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

70 results

Time (local)	Label
2021-11-10 11:20:09	ga_ls9c_ard_3-2-1_110082_2021-11-10_final.stac-item
2021-12-16 09:50:40	ga_ls9c_ard_3-2-1_095082_2021-12-16_final.stac-item
2021-12-16 11:26:45	ga_ls9c_ard_3-2-1_111075_2021-12-16_final.stac-item
2021-12-18 09:38:42	ga_ls9c_ard_3-2-1_093083_2021-12-18_final.stac-item
2021-12-20 09:27:33	ga_ls9c_ard_3-2-1_091086_2021-12-19_final.stac-item
2021-12-27 11:08:38	ga_ls9c_ard_3-2-1_108076_2021-12-27_final.stac-item
2022-01-17 09:47:27	ga_ls9c_ard_3-2-1_095074_2022-01-17_final.stac-item
2022-01-31 11:39:07	ga_ls9c_ard_3-2-1_113075_2022-01-31_final.stac-item
2022-02-11 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-02-11_final.stac-item
2022-02-13 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-02-13_final.stac-item
2022-03-12 09:12:56	ga_ls9c_ard_3-2-1_089081_2022-03-11_final.stac-item
2022-03-20 09:58:22	ga_ls9c_ard_3-2-1_097071_2022-03-20_final.stac-item
2022-03-21 10:40:49	ga_ls9c_ard_3-2-1_104069_2022-03-21_final.stac-item
2022-04-19 11:50:36	ga_ls9c_ard_3-2-1_115074_2022-04-19_final.stac-item
2022-04-20 10:57:21	ga_ls9c_ard_3-2-1_106080_2022-04-20_final.stac-item
2022-04-28 10:09:05	ga_ls9c_ard_3-2-1_098083_2022-04-28_final.stac-item
2022-04-29 09:13:28	ga_ls9c_ard_3-2-1_089083_2022-04-28_final.stac-item
2022-05-13 10:59:47	ga_ls9c_ard_3-2-1_107071_2022-05-13_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-06-14 09:25:41	ga_ls9c_ard_3-2-1_091083_2022-06-13_final.stac-item
2022-07-28 09:51:12	ga_ls9c_ard_3-2-1_095084_2022-07-28_final.stac-item
2022-08-25 10:12:57	ga_ls9c_ard_3-2-1_099076_2022-08-25_final.stac-item
2022-08-26 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-08-26_final.stac-item
2022-09-07 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-09-07_final.stac-item
2022-09-21 11:35:24	ga_ls9c_ard_3-2-1_112081_2022-09-21_final.stac-item
2022-09-27 09:22:39	ga_ls9c_ard_3-2-1_090089_2022-09-26_final.stac-item
2022-10-18 09:35:17	ga_ls9c_ard_3-2-1_093074_2022-10-18_final.stac-item
2022-10-20 11:05:25	ga_ls9c_ard_3-2-1_107083_2022-10-20_final.stac-item
2022-10-28 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-10-28_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-16 10:41:42	ga_ls9c_ard_3-2-1_104070_2022-11-16_final.stac-item
2022-12-14 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-14_final.stac-item
2022-12-14 11:08:24	ga_ls9c_ard_3-2-1_108075_2022-12-14_final.stac-item
2023-01-04 09:50:51	ga_ls9c_ard_3-2-1_095082_2023-01-04_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-08 11:01:01	ga_ls9c_ard_3-2-1_107072_2023-01-08_final.stac-item
2023-01-15 11:07:08	ga_ls9c_ard_3-2-1_108072_2023-01-15_final.stac-item
2023-01-26 09:15:18	ga_ls9c_ard_3-2-1_089086_2023-01-25_final.stac-item
2023-03-08 09:04:54	ga_ls9c_ard_3-2-1_088076_2023-03-07_interim.stac-item
2023-03-09 11:25:26	ga_ls9c_ard_3-2-1_111072_2023-03-09_final.stac-item
2023-04-02 10:36:36	ga_ls9c_ard_3-2-1_103074_2023-04-02_final.stac-item
2023-04-06 10:12:40	ga_ls9c_ard_3-2-1_099076_2023-04-06_final.stac-item
2023-04-07 10:53:32	ga_ls9c_ard_3-2-1_106070_2023-04-07_final.stac-item
2023-04-12 11:12:49	ga_ls9c_ard_3-2-1_109072_2023-04-12_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-06-04 09:55:38	ga_ls9c_ard_3-2-1_096081_2023-06-04_final.stac-item
2023-06-10 09:17:18	ga_ls9c_ard_3-2-1_090078_2023-06-09_final.stac-item
2023-06-16 10:17:01	ga_ls9c_ard_3-2-1_100073_2023-06-16_final.stac-item
2023-06-18 10:07:04	ga_ls9c_ard_3-2-1_098079_2023-06-18_final.stac-item
2023-07-19 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-07-19_final.stac-item
2023-09-04 10:18:04	ga_ls9c_ard_3-2-1_100074_2023-09-04_final.stac-item
2023-09-15 10:00:50	ga_ls9c_ard_3-2-1_097077_2023-09-15_final.stac-item
2023-09-22 10:07:24	ga_ls9c_ard_3-2-1_098078_2023-09-22_final.stac-item
2023-11-01 12:31:25	ga_ls9c_ard_3-2-1_122067_2023-11-01_final.stac-item
2023-12-07 10:29:06	ga_ls9c_ard_3-2-1_102070_2023-12-07_final.stac-item
2023-12-16 10:25:24	ga_ls9c_ard_3-2-1_101076_2023-12-16_final.stac-item
2023-12-19 09:18:38	ga_ls9c_ard_3-2-1_090079_2023-12-18_final.stac-item
2023-12-24 09:36:47	ga_ls9c_ard_3-2-1_093078_2023-12-24_final.stac-item
2023-12-26 09:22:25	ga_ls9c_ard_3-2-1_091073_2023-12-25_final.stac-item
2024-01-02 09:32:08	ga_ls9c_ard_3-2-1_092082_2024-01-02_final.stac-item
2024-01-04 10:53:50	ga_ls9c_ard_3-2-1_106070_2024-01-04_final.stac-item
2024-01-21 11:40:41	ga_ls9c_ard_3-2-1_113079_2024-01-21_final.stac-item
2024-02-01 11:21:00	ga_ls9c_ard_3-2-1_110076_2024-02-01_final.stac-item
2024-02-03 09:34:57	ga_ls9c_ard_3-2-1_092089_2024-02-03_final.stac-item
2024-02-20 11:51:45	ga_ls9c_ard_3-2-1_115076_2024-02-20_final.stac-item
2024-03-15 09:23:50	ga_ls9c_ard_3-2-1_091077_2024-03-14_final.stac-item
2024-04-01 11:47:02	ga_ls9c_ard_3-2-1_114080_2024-04-01_final.stac-item
2024-04-19 09:56:46	ga_ls9c_ard_3-2-1_096083_2024-04-19_final.stac-item
2024-05-02 11:01:46	ga_ls9c_ard_3-2-1_107076_2024-05-02_nrt.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