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
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-08 10:37:25	ga_ls9c_ard_3-2-1_103075_2021-12-08_final.stac-item
2021-12-09 11:21:04	ga_ls9c_ard_3-2-1_110076_2021-12-09_final.stac-item
2021-12-10 10:25:02	ga_ls9c_ard_3-2-1_101075_2021-12-10_final.stac-item
2021-12-11 09:29:48	ga_ls9c_ard_3-2-1_092076_2021-12-10_final.stac-item
2021-12-17 10:31:08	ga_ls9c_ard_3-2-1_102075_2021-12-17_final.stac-item
2021-12-26 10:24:58	ga_ls9c_ard_3-2-1_101075_2021-12-26_final.stac-item
2021-12-26 10:25:22	ga_ls9c_ard_3-2-1_101076_2021-12-26_final.stac-item
2021-12-27 09:29:45	ga_ls9c_ard_3-2-1_092076_2021-12-26_final.stac-item
2022-01-01 11:27:10	ga_ls9c_ard_3-2-1_111076_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
2022-01-09 10:37:18	ga_ls9c_ard_3-2-1_103075_2022-01-09_final.stac-item
2022-01-10 11:20:57	ga_ls9c_ard_3-2-1_110076_2022-01-10_final.stac-item
2022-01-11 10:25:19	ga_ls9c_ard_3-2-1_101076_2022-01-11_final.stac-item
2022-01-17 11:27:08	ga_ls9c_ard_3-2-1_111076_2022-01-17_final.stac-item
2022-01-18 10:31:07	ga_ls9c_ard_3-2-1_102075_2022-01-18_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-01-26 11:20:59	ga_ls9c_ard_3-2-1_110076_2022-01-26_final.stac-item
2022-01-28 09:29:44	ga_ls9c_ard_3-2-1_092076_2022-01-27_final.stac-item
2022-02-03 10:31:08	ga_ls9c_ard_3-2-1_102075_2022-02-03_final.stac-item
2022-02-04 11:14:47	ga_ls9c_ard_3-2-1_109076_2022-02-04_final.stac-item
2022-02-05 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-02-05_final.stac-item
2022-02-06 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-02-05_final.stac-item
2022-02-10 10:37:17	ga_ls9c_ard_3-2-1_103075_2022-02-10_final.stac-item
2022-02-12 10:25:18	ga_ls9c_ard_3-2-1_101076_2022-02-12_final.stac-item
2022-02-18 11:27:03	ga_ls9c_ard_3-2-1_111076_2022-02-18_final.stac-item
2022-02-20 11:14:40	ga_ls9c_ard_3-2-1_109076_2022-02-20_final.stac-item
2022-02-26 10:37:07	ga_ls9c_ard_3-2-1_103075_2022-02-26_final.stac-item
2022-03-07 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-03-07_final.stac-item
2022-03-08 11:14:33	ga_ls9c_ard_3-2-1_109076_2022-03-08_final.stac-item
2022-03-10 09:23:18	ga_ls9c_ard_3-2-1_091076_2022-03-09_final.stac-item
2022-03-23 10:30:50	ga_ls9c_ard_3-2-1_102075_2022-03-23_final.stac-item
2022-03-24 11:14:29	ga_ls9c_ard_3-2-1_109076_2022-03-24_final.stac-item
2022-03-26 09:23:14	ga_ls9c_ard_3-2-1_091076_2022-03-25_final.stac-item
2022-03-30 10:36:59	ga_ls9c_ard_3-2-1_103075_2022-03-30_final.stac-item
2022-03-31 11:20:39	ga_ls9c_ard_3-2-1_110076_2022-03-31_final.stac-item
2022-04-02 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-04-01_final.stac-item
2022-04-07 11:26:48	ga_ls9c_ard_3-2-1_111076_2022-04-07_final.stac-item
2022-04-08 10:30:47	ga_ls9c_ard_3-2-1_102075_2022-04-08_final.stac-item
2022-04-17 10:24:30	ga_ls9c_ard_3-2-1_101075_2022-04-17_final.stac-item
2022-04-23 11:26:38	ga_ls9c_ard_3-2-1_111076_2022-04-23_final.stac-item
2022-04-25 11:14:17	ga_ls9c_ard_3-2-1_109076_2022-04-25_final.stac-item
2022-04-26 10:18:15	ga_ls9c_ard_3-2-1_100075_2022-04-26_final.stac-item
2022-04-27 09:23:02	ga_ls9c_ard_3-2-1_091076_2022-04-26_final.stac-item
2022-05-01 10:36:47	ga_ls9c_ard_3-2-1_103075_2022-05-01_final.stac-item
2022-05-03 10:24:48	ga_ls9c_ard_3-2-1_101076_2022-05-03_final.stac-item
2022-05-04 09:29:11	ga_ls9c_ard_3-2-1_092076_2022-05-03_final.stac-item
2022-05-09 11:26:33	ga_ls9c_ard_3-2-1_111076_2022-05-09_final.stac-item
2022-05-11 11:14:10	ga_ls9c_ard_3-2-1_109076_2022-05-11_final.stac-item
2022-05-13 09:22:54	ga_ls9c_ard_3-2-1_091076_2022-05-12_final.stac-item
2022-05-17 10:36:36	ga_ls9c_ard_3-2-1_103075_2022-05-17_final.stac-item
2022-05-18 11:20:15	ga_ls9c_ard_3-2-1_110076_2022-05-18_final.stac-item
2022-05-19 10:24:12	ga_ls9c_ard_3-2-1_101075_2022-05-19_final.stac-item
2022-05-19 10:24:36	ga_ls9c_ard_3-2-1_101076_2022-05-19_final.stac-item
2022-05-27 11:14:02	ga_ls9c_ard_3-2-1_109076_2022-05-27_final.stac-item
2022-05-29 09:22:48	ga_ls9c_ard_3-2-1_091076_2022-05-28_final.stac-item
2022-06-04 10:24:37	ga_ls9c_ard_3-2-1_101076_2022-06-04_final.stac-item
2022-06-20 10:24:25	ga_ls9c_ard_3-2-1_101075_2022-06-20_final.stac-item
2022-06-21 09:29:13	ga_ls9c_ard_3-2-1_092076_2022-06-20_final.stac-item
2022-06-28 11:14:24	ga_ls9c_ard_3-2-1_109076_2022-06-28_final.stac-item
2022-06-30 09:23:09	ga_ls9c_ard_3-2-1_091076_2022-06-29_final.stac-item
2022-07-05 11:20:34	ga_ls9c_ard_3-2-1_110076_2022-07-05_final.stac-item
2022-07-06 10:24:56	ga_ls9c_ard_3-2-1_101076_2022-07-06_final.stac-item
2022-07-07 09:29:18	ga_ls9c_ard_3-2-1_092076_2022-07-06_final.stac-item
2022-07-21 11:20:37	ga_ls9c_ard_3-2-1_110076_2022-07-21_final.stac-item
2022-07-23 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-07-22_final.stac-item
2022-08-01 09:23:20	ga_ls9c_ard_3-2-1_091076_2022-07-31_final.stac-item
2022-08-14 10:31:03	ga_ls9c_ard_3-2-1_102075_2022-08-14_final.stac-item
2022-08-15 11:14:43	ga_ls9c_ard_3-2-1_109076_2022-08-15_final.stac-item
2022-08-23 10:25:18	ga_ls9c_ard_3-2-1_101076_2022-08-23_final.stac-item
2022-08-31 11:14:46	ga_ls9c_ard_3-2-1_109076_2022-08-31_final.stac-item
2022-09-07 11:20:55	ga_ls9c_ard_3-2-1_110076_2022-09-07_final.stac-item
2022-09-14 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-09-14_final.stac-item
2022-09-15 10:31:09	ga_ls9c_ard_3-2-1_102075_2022-09-15_final.stac-item
2022-09-22 10:37:23	ga_ls9c_ard_3-2-1_103075_2022-09-22_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-03 10:19:15	ga_ls9c_ard_3-2-1_100076_2022-10-03_final.stac-item
2022-10-04 09:23:38	ga_ls9c_ard_3-2-1_091076_2022-10-03_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-10 10:25:28	ga_ls9c_ard_3-2-1_101076_2022-10-10_final.stac-item
2022-10-11 09:29:52	ga_ls9c_ard_3-2-1_092076_2022-10-10_final.stac-item
2022-10-16 11:27:19	ga_ls9c_ard_3-2-1_111076_2022-10-16_final.stac-item
2022-10-20 09:23:44	ga_ls9c_ard_3-2-1_091076_2022-10-19_final.stac-item
2022-10-26 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-10-26_final.stac-item
2022-11-01 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-11-01_final.stac-item
2022-11-11 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-11-11_final.stac-item
2022-11-12 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-11-11_final.stac-item
2022-11-21 09:23:45	ga_ls9c_ard_3-2-1_091076_2022-11-20_final.stac-item
2022-11-27 10:25:31	ga_ls9c_ard_3-2-1_101076_2022-11-27_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-14 09:29:54	ga_ls9c_ard_3-2-1_092076_2022-12-13_final.stac-item
2022-12-23 09:23:40	ga_ls9c_ard_3-2-1_091076_2022-12-22_final.stac-item
2023-01-08 09:23:44	ga_ls9c_ard_3-2-1_091076_2023-01-07_final.stac-item
2023-01-14 10:25:29	ga_ls9c_ard_3-2-1_101076_2023-01-14_final.stac-item
2023-01-23 10:19:14	ga_ls9c_ard_3-2-1_100076_2023-01-23_final.stac-item
2023-01-24 09:23:38	ga_ls9c_ard_3-2-1_091076_2023-01-23_final.stac-item
2023-01-30 10:25:31	ga_ls9c_ard_3-2-1_101076_2023-01-30_final.stac-item
2023-04-13 10:18:46	ga_ls9c_ard_3-2-1_100076_2023-04-13_final.stac-item
2023-04-20 10:24:56	ga_ls9c_ard_3-2-1_101076_2023-04-20_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_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