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
2021-11-23 11:45:04	ga_ls9c_ard_3-2-1_114079_2021-11-23_final.stac-item
2021-12-05 11:45:26	ga_ls9c_ard_3-2-1_114075_2021-12-05_final.stac-item
2021-12-12 11:52:44	ga_ls9c_ard_3-2-1_115078_2021-12-12_final.stac-item
2021-12-15 10:43:31	ga_ls9c_ard_3-2-1_104075_2021-12-15_final.stac-item
2022-01-06 11:45:18	ga_ls9c_ard_3-2-1_114075_2022-01-06_final.stac-item
2022-01-12 11:07:47	ga_ls9c_ard_3-2-1_108074_2022-01-12_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-01-27 10:25:21	ga_ls9c_ard_3-2-1_101076_2022-01-27_final.stac-item
2022-02-01 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-01-31_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-03-31 09:45:45	ga_ls9c_ard_3-2-1_094086_2022-03-31_final.stac-item
2022-04-04 10:55:07	ga_ls9c_ard_3-2-1_106074_2022-04-04_final.stac-item
2022-04-05 10:01:30	ga_ls9c_ard_3-2-1_097079_2022-04-05_final.stac-item
2022-04-12 11:45:18	ga_ls9c_ard_3-2-1_114076_2022-04-12_final.stac-item
2022-04-16 11:18:33	ga_ls9c_ard_3-2-1_110071_2022-04-16_final.stac-item
2022-05-02 11:19:14	ga_ls9c_ard_3-2-1_110073_2022-05-02_final.stac-item
2022-05-07 09:58:51	ga_ls9c_ard_3-2-1_097073_2022-05-07_final.stac-item
2022-05-14 10:03:21	ga_ls9c_ard_3-2-1_098069_2022-05-14_final.stac-item
2022-05-14 11:45:02	ga_ls9c_ard_3-2-1_114076_2022-05-14_final.stac-item
2022-05-18 09:43:45	ga_ls9c_ard_3-2-1_094082_2022-05-18_final.stac-item
2022-06-06 10:11:04	ga_ls9c_ard_3-2-1_099073_2022-06-06_final.stac-item
2022-06-06 11:51:56	ga_ls9c_ard_3-2-1_115078_2022-06-06_final.stac-item
2022-06-20 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-06-20_final.stac-item
2022-06-28 11:14:48	ga_ls9c_ard_3-2-1_109077_2022-06-28_final.stac-item
2022-07-27 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-07-27_final.stac-item
2022-08-01 09:26:56	ga_ls9c_ard_3-2-1_091085_2022-07-31_final.stac-item
2022-08-01 09:27:44	ga_ls9c_ard_3-2-1_091087_2022-07-31_final.stac-item
2022-08-19 10:48:01	ga_ls9c_ard_3-2-1_105071_2022-08-19_final.stac-item
2022-08-25 10:11:45	ga_ls9c_ard_3-2-1_099073_2022-08-25_final.stac-item
2022-08-26 09:18:32	ga_ls9c_ard_3-2-1_090079_2022-08-25_final.stac-item
2022-09-02 09:28:42	ga_ls9c_ard_3-2-1_091089_2022-09-01_final.stac-item
2022-09-19 10:05:16	ga_ls9c_ard_3-2-1_098072_2022-09-19_final.stac-item
2022-09-19 11:45:45	ga_ls9c_ard_3-2-1_114076_2022-09-19_final.stac-item
2022-10-05 11:45:46	ga_ls9c_ard_3-2-1_114076_2022-10-05_final.stac-item
2022-10-06 10:48:57	ga_ls9c_ard_3-2-1_105073_2022-10-06_final.stac-item
2022-10-09 11:23:52	ga_ls9c_ard_3-2-1_110083_2022-10-09_final.stac-item
2022-10-13 10:54:48	ga_ls9c_ard_3-2-1_106072_2022-10-13_final.stac-item
2022-10-19 10:17:45	ga_ls9c_ard_3-2-1_100072_2022-10-19_final.stac-item
2022-10-21 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-10-21_final.stac-item
2022-10-31 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-10-31_final.stac-item
2022-11-10 11:20:46	ga_ls9c_ard_3-2-1_110075_2022-11-10_final.stac-item
2023-02-16 11:08:23	ga_ls9c_ard_3-2-1_108075_2023-02-16_final.stac-item
2023-02-23 09:40:19	ga_ls9c_ard_3-2-1_093087_2023-02-23_final.stac-item
2023-03-10 10:29:48	ga_ls9c_ard_3-2-1_102072_2023-03-10_final.stac-item
2023-03-15 09:16:16	ga_ls9c_ard_3-2-1_089089_2023-03-14_final.stac-item
2023-03-18 09:41:34	ga_ls9c_ard_3-2-1_094075_2023-03-18_final.stac-item
2023-03-18 11:18:51	ga_ls9c_ard_3-2-1_110071_2023-03-18_final.stac-item
2023-03-21 10:15:38	ga_ls9c_ard_3-2-1_099083_2023-03-21_final.stac-item
2023-03-21 10:16:02	ga_ls9c_ard_3-2-1_099084_2023-03-21_final.stac-item
2023-03-21 11:52:07	ga_ls9c_ard_3-2-1_115077_2023-03-21_final.stac-item
2023-04-02 10:34:12	ga_ls9c_ard_3-2-1_103068_2023-04-02_final.stac-item
2023-04-08 09:59:30	ga_ls9c_ard_3-2-1_097074_2023-04-08_final.stac-item
2023-04-09 10:41:09	ga_ls9c_ard_3-2-1_104070_2023-04-09_final.stac-item
2023-04-09 10:42:45	ga_ls9c_ard_3-2-1_104074_2023-04-09_final.stac-item
2023-04-10 09:50:42	ga_ls9c_ard_3-2-1_095083_2023-04-10_final.stac-item
2023-04-14 09:25:55	ga_ls9c_ard_3-2-1_091083_2023-04-13_final.stac-item
2023-04-16 10:48:27	ga_ls9c_ard_3-2-1_105073_2023-04-16_final.stac-item
2023-05-02 10:48:18	ga_ls9c_ard_3-2-1_105073_2023-05-02_final.stac-item
2023-05-03 09:57:03	ga_ls9c_ard_3-2-1_096084_2023-05-03_final.stac-item
2023-05-07 09:29:07	ga_ls9c_ard_3-2-1_092076_2023-05-06_final.stac-item
2023-05-09 09:18:45	ga_ls9c_ard_3-2-1_090081_2023-05-08_final.stac-item
2023-05-09 10:53:38	ga_ls9c_ard_3-2-1_106071_2023-05-09_final.stac-item
2023-05-10 09:58:25	ga_ls9c_ard_3-2-1_097072_2023-05-10_final.stac-item
2023-05-10 11:40:29	ga_ls9c_ard_3-2-1_113080_2023-05-10_final.stac-item
2023-05-13 10:28:06	ga_ls9c_ard_3-2-1_102069_2023-05-13_final.stac-item
2023-05-17 11:45:01	ga_ls9c_ard_3-2-1_114076_2023-05-17_final.stac-item
2023-05-18 09:13:18	ga_ls9c_ard_3-2-1_089083_2023-05-17_final.stac-item
2023-05-19 09:51:45	ga_ls9c_ard_3-2-1_096071_2023-05-19_final.stac-item
2023-06-21 10:38:46	ga_ls9c_ard_3-2-1_103081_2023-06-21_final.stac-item
2023-06-23 10:27:12	ga_ls9c_ard_3-2-1_101083_2023-06-23_final.stac-item
2023-06-27 11:37:48	ga_ls9c_ard_3-2-1_113074_2023-06-27_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 09:49:49	ga_ls9c_ard_3-2-1_095082_2023-06-29_final.stac-item
2023-07-01 09:37:06	ga_ls9c_ard_3-2-1_093081_2023-07-01_final.stac-item
2023-07-04 11:45:20	ga_ls9c_ard_3-2-1_114077_2023-07-04_final.stac-item
2023-07-09 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-09_final.stac-item
2023-07-11 10:12:42	ga_ls9c_ard_3-2-1_099077_2023-07-11_final.stac-item
2023-07-12 09:17:05	ga_ls9c_ard_3-2-1_090077_2023-07-11_final.stac-item
2023-07-12 09:17:53	ga_ls9c_ard_3-2-1_090079_2023-07-11_final.stac-item
2023-09-04 10:21:40	ga_ls9c_ard_3-2-1_100083_2023-09-04_final.stac-item
2023-09-07 10:46:37	ga_ls9c_ard_3-2-1_105068_2023-09-07_final.stac-item
2023-09-08 09:53:00	ga_ls9c_ard_3-2-1_096073_2023-09-08_final.stac-item
2023-09-08 09:58:12	ga_ls9c_ard_3-2-1_096086_2023-09-08_final.stac-item
2023-09-08 11:35:29	ga_ls9c_ard_3-2-1_112082_2023-09-08_final.stac-item
2023-09-10 11:18:21	ga_ls9c_ard_3-2-1_110070_2023-09-10_final.stac-item
2023-09-12 09:31:55	ga_ls9c_ard_3-2-1_092082_2023-09-12_final.stac-item
2023-09-13 10:12:47	ga_ls9c_ard_3-2-1_099076_2023-09-13_final.stac-item
2023-09-13 11:51:41	ga_ls9c_ard_3-2-1_115076_2023-09-13_final.stac-item
2023-09-19 11:12:12	ga_ls9c_ard_3-2-1_109070_2023-09-19_final.stac-item
2023-09-22 10:07:48	ga_ls9c_ard_3-2-1_098079_2023-09-22_final.stac-item
2023-09-23 10:51:03	ga_ls9c_ard_3-2-1_105079_2023-09-23_final.stac-item
2023-09-29 10:09:32	ga_ls9c_ard_3-2-1_099068_2023-09-29_final.stac-item
2023-09-30 10:57:37	ga_ls9c_ard_3-2-1_106080_2023-09-30_final.stac-item
2023-10-01 09:58:01	ga_ls9c_ard_3-2-1_097070_2023-10-01_final.stac-item
2023-10-02 10:42:06	ga_ls9c_ard_3-2-1_104072_2023-10-02_final.stac-item
2023-10-07 09:26:12	ga_ls9c_ard_3-2-1_091083_2023-10-06_final.stac-item
2023-10-07 09:27:00	ga_ls9c_ard_3-2-1_091085_2023-10-06_final.stac-item
2023-10-07 09:27:24	ga_ls9c_ard_3-2-1_091086_2023-10-06_final.stac-item
2023-10-08 10:05:52	ga_ls9c_ard_3-2-1_098074_2023-10-08_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years