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
2021-11-06 10:16:11	ga_ls9c_ard_3-2-1_100075_2021-11-06_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2022-01-05 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-05_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-02-16 11:41:26	ga_ls9c_ard_3-2-1_113081_2022-02-16_final.stac-item
2022-04-17 10:26:54	ga_ls9c_ard_3-2-1_101081_2022-04-17_final.stac-item
2022-05-23 11:40:45	ga_ls9c_ard_3-2-1_113081_2022-05-23_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-06-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2022-06-23_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-12 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-08-12_final.stac-item
2022-08-15 11:13:07	ga_ls9c_ard_3-2-1_109072_2022-08-15_final.stac-item
2022-08-26 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-08-26_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-11-03 09:37:14	ga_ls9c_ard_3-2-1_093079_2022-11-03_final.stac-item
2022-12-07 11:02:12	ga_ls9c_ard_3-2-1_107075_2022-12-07_final.stac-item
2022-12-08 10:08:35	ga_ls9c_ard_3-2-1_098080_2022-12-08_final.stac-item
2022-12-30 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-30_final.stac-item
2023-01-24 09:26:25	ga_ls9c_ard_3-2-1_091083_2023-01-23_final.stac-item
2023-02-03 11:41:43	ga_ls9c_ard_3-2-1_113081_2023-02-03_final.stac-item
2023-02-04 10:40:55	ga_ls9c_ard_3-2-1_104068_2023-02-04_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 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-07 09:38:56	ga_ls9c_ard_3-2-1_093083_2023-02-07_final.stac-item
2023-02-08 10:19:01	ga_ls9c_ard_3-2-1_100075_2023-02-08_final.stac-item
2023-02-14 09:46:41	ga_ls9c_ard_3-2-1_094087_2023-02-14_final.stac-item
2023-04-23 09:19:44	ga_ls9c_ard_3-2-1_090083_2023-04-22_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-04-24 10:01:47	ga_ls9c_ard_3-2-1_097080_2023-04-24_final.stac-item
2023-04-25 10:43:02	ga_ls9c_ard_3-2-1_104075_2023-04-25_final.stac-item
2023-04-26 11:26:17	ga_ls9c_ard_3-2-1_111075_2023-04-26_final.stac-item
2023-04-26 11:27:05	ga_ls9c_ard_3-2-1_111077_2023-04-26_final.stac-item
2023-04-26 11:29:29	ga_ls9c_ard_3-2-1_111083_2023-04-26_final.stac-item
2023-04-27 10:31:27	ga_ls9c_ard_3-2-1_102077_2023-04-27_final.stac-item
2023-04-27 10:32:15	ga_ls9c_ard_3-2-1_102079_2023-04-27_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-04-30 11:03:06	ga_ls9c_ard_3-2-1_107079_2023-04-30_final.stac-item
2023-05-28 09:45:53	ga_ls9c_ard_3-2-1_095072_2023-05-28_final.stac-item
2023-05-28 09:47:29	ga_ls9c_ard_3-2-1_095076_2023-05-28_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-05-28 11:25:34	ga_ls9c_ard_3-2-1_111074_2023-05-28_final.stac-item
2023-05-28 11:27:09	ga_ls9c_ard_3-2-1_111078_2023-05-28_final.stac-item
2023-05-28 11:27:57	ga_ls9c_ard_3-2-1_111080_2023-05-28_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-08-02 09:33:21	ga_ls9c_ard_3-2-1_093071_2023-08-02_final.stac-item
2023-08-02 09:36:09	ga_ls9c_ard_3-2-1_093078_2023-08-02_final.stac-item
2023-08-02 11:13:26	ga_ls9c_ard_3-2-1_109074_2023-08-02_final.stac-item
2023-10-15 10:13:21	ga_ls9c_ard_3-2-1_099077_2023-10-15_final.stac-item
2023-10-15 11:51:02	ga_ls9c_ard_3-2-1_115074_2023-10-15_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-16 09:20:08	ga_ls9c_ard_3-2-1_090083_2023-10-15_final.stac-item
2023-10-16 10:55:01	ga_ls9c_ard_3-2-1_106073_2023-10-16_final.stac-item
2023-10-17 10:00:12	ga_ls9c_ard_3-2-1_097075_2023-10-17_final.stac-item
2023-10-17 10:03:24	ga_ls9c_ard_3-2-1_097083_2023-10-17_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-18 10:44:16	ga_ls9c_ard_3-2-1_104077_2023-10-18_final.stac-item
2023-10-18 10:44:40	ga_ls9c_ard_3-2-1_104078_2023-10-18_final.stac-item
2023-10-19 09:52:38	ga_ls9c_ard_3-2-1_095087_2023-10-19_final.stac-item
2023-10-19 11:27:08	ga_ls9c_ard_3-2-1_111076_2023-10-19_final.stac-item
2023-10-19 11:27:56	ga_ls9c_ard_3-2-1_111078_2023-10-19_final.stac-item
2023-10-19 11:29:32	ga_ls9c_ard_3-2-1_111082_2023-10-19_final.stac-item
2023-10-21 09:36:41	ga_ls9c_ard_3-2-1_093078_2023-10-21_final.stac-item
2023-10-21 11:16:46	ga_ls9c_ard_3-2-1_109081_2023-10-21_final.stac-item
2023-10-21 11:17:10	ga_ls9c_ard_3-2-1_109082_2023-10-21_final.stac-item
2023-10-21 11:17:58	ga_ls9c_ard_3-2-1_109084_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 10:21:56	ga_ls9c_ard_3-2-1_100083_2023-10-22_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2023-10-24 10:08:22	ga_ls9c_ard_3-2-1_098080_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
2023-10-25 10:51:14	ga_ls9c_ard_3-2-1_105079_2023-10-25_final.stac-item
2023-10-26 09:56:00	ga_ls9c_ard_3-2-1_096080_2023-10-26_final.stac-item
2023-10-26 11:32:53	ga_ls9c_ard_3-2-1_112075_2023-10-26_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_2023-10-27_final.stac-item
2023-10-27 10:37:39	ga_ls9c_ard_3-2-1_103076_2023-10-27_final.stac-item
2023-10-27 10:40:03	ga_ls9c_ard_3-2-1_103082_2023-10-27_final.stac-item
2023-10-28 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-28_final.stac-item
2023-10-28 11:21:18	ga_ls9c_ard_3-2-1_110077_2023-10-28_final.stac-item
2023-10-29 10:26:52	ga_ls9c_ard_3-2-1_101080_2023-10-29_final.stac-item
2023-10-29 10:27:40	ga_ls9c_ard_3-2-1_101082_2023-10-29_final.stac-item
2023-10-30 11:09:19	ga_ls9c_ard_3-2-1_108078_2023-10-30_final.stac-item
2023-11-01 09:17:39	ga_ls9c_ard_3-2-1_090077_2023-10-31_final.stac-item
2023-11-02 10:02:53	ga_ls9c_ard_3-2-1_097082_2023-11-02_final.stac-item
2023-11-04 09:49:43	ga_ls9c_ard_3-2-1_095080_2023-11-04_final.stac-item
2023-11-15 09:32:49	ga_ls9c_ard_3-2-1_092084_2023-11-15_final.stac-item
2023-11-15 09:33:37	ga_ls9c_ard_3-2-1_092086_2023-11-15_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-16 10:12:06	ga_ls9c_ard_3-2-1_099074_2023-11-16_final.stac-item
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_final.stac-item
2023-11-20 09:49:50	ga_ls9c_ard_3-2-1_095080_2023-11-20_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_2023-11-23_final.stac-item
2023-11-23 10:21:11	ga_ls9c_ard_3-2-1_100081_2023-11-23_final.stac-item
2023-11-23 10:21:59	ga_ls9c_ard_3-2-1_100083_2023-11-23_final.stac-item
2023-11-23 11:58:04	ga_ls9c_ard_3-2-1_116076_2023-11-23_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_final.stac-item
2023-11-25 10:06:03	ga_ls9c_ard_3-2-1_098074_2023-11-25_final.stac-item
2023-11-26 10:49:43	ga_ls9c_ard_3-2-1_105075_2023-11-26_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