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
2021-10-31 11:10:48	ga_ls9c_ard_3-2-1_109071_2021-10-31_final.stac-item
2021-11-05 11:13:17	ga_ls9c_ard_3-2-1_109071_2021-11-05_final.stac-item
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-11-20 11:20:41	ga_ls9c_ard_3-2-1_110071_2021-11-20_final.stac-item
2021-11-24 10:42:47	ga_ls9c_ard_3-2-1_104070_2021-11-24_final.stac-item
2021-12-18 11:12:48	ga_ls9c_ard_3-2-1_109071_2021-12-18_final.stac-item
2021-12-30 09:58:15	ga_ls9c_ard_3-2-1_097070_2021-12-30_final.stac-item
2022-01-03 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-01-03_final.stac-item
2022-01-12 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-01-12_final.stac-item
2022-01-28 11:06:37	ga_ls9c_ard_3-2-1_108071_2022-01-28_final.stac-item
2022-02-04 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-02-04_final.stac-item
2022-02-27 11:18:46	ga_ls9c_ard_3-2-1_110071_2022-02-27_final.stac-item
2022-03-08 11:12:33	ga_ls9c_ard_3-2-1_109071_2022-03-08_final.stac-item
2022-04-02 11:06:18	ga_ls9c_ard_3-2-1_108071_2022-04-02_final.stac-item
2022-04-09 11:12:26	ga_ls9c_ard_3-2-1_109071_2022-04-09_final.stac-item
2022-05-02 11:18:26	ga_ls9c_ard_3-2-1_110071_2022-05-02_final.stac-item
2022-05-20 11:05:51	ga_ls9c_ard_3-2-1_108071_2022-05-20_final.stac-item
2022-06-05 11:05:53	ga_ls9c_ard_3-2-1_108071_2022-06-05_final.stac-item
2022-06-08 09:57:30	ga_ls9c_ard_3-2-1_097070_2022-06-08_final.stac-item
2022-06-10 11:24:02	ga_ls9c_ard_3-2-1_111070_2022-06-10_final.stac-item
2022-06-18 10:34:42	ga_ls9c_ard_3-2-1_103070_2022-06-18_final.stac-item
2022-06-19 11:18:24	ga_ls9c_ard_3-2-1_110071_2022-06-19_final.stac-item
2022-06-26 11:24:22	ga_ls9c_ard_3-2-1_111070_2022-06-26_final.stac-item
2022-07-05 11:18:34	ga_ls9c_ard_3-2-1_110071_2022-07-05_final.stac-item
2022-07-07 11:05:48	ga_ls9c_ard_3-2-1_108070_2022-07-07_final.stac-item
2022-07-07 11:06:12	ga_ls9c_ard_3-2-1_108071_2022-07-07_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-07-14 11:12:19	ga_ls9c_ard_3-2-1_109071_2022-07-14_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-07-19 09:51:40	ga_ls9c_ard_3-2-1_096070_2022-07-19_final.stac-item
2022-07-20 10:34:56	ga_ls9c_ard_3-2-1_103070_2022-07-20_final.stac-item
2022-07-23 11:05:53	ga_ls9c_ard_3-2-1_108070_2022-07-23_final.stac-item
2022-07-23 11:06:17	ga_ls9c_ard_3-2-1_108071_2022-07-23_final.stac-item
2022-07-26 09:57:57	ga_ls9c_ard_3-2-1_097070_2022-07-26_final.stac-item
2022-08-05 10:35:09	ga_ls9c_ard_3-2-1_103070_2022-08-05_final.stac-item
2022-08-11 09:58:08	ga_ls9c_ard_3-2-1_097070_2022-08-11_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-15 11:12:43	ga_ls9c_ard_3-2-1_109071_2022-08-15_final.stac-item
2022-08-21 10:35:16	ga_ls9c_ard_3-2-1_103070_2022-08-21_final.stac-item
2022-08-24 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-08-24_final.stac-item
2022-08-28 10:41:28	ga_ls9c_ard_3-2-1_104070_2022-08-28_final.stac-item
2022-08-29 11:24:44	ga_ls9c_ard_3-2-1_111070_2022-08-29_final.stac-item
2022-08-31 11:12:46	ga_ls9c_ard_3-2-1_109071_2022-08-31_final.stac-item
2022-09-04 10:47:38	ga_ls9c_ard_3-2-1_105070_2022-09-04_final.stac-item
2022-09-07 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-09-07_final.stac-item
2022-09-09 11:06:34	ga_ls9c_ard_3-2-1_108071_2022-09-09_final.stac-item
2022-09-16 11:12:50	ga_ls9c_ard_3-2-1_109071_2022-09-16_final.stac-item
2022-09-22 10:35:23	ga_ls9c_ard_3-2-1_103070_2022-09-22_final.stac-item
2022-09-25 11:06:42	ga_ls9c_ard_3-2-1_108071_2022-09-25_final.stac-item
2022-10-09 11:19:05	ga_ls9c_ard_3-2-1_110071_2022-10-09_final.stac-item
2022-10-14 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-14_final.stac-item
2022-10-16 11:24:56	ga_ls9c_ard_3-2-1_111070_2022-10-16_final.stac-item
2022-10-26 10:23:08	ga_ls9c_ard_3-2-1_101070_2022-10-26_final.stac-item
2022-10-27 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-10-27_final.stac-item
2022-11-24 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-24_final.stac-item
2022-11-25 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-11-25_final.stac-item
2022-11-26 11:19:09	ga_ls9c_ard_3-2-1_110071_2022-11-26_final.stac-item
2022-11-27 10:23:08	ga_ls9c_ard_3-2-1_101070_2022-11-27_final.stac-item
2022-12-02 10:41:38	ga_ls9c_ard_3-2-1_104070_2022-12-02_final.stac-item
2022-12-05 11:12:57	ga_ls9c_ard_3-2-1_109071_2022-12-05_final.stac-item
2022-12-21 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-12-21_final.stac-item
2022-12-28 11:19:08	ga_ls9c_ard_3-2-1_110071_2022-12-28_final.stac-item
2023-01-06 11:12:59	ga_ls9c_ard_3-2-1_109071_2023-01-06_final.stac-item
2023-01-15 11:06:44	ga_ls9c_ard_3-2-1_108071_2023-01-15_final.stac-item
2023-01-22 11:12:50	ga_ls9c_ard_3-2-1_109071_2023-01-22_final.stac-item
2023-02-07 11:13:02	ga_ls9c_ard_3-2-1_109071_2023-02-07_final.stac-item
2023-03-04 11:06:35	ga_ls9c_ard_3-2-1_108071_2023-03-04_final.stac-item
2023-05-30 11:12:00	ga_ls9c_ard_3-2-1_109071_2023-05-30_final.stac-item
2023-06-21 10:34:22	ga_ls9c_ard_3-2-1_103070_2023-06-21_final.stac-item
2023-07-07 10:34:36	ga_ls9c_ard_3-2-1_103070_2023-07-07_final.stac-item
2023-07-10 11:05:55	ga_ls9c_ard_3-2-1_108071_2023-07-10_final.stac-item
2023-07-15 11:24:06	ga_ls9c_ard_3-2-1_111070_2023-07-15_final.stac-item
2023-07-26 11:05:57	ga_ls9c_ard_3-2-1_108071_2023-07-26_final.stac-item
2023-07-29 09:57:37	ga_ls9c_ard_3-2-1_097070_2023-07-29_final.stac-item
2023-07-31 11:24:10	ga_ls9c_ard_3-2-1_111070_2023-07-31_final.stac-item
2023-08-08 10:34:49	ga_ls9c_ard_3-2-1_103070_2023-08-08_final.stac-item
2023-08-11 11:06:07	ga_ls9c_ard_3-2-1_108071_2023-08-11_final.stac-item
2023-08-14 09:57:44	ga_ls9c_ard_3-2-1_097070_2023-08-14_final.stac-item
2023-08-15 10:41:00	ga_ls9c_ard_3-2-1_104070_2023-08-15_final.stac-item
2023-08-27 11:06:15	ga_ls9c_ard_3-2-1_108071_2023-08-27_final.stac-item
2023-08-30 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-08-30_final.stac-item
2023-09-01 11:24:26	ga_ls9c_ard_3-2-1_111070_2023-09-01_final.stac-item
2023-09-09 10:35:05	ga_ls9c_ard_3-2-1_103070_2023-09-09_final.stac-item
2023-09-12 11:06:25	ga_ls9c_ard_3-2-1_108071_2023-09-12_final.stac-item
2023-09-17 11:24:34	ga_ls9c_ard_3-2-1_111070_2023-09-17_final.stac-item
2023-09-28 11:06:20	ga_ls9c_ard_3-2-1_108071_2023-09-28_final.stac-item
2023-10-01 09:58:01	ga_ls9c_ard_3-2-1_097070_2023-10-01_final.stac-item
2023-10-14 11:06:34	ga_ls9c_ard_3-2-1_108071_2023-10-14_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-11-15 11:06:31	ga_ls9c_ard_3-2-1_108071_2023-11-15_final.stac-item
2023-11-18 09:58:10	ga_ls9c_ard_3-2-1_097070_2023-11-18_final.stac-item
2023-12-01 11:06:39	ga_ls9c_ard_3-2-1_108071_2023-12-01_final.stac-item
2023-12-17 11:06:40	ga_ls9c_ard_3-2-1_108071_2023-12-17_final.stac-item
2023-12-20 09:58:18	ga_ls9c_ard_3-2-1_097070_2023-12-20_final.stac-item
2023-12-22 11:24:50	ga_ls9c_ard_3-2-1_111070_2023-12-22_final.stac-item
2024-01-02 11:06:37	ga_ls9c_ard_3-2-1_108071_2024-01-02_final.stac-item
2024-01-05 09:58:12	ga_ls9c_ard_3-2-1_097070_2024-01-05_final.stac-item
2024-01-14 09:52:04	ga_ls9c_ard_3-2-1_096070_2024-01-14_final.stac-item
2024-01-18 11:06:37	ga_ls9c_ard_3-2-1_108071_2024-01-18_final.stac-item
2024-02-03 11:06:39	ga_ls9c_ard_3-2-1_108071_2024-02-03_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