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

80 results

Time (local)	Label
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-12-05 11:45:02	ga_ls9c_ard_3-2-1_114074_2021-12-05_final.stac-item
2022-01-04 10:20:46	ga_ls9c_ard_3-2-1_100080_2022-01-04_final.stac-item
2022-01-28 11:10:37	ga_ls9c_ard_3-2-1_108081_2022-01-28_final.stac-item
2022-02-06 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-02-05_final.stac-item
2022-04-05 11:41:58	ga_ls9c_ard_3-2-1_113083_2022-04-05_final.stac-item
2022-04-14 11:36:07	ga_ls9c_ard_3-2-1_112084_2022-04-14_final.stac-item
2022-05-01 10:34:47	ga_ls9c_ard_3-2-1_103070_2022-05-01_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-21 10:08:38	ga_ls9c_ard_3-2-1_099067_2022-05-21_final.stac-item
2022-05-27 11:12:02	ga_ls9c_ard_3-2-1_109071_2022-05-27_final.stac-item
2022-05-28 10:20:48	ga_ls9c_ard_3-2-1_100082_2022-05-28_final.stac-item
2022-06-23 09:20:07	ga_ls9c_ard_3-2-1_090084_2022-06-22_final.stac-item
2022-07-05 09:45:16	ga_ls9c_ard_3-2-1_094085_2022-07-05_final.stac-item
2022-07-22 10:22:37	ga_ls9c_ard_3-2-1_101070_2022-07-22_final.stac-item
2022-07-29 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-07-29_final.stac-item
2022-08-10 09:20:27	ga_ls9c_ard_3-2-1_090084_2022-08-09_final.stac-item
2022-08-24 11:11:22	ga_ls9c_ard_3-2-1_108083_2022-08-24_final.stac-item
2022-08-26 10:54:13	ga_ls9c_ard_3-2-1_106071_2022-08-26_final.stac-item
2022-08-31 11:16:45	ga_ls9c_ard_3-2-1_109081_2022-08-31_final.stac-item
2022-09-06 10:36:52	ga_ls9c_ard_3-2-1_103074_2022-09-06_final.stac-item
2022-09-20 10:47:44	ga_ls9c_ard_3-2-1_105070_2022-09-20_final.stac-item
2022-09-23 11:19:03	ga_ls9c_ard_3-2-1_110071_2022-09-23_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-26 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-10-26_final.stac-item
2022-10-30 09:59:36	ga_ls9c_ard_3-2-1_097073_2022-10-30_final.stac-item
2022-11-10 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-10_final.stac-item
2022-11-13 10:12:23	ga_ls9c_ard_3-2-1_099074_2022-11-13_final.stac-item
2022-11-19 11:12:12	ga_ls9c_ard_3-2-1_109069_2022-11-19_final.stac-item
2022-11-20 10:21:22	ga_ls9c_ard_3-2-1_100081_2022-11-20_final.stac-item
2022-11-21 09:24:33	ga_ls9c_ard_3-2-1_091078_2022-11-20_final.stac-item
2022-11-23 10:49:04	ga_ls9c_ard_3-2-1_105073_2022-11-23_final.stac-item
2022-12-19 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-12-19_final.stac-item
2022-12-19 11:30:06	ga_ls9c_ard_3-2-1_111083_2022-12-19_final.stac-item
2023-02-21 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-02-21_final.stac-item
2023-04-01 09:52:08	ga_ls9c_ard_3-2-1_096071_2023-04-01_final.stac-item
2023-04-05 09:29:25	ga_ls9c_ard_3-2-1_092076_2023-04-04_final.stac-item
2023-04-06 10:15:51	ga_ls9c_ard_3-2-1_099084_2023-04-06_final.stac-item
2023-04-18 10:38:29	ga_ls9c_ard_3-2-1_103079_2023-04-18_final.stac-item
2023-05-02 09:12:13	ga_ls9c_ard_3-2-1_089080_2023-05-01_final.stac-item
2023-05-09 10:57:14	ga_ls9c_ard_3-2-1_106080_2023-05-09_final.stac-item
2023-05-12 09:50:02	ga_ls9c_ard_3-2-1_095082_2023-05-12_final.stac-item
2023-05-17 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-05-17_final.stac-item
2023-06-10 09:16:30	ga_ls9c_ard_3-2-1_090076_2023-06-09_final.stac-item
2023-06-17 09:21:00	ga_ls9c_ard_3-2-1_091072_2023-06-16_final.stac-item
2023-06-19 09:12:14	ga_ls9c_ard_3-2-1_089081_2023-06-18_final.stac-item
2023-06-23 10:23:36	ga_ls9c_ard_3-2-1_101074_2023-06-23_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-08-19 11:58:22	ga_ls9c_ard_3-2-1_116078_2023-08-19_final.stac-item
2023-09-01 11:24:50	ga_ls9c_ard_3-2-1_111071_2023-09-01_final.stac-item
2023-09-06 10:08:08	ga_ls9c_ard_3-2-1_098080_2023-09-06_final.stac-item
2023-09-21 11:03:50	ga_ls9c_ard_3-2-1_107080_2023-09-21_final.stac-item
2023-09-28 09:31:03	ga_ls9c_ard_3-2-1_092080_2023-09-28_final.stac-item
2023-09-30 09:17:56	ga_ls9c_ard_3-2-1_090078_2023-09-29_final.stac-item
2023-10-08 10:08:16	ga_ls9c_ard_3-2-1_098080_2023-10-08_final.stac-item
2023-10-14 11:05:46	ga_ls9c_ard_3-2-1_108069_2023-10-14_final.stac-item
2023-10-19 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-10-19_final.stac-item
2023-10-24 11:46:52	ga_ls9c_ard_3-2-1_114079_2023-10-24_final.stac-item
2023-10-28 11:21:42	ga_ls9c_ard_3-2-1_110078_2023-10-28_final.stac-item
2023-11-08 11:03:56	ga_ls9c_ard_3-2-1_107080_2023-11-08_final.stac-item
2023-11-11 09:52:46	ga_ls9c_ard_3-2-1_096072_2023-11-11_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-12-01 11:11:26	ga_ls9c_ard_3-2-1_108083_2023-12-01_final.stac-item
2023-12-03 09:19:47	ga_ls9c_ard_3-2-1_090082_2023-12-02_final.stac-item
2023-12-10 09:25:07	ga_ls9c_ard_3-2-1_091080_2023-12-09_final.stac-item
2023-12-18 11:51:56	ga_ls9c_ard_3-2-1_115076_2023-12-18_final.stac-item
2024-01-21 10:01:48	ga_ls9c_ard_3-2-1_097079_2024-01-21_final.stac-item
2024-02-01 09:45:42	ga_ls9c_ard_3-2-1_094085_2024-02-01_final.stac-item
2024-02-13 10:08:25	ga_ls9c_ard_3-2-1_098080_2024-02-13_final.stac-item
2024-02-16 10:38:28	ga_ls9c_ard_3-2-1_103078_2024-02-16_final.stac-item
2024-02-17 11:20:55	ga_ls9c_ard_3-2-1_110076_2024-02-17_final.stac-item
2024-02-26 11:13:02	ga_ls9c_ard_3-2-1_109072_2024-02-26_final.stac-item
2024-04-05 09:46:13	ga_ls9c_ard_3-2-1_094087_2024-04-05_final.stac-item
2024-04-25 09:17:31	ga_ls9c_ard_3-2-1_090078_2024-04-24_final.stac-item
2024-05-05 09:51:23	ga_ls9c_ard_3-2-1_096070_2024-05-05_final.stac-item
2024-05-07 09:44:37	ga_ls9c_ard_3-2-1_094084_2024-05-07_final.stac-item
2024-05-14 09:47:08	ga_ls9c_ard_3-2-1_095075_2024-05-14_final.stac-item
2024-05-14 11:27:13	ga_ls9c_ard_3-2-1_111078_2024-05-14_final.stac-item
2024-05-15 10:28:47	ga_ls9c_ard_3-2-1_102071_2024-05-15_final.stac-item
2024-05-25 09:32:52	ga_ls9c_ard_3-2-1_092086_2024-05-25_nrt.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