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
2021-11-12 11:01:48	ga_ls9c_ard_3-2-1_106083_2021-11-12_final.stac-item
2021-12-04 09:28:05	ga_ls9c_ard_3-2-1_091087_2021-12-03_final.stac-item
2021-12-09 09:40:59	ga_ls9c_ard_3-2-1_094073_2021-12-09_final.stac-item
2021-12-12 10:15:50	ga_ls9c_ard_3-2-1_099083_2021-12-12_final.stac-item
2021-12-23 09:52:04	ga_ls9c_ard_3-2-1_096070_2021-12-23_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-03 11:14:48	ga_ls9c_ard_3-2-1_109076_2022-01-03_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-01-24 11:32:32	ga_ls9c_ard_3-2-1_112074_2022-01-24_final.stac-item
2022-01-28 09:28:08	ga_ls9c_ard_3-2-1_092072_2022-01-27_final.stac-item
2022-02-07 10:09:35	ga_ls9c_ard_3-2-1_098083_2022-02-07_final.stac-item
2022-02-07 10:09:59	ga_ls9c_ard_3-2-1_098084_2022-02-07_final.stac-item
2022-02-16 11:37:50	ga_ls9c_ard_3-2-1_113072_2022-02-16_final.stac-item
2022-02-24 10:49:30	ga_ls9c_ard_3-2-1_105075_2022-02-24_final.stac-item
2022-02-27 09:40:41	ga_ls9c_ard_3-2-1_094073_2022-02-27_final.stac-item
2022-03-12 10:49:02	ga_ls9c_ard_3-2-1_105074_2022-03-12_final.stac-item
2022-03-19 10:55:59	ga_ls9c_ard_3-2-1_106076_2022-03-19_final.stac-item
2022-03-31 09:40:10	ga_ls9c_ard_3-2-1_094072_2022-03-31_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-13 09:12:47	ga_ls9c_ard_3-2-1_089081_2022-04-12_final.stac-item
2022-04-17 10:27:42	ga_ls9c_ard_3-2-1_101083_2022-04-17_final.stac-item
2022-05-13 09:21:18	ga_ls9c_ard_3-2-1_091072_2022-05-12_final.stac-item
2022-05-18 11:23:02	ga_ls9c_ard_3-2-1_110083_2022-05-18_final.stac-item
2022-05-19 10:22:37	ga_ls9c_ard_3-2-1_101071_2022-05-19_final.stac-item
2022-05-23 09:57:29	ga_ls9c_ard_3-2-1_097070_2022-05-23_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-05-29 09:21:12	ga_ls9c_ard_3-2-1_091072_2022-05-28_final.stac-item
2022-06-05 11:07:05	ga_ls9c_ard_3-2-1_108074_2022-06-05_final.stac-item
2022-06-13 10:19:17	ga_ls9c_ard_3-2-1_100078_2022-06-13_final.stac-item
2022-06-22 10:10:07	ga_ls9c_ard_3-2-1_099070_2022-06-22_final.stac-item
2022-06-22 10:12:55	ga_ls9c_ard_3-2-1_099077_2022-06-22_final.stac-item
2022-06-26 09:52:17	ga_ls9c_ard_3-2-1_095087_2022-06-26_final.stac-item
2022-06-30 11:01:38	ga_ls9c_ard_3-2-1_107075_2022-06-30_final.stac-item
2022-07-01 10:07:37	ga_ls9c_ard_3-2-1_098079_2022-07-01_final.stac-item
2022-07-08 10:08:58	ga_ls9c_ard_3-2-1_099067_2022-07-08_final.stac-item
2022-07-08 10:10:34	ga_ls9c_ard_3-2-1_099071_2022-07-08_final.stac-item
2022-07-16 11:04:46	ga_ls9c_ard_3-2-1_107083_2022-07-16_final.stac-item
2022-07-25 10:55:57	ga_ls9c_ard_3-2-1_106076_2022-07-25_final.stac-item
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-08-17 09:26:41	ga_ls9c_ard_3-2-1_091084_2022-08-16_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-09-02 09:23:07	ga_ls9c_ard_3-2-1_091075_2022-09-01_final.stac-item
2022-09-05 11:32:06	ga_ls9c_ard_3-2-1_112073_2022-09-05_final.stac-item
2022-09-27 10:58:44	ga_ls9c_ard_3-2-1_106082_2022-09-27_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-07 11:32:37	ga_ls9c_ard_3-2-1_112074_2022-10-07_final.stac-item
2022-10-09 09:41:00	ga_ls9c_ard_3-2-1_094073_2022-10-09_final.stac-item
2022-10-17 10:33:18	ga_ls9c_ard_3-2-1_102080_2022-10-17_final.stac-item
2022-10-20 11:00:13	ga_ls9c_ard_3-2-1_107070_2022-10-20_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-13 10:11:12	ga_ls9c_ard_3-2-1_099071_2022-11-13_final.stac-item
2022-11-13 10:11:36	ga_ls9c_ard_3-2-1_099072_2022-11-13_final.stac-item
2022-11-14 09:17:58	ga_ls9c_ard_3-2-1_090077_2022-11-13_final.stac-item
2022-11-16 10:46:29	ga_ls9c_ard_3-2-1_104082_2022-11-16_final.stac-item
2022-12-11 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-12-11_final.stac-item
2022-12-15 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-12-15_final.stac-item
2022-12-21 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-12-21_final.stac-item
2022-12-26 09:58:35	ga_ls9c_ard_3-2-1_096086_2022-12-26_final.stac-item
2023-01-09 11:47:52	ga_ls9c_ard_3-2-1_114081_2023-01-09_final.stac-item
2023-01-10 09:10:33	ga_ls9c_ard_3-2-1_089074_2023-01-09_final.stac-item
2023-01-16 10:15:53	ga_ls9c_ard_3-2-1_099083_2023-01-16_final.stac-item
2023-03-10 10:28:12	ga_ls9c_ard_3-2-1_102068_2023-03-10_final.stac-item
2023-03-14 10:03:06	ga_ls9c_ard_3-2-1_098067_2023-03-14_final.stac-item
2023-03-16 11:32:25	ga_ls9c_ard_3-2-1_112074_2023-03-16_final.stac-item
2023-03-18 11:20:03	ga_ls9c_ard_3-2-1_110074_2023-03-18_final.stac-item
2023-04-06 10:13:28	ga_ls9c_ard_3-2-1_099078_2023-04-06_final.stac-item
2023-04-14 11:05:12	ga_ls9c_ard_3-2-1_107084_2023-04-14_final.stac-item
2023-04-22 10:09:46	ga_ls9c_ard_3-2-1_099069_2023-04-22_final.stac-item
2023-04-22 10:13:22	ga_ls9c_ard_3-2-1_099078_2023-04-22_final.stac-item
2023-05-01 10:02:40	ga_ls9c_ard_3-2-1_098067_2023-05-01_final.stac-item
2023-06-06 11:19:21	ga_ls9c_ard_3-2-1_110074_2023-06-06_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-07-03 11:00:52	ga_ls9c_ard_3-2-1_107074_2023-07-03_final.stac-item
2023-07-06 09:57:43	ga_ls9c_ard_3-2-1_096086_2023-07-06_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-19 10:59:22	ga_ls9c_ard_3-2-1_107070_2023-07-19_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-08-16 11:23:28	ga_ls9c_ard_3-2-1_111068_2023-08-16_final.stac-item
2023-08-20 09:25:52	ga_ls9c_ard_3-2-1_091083_2023-08-19_final.stac-item
2023-09-19 11:17:48	ga_ls9c_ard_3-2-1_109084_2023-09-19_final.stac-item
2023-09-23 09:13:22	ga_ls9c_ard_3-2-1_089082_2023-09-22_final.stac-item
2023-09-24 11:32:18	ga_ls9c_ard_3-2-1_112074_2023-09-24_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-09-29 10:13:08	ga_ls9c_ard_3-2-1_099077_2023-09-29_final.stac-item
2023-10-09 09:12:15	ga_ls9c_ard_3-2-1_089079_2023-10-08_final.stac-item
2023-10-11 10:39:37	ga_ls9c_ard_3-2-1_103081_2023-10-11_final.stac-item
2023-10-14 11:08:10	ga_ls9c_ard_3-2-1_108075_2023-10-14_final.stac-item
2023-10-23 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-10-22_final.stac-item
2023-10-24 10:09:34	ga_ls9c_ard_3-2-1_098083_2023-10-24_final.stac-item
2023-11-03 09:07:15	ga_ls9c_ard_3-2-1_088082_2023-11-02_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-11-10 10:49:59	ga_ls9c_ard_3-2-1_105076_2023-11-10_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-11-18 09:57:22	ga_ls9c_ard_3-2-1_097068_2023-11-18_final.stac-item
2023-11-27 11:32:35	ga_ls9c_ard_3-2-1_112074_2023-11-27_final.stac-item
2023-12-22 11:26:26	ga_ls9c_ard_3-2-1_111074_2023-12-22_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