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
2021-11-05 09:36:13	ga_ls9c_ard_3-2-1_093075_2021-11-05_final.stac-item
2021-11-17 09:22:52	ga_ls9c_ard_3-2-1_091076_2021-11-16_final.stac-item
2021-11-22 11:02:20	ga_ls9c_ard_3-2-1_107072_2021-11-22_final.stac-item
2021-12-04 11:03:22	ga_ls9c_ard_3-2-1_107078_2021-12-04_final.stac-item
2021-12-06 09:16:30	ga_ls9c_ard_3-2-1_089089_2021-12-05_final.stac-item
2021-12-14 11:37:57	ga_ls9c_ard_3-2-1_113072_2021-12-14_final.stac-item
2021-12-16 11:30:21	ga_ls9c_ard_3-2-1_111084_2021-12-16_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2021-12-24 10:38:08	ga_ls9c_ard_3-2-1_103077_2021-12-24_final.stac-item
2021-12-30 10:00:39	ga_ls9c_ard_3-2-1_097076_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
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-01 11:29:34	ga_ls9c_ard_3-2-1_111082_2022-01-01_final.stac-item
2022-01-08 09:56:26	ga_ls9c_ard_3-2-1_096081_2022-01-08_final.stac-item
2022-01-10 11:20:57	ga_ls9c_ard_3-2-1_110076_2022-01-10_final.stac-item
2022-01-15 11:39:05	ga_ls9c_ard_3-2-1_113075_2022-01-15_final.stac-item
2022-01-22 11:46:05	ga_ls9c_ard_3-2-1_114077_2022-01-22_final.stac-item
2022-01-24 09:53:39	ga_ls9c_ard_3-2-1_096074_2022-01-24_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-01-25 10:39:19	ga_ls9c_ard_3-2-1_103080_2022-01-25_final.stac-item
2022-02-06 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-02-05_final.stac-item
2022-02-16 10:00:57	ga_ls9c_ard_3-2-1_097077_2022-02-16_final.stac-item
2022-02-18 11:27:27	ga_ls9c_ard_3-2-1_111077_2022-02-18_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-02-19 10:33:49	ga_ls9c_ard_3-2-1_102082_2022-02-19_final.stac-item
2022-02-20 09:38:59	ga_ls9c_ard_3-2-1_093084_2022-02-20_final.stac-item
2022-02-22 11:00:41	ga_ls9c_ard_3-2-1_107072_2022-02-22_final.stac-item
2022-02-25 11:33:57	ga_ls9c_ard_3-2-1_112078_2022-02-25_final.stac-item
2022-02-28 10:27:07	ga_ls9c_ard_3-2-1_101081_2022-02-28_final.stac-item
2022-03-08 11:17:21	ga_ls9c_ard_3-2-1_109083_2022-03-08_final.stac-item
2022-04-19 10:14:54	ga_ls9c_ard_3-2-1_099082_2022-04-19_final.stac-item
2022-04-24 10:31:25	ga_ls9c_ard_3-2-1_102077_2022-04-24_final.stac-item
2022-05-05 10:14:49	ga_ls9c_ard_3-2-1_099082_2022-05-05_final.stac-item
2022-05-05 11:50:31	ga_ls9c_ard_3-2-1_115074_2022-05-05_final.stac-item
2022-05-16 09:53:45	ga_ls9c_ard_3-2-1_096076_2022-05-16_final.stac-item
2022-05-27 09:34:21	ga_ls9c_ard_3-2-1_093074_2022-05-27_final.stac-item
2022-05-31 10:52:07	ga_ls9c_ard_3-2-1_105083_2022-05-31_final.stac-item
2022-06-01 11:35:23	ga_ls9c_ard_3-2-1_112083_2022-06-01_final.stac-item
2022-06-20 10:23:13	ga_ls9c_ard_3-2-1_101072_2022-06-20_final.stac-item
2022-06-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2022-06-23_final.stac-item
2022-07-04 10:38:06	ga_ls9c_ard_3-2-1_103078_2022-07-04_final.stac-item
2022-07-10 11:40:40	ga_ls9c_ard_3-2-1_113080_2022-07-10_final.stac-item
2022-07-12 11:29:29	ga_ls9c_ard_3-2-1_111083_2022-07-12_final.stac-item
2022-07-21 11:21:25	ga_ls9c_ard_3-2-1_110078_2022-07-21_final.stac-item
2022-08-08 09:31:12	ga_ls9c_ard_3-2-1_092080_2022-08-08_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-08-10 10:58:32	ga_ls9c_ard_3-2-1_106082_2022-08-10_final.stac-item
2022-08-28 10:42:40	ga_ls9c_ard_3-2-1_104073_2022-08-28_final.stac-item
2022-09-03 11:47:15	ga_ls9c_ard_3-2-1_114080_2022-09-03_final.stac-item
2022-09-04 09:13:09	ga_ls9c_ard_3-2-1_089081_2022-09-03_final.stac-item
2022-09-09 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-09-09_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-10-13 09:19:31	ga_ls9c_ard_3-2-1_090081_2022-10-12_final.stac-item
2022-10-16 11:24:08	ga_ls9c_ard_3-2-1_111068_2022-10-16_final.stac-item
2022-11-03 11:17:19	ga_ls9c_ard_3-2-1_109082_2022-11-03_final.stac-item
2022-11-04 10:20:30	ga_ls9c_ard_3-2-1_100079_2022-11-04_final.stac-item
2022-11-04 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-11-04_final.stac-item
2022-11-28 09:29:53	ga_ls9c_ard_3-2-1_092076_2022-11-27_final.stac-item
2022-12-02 10:43:38	ga_ls9c_ard_3-2-1_104075_2022-12-02_final.stac-item
2022-12-08 10:06:35	ga_ls9c_ard_3-2-1_098075_2022-12-08_final.stac-item
2022-12-13 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-12-13_final.stac-item
2022-12-17 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-12-17_final.stac-item
2022-12-17 11:42:29	ga_ls9c_ard_3-2-1_113083_2022-12-17_final.stac-item
2022-12-28 11:20:44	ga_ls9c_ard_3-2-1_110075_2022-12-28_final.stac-item
2023-01-09 11:45:52	ga_ls9c_ard_3-2-1_114076_2023-01-09_final.stac-item
2023-01-09 11:46:40	ga_ls9c_ard_3-2-1_114078_2023-01-09_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-22 09:40:20	ga_ls9c_ard_3-2-1_093087_2023-01-22_final.stac-item
2023-01-29 11:24:44	ga_ls9c_ard_3-2-1_110085_2023-01-29_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 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-01-31_final.stac-item
2023-02-02 09:20:46	ga_ls9c_ard_3-2-1_090084_2023-02-01_final.stac-item
2023-02-07 11:13:02	ga_ls9c_ard_3-2-1_109071_2023-02-07_final.stac-item
2023-02-07 11:15:50	ga_ls9c_ard_3-2-1_109078_2023-02-07_final.stac-item
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-03-29 09:28:26	ga_ls9c_ard_3-2-1_091089_2023-03-28_final.stac-item
2023-04-01 09:56:56	ga_ls9c_ard_3-2-1_096083_2023-04-01_final.stac-item
2023-04-02 10:35:24	ga_ls9c_ard_3-2-1_103071_2023-04-02_final.stac-item
2023-04-13 10:21:58	ga_ls9c_ard_3-2-1_100084_2023-04-13_final.stac-item
2023-04-27 10:30:15	ga_ls9c_ard_3-2-1_102074_2023-04-27_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-05-20 10:34:36	ga_ls9c_ard_3-2-1_103070_2023-05-20_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-05-30 11:12:48	ga_ls9c_ard_3-2-1_109073_2023-05-30_final.stac-item
2023-06-24 09:31:58	ga_ls9c_ard_3-2-1_092084_2023-06-24_final.stac-item
2023-06-27 11:40:12	ga_ls9c_ard_3-2-1_113080_2023-06-27_final.stac-item
2023-07-01 11:16:47	ga_ls9c_ard_3-2-1_109083_2023-07-01_final.stac-item
2023-07-05 10:48:56	ga_ls9c_ard_3-2-1_105075_2023-07-05_final.stac-item
2023-07-25 10:23:51	ga_ls9c_ard_3-2-1_101074_2023-07-25_final.stac-item
2023-07-27 10:08:45	ga_ls9c_ard_3-2-1_099067_2023-07-27_final.stac-item
2023-08-13 10:58:09	ga_ls9c_ard_3-2-1_106082_2023-08-13_final.stac-item
2023-08-16 09:45:46	ga_ls9c_ard_3-2-1_095071_2023-08-16_final.stac-item
2023-10-15 11:53:02	ga_ls9c_ard_3-2-1_115079_2023-10-15_final.stac-item
2023-10-18 10:43:28	ga_ls9c_ard_3-2-1_104075_2023-10-18_final.stac-item
2023-10-26 11:35:17	ga_ls9c_ard_3-2-1_112081_2023-10-26_final.stac-item
2023-11-04 11:23:49	ga_ls9c_ard_3-2-1_111068_2023-11-04_final.stac-item
2023-11-17 09:19:17	ga_ls9c_ard_3-2-1_090081_2023-11-16_final.stac-item
2023-11-19 10:44:15	ga_ls9c_ard_3-2-1_104077_2023-11-19_final.stac-item
2023-11-23 10:17:59	ga_ls9c_ard_3-2-1_100073_2023-11-23_final.stac-item
2023-11-24 09:26:46	ga_ls9c_ard_3-2-1_091084_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