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

74 results

Time (local)	Label
2021-11-03 11:36:48	ga_ls9c_ard_3-2-1_112083_2021-11-03_final.stac-item
2021-11-05 11:14:05	ga_ls9c_ard_3-2-1_109073_2021-11-05_final.stac-item
2021-11-08 10:01:01	ga_ls9c_ard_3-2-1_097084_2021-11-08_final.stac-item
2021-11-23 10:01:38	ga_ls9c_ard_3-2-1_098067_2021-11-23_final.stac-item
2022-01-03 09:35:31	ga_ls9c_ard_3-2-1_093075_2022-01-03_final.stac-item
2022-01-03 11:13:12	ga_ls9c_ard_3-2-1_109072_2022-01-03_final.stac-item
2022-02-18 11:23:52	ga_ls9c_ard_3-2-1_111068_2022-02-18_final.stac-item
2022-03-29 11:31:25	ga_ls9c_ard_3-2-1_112072_2022-03-29_final.stac-item
2022-04-07 11:25:13	ga_ls9c_ard_3-2-1_111072_2022-04-07_final.stac-item
2022-04-20 09:20:04	ga_ls9c_ard_3-2-1_090084_2022-04-19_final.stac-item
2022-04-27 09:23:02	ga_ls9c_ard_3-2-1_091076_2022-04-26_final.stac-item
2022-04-28 11:46:46	ga_ls9c_ard_3-2-1_114080_2022-04-28_final.stac-item
2022-05-05 10:15:13	ga_ls9c_ard_3-2-1_099083_2022-05-05_final.stac-item
2022-05-24 09:06:39	ga_ls9c_ard_3-2-1_088082_2022-05-23_final.stac-item
2022-05-28 10:16:49	ga_ls9c_ard_3-2-1_100072_2022-05-28_final.stac-item
2022-06-21 11:08:06	ga_ls9c_ard_3-2-1_108076_2022-06-21_final.stac-item
2022-07-05 09:40:29	ga_ls9c_ard_3-2-1_094073_2022-07-05_final.stac-item
2022-07-07 11:07:00	ga_ls9c_ard_3-2-1_108073_2022-07-07_final.stac-item
2022-07-23 09:29:00	ga_ls9c_ard_3-2-1_092075_2022-07-22_final.stac-item
2022-07-25 10:53:57	ga_ls9c_ard_3-2-1_106071_2022-07-25_final.stac-item
2022-07-26 10:03:56	ga_ls9c_ard_3-2-1_097085_2022-07-26_final.stac-item
2022-08-06 09:42:20	ga_ls9c_ard_3-2-1_094077_2022-08-06_final.stac-item
2022-08-11 09:58:32	ga_ls9c_ard_3-2-1_097071_2022-08-11_final.stac-item
2022-08-13 11:25:28	ga_ls9c_ard_3-2-1_111072_2022-08-13_final.stac-item
2022-08-18 10:05:09	ga_ls9c_ard_3-2-1_098072_2022-08-18_final.stac-item
2022-09-11 10:55:26	ga_ls9c_ard_3-2-1_106074_2022-09-11_final.stac-item
2022-10-13 09:19:07	ga_ls9c_ard_3-2-1_090080_2022-10-12_final.stac-item
2022-10-13 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-10-13_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-22 10:47:28	ga_ls9c_ard_3-2-1_105069_2022-10-22_final.stac-item
2022-11-08 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-11-08_final.stac-item
2022-11-18 10:29:44	ga_ls9c_ard_3-2-1_102071_2022-11-18_final.stac-item
2022-11-25 10:39:05	ga_ls9c_ard_3-2-1_103079_2022-11-25_final.stac-item
2022-12-05 11:15:45	ga_ls9c_ard_3-2-1_109078_2022-12-05_final.stac-item
2023-01-19 09:07:03	ga_ls9c_ard_3-2-1_088081_2023-01-18_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-07 09:40:08	ga_ls9c_ard_3-2-1_093086_2023-02-07_final.stac-item
2023-02-15 10:23:57	ga_ls9c_ard_3-2-1_101072_2023-02-15_final.stac-item
2023-02-23 09:37:31	ga_ls9c_ard_3-2-1_093080_2023-02-23_final.stac-item
2023-03-09 11:30:13	ga_ls9c_ard_3-2-1_111084_2023-03-09_final.stac-item
2023-03-15 09:14:40	ga_ls9c_ard_3-2-1_089085_2023-03-14_final.stac-item
2023-03-17 10:37:59	ga_ls9c_ard_3-2-1_103077_2023-03-17_final.stac-item
2023-03-25 11:26:32	ga_ls9c_ard_3-2-1_111075_2023-03-25_final.stac-item
2023-04-01 09:56:56	ga_ls9c_ard_3-2-1_096083_2023-04-01_final.stac-item
2023-04-07 10:53:56	ga_ls9c_ard_3-2-1_106071_2023-04-07_final.stac-item
2023-04-30 11:01:54	ga_ls9c_ard_3-2-1_107076_2023-04-30_final.stac-item
2023-05-16 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-05-15_final.stac-item
2023-05-31 10:17:58	ga_ls9c_ard_3-2-1_100075_2023-05-31_final.stac-item
2023-06-04 09:57:14	ga_ls9c_ard_3-2-1_096085_2023-06-04_final.stac-item
2023-07-06 09:54:55	ga_ls9c_ard_3-2-1_096079_2023-07-06_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-08-05 10:04:41	ga_ls9c_ard_3-2-1_098072_2023-08-05_final.stac-item
2023-08-12 10:08:54	ga_ls9c_ard_3-2-1_099067_2023-08-12_final.stac-item
2023-08-19 10:17:05	ga_ls9c_ard_3-2-1_100072_2023-08-19_final.stac-item
2023-09-14 10:54:04	ga_ls9c_ard_3-2-1_106071_2023-09-14_final.stac-item
2023-10-23 09:25:31	ga_ls9c_ard_3-2-1_091081_2023-10-22_final.stac-item
2023-11-09 11:47:12	ga_ls9c_ard_3-2-1_114080_2023-11-09_final.stac-item
2023-11-20 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-11-20_final.stac-item
2023-12-03 10:55:28	ga_ls9c_ard_3-2-1_106074_2023-12-03_final.stac-item
2023-12-09 10:19:56	ga_ls9c_ard_3-2-1_100078_2023-12-09_final.stac-item
2023-12-15 09:45:43	ga_ls9c_ard_3-2-1_094085_2023-12-15_final.stac-item
2023-12-26 09:28:25	ga_ls9c_ard_3-2-1_091088_2023-12-25_final.stac-item
2024-01-30 09:53:40	ga_ls9c_ard_3-2-1_096074_2024-01-30_final.stac-item
2024-02-25 10:30:58	ga_ls9c_ard_3-2-1_102075_2024-02-25_final.stac-item
2024-03-02 09:53:33	ga_ls9c_ard_3-2-1_096074_2024-03-02_final.stac-item
2024-03-07 11:52:11	ga_ls9c_ard_3-2-1_115077_2024-03-07_final.stac-item
2024-03-15 11:02:19	ga_ls9c_ard_3-2-1_107076_2024-03-15_final.stac-item
2024-03-22 09:33:11	ga_ls9c_ard_3-2-1_092085_2024-03-22_final.stac-item
2024-03-25 11:42:08	ga_ls9c_ard_3-2-1_113083_2024-03-25_final.stac-item
2024-04-05 11:20:42	ga_ls9c_ard_3-2-1_110076_2024-04-05_final.stac-item
2024-04-13 10:29:11	ga_ls9c_ard_3-2-1_102071_2024-04-13_final.stac-item
2024-04-18 09:13:56	ga_ls9c_ard_3-2-1_089084_2024-04-17_final.stac-item
2024-04-30 09:34:51	ga_ls9c_ard_3-2-1_093075_2024-04-30_final.stac-item
2024-05-13 10:41:11	ga_ls9c_ard_3-2-1_104071_2024-05-13_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