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
2021-11-14 10:40:16	ga_ls9c_ard_3-2-1_103076_2021-11-14_final.stac-item
2021-12-13 10:56:18	ga_ls9c_ard_3-2-1_106076_2021-12-13_final.stac-item
2022-01-14 10:56:37	ga_ls9c_ard_3-2-1_106077_2022-01-14_final.stac-item
2022-01-19 09:37:05	ga_ls9c_ard_3-2-1_093079_2022-01-19_final.stac-item
2022-01-20 10:20:21	ga_ls9c_ard_3-2-1_100079_2022-01-20_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-01-28 09:31:20	ga_ls9c_ard_3-2-1_092080_2022-01-28_final.stac-item
2022-02-01 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-02-01_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-03-03 09:19:07	ga_ls9c_ard_3-2-1_090081_2022-03-02_final.stac-item
2022-03-11 10:08:10	ga_ls9c_ard_3-2-1_098080_2022-03-11_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-03-30 10:37:47	ga_ls9c_ard_3-2-1_103077_2022-03-30_final.stac-item
2022-04-16 09:44:51	ga_ls9c_ard_3-2-1_094084_2022-04-16_final.stac-item
2022-04-27 09:23:50	ga_ls9c_ard_3-2-1_091078_2022-04-26_final.stac-item
2022-05-25 09:47:06	ga_ls9c_ard_3-2-1_095075_2022-05-25_final.stac-item
2022-06-23 09:19:43	ga_ls9c_ard_3-2-1_090083_2022-06-22_final.stac-item
2022-07-23 09:31:00	ga_ls9c_ard_3-2-1_092080_2022-07-23_final.stac-item
2022-07-26 09:59:33	ga_ls9c_ard_3-2-1_097074_2022-07-26_final.stac-item
2022-08-13 09:47:47	ga_ls9c_ard_3-2-1_095075_2022-08-13_final.stac-item
2022-09-13 10:45:53	ga_ls9c_ard_3-2-1_104081_2022-09-13_final.stac-item
2022-09-28 10:03:31	ga_ls9c_ard_3-2-1_097083_2022-09-28_final.stac-item
2022-09-30 09:50:45	ga_ls9c_ard_3-2-1_095082_2022-09-30_final.stac-item
2022-10-10 10:25:04	ga_ls9c_ard_3-2-1_101075_2022-10-10_final.stac-item
2022-10-19 10:18:33	ga_ls9c_ard_3-2-1_100074_2022-10-19_final.stac-item
2022-10-21 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-10-21_final.stac-item
2022-10-26 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-10-26_final.stac-item
2022-10-29 10:57:37	ga_ls9c_ard_3-2-1_106079_2022-10-29_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_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
2022-11-05 09:24:53	ga_ls9c_ard_3-2-1_091079_2022-11-04_final.stac-item
2022-11-09 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-11-09_final.stac-item
2022-11-10 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-10_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-18 10:32:08	ga_ls9c_ard_3-2-1_102077_2022-11-18_final.stac-item
2022-11-19 09:36:54	ga_ls9c_ard_3-2-1_093078_2022-11-19_final.stac-item
2022-12-01 11:39:39	ga_ls9c_ard_3-2-1_113076_2022-12-01_final.stac-item
2022-12-03 11:30:05	ga_ls9c_ard_3-2-1_111083_2022-12-03_final.stac-item
2022-12-08 10:06:59	ga_ls9c_ard_3-2-1_098076_2022-12-08_final.stac-item
2022-12-10 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-12-10_final.stac-item
2022-12-17 10:01:36	ga_ls9c_ard_3-2-1_097078_2022-12-17_final.stac-item
2022-12-18 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-12-18_final.stac-item
2022-12-18 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-12-18_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-26 09:57:23	ga_ls9c_ard_3-2-1_096083_2022-12-26_final.stac-item
2023-01-04 09:52:03	ga_ls9c_ard_3-2-1_095085_2023-01-04_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-17 09:18:39	ga_ls9c_ard_3-2-1_090079_2023-01-16_final.stac-item
2023-01-24 11:01:19	ga_ls9c_ard_3-2-1_107073_2023-01-24_final.stac-item
2023-01-31 09:33:06	ga_ls9c_ard_3-2-1_092084_2023-01-31_final.stac-item
2023-02-02 09:20:22	ga_ls9c_ard_3-2-1_090083_2023-02-01_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-02 10:57:15	ga_ls9c_ard_3-2-1_106078_2023-02-02_final.stac-item
2023-02-05 11:29:23	ga_ls9c_ard_3-2-1_111081_2023-02-05_final.stac-item
2023-02-06 10:32:10	ga_ls9c_ard_3-2-1_102077_2023-02-06_final.stac-item
2023-02-07 09:36:33	ga_ls9c_ard_3-2-1_093077_2023-02-07_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-09 11:03:52	ga_ls9c_ard_3-2-1_107079_2023-02-09_final.stac-item
2023-02-10 10:07:03	ga_ls9c_ard_3-2-1_098076_2023-02-10_final.stac-item
2023-02-11 09:13:01	ga_ls9c_ard_3-2-1_089080_2023-02-10_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-04-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2023-04-23_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-03 09:52:16	ga_ls9c_ard_3-2-1_096072_2023-05-03_final.stac-item
2023-05-08 10:14:46	ga_ls9c_ard_3-2-1_099082_2023-05-08_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-06-23 10:25:12	ga_ls9c_ard_3-2-1_101078_2023-06-23_final.stac-item
2023-06-27 11:40:12	ga_ls9c_ard_3-2-1_113080_2023-06-27_final.stac-item
2023-07-17 09:38:26	ga_ls9c_ard_3-2-1_093084_2023-07-17_final.stac-item
2023-07-19 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-07-18_final.stac-item
2023-07-25 10:24:39	ga_ls9c_ard_3-2-1_101076_2023-07-25_final.stac-item
2023-10-15 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-23 09:25:31	ga_ls9c_ard_3-2-1_091081_2023-10-22_final.stac-item
2023-10-23 11:01:12	ga_ls9c_ard_3-2-1_107073_2023-10-23_final.stac-item
2023-10-23 11:02:48	ga_ls9c_ard_3-2-1_107077_2023-10-23_final.stac-item
2023-10-23 11:03:36	ga_ls9c_ard_3-2-1_107079_2023-10-23_final.stac-item
2023-10-27 10:39:15	ga_ls9c_ard_3-2-1_103080_2023-10-27_final.stac-item
2023-10-28 11:21:42	ga_ls9c_ard_3-2-1_110078_2023-10-28_final.stac-item
2023-10-29 10:24:29	ga_ls9c_ard_3-2-1_101074_2023-10-29_final.stac-item
2023-10-30 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-10-30_final.stac-item
2023-10-30 11:10:55	ga_ls9c_ard_3-2-1_108082_2023-10-30_final.stac-item
2023-10-31 11:50:58	ga_ls9c_ard_3-2-1_115074_2023-10-31_final.stac-item
2023-11-04 11:26:37	ga_ls9c_ard_3-2-1_111075_2023-11-04_final.stac-item
2023-11-14 10:22:52	ga_ls9c_ard_3-2-1_101070_2023-11-14_final.stac-item
2023-11-14 10:24:27	ga_ls9c_ard_3-2-1_101074_2023-11-14_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-17 10:56:34	ga_ls9c_ard_3-2-1_106077_2023-11-17_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-11-24 09:27:34	ga_ls9c_ard_3-2-1_091086_2023-11-23_final.stac-item
2023-11-27 11:34:10	ga_ls9c_ard_3-2-1_112078_2023-11-27_final.stac-item
2023-11-29 11:23:01	ga_ls9c_ard_3-2-1_110081_2023-11-29_final.stac-item
2024-02-16 10:37:40	ga_ls9c_ard_3-2-1_103076_2024-02-16_final.stac-item
2024-02-17 09:45:37	ga_ls9c_ard_3-2-1_094085_2024-02-17_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