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
2021-11-09 10:40:11	ga_ls9c_ard_3-2-1_103082_2021-11-09_final.stac-item
2021-11-10 11:20:09	ga_ls9c_ard_3-2-1_110082_2021-11-10_final.stac-item
2021-11-18 10:05:09	ga_ls9c_ard_3-2-1_097082_2021-11-18_final.stac-item
2021-12-10 10:27:49	ga_ls9c_ard_3-2-1_101082_2021-12-10_final.stac-item
2021-12-16 09:50:40	ga_ls9c_ard_3-2-1_095082_2021-12-16_final.stac-item
2021-12-17 10:33:55	ga_ls9c_ard_3-2-1_102082_2021-12-17_final.stac-item
2021-12-21 10:09:13	ga_ls9c_ard_3-2-1_098082_2021-12-21_final.stac-item
2021-12-26 10:27:46	ga_ls9c_ard_3-2-1_101082_2021-12-26_final.stac-item
2021-12-28 10:15:24	ga_ls9c_ard_3-2-1_099082_2021-12-28_final.stac-item
2022-01-07 10:52:28	ga_ls9c_ard_3-2-1_105082_2022-01-07_final.stac-item
2022-01-09 10:40:05	ga_ls9c_ard_3-2-1_103082_2022-01-09_final.stac-item
2022-03-26 11:04:30	ga_ls9c_ard_3-2-1_107082_2022-03-26_final.stac-item
2022-05-29 11:04:04	ga_ls9c_ard_3-2-1_107082_2022-05-29_final.stac-item
2022-05-30 10:08:27	ga_ls9c_ard_3-2-1_098082_2022-05-30_final.stac-item
2022-05-31 10:51:43	ga_ls9c_ard_3-2-1_105082_2022-05-31_final.stac-item
2022-06-04 10:27:01	ga_ls9c_ard_3-2-1_101082_2022-06-04_final.stac-item
2022-06-08 10:02:17	ga_ls9c_ard_3-2-1_097082_2022-06-08_final.stac-item
2022-06-10 09:49:56	ga_ls9c_ard_3-2-1_095082_2022-06-10_final.stac-item
2022-06-10 11:28:49	ga_ls9c_ard_3-2-1_111082_2022-06-10_final.stac-item
2022-06-15 10:08:33	ga_ls9c_ard_3-2-1_098082_2022-06-15_final.stac-item
2022-06-16 10:51:50	ga_ls9c_ard_3-2-1_105082_2022-06-16_final.stac-item
2022-06-20 10:27:12	ga_ls9c_ard_3-2-1_101082_2022-06-20_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-06-30 11:04:26	ga_ls9c_ard_3-2-1_107082_2022-06-30_final.stac-item
2022-07-03 09:56:26	ga_ls9c_ard_3-2-1_096082_2022-07-03_final.stac-item
2022-07-04 10:39:42	ga_ls9c_ard_3-2-1_103082_2022-07-04_final.stac-item
2022-07-06 10:27:20	ga_ls9c_ard_3-2-1_101082_2022-07-06_final.stac-item
2022-07-12 11:29:06	ga_ls9c_ard_3-2-1_111082_2022-07-12_final.stac-item
2022-07-15 10:21:05	ga_ls9c_ard_3-2-1_100082_2022-07-15_final.stac-item
2022-07-17 10:08:46	ga_ls9c_ard_3-2-1_098082_2022-07-17_final.stac-item
2022-07-18 10:52:03	ga_ls9c_ard_3-2-1_105082_2022-07-18_final.stac-item
2022-07-21 11:23:00	ga_ls9c_ard_3-2-1_110082_2022-07-21_final.stac-item
2022-07-25 10:58:21	ga_ls9c_ard_3-2-1_106082_2022-07-25_final.stac-item
2022-07-26 10:02:44	ga_ls9c_ard_3-2-1_097082_2022-07-26_final.stac-item
2022-07-29 10:33:41	ga_ls9c_ard_3-2-1_102082_2022-07-29_final.stac-item
2022-08-05 10:39:57	ga_ls9c_ard_3-2-1_103082_2022-08-05_final.stac-item
2022-08-07 10:27:36	ga_ls9c_ard_3-2-1_101082_2022-08-07_final.stac-item
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final.stac-item
2022-08-14 10:33:51	ga_ls9c_ard_3-2-1_102082_2022-08-14_final.stac-item
2022-08-17 11:04:46	ga_ls9c_ard_3-2-1_107082_2022-08-17_final.stac-item
2022-08-18 10:09:09	ga_ls9c_ard_3-2-1_098082_2022-08-18_final.stac-item
2022-08-19 10:52:25	ga_ls9c_ard_3-2-1_105082_2022-08-19_final.stac-item
2022-08-22 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-08-22_final.stac-item
2022-08-23 10:27:42	ga_ls9c_ard_3-2-1_101082_2022-08-23_final.stac-item
2022-08-27 10:02:59	ga_ls9c_ard_3-2-1_097082_2022-08-27_final.stac-item
2022-08-30 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-08-30_final.stac-item
2022-09-08 10:27:42	ga_ls9c_ard_3-2-1_101082_2022-09-08_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-15 10:33:57	ga_ls9c_ard_3-2-1_102082_2022-09-15_final.stac-item
2022-09-24 10:27:49	ga_ls9c_ard_3-2-1_101082_2022-09-24_final.stac-item
2022-10-01 10:34:01	ga_ls9c_ard_3-2-1_102082_2022-10-01_final.stac-item
2022-10-03 10:21:39	ga_ls9c_ard_3-2-1_100082_2022-10-03_final.stac-item
2022-10-13 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-10-13_final.stac-item
2022-10-22 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-10-22_final.stac-item
2022-10-23 09:57:02	ga_ls9c_ard_3-2-1_096082_2022-10-23_final.stac-item
2022-11-01 09:50:49	ga_ls9c_ard_3-2-1_095082_2022-11-01_final.stac-item
2022-11-01 11:29:42	ga_ls9c_ard_3-2-1_111082_2022-11-01_final.stac-item
2022-11-02 10:34:04	ga_ls9c_ard_3-2-1_102082_2022-11-02_final.stac-item
2022-11-09 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-11-09_final.stac-item
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final.stac-item
2022-11-13 10:15:35	ga_ls9c_ard_3-2-1_099082_2022-11-13_final.stac-item
2022-11-17 09:50:52	ga_ls9c_ard_3-2-1_095082_2022-11-17_final.stac-item
2022-11-20 10:21:46	ga_ls9c_ard_3-2-1_100082_2022-11-20_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-11-27 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-11-27_final.stac-item
2022-12-01 10:03:10	ga_ls9c_ard_3-2-1_097082_2022-12-01_final.stac-item
2022-12-03 09:50:48	ga_ls9c_ard_3-2-1_095082_2022-12-03_final.stac-item
2022-12-04 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-04_final.stac-item
2022-12-16 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-12-16_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2022-12-29 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-12-29_final.stac-item
2023-01-01 10:58:50	ga_ls9c_ard_3-2-1_106082_2023-01-01_final.stac-item
2023-01-02 10:03:12	ga_ls9c_ard_3-2-1_097082_2023-01-02_final.stac-item
2023-01-05 10:34:07	ga_ls9c_ard_3-2-1_102082_2023-01-05_final.stac-item
2023-01-14 10:27:52	ga_ls9c_ard_3-2-1_101082_2023-01-14_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-21 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-02-21_final.stac-item
2023-02-22 10:33:58	ga_ls9c_ard_3-2-1_102082_2023-02-22_final.stac-item
2023-06-19 10:51:31	ga_ls9c_ard_3-2-1_105082_2023-06-19_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-07-08 11:22:39	ga_ls9c_ard_3-2-1_110082_2023-07-08_final.stac-item
2023-07-17 11:16:31	ga_ls9c_ard_3-2-1_109082_2023-07-17_final.stac-item
2023-07-24 11:22:41	ga_ls9c_ard_3-2-1_110082_2023-07-24_final.stac-item
2023-08-02 11:16:38	ga_ls9c_ard_3-2-1_109082_2023-08-02_final.stac-item
2023-08-10 10:27:15	ga_ls9c_ard_3-2-1_101082_2023-08-10_final.stac-item
2023-08-17 10:33:25	ga_ls9c_ard_3-2-1_102082_2023-08-17_final.stac-item
2023-08-26 10:27:22	ga_ls9c_ard_3-2-1_101082_2023-08-26_final.stac-item
2023-09-11 10:27:32	ga_ls9c_ard_3-2-1_101082_2023-09-11_final.stac-item
2023-10-04 10:33:45	ga_ls9c_ard_3-2-1_102082_2023-10-04_final.stac-item
2023-10-29 10:27:40	ga_ls9c_ard_3-2-1_101082_2023-10-29_final.stac-item
2023-12-16 10:27:48	ga_ls9c_ard_3-2-1_101082_2023-12-16_final.stac-item
2024-01-01 10:27:46	ga_ls9c_ard_3-2-1_101082_2024-01-01_final.stac-item
2024-01-17 10:27:45	ga_ls9c_ard_3-2-1_101082_2024-01-17_final.stac-item
2024-01-24 10:33:51	ga_ls9c_ard_3-2-1_102082_2024-01-24_final.stac-item
2024-02-21 10:58:29	ga_ls9c_ard_3-2-1_106082_2024-02-21_final.stac-item
2024-03-06 11:10:55	ga_ls9c_ard_3-2-1_108082_2024-03-06_final.stac-item
2024-03-15 11:04:43	ga_ls9c_ard_3-2-1_107082_2024-03-15_final.stac-item
2024-03-19 10:39:59	ga_ls9c_ard_3-2-1_103082_2024-03-19_final.stac-item
2024-03-28 10:33:41	ga_ls9c_ard_3-2-1_102082_2024-03-28_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