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
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-11-18 10:05:33	ga_ls9c_ard_3-2-1_097083_2021-11-18_final.stac-item
2021-11-24 10:45:34	ga_ls9c_ard_3-2-1_104077_2021-11-24_final.stac-item
2021-12-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2021-12-08_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2022-01-07 10:52:28	ga_ls9c_ard_3-2-1_105082_2022-01-07_final.stac-item
2022-01-16 10:41:28	ga_ls9c_ard_3-2-1_104070_2022-01-16_final.stac-item
2022-01-23 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-23_final.stac-item
2022-02-02 09:47:52	ga_ls9c_ard_3-2-1_095075_2022-02-02_final.stac-item
2022-02-17 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-02-17_final.stac-item
2022-02-24 10:52:18	ga_ls9c_ard_3-2-1_105082_2022-02-24_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-07-16 09:23:54	ga_ls9c_ard_3-2-1_091078_2022-07-15_final.stac-item
2022-07-27 10:43:37	ga_ls9c_ard_3-2-1_104076_2022-07-27_final.stac-item
2022-08-05 10:38:21	ga_ls9c_ard_3-2-1_103078_2022-08-05_final.stac-item
2022-08-15 11:13:07	ga_ls9c_ard_3-2-1_109072_2022-08-15_final.stac-item
2022-09-27 10:57:32	ga_ls9c_ard_3-2-1_106079_2022-09-27_final.stac-item
2022-10-05 11:44:59	ga_ls9c_ard_3-2-1_114074_2022-10-05_final.stac-item
2022-10-12 11:51:13	ga_ls9c_ard_3-2-1_115074_2022-10-12_final.stac-item
2022-11-25 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-25_final.stac-item
2022-12-04 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-04_final.stac-item
2022-12-30 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-30_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-08 09:25:19	ga_ls9c_ard_3-2-1_091080_2023-01-07_final.stac-item
2023-01-14 10:23:53	ga_ls9c_ard_3-2-1_101072_2023-01-14_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-20 09:48:41	ga_ls9c_ard_3-2-1_095077_2023-01-20_final.stac-item
2023-02-03 10:01:15	ga_ls9c_ard_3-2-1_097077_2023-02-03_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-05 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-05 11:27:23	ga_ls9c_ard_3-2-1_111076_2023-02-05_final.stac-item
2023-02-07 11:14:38	ga_ls9c_ard_3-2-1_109075_2023-02-07_final.stac-item
2023-02-09 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-10 10:07:51	ga_ls9c_ard_3-2-1_098078_2023-02-10_final.stac-item
2023-02-16 09:31:30	ga_ls9c_ard_3-2-1_092080_2023-02-16_final.stac-item
2023-04-23 09:18:32	ga_ls9c_ard_3-2-1_090080_2023-04-22_final.stac-item
2023-04-24 11:38:40	ga_ls9c_ard_3-2-1_113075_2023-04-24_final.stac-item
2023-04-25 10:43:02	ga_ls9c_ard_3-2-1_104075_2023-04-25_final.stac-item
2023-04-25 10:43:26	ga_ls9c_ard_3-2-1_104076_2023-04-25_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-25 10:45:26	ga_ls9c_ard_3-2-1_104081_2023-04-25_final.stac-item
2023-04-26 09:50:12	ga_ls9c_ard_3-2-1_095082_2023-04-26_final.stac-item
2023-04-26 09:51:24	ga_ls9c_ard_3-2-1_095085_2023-04-26_final.stac-item
2023-04-27 10:31:03	ga_ls9c_ard_3-2-1_102076_2023-04-27_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 09:36:13	ga_ls9c_ard_3-2-1_093078_2023-04-28_final.stac-item
2023-04-29 10:19:51	ga_ls9c_ard_3-2-1_100079_2023-04-29_final.stac-item
2023-04-30 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-04-30_final.stac-item
2023-04-30 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-04-30_final.stac-item
2023-05-28 09:47:29	ga_ls9c_ard_3-2-1_095076_2023-05-28_final.stac-item
2023-07-05 10:49:44	ga_ls9c_ard_3-2-1_105077_2023-07-05_final.stac-item
2023-07-16 10:32:28	ga_ls9c_ard_3-2-1_102080_2023-07-16_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_2023-07-20_final.stac-item
2023-07-25 10:22:40	ga_ls9c_ard_3-2-1_101071_2023-07-25_final.stac-item
2023-07-26 11:07:08	ga_ls9c_ard_3-2-1_108074_2023-07-26_final.stac-item
2023-07-29 09:56:49	ga_ls9c_ard_3-2-1_097068_2023-07-29_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_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
2023-10-15 10:14:57	ga_ls9c_ard_3-2-1_099081_2023-10-15_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-17 10:01:00	ga_ls9c_ard_3-2-1_097077_2023-10-17_final.stac-item
2023-10-17 10:03:48	ga_ls9c_ard_3-2-1_097084_2023-10-17_final.stac-item
2023-10-18 10:44:16	ga_ls9c_ard_3-2-1_104077_2023-10-18_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-10-19 09:49:51	ga_ls9c_ard_3-2-1_095080_2023-10-19_final.stac-item
2023-10-19 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-10-19_final.stac-item
2023-10-19 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-10-19_final.stac-item
2023-10-19 11:24:20	ga_ls9c_ard_3-2-1_111069_2023-10-19_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-22 10:18:45	ga_ls9c_ard_3-2-1_100075_2023-10-22_final.stac-item
2023-10-22 10:21:09	ga_ls9c_ard_3-2-1_100081_2023-10-22_final.stac-item
2023-10-22 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-10-22_final.stac-item
2023-10-24 10:09:10	ga_ls9c_ard_3-2-1_098082_2023-10-24_final.stac-item
2023-10-25 10:46:50	ga_ls9c_ard_3-2-1_105068_2023-10-25_final.stac-item
2023-10-27 10:36:28	ga_ls9c_ard_3-2-1_103073_2023-10-27_final.stac-item
2023-11-01 10:56:55	ga_ls9c_ard_3-2-1_106078_2023-11-01_final.stac-item
2023-11-02 11:40:58	ga_ls9c_ard_3-2-1_113080_2023-11-02_final.stac-item
2023-11-04 09:48:32	ga_ls9c_ard_3-2-1_095077_2023-11-04_final.stac-item
2023-11-04 09:49:43	ga_ls9c_ard_3-2-1_095080_2023-11-04_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_final.stac-item
2023-11-04 11:30:12	ga_ls9c_ard_3-2-1_111084_2023-11-04_final.stac-item
2023-11-15 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-11-15_final.stac-item
2023-11-16 10:12:06	ga_ls9c_ard_3-2-1_099074_2023-11-16_final.stac-item
2023-11-16 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-11-16_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-17 10:55:46	ga_ls9c_ard_3-2-1_106075_2023-11-17_final.stac-item
2023-11-17 10:56:34	ga_ls9c_ard_3-2-1_106077_2023-11-17_final.stac-item
2023-11-18 09:58:10	ga_ls9c_ard_3-2-1_097070_2023-11-18_final.stac-item
2023-11-18 11:41:03	ga_ls9c_ard_3-2-1_113080_2023-11-18_final.stac-item
2023-11-20 09:49:50	ga_ls9c_ard_3-2-1_095080_2023-11-20_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-11-21 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-11-21_final.stac-item
2023-11-23 10:21:11	ga_ls9c_ard_3-2-1_100081_2023-11-23_final.stac-item
2023-11-24 11:04:27	ga_ls9c_ard_3-2-1_107081_2023-11-24_final.stac-item
2023-11-25 10:06:03	ga_ls9c_ard_3-2-1_098074_2023-11-25_final.stac-item
2023-11-29 11:21:01	ga_ls9c_ard_3-2-1_110076_2023-11-29_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