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
2021-11-11 10:19:03	ga_ls9c_ard_3-2-1_100076_2021-11-11_final.stac-item
2021-11-14 10:37:05	ga_ls9c_ard_3-2-1_103068_2021-11-14_final.stac-item
2021-11-19 10:41:32	ga_ls9c_ard_3-2-1_104073_2021-11-19_final.stac-item
2021-11-23 10:03:38	ga_ls9c_ard_3-2-1_098072_2021-11-23_final.stac-item
2021-12-06 10:52:59	ga_ls9c_ard_3-2-1_105083_2021-12-06_final.stac-item
2021-12-07 09:56:57	ga_ls9c_ard_3-2-1_096082_2021-12-07_final.stac-item
2021-12-07 11:33:03	ga_ls9c_ard_3-2-1_112075_2021-12-07_final.stac-item
2021-12-17 10:31:32	ga_ls9c_ard_3-2-1_102076_2021-12-17_final.stac-item
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_2021-12-19_final.stac-item
2021-12-20 11:04:02	ga_ls9c_ard_3-2-1_107080_2021-12-20_final.stac-item
2021-12-30 10:03:02	ga_ls9c_ard_3-2-1_097082_2021-12-30_final.stac-item
2021-12-30 11:41:08	ga_ls9c_ard_3-2-1_113080_2021-12-30_final.stac-item
2022-01-09 10:39:17	ga_ls9c_ard_3-2-1_103080_2022-01-09_final.stac-item
2022-01-15 10:01:48	ga_ls9c_ard_3-2-1_097079_2022-01-15_final.stac-item
2022-02-04 09:39:54	ga_ls9c_ard_3-2-1_093086_2022-02-04_final.stac-item
2022-02-11 09:44:27	ga_ls9c_ard_3-2-1_094082_2022-02-11_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-02-17 10:41:01	ga_ls9c_ard_3-2-1_104069_2022-02-17_final.stac-item
2022-03-11 10:08:10	ga_ls9c_ard_3-2-1_098080_2022-03-11_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-04-08 10:29:35	ga_ls9c_ard_3-2-1_102072_2022-04-08_final.stac-item
2022-04-27 11:00:19	ga_ls9c_ard_3-2-1_107072_2022-04-27_final.stac-item
2022-04-28 10:06:17	ga_ls9c_ard_3-2-1_098076_2022-04-28_final.stac-item
2022-05-02 11:23:38	ga_ls9c_ard_3-2-1_110084_2022-05-02_final.stac-item
2022-05-14 10:05:45	ga_ls9c_ard_3-2-1_098075_2022-05-14_final.stac-item
2022-06-01 11:34:35	ga_ls9c_ard_3-2-1_112081_2022-06-01_final.stac-item
2022-06-10 11:27:38	ga_ls9c_ard_3-2-1_111079_2022-06-10_final.stac-item
2022-06-19 09:42:42	ga_ls9c_ard_3-2-1_094079_2022-06-19_final.stac-item
2022-06-19 11:22:00	ga_ls9c_ard_3-2-1_110080_2022-06-19_final.stac-item
2022-06-20 10:25:36	ga_ls9c_ard_3-2-1_101078_2022-06-20_final.stac-item
2022-07-08 11:51:51	ga_ls9c_ard_3-2-1_115077_2022-07-08_final.stac-item
2022-07-09 09:17:44	ga_ls9c_ard_3-2-1_090078_2022-07-08_final.stac-item
2022-07-10 09:59:00	ga_ls9c_ard_3-2-1_097073_2022-07-10_final.stac-item
2022-07-20 10:36:08	ga_ls9c_ard_3-2-1_103073_2022-07-20_final.stac-item
2022-07-25 10:57:33	ga_ls9c_ard_3-2-1_106080_2022-07-25_final.stac-item
2022-07-28 11:27:42	ga_ls9c_ard_3-2-1_111078_2022-07-28_final.stac-item
2022-07-30 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-07-30_final.stac-item
2022-08-06 09:43:32	ga_ls9c_ard_3-2-1_094080_2022-08-06_final.stac-item
2022-08-08 11:08:53	ga_ls9c_ard_3-2-1_108077_2022-08-08_final.stac-item
2022-08-16 10:20:18	ga_ls9c_ard_3-2-1_100079_2022-08-16_final.stac-item
2022-08-19 10:48:01	ga_ls9c_ard_3-2-1_105071_2022-08-19_final.stac-item
2022-08-21 10:40:03	ga_ls9c_ard_3-2-1_103082_2022-08-21_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-08-31 11:15:33	ga_ls9c_ard_3-2-1_109078_2022-08-31_final.stac-item
2022-09-12 09:58:37	ga_ls9c_ard_3-2-1_097071_2022-09-12_final.stac-item
2022-09-13 10:41:54	ga_ls9c_ard_3-2-1_104071_2022-09-13_final.stac-item
2022-09-17 10:18:24	ga_ls9c_ard_3-2-1_100074_2022-09-17_final.stac-item
2022-09-19 11:47:21	ga_ls9c_ard_3-2-1_114080_2022-09-19_final.stac-item
2022-09-26 10:13:05	ga_ls9c_ard_3-2-1_099076_2022-09-26_final.stac-item
2022-09-29 10:44:47	ga_ls9c_ard_3-2-1_104078_2022-09-29_final.stac-item
2022-10-02 09:34:00	ga_ls9c_ard_3-2-1_093071_2022-10-02_final.stac-item
2022-10-08 10:38:12	ga_ls9c_ard_3-2-1_103077_2022-10-08_final.stac-item
2022-10-11 11:11:56	ga_ls9c_ard_3-2-1_108084_2022-10-11_final.stac-item
2022-10-22 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-10-22_final.stac-item
2022-11-04 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-11-04_final.stac-item
2022-11-04 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-11-04_final.stac-item
2022-11-06 10:06:34	ga_ls9c_ard_3-2-1_098075_2022-11-06_final.stac-item
2022-11-09 10:37:53	ga_ls9c_ard_3-2-1_103076_2022-11-09_final.stac-item
2022-11-16 10:45:41	ga_ls9c_ard_3-2-1_104080_2022-11-16_final.stac-item
2022-11-19 11:15:24	ga_ls9c_ard_3-2-1_109077_2022-11-19_final.stac-item
2022-12-01 10:01:10	ga_ls9c_ard_3-2-1_097077_2022-12-01_final.stac-item
2022-12-01 11:39:15	ga_ls9c_ard_3-2-1_113075_2022-12-01_final.stac-item
2022-12-03 11:25:18	ga_ls9c_ard_3-2-1_111071_2022-12-03_final.stac-item
2022-12-04 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-04_final.stac-item
2022-12-08 10:07:23	ga_ls9c_ard_3-2-1_098077_2022-12-08_final.stac-item
2022-12-12 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-12-12_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-17 10:04:00	ga_ls9c_ard_3-2-1_097084_2022-12-17_final.stac-item
2023-01-02 10:03:12	ga_ls9c_ard_3-2-1_097082_2023-01-02_final.stac-item
2023-01-30 10:27:55	ga_ls9c_ard_3-2-1_101082_2023-01-30_final.stac-item
2023-01-31 11:10:00	ga_ls9c_ard_3-2-1_108079_2023-01-31_final.stac-item
2023-02-02 10:58:03	ga_ls9c_ard_3-2-1_106080_2023-02-02_final.stac-item
2023-02-10 10:08:15	ga_ls9c_ard_3-2-1_098079_2023-02-10_final.stac-item
2023-02-10 11:46:20	ga_ls9c_ard_3-2-1_114077_2023-02-10_final.stac-item
2023-02-14 09:42:42	ga_ls9c_ard_3-2-1_094077_2023-02-14_final.stac-item
2023-02-16 11:11:11	ga_ls9c_ard_3-2-1_108082_2023-02-16_final.stac-item
2023-02-18 10:58:23	ga_ls9c_ard_3-2-1_106081_2023-02-18_final.stac-item
2023-03-11 09:35:23	ga_ls9c_ard_3-2-1_093075_2023-03-11_final.stac-item
2023-03-12 10:21:26	ga_ls9c_ard_3-2-1_100082_2023-03-12_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-14 10:07:53	ga_ls9c_ard_3-2-1_098079_2023-03-14_final.stac-item
2023-03-25 09:47:39	ga_ls9c_ard_3-2-1_095075_2023-03-25_final.stac-item
2023-04-06 10:12:16	ga_ls9c_ard_3-2-1_099075_2023-04-06_final.stac-item
2023-04-08 10:00:17	ga_ls9c_ard_3-2-1_097076_2023-04-08_final.stac-item
2023-04-10 09:49:06	ga_ls9c_ard_3-2-1_095079_2023-04-10_final.stac-item
2023-04-16 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-04-15_final.stac-item
2023-05-04 10:36:18	ga_ls9c_ard_3-2-1_103074_2023-05-04_final.stac-item
2023-06-05 10:36:29	ga_ls9c_ard_3-2-1_103075_2023-06-05_final.stac-item
2023-06-10 09:18:30	ga_ls9c_ard_3-2-1_090081_2023-06-09_final.stac-item
2023-06-21 10:35:58	ga_ls9c_ard_3-2-1_103074_2023-06-21_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-10-13 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-13_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-27 10:37:39	ga_ls9c_ard_3-2-1_103076_2023-10-27_final.stac-item
2023-10-31 11:50:58	ga_ls9c_ard_3-2-1_115074_2023-10-31_final.stac-item
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final.stac-item
2023-11-01 09:20:26	ga_ls9c_ard_3-2-1_090084_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
2023-11-02 11:41:22	ga_ls9c_ard_3-2-1_113081_2023-11-02_final.stac-item
2023-11-21 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-11-21_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