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 10:56:27	ga_ls9c_ard_3-2-1_106082_2021-11-02_final.stac-item
2021-11-05 11:17:40	ga_ls9c_ard_3-2-1_109082_2021-11-05_final.stac-item
2021-11-07 10:58:56	ga_ls9c_ard_3-2-1_106082_2021-11-07_final.stac-item
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
2021-11-13 10:02:42	ga_ls9c_ard_3-2-1_097082_2021-11-13_final.stac-item
2021-11-17 09:25:40	ga_ls9c_ard_3-2-1_091083_2021-11-16_final.stac-item
2021-11-18 10:05:09	ga_ls9c_ard_3-2-1_097082_2021-11-18_final.stac-item
2021-11-22 09:28:03	ga_ls9c_ard_3-2-1_091083_2021-11-21_final.stac-item
2021-11-22 11:06:19	ga_ls9c_ard_3-2-1_107082_2021-11-22_final.stac-item
2021-11-23 10:07:36	ga_ls9c_ard_3-2-1_098082_2021-11-23_final.stac-item
2021-12-16 09:50:40	ga_ls9c_ard_3-2-1_095082_2021-12-16_final.stac-item
2021-12-20 11:04:50	ga_ls9c_ard_3-2-1_107082_2021-12-20_final.stac-item
2021-12-27 09:32:33	ga_ls9c_ard_3-2-1_092083_2021-12-27_final.stac-item
2022-01-12 09:32:29	ga_ls9c_ard_3-2-1_092083_2022-01-12_final.stac-item
2022-04-02 09:32:12	ga_ls9c_ard_3-2-1_092083_2022-04-02_final.stac-item
2022-05-31 10:51:43	ga_ls9c_ard_3-2-1_105082_2022-05-31_final.stac-item
2022-06-14 11:04:10	ga_ls9c_ard_3-2-1_107082_2022-06-14_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
2022-06-26 09:50:17	ga_ls9c_ard_3-2-1_095082_2022-06-26_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-07-06 10:27:20	ga_ls9c_ard_3-2-1_101082_2022-07-06_final.stac-item
2022-07-09 10:58:13	ga_ls9c_ard_3-2-1_106082_2022-07-09_final.stac-item
2022-07-14 11:16:43	ga_ls9c_ard_3-2-1_109082_2022-07-14_final.stac-item
2022-07-15 10:21:05	ga_ls9c_ard_3-2-1_100082_2022-07-15_final.stac-item
2022-07-18 10:52:03	ga_ls9c_ard_3-2-1_105082_2022-07-18_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-26 10:02:44	ga_ls9c_ard_3-2-1_097082_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
2022-07-30 09:38:04	ga_ls9c_ard_3-2-1_093082_2022-07-30_final.stac-item
2022-08-01 11:04:37	ga_ls9c_ard_3-2-1_107082_2022-08-01_final.stac-item
2022-08-05 10:39:57	ga_ls9c_ard_3-2-1_103082_2022-08-05_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
2022-09-02 11:04:47	ga_ls9c_ard_3-2-1_107082_2022-09-02_final.stac-item
2022-09-06 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-09-06_final.stac-item
2022-09-09 09:32:28	ga_ls9c_ard_3-2-1_092083_2022-09-09_final.stac-item
2022-09-09 11:10:57	ga_ls9c_ard_3-2-1_108082_2022-09-09_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-21 09:56:54	ga_ls9c_ard_3-2-1_096082_2022-09-21_final.stac-item
2022-09-25 09:32:36	ga_ls9c_ard_3-2-1_092083_2022-09-25_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
2022-10-20 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-10-20_final.stac-item
2022-10-27 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-10-27_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 09:50:49	ga_ls9c_ard_3-2-1_095082_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
2022-11-12 09:32:43	ga_ls9c_ard_3-2-1_092083_2022-11-12_final.stac-item
2022-12-03 09:50:48	ga_ls9c_ard_3-2-1_095082_2022-12-03_final.stac-item
2022-12-05 11:17:21	ga_ls9c_ard_3-2-1_109082_2022-12-05_final.stac-item
2022-12-29 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-12-29_final.stac-item
2022-12-30 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-30_final.stac-item
2023-01-15 09:32:38	ga_ls9c_ard_3-2-1_092083_2023-01-15_final.stac-item
2023-01-31 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-01-31_final.stac-item
2023-02-16 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-02-16_final.stac-item
2023-03-04 09:32:29	ga_ls9c_ard_3-2-1_092083_2023-03-04_final.stac-item
2023-03-20 09:32:23	ga_ls9c_ard_3-2-1_092083_2023-03-20_final.stac-item
2023-04-05 09:32:12	ga_ls9c_ard_3-2-1_092083_2023-04-05_final.stac-item
2023-04-21 09:32:06	ga_ls9c_ard_3-2-1_092083_2023-04-21_final.stac-item
2023-05-07 09:31:54	ga_ls9c_ard_3-2-1_092083_2023-05-07_final.stac-item
2023-05-23 09:31:45	ga_ls9c_ard_3-2-1_092083_2023-05-23_final.stac-item
2023-06-08 09:31:40	ga_ls9c_ard_3-2-1_092083_2023-06-08_final.stac-item
2023-06-17 11:03:53	ga_ls9c_ard_3-2-1_107082_2023-06-17_final.stac-item
2023-06-19 10:51:31	ga_ls9c_ard_3-2-1_105082_2023-06-19_final.stac-item
2023-06-24 09:31:34	ga_ls9c_ard_3-2-1_092083_2023-06-24_final.stac-item
2023-06-26 10:57:42	ga_ls9c_ard_3-2-1_106082_2023-06-26_final.stac-item
2023-07-01 09:37:30	ga_ls9c_ard_3-2-1_093082_2023-07-01_final.stac-item
2023-07-01 11:16:23	ga_ls9c_ard_3-2-1_109082_2023-07-01_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-07-10 09:31:50	ga_ls9c_ard_3-2-1_092083_2023-07-10_final.stac-item
2023-07-10 11:10:19	ga_ls9c_ard_3-2-1_108082_2023-07-10_final.stac-item
2023-07-12 10:57:58	ga_ls9c_ard_3-2-1_106082_2023-07-12_final.stac-item
2023-07-13 10:02:21	ga_ls9c_ard_3-2-1_097082_2023-07-13_final.stac-item
2023-07-15 09:50:00	ga_ls9c_ard_3-2-1_095082_2023-07-15_final.stac-item
2023-07-17 09:37:38	ga_ls9c_ard_3-2-1_093082_2023-07-17_final.stac-item
2023-07-22 09:56:10	ga_ls9c_ard_3-2-1_096082_2023-07-22_final.stac-item
2023-07-26 09:31:51	ga_ls9c_ard_3-2-1_092083_2023-07-26_final.stac-item
2023-08-07 09:56:20	ga_ls9c_ard_3-2-1_096082_2023-08-07_final.stac-item
2023-08-09 09:43:59	ga_ls9c_ard_3-2-1_094082_2023-08-09_final.stac-item
2023-08-09 11:22:52	ga_ls9c_ard_3-2-1_110082_2023-08-09_final.stac-item
2023-08-11 09:32:01	ga_ls9c_ard_3-2-1_092083_2023-08-11_final.stac-item
2023-08-16 09:50:10	ga_ls9c_ard_3-2-1_095082_2023-08-16_final.stac-item
2023-08-25 11:22:59	ga_ls9c_ard_3-2-1_110082_2023-08-25_final.stac-item
2023-08-27 09:32:09	ga_ls9c_ard_3-2-1_092083_2023-08-27_final.stac-item
2023-09-01 09:50:20	ga_ls9c_ard_3-2-1_095082_2023-09-01_final.stac-item
2023-09-10 11:23:09	ga_ls9c_ard_3-2-1_110082_2023-09-10_final.stac-item
2023-09-12 09:32:19	ga_ls9c_ard_3-2-1_092083_2023-09-12_final.stac-item
2023-09-17 09:50:29	ga_ls9c_ard_3-2-1_095082_2023-09-17_final.stac-item
2023-09-24 09:56:37	ga_ls9c_ard_3-2-1_096082_2023-09-24_final.stac-item
2023-09-26 11:23:07	ga_ls9c_ard_3-2-1_110082_2023-09-26_final.stac-item
2023-09-28 09:32:15	ga_ls9c_ard_3-2-1_092083_2023-09-28_final.stac-item
2023-10-12 09:44:24	ga_ls9c_ard_3-2-1_094082_2023-10-12_final.stac-item
2023-10-12 11:23:17	ga_ls9c_ard_3-2-1_110082_2023-10-12_final.stac-item
2023-11-11 09:56:45	ga_ls9c_ard_3-2-1_096082_2023-11-11_final.stac-item
2023-11-13 11:23:16	ga_ls9c_ard_3-2-1_110082_2023-11-13_final.stac-item
2023-11-22 09:38:18	ga_ls9c_ard_3-2-1_093082_2023-11-22_final.stac-item
2024-01-09 09:38:17	ga_ls9c_ard_3-2-1_093082_2024-01-09_final.stac-item
2024-01-21 10:03:00	ga_ls9c_ard_3-2-1_097082_2024-01-21_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