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
2021-11-02 09:17:47	ga_ls9c_ard_3-2-1_090082_2021-11-01_final.stac-item
2021-11-07 09:20:16	ga_ls9c_ard_3-2-1_090082_2021-11-06_final.stac-item
2021-12-04 11:04:58	ga_ls9c_ard_3-2-1_107082_2021-12-04_final.stac-item
2021-12-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2021-12-08_final.stac-item
2021-12-13 10:58:41	ga_ls9c_ard_3-2-1_106082_2021-12-13_final.stac-item
2021-12-29 09:19:47	ga_ls9c_ard_3-2-1_090082_2021-12-28_final.stac-item
2022-01-01 11:29:34	ga_ls9c_ard_3-2-1_111082_2022-01-01_final.stac-item
2022-01-12 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-01-12_final.stac-item
2022-01-23 09:13:35	ga_ls9c_ard_3-2-1_089082_2022-01-22_final.stac-item
2022-01-30 10:58:39	ga_ls9c_ard_3-2-1_106082_2022-01-30_final.stac-item
2022-02-01 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-02-01_final.stac-item
2022-02-02 11:29:33	ga_ls9c_ard_3-2-1_111082_2022-02-02_final.stac-item
2022-02-06 09:25:56	ga_ls9c_ard_3-2-1_091082_2022-02-05_final.stac-item
2022-02-06 11:04:49	ga_ls9c_ard_3-2-1_107082_2022-02-06_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-02-15 10:58:35	ga_ls9c_ard_3-2-1_106082_2022-02-15_final.stac-item
2022-02-18 11:29:27	ga_ls9c_ard_3-2-1_111082_2022-02-18_final.stac-item
2022-03-05 10:46:02	ga_ls9c_ard_3-2-1_104082_2022-03-05_final.stac-item
2022-03-26 11:04:30	ga_ls9c_ard_3-2-1_107082_2022-03-26_final.stac-item
2022-04-06 10:45:57	ga_ls9c_ard_3-2-1_104082_2022-04-06_final.stac-item
2022-04-20 09:19:16	ga_ls9c_ard_3-2-1_090082_2022-04-19_final.stac-item
2022-05-15 09:12:54	ga_ls9c_ard_3-2-1_089082_2022-05-14_final.stac-item
2022-05-29 11:04:04	ga_ls9c_ard_3-2-1_107082_2022-05-29_final.stac-item
2022-06-07 09:19:02	ga_ls9c_ard_3-2-1_090082_2022-06-06_final.stac-item
2022-06-10 11:28:49	ga_ls9c_ard_3-2-1_111082_2022-06-10_final.stac-item
2022-06-14 09:25:17	ga_ls9c_ard_3-2-1_091082_2022-06-13_final.stac-item
2022-06-16 09:12:57	ga_ls9c_ard_3-2-1_089082_2022-06-15_final.stac-item
2022-06-23 09:19:19	ga_ls9c_ard_3-2-1_090082_2022-06-22_final.stac-item
2022-06-25 09:07:01	ga_ls9c_ard_3-2-1_088082_2022-06-24_final.stac-item
2022-06-30 11:04:26	ga_ls9c_ard_3-2-1_107082_2022-06-30_final.stac-item
2022-07-07 09:31:42	ga_ls9c_ard_3-2-1_092082_2022-07-07_final.stac-item
2022-07-12 11:29:06	ga_ls9c_ard_3-2-1_111082_2022-07-12_final.stac-item
2022-07-16 09:25:29	ga_ls9c_ard_3-2-1_091082_2022-07-15_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-25 10:58:21	ga_ls9c_ard_3-2-1_106082_2022-07-25_final.stac-item
2022-07-27 09:07:08	ga_ls9c_ard_3-2-1_088082_2022-07-26_final.stac-item
2022-07-27 10:46:01	ga_ls9c_ard_3-2-1_104082_2022-07-27_final.stac-item
2022-08-03 09:13:24	ga_ls9c_ard_3-2-1_089082_2022-08-02_final.stac-item
2022-08-10 09:19:39	ga_ls9c_ard_3-2-1_090082_2022-08-09_final.stac-item
2022-08-17 11:04:46	ga_ls9c_ard_3-2-1_107082_2022-08-17_final.stac-item
2022-08-26 09:19:44	ga_ls9c_ard_3-2-1_090082_2022-08-25_final.stac-item
2022-08-28 09:07:22	ga_ls9c_ard_3-2-1_088082_2022-08-27_final.stac-item
2022-09-02 09:25:54	ga_ls9c_ard_3-2-1_091082_2022-09-01_final.stac-item
2022-09-04 09:13:33	ga_ls9c_ard_3-2-1_089082_2022-09-03_final.stac-item
2022-09-06 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-09-06_final.stac-item
2022-09-11 09:19:44	ga_ls9c_ard_3-2-1_090082_2022-09-10_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-18 09:25:59	ga_ls9c_ard_3-2-1_091082_2022-09-17_final.stac-item
2022-09-20 09:13:38	ga_ls9c_ard_3-2-1_089082_2022-09-19_final.stac-item
2022-09-22 10:40:10	ga_ls9c_ard_3-2-1_103082_2022-09-22_final.stac-item
2022-09-27 09:19:51	ga_ls9c_ard_3-2-1_090082_2022-09-26_final.stac-item
2022-10-06 09:13:39	ga_ls9c_ard_3-2-1_089082_2022-10-05_final.stac-item
2022-10-11 09:32:15	ga_ls9c_ard_3-2-1_092082_2022-10-11_final.stac-item
2022-10-13 09:19:55	ga_ls9c_ard_3-2-1_090082_2022-10-12_final.stac-item
2022-10-13 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-10-13_final.stac-item
2022-10-15 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-14_final.stac-item
2022-10-24 10:40:18	ga_ls9c_ard_3-2-1_103082_2022-10-24_final.stac-item
2022-10-29 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-10-29_final.stac-item
2022-10-31 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-31_final.stac-item
2022-11-01 11:29:42	ga_ls9c_ard_3-2-1_111082_2022-11-01_final.stac-item
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final.stac-item
2022-11-05 11:04:58	ga_ls9c_ard_3-2-1_107082_2022-11-05_final.stac-item
2022-11-16 10:46:29	ga_ls9c_ard_3-2-1_104082_2022-11-16_final.stac-item
2022-11-21 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-11-21_final.stac-item
2022-11-28 09:32:17	ga_ls9c_ard_3-2-1_092082_2022-11-28_final.stac-item
2022-11-30 09:19:55	ga_ls9c_ard_3-2-1_090082_2022-11-29_final.stac-item
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final.stac-item
2022-12-02 10:46:25	ga_ls9c_ard_3-2-1_104082_2022-12-02_final.stac-item
2022-12-07 09:26:07	ga_ls9c_ard_3-2-1_091082_2022-12-06_final.stac-item
2022-12-14 09:32:18	ga_ls9c_ard_3-2-1_092082_2022-12-14_final.stac-item
2022-12-16 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-12-16_final.stac-item
2022-12-18 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-12-18_final.stac-item
2022-12-19 11:29:42	ga_ls9c_ard_3-2-1_111082_2022-12-19_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2022-12-23 11:04:57	ga_ls9c_ard_3-2-1_107082_2022-12-23_final.stac-item
2022-12-25 09:13:43	ga_ls9c_ard_3-2-1_089082_2022-12-24_final.stac-item
2022-12-27 10:40:15	ga_ls9c_ard_3-2-1_103082_2022-12-27_final.stac-item
2023-01-01 09:19:57	ga_ls9c_ard_3-2-1_090082_2022-12-31_final.stac-item
2023-01-01 10:58:50	ga_ls9c_ard_3-2-1_106082_2023-01-01_final.stac-item
2023-01-08 09:26:07	ga_ls9c_ard_3-2-1_091082_2023-01-07_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_2023-01-09_final.stac-item
2023-01-12 10:40:15	ga_ls9c_ard_3-2-1_103082_2023-01-12_final.stac-item
2023-01-17 09:19:51	ga_ls9c_ard_3-2-1_090082_2023-01-16_final.stac-item
2023-01-19 10:46:20	ga_ls9c_ard_3-2-1_104082_2023-01-19_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-24 09:26:01	ga_ls9c_ard_3-2-1_091082_2023-01-23_final.stac-item
2023-01-26 09:13:42	ga_ls9c_ard_3-2-1_089082_2023-01-25_final.stac-item
2023-02-11 09:13:49	ga_ls9c_ard_3-2-1_089082_2023-02-10_final.stac-item
2023-02-21 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-02-21_final.stac-item
2023-03-01 10:40:06	ga_ls9c_ard_3-2-1_103082_2023-03-01_final.stac-item
2023-03-15 09:13:28	ga_ls9c_ard_3-2-1_089082_2023-03-14_final.stac-item
2023-03-22 09:19:36	ga_ls9c_ard_3-2-1_090082_2023-03-21_final.stac-item
2023-03-31 09:13:16	ga_ls9c_ard_3-2-1_089082_2023-03-30_final.stac-item
2023-04-26 11:29:05	ga_ls9c_ard_3-2-1_111082_2023-04-26_final.stac-item
2023-06-19 09:12:38	ga_ls9c_ard_3-2-1_089082_2023-06-18_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-07-03 09:25:10	ga_ls9c_ard_3-2-1_091082_2023-07-02_final.stac-item
2023-07-05 09:12:50	ga_ls9c_ard_3-2-1_089082_2023-07-04_final.stac-item
2023-07-12 09:19:05	ga_ls9c_ard_3-2-1_090082_2023-07-11_final.stac-item
2023-07-14 09:06:44	ga_ls9c_ard_3-2-1_088082_2023-07-13_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