_ard_3-2-1_109082_2023-04-28_final.stac-item
2023-05-01 10:05:04	ga_ls9c_ard_3-2-1_098073_2023-05-01_final.stac-item
2023-05-03 11:35:08	ga_ls9c_ard_3-2-1_112082_2023-05-03_final.stac-item
2023-05-06 10:22:20	ga_ls9c_ard_3-2-1_101070_2023-05-06_final.stac-item
2023-05-06 10:25:08	ga_ls9c_ard_3-2-1_101077_2023-05-06_final.stac-item
2023-05-10 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-05-10_final.stac-item
2023-05-12 09:46:50	ga_ls9c_ard_3-2-1_095074_2023-05-12_final.stac-item
2023-05-13 10:28:30	ga_ls9c_ard_3-2-1_102070_2023-05-13_final.stac-item
2023-05-16 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-05-15_final.stac-item
2023-05-18 10:51:23	ga_ls9c_ard_3-2-1_105081_2023-05-18_final.stac-item
2023-05-19 11:35:25	ga_ls9c_ard_3-2-1_112083_2023-05-19_final.stac-item
2023-05-30 11:12:48	ga_ls9c_ard_3-2-1_109073_2023-05-30_final.stac-item
2023-06-20 09:51:07	ga_ls9c_ard_3-2-1_096070_2023-06-20_final.stac-item
2023-06-28 10:40:13	ga_ls9c_ard_3-2-1_104069_2023-06-28_final.stac-item
2023-06-28 10:40:37	ga_ls9c_ard_3-2-1_104070_2023-06-28_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-06 09:51:43	ga_ls9c_ard_3-2-1_096071_2023-07-06_final.stac-item
2023-07-06 11:35:24	ga_ls9c_ard_3-2-1_112083_2023-07-06_final.stac-item
2023-07-15 09:47:12	ga_ls9c_ard_3-2-1_095075_2023-07-15_final.stac-item
2023-07-15 09:50:24	ga_ls9c_ard_3-2-1_095083_2023-07-15_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_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 09:14:30	ga_ls9c_ard_3-2-1_089086_2023-07-20_final.stac-item
2023-07-24 11:23:05	ga_ls9c_ard_3-2-1_110083_2023-07-24_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-04 09:23:25	ga_ls9c_ard_3-2-1_091077_2023-08-03_final.stac-item
2023-08-14 11:41:25	ga_ls9c_ard_3-2-1_113082_2023-08-14_final.stac-item
2023-10-24 11:46:52	ga_ls9c_ard_3-2-1_114079_2023-10-24_final.stac-item
2023-10-25 09:15:09	ga_ls9c_ard_3-2-1_089086_2023-10-24_final.stac-item
2023-10-26 09:52:25	ga_ls9c_ard_3-2-1_096071_2023-10-26_final.stac-item
2023-10-27 10:36:28	ga_ls9c_ard_3-2-1_103073_2023-10-27_final.stac-item
2023-10-31 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-10-31_final.stac-item
2023-11-01 09:21:14	ga_ls9c_ard_3-2-1_090086_2023-10-31_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-15 11:10:54	ga_ls9c_ard_3-2-1_108082_2023-11-15_final.stac-item
2023-11-18 11:39:03	ga_ls9c_ard_3-2-1_113075_2023-11-18_final.stac-item
2023-11-22 09:40:18	ga_ls9c_ard_3-2-1_093087_2023-11-22_final.stac-item
2023-11-23 10:17:59	ga_ls9c_ard_3-2-1_100073_2023-11-23_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