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
2021-11-04 10:35:43	ga_ls9c_ard_3-2-1_103077_2021-11-04_final.stac-item
2021-11-07 09:18:16	ga_ls9c_ard_3-2-1_090077_2021-11-06_final.stac-item
2021-11-08 11:36:54	ga_ls9c_ard_3-2-1_113077_2021-11-08_final.stac-item
2021-11-09 10:38:12	ga_ls9c_ard_3-2-1_103077_2021-11-09_final.stac-item
2021-11-12 09:20:45	ga_ls9c_ard_3-2-1_091077_2021-11-11_final.stac-item
2021-11-14 10:40:40	ga_ls9c_ard_3-2-1_103077_2021-11-14_final.stac-item
2021-11-24 10:45:34	ga_ls9c_ard_3-2-1_104077_2021-11-24_final.stac-item
2021-12-11 11:09:05	ga_ls9c_ard_3-2-1_108077_2021-12-11_final.stac-item
2021-12-18 09:36:19	ga_ls9c_ard_3-2-1_093077_2021-12-18_final.stac-item
2021-12-24 10:38:08	ga_ls9c_ard_3-2-1_103077_2021-12-24_final.stac-item
2022-02-15 09:17:42	ga_ls9c_ard_3-2-1_090077_2022-02-14_final.stac-item
2022-03-01 11:08:46	ga_ls9c_ard_3-2-1_108077_2022-03-01_final.stac-item
2022-03-31 09:42:10	ga_ls9c_ard_3-2-1_094077_2022-03-31_final.stac-item
2022-05-29 11:02:05	ga_ls9c_ard_3-2-1_107077_2022-05-29_final.stac-item
2022-05-31 09:10:50	ga_ls9c_ard_3-2-1_089077_2022-05-30_final.stac-item
2022-06-05 11:08:17	ga_ls9c_ard_3-2-1_108077_2022-06-05_final.stac-item
2022-06-07 09:17:02	ga_ls9c_ard_3-2-1_090077_2022-06-06_final.stac-item
2022-06-17 11:33:06	ga_ls9c_ard_3-2-1_112077_2022-06-17_final.stac-item
2022-06-19 11:20:48	ga_ls9c_ard_3-2-1_110077_2022-06-19_final.stac-item
2022-06-23 09:17:20	ga_ls9c_ard_3-2-1_090077_2022-06-22_final.stac-item
2022-06-28 09:35:55	ga_ls9c_ard_3-2-1_093077_2022-06-28_final.stac-item
2022-06-30 11:02:26	ga_ls9c_ard_3-2-1_107077_2022-06-30_final.stac-item
2022-07-02 09:11:11	ga_ls9c_ard_3-2-1_089077_2022-07-01_final.stac-item
2022-07-03 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-03_final.stac-item
2022-07-04 10:37:42	ga_ls9c_ard_3-2-1_103077_2022-07-04_final.stac-item
2022-07-09 10:56:13	ga_ls9c_ard_3-2-1_106077_2022-07-09_final.stac-item
2022-07-12 11:27:06	ga_ls9c_ard_3-2-1_111077_2022-07-12_final.stac-item
2022-07-16 11:02:23	ga_ls9c_ard_3-2-1_107077_2022-07-16_final.stac-item
2022-07-25 09:17:28	ga_ls9c_ard_3-2-1_090077_2022-07-24_final.stac-item
2022-07-25 10:56:21	ga_ls9c_ard_3-2-1_106077_2022-07-25_final.stac-item
2022-07-28 11:27:18	ga_ls9c_ard_3-2-1_111077_2022-07-28_final.stac-item
2022-07-29 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-07-29_final.stac-item
2022-08-04 11:33:34	ga_ls9c_ard_3-2-1_112077_2022-08-04_final.stac-item
2022-08-05 10:37:57	ga_ls9c_ard_3-2-1_103077_2022-08-05_final.stac-item
2022-08-06 11:21:13	ga_ls9c_ard_3-2-1_110077_2022-08-06_final.stac-item
2022-08-10 09:17:39	ga_ls9c_ard_3-2-1_090077_2022-08-09_final.stac-item
2022-08-17 11:02:46	ga_ls9c_ard_3-2-1_107077_2022-08-17_final.stac-item
2022-08-20 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-08-20_final.stac-item
2022-08-21 10:38:04	ga_ls9c_ard_3-2-1_103077_2022-08-21_final.stac-item
2022-08-22 11:21:20	ga_ls9c_ard_3-2-1_110077_2022-08-22_final.stac-item
2022-08-26 09:17:44	ga_ls9c_ard_3-2-1_090077_2022-08-25_final.stac-item
2022-08-30 10:31:54	ga_ls9c_ard_3-2-1_102077_2022-08-30_final.stac-item
2022-09-04 09:11:33	ga_ls9c_ard_3-2-1_089077_2022-09-03_final.stac-item
2022-09-05 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-09-05_final.stac-item
2022-09-11 09:17:45	ga_ls9c_ard_3-2-1_090077_2022-09-10_final.stac-item
2022-09-13 10:44:17	ga_ls9c_ard_3-2-1_104077_2022-09-13_final.stac-item
2022-09-16 09:36:20	ga_ls9c_ard_3-2-1_093077_2022-09-16_final.stac-item
2022-09-21 11:33:48	ga_ls9c_ard_3-2-1_112077_2022-09-21_final.stac-item
2022-09-27 10:56:44	ga_ls9c_ard_3-2-1_106077_2022-09-27_final.stac-item
2022-09-30 11:27:39	ga_ls9c_ard_3-2-1_111077_2022-09-30_final.stac-item
2022-10-02 09:36:24	ga_ls9c_ard_3-2-1_093077_2022-10-02_final.stac-item
2022-10-07 11:33:49	ga_ls9c_ard_3-2-1_112077_2022-10-07_final.stac-item
2022-10-08 10:38:12	ga_ls9c_ard_3-2-1_103077_2022-10-08_final.stac-item
2022-10-09 11:21:29	ga_ls9c_ard_3-2-1_110077_2022-10-09_final.stac-item
2022-10-11 11:09:09	ga_ls9c_ard_3-2-1_108077_2022-10-11_final.stac-item
2022-10-13 09:17:55	ga_ls9c_ard_3-2-1_090077_2022-10-12_final.stac-item
2022-10-16 11:27:43	ga_ls9c_ard_3-2-1_111077_2022-10-16_final.stac-item
2022-10-18 09:36:29	ga_ls9c_ard_3-2-1_093077_2022-10-18_final.stac-item
2022-10-20 11:03:01	ga_ls9c_ard_3-2-1_107077_2022-10-20_final.stac-item
2022-10-22 09:11:46	ga_ls9c_ard_3-2-1_089077_2022-10-21_final.stac-item
2022-10-29 09:17:56	ga_ls9c_ard_3-2-1_090077_2022-10-28_final.stac-item
2022-11-05 11:02:58	ga_ls9c_ard_3-2-1_107077_2022-11-05_final.stac-item
2022-11-08 11:33:54	ga_ls9c_ard_3-2-1_112077_2022-11-08_final.stac-item
2022-11-12 11:09:12	ga_ls9c_ard_3-2-1_108077_2022-11-12_final.stac-item
2022-11-14 09:17:58	ga_ls9c_ard_3-2-1_090077_2022-11-13_final.stac-item
2022-11-19 09:36:31	ga_ls9c_ard_3-2-1_093077_2022-11-19_final.stac-item
2022-11-21 11:03:02	ga_ls9c_ard_3-2-1_107077_2022-11-21_final.stac-item
2022-11-24 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-11-24_final.stac-item
2022-11-26 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-26_final.stac-item
2022-11-30 09:17:55	ga_ls9c_ard_3-2-1_090077_2022-11-29_final.stac-item
2022-12-05 09:36:28	ga_ls9c_ard_3-2-1_093077_2022-12-05_final.stac-item
2022-12-16 09:17:56	ga_ls9c_ard_3-2-1_090077_2022-12-15_final.stac-item
2022-12-21 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-12-21_final.stac-item
2022-12-26 11:33:52	ga_ls9c_ard_3-2-1_112077_2022-12-26_final.stac-item
2022-12-30 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-30_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-01-11 11:33:54	ga_ls9c_ard_3-2-1_112077_2023-01-11_final.stac-item
2023-01-20 11:27:34	ga_ls9c_ard_3-2-1_111077_2023-01-20_final.stac-item
2023-02-02 09:17:58	ga_ls9c_ard_3-2-1_090077_2023-02-01_final.stac-item
2023-06-26 09:16:49	ga_ls9c_ard_3-2-1_090077_2023-06-25_final.stac-item
2023-06-29 11:26:42	ga_ls9c_ard_3-2-1_111077_2023-06-29_final.stac-item
2023-07-01 09:35:30	ga_ls9c_ard_3-2-1_093077_2023-07-01_final.stac-item
2023-07-06 11:33:00	ga_ls9c_ard_3-2-1_112077_2023-07-06_final.stac-item
2023-07-08 11:20:40	ga_ls9c_ard_3-2-1_110077_2023-07-08_final.stac-item
2023-07-12 09:17:05	ga_ls9c_ard_3-2-1_090077_2023-07-11_final.stac-item
2023-07-15 11:26:53	ga_ls9c_ard_3-2-1_111077_2023-07-15_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-07-24 11:20:41	ga_ls9c_ard_3-2-1_110077_2023-07-24_final.stac-item
2023-08-07 11:33:13	ga_ls9c_ard_3-2-1_112077_2023-08-07_final.stac-item
2023-08-16 11:27:03	ga_ls9c_ard_3-2-1_111077_2023-08-16_final.stac-item
2023-08-23 11:33:19	ga_ls9c_ard_3-2-1_112077_2023-08-23_final.stac-item
2023-08-25 11:20:59	ga_ls9c_ard_3-2-1_110077_2023-08-25_final.stac-item
2023-09-01 11:27:14	ga_ls9c_ard_3-2-1_111077_2023-09-01_final.stac-item
2023-09-08 11:33:29	ga_ls9c_ard_3-2-1_112077_2023-09-08_final.stac-item
2023-09-24 11:33:30	ga_ls9c_ard_3-2-1_112077_2023-09-24_final.stac-item
2023-09-26 11:21:07	ga_ls9c_ard_3-2-1_110077_2023-09-26_final.stac-item
2023-10-03 11:27:22	ga_ls9c_ard_3-2-1_111077_2023-10-03_final.stac-item
2023-10-10 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-10-10_final.stac-item
2023-11-13 11:21:17	ga_ls9c_ard_3-2-1_110077_2023-11-13_final.stac-item
2023-11-27 11:33:46	ga_ls9c_ard_3-2-1_112077_2023-11-27_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