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
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_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
2022-01-31 10:02:14	ga_ls9c_ard_3-2-1_097080_2022-01-31_final.stac-item
2022-02-03 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-02-03_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-03-24 09:36:00	ga_ls9c_ard_3-2-1_093077_2022-03-24_final.stac-item
2022-05-02 09:42:45	ga_ls9c_ard_3-2-1_094079_2022-05-02_final.stac-item
2022-05-08 10:41:42	ga_ls9c_ard_3-2-1_104072_2022-05-08_final.stac-item
2022-05-30 10:04:52	ga_ls9c_ard_3-2-1_098073_2022-05-30_final.stac-item
2022-06-12 09:36:25	ga_ls9c_ard_3-2-1_093079_2022-06-12_final.stac-item
2022-06-19 09:43:06	ga_ls9c_ard_3-2-1_094080_2022-06-19_final.stac-item
2022-07-18 10:48:28	ga_ls9c_ard_3-2-1_105073_2022-07-18_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-08-05 10:35:33	ga_ls9c_ard_3-2-1_103071_2022-08-05_final.stac-item
2022-08-07 10:22:49	ga_ls9c_ard_3-2-1_101070_2022-08-07_final.stac-item
2022-09-24 10:23:02	ga_ls9c_ard_3-2-1_101070_2022-09-24_final.stac-item
2022-09-29 10:42:23	ga_ls9c_ard_3-2-1_104072_2022-09-29_final.stac-item
2022-10-02 09:38:48	ga_ls9c_ard_3-2-1_093083_2022-10-02_final.stac-item
2022-10-04 09:24:50	ga_ls9c_ard_3-2-1_091079_2022-10-03_final.stac-item
2022-10-09 11:18:41	ga_ls9c_ard_3-2-1_110070_2022-10-09_final.stac-item
2022-10-20 11:03:49	ga_ls9c_ard_3-2-1_107079_2022-10-20_final.stac-item
2022-10-20 11:05:49	ga_ls9c_ard_3-2-1_107084_2022-10-20_final.stac-item
2022-10-27 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-10-27_final.stac-item
2022-10-27 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-10-27_final.stac-item
2022-10-30 11:40:05	ga_ls9c_ard_3-2-1_113077_2022-10-30_final.stac-item
2022-11-11 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-11-11_final.stac-item
2022-11-12 11:07:13	ga_ls9c_ard_3-2-1_108072_2022-11-12_final.stac-item
2022-11-17 11:27:45	ga_ls9c_ard_3-2-1_111077_2022-11-17_final.stac-item
2022-12-01 10:03:10	ga_ls9c_ard_3-2-1_097082_2022-12-01_final.stac-item
2022-12-01 11:40:03	ga_ls9c_ard_3-2-1_113077_2022-12-01_final.stac-item
2022-12-05 09:37:16	ga_ls9c_ard_3-2-1_093079_2022-12-05_final.stac-item
2022-12-10 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-12-10_final.stac-item
2022-12-11 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-12-11_final.stac-item
2022-12-12 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-12-12_final.stac-item
2022-12-12 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-12-12_final.stac-item
2022-12-12 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-12-12_final.stac-item
2022-12-12 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-12-12_final.stac-item
2022-12-19 11:29:42	ga_ls9c_ard_3-2-1_111082_2022-12-19_final.stac-item
2022-12-21 11:15:20	ga_ls9c_ard_3-2-1_109077_2022-12-21_final.stac-item
2022-12-28 09:42:39	ga_ls9c_ard_3-2-1_094077_2022-12-28_final.stac-item
2022-12-28 09:45:50	ga_ls9c_ard_3-2-1_094085_2022-12-28_final.stac-item
2022-12-30 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-30_final.stac-item
2023-01-05 10:32:55	ga_ls9c_ard_3-2-1_102079_2023-01-05_final.stac-item
2023-01-16 10:15:29	ga_ls9c_ard_3-2-1_099082_2023-01-16_final.stac-item
2023-01-17 10:56:20	ga_ls9c_ard_3-2-1_106076_2023-01-17_final.stac-item
2023-01-18 10:00:41	ga_ls9c_ard_3-2-1_097076_2023-01-18_final.stac-item
2023-01-18 11:40:46	ga_ls9c_ard_3-2-1_113079_2023-01-18_final.stac-item
2023-01-29 11:23:56	ga_ls9c_ard_3-2-1_110083_2023-01-29_final.stac-item
2023-01-31 11:10:00	ga_ls9c_ard_3-2-1_108079_2023-01-31_final.stac-item
2023-02-01 10:15:35	ga_ls9c_ard_3-2-1_099082_2023-02-01_final.stac-item
2023-02-04 10:41:43	ga_ls9c_ard_3-2-1_104070_2023-02-04_final.stac-item
2023-02-12 09:56:40	ga_ls9c_ard_3-2-1_096081_2023-02-12_final.stac-item
2023-02-13 10:39:08	ga_ls9c_ard_3-2-1_103079_2023-02-13_final.stac-item
2023-03-01 10:38:30	ga_ls9c_ard_3-2-1_103078_2023-03-01_final.stac-item
2023-03-03 10:27:19	ga_ls9c_ard_3-2-1_101081_2023-03-03_final.stac-item
2023-03-11 09:38:58	ga_ls9c_ard_3-2-1_093084_2023-03-11_final.stac-item
2023-04-26 09:50:36	ga_ls9c_ard_3-2-1_095083_2023-04-26_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-04-30 11:04:18	ga_ls9c_ard_3-2-1_107082_2023-04-30_final.stac-item
2023-05-03 09:56:39	ga_ls9c_ard_3-2-1_096083_2023-05-03_final.stac-item
2023-05-07 11:09:11	ga_ls9c_ard_3-2-1_108079_2023-05-07_final.stac-item
2023-05-09 10:58:02	ga_ls9c_ard_3-2-1_106082_2023-05-09_final.stac-item
2023-05-10 10:00:48	ga_ls9c_ard_3-2-1_097078_2023-05-10_final.stac-item
2023-05-12 09:50:26	ga_ls9c_ard_3-2-1_095083_2023-05-12_final.stac-item
2023-05-16 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-05-16_final.stac-item
2023-05-17 10:06:08	ga_ls9c_ard_3-2-1_098076_2023-05-17_final.stac-item
2023-05-17 11:44:37	ga_ls9c_ard_3-2-1_114075_2023-05-17_final.stac-item
2023-05-17 11:45:01	ga_ls9c_ard_3-2-1_114076_2023-05-17_final.stac-item
2023-05-30 09:37:54	ga_ls9c_ard_3-2-1_093083_2023-05-30_final.stac-item
2023-05-30 11:15:36	ga_ls9c_ard_3-2-1_109080_2023-05-30_final.stac-item
2023-06-23 10:22:48	ga_ls9c_ard_3-2-1_101072_2023-06-23_final.stac-item
2023-06-26 10:57:18	ga_ls9c_ard_3-2-1_106081_2023-06-26_final.stac-item
2023-06-28 10:41:01	ga_ls9c_ard_3-2-1_104071_2023-06-28_final.stac-item
2023-06-29 09:47:25	ga_ls9c_ard_3-2-1_095076_2023-06-29_final.stac-item
2023-07-06 09:52:07	ga_ls9c_ard_3-2-1_096072_2023-07-06_final.stac-item
2023-07-16 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-16 10:30:52	ga_ls9c_ard_3-2-1_102076_2023-07-16_final.stac-item
2023-07-17 09:36:50	ga_ls9c_ard_3-2-1_093080_2023-07-17_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 11:00:10	ga_ls9c_ard_3-2-1_107072_2023-07-19_final.stac-item
2023-07-21 10:47:48	ga_ls9c_ard_3-2-1_105072_2023-07-21_final.stac-item
2023-07-23 10:37:50	ga_ls9c_ard_3-2-1_103078_2023-07-23_final.stac-item
2023-07-29 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-07-29_final.stac-item
2023-08-04 09:24:13	ga_ls9c_ard_3-2-1_091079_2023-08-03_final.stac-item
2023-08-04 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-08-04_final.stac-item
2023-08-04 11:05:05	ga_ls9c_ard_3-2-1_107084_2023-08-04_final.stac-item
2023-08-08 10:38:24	ga_ls9c_ard_3-2-1_103079_2023-08-08_final.stac-item
2023-10-14 09:31:16	ga_ls9c_ard_3-2-1_092080_2023-10-14_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-28 11:23:42	ga_ls9c_ard_3-2-1_110083_2023-10-28_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_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
2023-10-30 11:11:19	ga_ls9c_ard_3-2-1_108083_2023-10-30_final.stac-item
2023-11-02 10:00:53	ga_ls9c_ard_3-2-1_097077_2023-11-02_final.stac-item
2023-11-04 09:50:31	ga_ls9c_ard_3-2-1_095082_2023-11-04_final.stac-item
2023-11-15 09:31:37	ga_ls9c_ard_3-2-1_092081_2023-11-15_final.stac-item
2023-11-15 11:10:30	ga_ls9c_ard_3-2-1_108081_2023-11-15_final.stac-item
2023-11-18 11:39:51	ga_ls9c_ard_3-2-1_113077_2023-11-18_final.stac-item
2024-02-16 10:36:52	ga_ls9c_ard_3-2-1_103074_2024-02-16_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