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

61 results

Time (local)	Label
2021-11-10 11:15:22	ga_ls9c_ard_3-2-1_110070_2021-11-10_final.stac-item
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2021-12-05 10:05:21	ga_ls9c_ard_3-2-1_098072_2021-12-05_final.stac-item
2021-12-25 11:24:35	ga_ls9c_ard_3-2-1_110085_2021-12-25_final.stac-item
2021-12-30 09:58:39	ga_ls9c_ard_3-2-1_097071_2021-12-30_final.stac-item
2021-12-31 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-31_final.stac-item
2022-02-02 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-02-02_final.stac-item
2022-02-18 11:25:27	ga_ls9c_ard_3-2-1_111072_2022-02-18_final.stac-item
2022-03-02 11:51:13	ga_ls9c_ard_3-2-1_115075_2022-03-02_final.stac-item
2022-03-06 11:26:55	ga_ls9c_ard_3-2-1_111076_2022-03-06_final.stac-item
2022-03-19 10:55:59	ga_ls9c_ard_3-2-1_106076_2022-03-19_final.stac-item
2022-03-23 10:33:14	ga_ls9c_ard_3-2-1_102081_2022-03-23_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-04-05 11:38:23	ga_ls9c_ard_3-2-1_113074_2022-04-05_final.stac-item
2022-04-16 11:23:20	ga_ls9c_ard_3-2-1_110083_2022-04-16_final.stac-item
2022-04-21 10:01:19	ga_ls9c_ard_3-2-1_097079_2022-04-21_final.stac-item
2022-04-23 11:29:02	ga_ls9c_ard_3-2-1_111082_2022-04-23_final.stac-item
2022-05-26 10:32:46	ga_ls9c_ard_3-2-1_102081_2022-05-26_final.stac-item
2022-06-30 11:01:14	ga_ls9c_ard_3-2-1_107074_2022-06-30_final.stac-item
2022-07-24 11:52:46	ga_ls9c_ard_3-2-1_115079_2022-07-24_final.stac-item
2022-08-19 09:10:44	ga_ls9c_ard_3-2-1_089075_2022-08-18_final.stac-item
2022-08-24 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-08-24_final.stac-item
2022-08-29 09:47:26	ga_ls9c_ard_3-2-1_095074_2022-08-29_final.stac-item
2022-09-23 11:19:27	ga_ls9c_ard_3-2-1_110072_2022-09-23_final.stac-item
2022-10-08 10:35:25	ga_ls9c_ard_3-2-1_103070_2022-10-08_final.stac-item
2022-10-09 11:19:53	ga_ls9c_ard_3-2-1_110073_2022-10-09_final.stac-item
2022-10-18 09:37:17	ga_ls9c_ard_3-2-1_093079_2022-10-18_final.stac-item
2022-11-01 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-11-01_final.stac-item
2022-11-30 10:54:00	ga_ls9c_ard_3-2-1_106070_2022-11-30_final.stac-item
2022-12-16 09:18:20	ga_ls9c_ard_3-2-1_090078_2022-12-15_final.stac-item
2022-12-30 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-30_final.stac-item
2023-01-17 09:22:14	ga_ls9c_ard_3-2-1_090088_2023-01-16_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-03-22 10:55:41	ga_ls9c_ard_3-2-1_106075_2023-03-22_final.stac-item
2023-03-27 09:34:27	ga_ls9c_ard_3-2-1_093073_2023-03-27_final.stac-item
2023-04-06 11:51:57	ga_ls9c_ard_3-2-1_115077_2023-04-06_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-04-30 09:27:48	ga_ls9c_ard_3-2-1_091088_2023-04-29_final.stac-item
2023-05-08 10:15:10	ga_ls9c_ard_3-2-1_099083_2023-05-08_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-05-31 10:20:22	ga_ls9c_ard_3-2-1_100081_2023-05-31_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-19 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-07-18_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-21 10:04:22	ga_ls9c_ard_3-2-1_098071_2023-08-21_final.stac-item
2023-09-11 10:23:08	ga_ls9c_ard_3-2-1_101071_2023-09-11_final.stac-item
2023-09-25 10:39:52	ga_ls9c_ard_3-2-1_103082_2023-09-25_final.stac-item
2023-11-02 11:38:34	ga_ls9c_ard_3-2-1_113074_2023-11-02_final.stac-item
2023-11-08 11:05:32	ga_ls9c_ard_3-2-1_107084_2023-11-08_final.stac-item
2023-11-15 09:34:25	ga_ls9c_ard_3-2-1_092088_2023-11-15_final.stac-item
2023-12-18 10:11:27	ga_ls9c_ard_3-2-1_099072_2023-12-18_final.stac-item
2023-12-29 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-12-29_final.stac-item
2024-01-08 10:31:54	ga_ls9c_ard_3-2-1_102077_2024-01-08_final.stac-item
2024-02-14 09:13:35	ga_ls9c_ard_3-2-1_089082_2024-02-13_final.stac-item
2024-03-06 11:06:56	ga_ls9c_ard_3-2-1_108072_2024-03-06_final.stac-item
2024-03-09 09:59:45	ga_ls9c_ard_3-2-1_097074_2024-03-09_final.stac-item
2024-03-28 10:30:53	ga_ls9c_ard_3-2-1_102075_2024-03-28_final.stac-item
2024-03-29 09:34:51	ga_ls9c_ard_3-2-1_093074_2024-03-29_final.stac-item
2024-03-30 10:21:18	ga_ls9c_ard_3-2-1_100082_2024-03-30_final.stac-item
2024-04-13 10:28:23	ga_ls9c_ard_3-2-1_102069_2024-04-13_final.stac-item
2024-04-14 09:39:08	ga_ls9c_ard_3-2-1_093085_2024-04-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years