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 09:40:36	ga_ls9c_ard_3-2-1_093086_2021-11-05_final.stac-item
2021-11-18 10:01:58	ga_ls9c_ard_3-2-1_097074_2021-11-18_final.stac-item
2021-11-18 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-11-23 10:02:26	ga_ls9c_ard_3-2-1_098069_2021-11-23_final.stac-item
2021-12-06 10:52:11	ga_ls9c_ard_3-2-1_105081_2021-12-06_final.stac-item
2021-12-16 11:30:21	ga_ls9c_ard_3-2-1_111084_2021-12-16_final.stac-item
2021-12-29 09:20:59	ga_ls9c_ard_3-2-1_090085_2021-12-28_final.stac-item
2021-12-30 10:01:51	ga_ls9c_ard_3-2-1_097079_2021-12-30_final.stac-item
2022-01-07 10:52:04	ga_ls9c_ard_3-2-1_105081_2022-01-07_final.stac-item
2022-02-07 10:04:00	ga_ls9c_ard_3-2-1_098069_2022-02-07_final.stac-item
2022-02-18 11:27:03	ga_ls9c_ard_3-2-1_111076_2022-02-18_final.stac-item
2022-03-07 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-03-07_final.stac-item
2022-03-24 09:38:00	ga_ls9c_ard_3-2-1_093082_2022-03-24_final.stac-item
2022-03-24 09:38:48	ga_ls9c_ard_3-2-1_093084_2022-03-24_final.stac-item
2022-03-31 09:41:22	ga_ls9c_ard_3-2-1_094075_2022-03-31_final.stac-item
2022-04-05 11:38:47	ga_ls9c_ard_3-2-1_113075_2022-04-05_final.stac-item
2022-04-09 11:17:14	ga_ls9c_ard_3-2-1_109083_2022-04-09_final.stac-item
2022-04-12 11:46:54	ga_ls9c_ard_3-2-1_114080_2022-04-12_final.stac-item
2022-04-17 10:24:54	ga_ls9c_ard_3-2-1_101076_2022-04-17_final.stac-item
2022-04-25 09:39:47	ga_ls9c_ard_3-2-1_093087_2022-04-25_final.stac-item
2022-05-03 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-05-03_final.stac-item
2022-05-07 09:58:27	ga_ls9c_ard_3-2-1_097072_2022-05-07_final.stac-item
2022-05-20 11:07:51	ga_ls9c_ard_3-2-1_108076_2022-05-20_final.stac-item
2022-05-31 10:50:07	ga_ls9c_ard_3-2-1_105078_2022-05-31_final.stac-item
2022-06-06 11:52:44	ga_ls9c_ard_3-2-1_115080_2022-06-06_final.stac-item
2022-06-07 10:53:55	ga_ls9c_ard_3-2-1_106072_2022-06-07_final.stac-item
2022-06-08 11:39:11	ga_ls9c_ard_3-2-1_113077_2022-06-08_final.stac-item
2022-06-18 10:37:06	ga_ls9c_ard_3-2-1_103076_2022-06-18_final.stac-item
2022-07-07 09:33:18	ga_ls9c_ard_3-2-1_092086_2022-07-07_final.stac-item
2022-07-10 10:02:35	ga_ls9c_ard_3-2-1_097082_2022-07-10_final.stac-item
2022-07-10 11:40:40	ga_ls9c_ard_3-2-1_113080_2022-07-10_final.stac-item
2022-08-01 11:05:25	ga_ls9c_ard_3-2-1_107084_2022-08-01_final.stac-item
2022-08-11 10:00:56	ga_ls9c_ard_3-2-1_097077_2022-08-11_final.stac-item
2022-08-16 10:17:30	ga_ls9c_ard_3-2-1_100072_2022-08-16_final.stac-item
2022-08-18 10:03:10	ga_ls9c_ard_3-2-1_098067_2022-08-18_final.stac-item
2022-08-21 10:36:52	ga_ls9c_ard_3-2-1_103074_2022-08-21_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-09-15 10:31:57	ga_ls9c_ard_3-2-1_102077_2022-09-15_final.stac-item
2022-09-18 11:04:04	ga_ls9c_ard_3-2-1_107080_2022-09-18_final.stac-item
2022-09-20 10:47:44	ga_ls9c_ard_3-2-1_105070_2022-09-20_final.stac-item
2022-09-25 11:06:42	ga_ls9c_ard_3-2-1_108071_2022-09-25_final.stac-item
2022-10-15 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-15_final.stac-item
2022-10-18 09:40:05	ga_ls9c_ard_3-2-1_093086_2022-10-18_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-20 11:05:25	ga_ls9c_ard_3-2-1_107083_2022-10-20_final.stac-item
2022-10-22 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-10-22_final.stac-item
2022-10-22 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-10-22_final.stac-item
2022-10-24 10:40:18	ga_ls9c_ard_3-2-1_103082_2022-10-24_final.stac-item
2022-10-28 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-10-28_final.stac-item
2022-11-09 10:37:53	ga_ls9c_ard_3-2-1_103076_2022-11-09_final.stac-item
2022-11-09 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-11-09_final.stac-item
2022-11-13 11:52:04	ga_ls9c_ard_3-2-1_115076_2022-11-13_final.stac-item
2022-11-23 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-11-23_final.stac-item
2022-12-23 09:26:28	ga_ls9c_ard_3-2-1_091083_2022-12-22_final.stac-item
2022-12-31 10:15:10	ga_ls9c_ard_3-2-1_099081_2022-12-31_final.stac-item
2023-01-13 11:21:31	ga_ls9c_ard_3-2-1_110077_2023-01-13_final.stac-item
2023-01-14 10:25:53	ga_ls9c_ard_3-2-1_101077_2023-01-14_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-21 10:31:09	ga_ls9c_ard_3-2-1_102075_2023-01-21_final.stac-item
2023-01-21 10:31:57	ga_ls9c_ard_3-2-1_102077_2023-01-21_final.stac-item
2023-01-26 10:50:35	ga_ls9c_ard_3-2-1_105077_2023-01-26_final.stac-item
2023-02-02 09:19:34	ga_ls9c_ard_3-2-1_090081_2023-02-01_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-03 11:41:20	ga_ls9c_ard_3-2-1_113080_2023-02-03_final.stac-item
2023-02-07 11:17:50	ga_ls9c_ard_3-2-1_109083_2023-02-07_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_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 09:45:29	ga_ls9c_ard_3-2-1_094084_2023-02-14_final.stac-item
2023-02-20 09:07:54	ga_ls9c_ard_3-2-1_088083_2023-02-19_final.stac-item
2023-03-02 11:21:21	ga_ls9c_ard_3-2-1_110077_2023-03-02_final.stac-item
2023-04-05 09:31:24	ga_ls9c_ard_3-2-1_092081_2023-04-05_final.stac-item
2023-04-12 09:33:32	ga_ls9c_ard_3-2-1_093071_2023-04-12_final.stac-item
2023-04-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2023-04-23_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-05-02 09:16:12	ga_ls9c_ard_3-2-1_089090_2023-05-01_final.stac-item
2023-05-02 10:49:54	ga_ls9c_ard_3-2-1_105077_2023-05-02_final.stac-item
2023-05-03 09:56:39	ga_ls9c_ard_3-2-1_096083_2023-05-03_final.stac-item
2023-05-09 09:17:33	ga_ls9c_ard_3-2-1_090078_2023-05-08_final.stac-item
2023-05-13 10:30:06	ga_ls9c_ard_3-2-1_102074_2023-05-13_final.stac-item
2023-05-17 10:03:44	ga_ls9c_ard_3-2-1_098070_2023-05-17_final.stac-item
2023-05-18 09:12:06	ga_ls9c_ard_3-2-1_089080_2023-05-17_final.stac-item
2023-05-31 10:17:35	ga_ls9c_ard_3-2-1_100074_2023-05-31_final.stac-item
2023-06-19 10:47:56	ga_ls9c_ard_3-2-1_105073_2023-06-19_final.stac-item
2023-06-20 09:57:06	ga_ls9c_ard_3-2-1_096085_2023-06-20_final.stac-item
2023-06-24 11:04:52	ga_ls9c_ard_3-2-1_108069_2023-06-24_final.stac-item
2023-07-05 09:16:02	ga_ls9c_ard_3-2-1_089090_2023-07-04_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-19 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-07-18_final.stac-item
2023-08-02 09:34:57	ga_ls9c_ard_3-2-1_093075_2023-08-02_final.stac-item
2023-08-03 11:57:31	ga_ls9c_ard_3-2-1_116076_2023-08-03_final.stac-item
2023-08-05 11:44:22	ga_ls9c_ard_3-2-1_114074_2023-08-05_final.stac-item
2023-08-09 11:20:52	ga_ls9c_ard_3-2-1_110077_2023-08-09_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-26 09:52:01	ga_ls9c_ard_3-2-1_096070_2023-10-26_final.stac-item
2023-11-01 09:19:38	ga_ls9c_ard_3-2-1_090082_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 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-16 11:50:59	ga_ls9c_ard_3-2-1_115074_2023-11-16_final.stac-item
2023-11-23 10:18:47	ga_ls9c_ard_3-2-1_100075_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