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

64 results

Time (local)	Label
2021-12-19 10:17:35	ga_ls9c_ard_3-2-1_100072_2021-12-19_final.stac-item
2022-01-12 09:29:18	ga_ls9c_ard_3-2-1_092075_2022-01-11_final.stac-item
2022-01-31 11:38:43	ga_ls9c_ard_3-2-1_113074_2022-01-31_final.stac-item
2022-02-18 09:47:46	ga_ls9c_ard_3-2-1_095075_2022-02-18_final.stac-item
2022-02-20 09:40:11	ga_ls9c_ard_3-2-1_093087_2022-02-20_final.stac-item
2022-03-19 10:55:11	ga_ls9c_ard_3-2-1_106074_2022-03-19_final.stac-item
2022-03-23 10:32:50	ga_ls9c_ard_3-2-1_102080_2022-03-23_final.stac-item
2022-04-02 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-04-01_final.stac-item
2022-04-02 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-04-02_final.stac-item
2022-04-19 10:15:42	ga_ls9c_ard_3-2-1_099084_2022-04-19_final.stac-item
2022-04-19 11:51:24	ga_ls9c_ard_3-2-1_115076_2022-04-19_final.stac-item
2022-05-10 10:29:43	ga_ls9c_ard_3-2-1_102073_2022-05-10_final.stac-item
2022-05-28 10:17:13	ga_ls9c_ard_3-2-1_100073_2022-05-28_final.stac-item
2022-07-02 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-07-01_final.stac-item
2022-07-08 10:14:57	ga_ls9c_ard_3-2-1_099082_2022-07-08_final.stac-item
2022-07-23 11:11:05	ga_ls9c_ard_3-2-1_108083_2022-07-23_final.stac-item
2022-08-01 11:01:26	ga_ls9c_ard_3-2-1_107074_2022-08-01_final.stac-item
2022-09-10 10:11:21	ga_ls9c_ard_3-2-1_099072_2022-09-10_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-10-05 11:44:59	ga_ls9c_ard_3-2-1_114074_2022-10-05_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-11-30 10:56:00	ga_ls9c_ard_3-2-1_106075_2022-11-30_final.stac-item
2022-12-12 09:41:28	ga_ls9c_ard_3-2-1_094074_2022-12-12_final.stac-item
2022-12-14 09:28:19	ga_ls9c_ard_3-2-1_092072_2022-12-13_final.stac-item
2022-12-19 09:48:50	ga_ls9c_ard_3-2-1_095077_2022-12-19_final.stac-item
2022-12-21 09:40:27	ga_ls9c_ard_3-2-1_093087_2022-12-21_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2022-12-25 09:14:07	ga_ls9c_ard_3-2-1_089083_2022-12-24_final.stac-item
2023-01-31 11:08:48	ga_ls9c_ard_3-2-1_108076_2023-01-31_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-01 11:53:16	ga_ls9c_ard_3-2-1_115079_2023-02-01_final.stac-item
2023-03-13 09:21:50	ga_ls9c_ard_3-2-1_091072_2023-03-12_final.stac-item
2023-03-14 10:03:54	ga_ls9c_ard_3-2-1_098069_2023-03-14_final.stac-item
2023-03-15 09:11:28	ga_ls9c_ard_3-2-1_089077_2023-03-14_final.stac-item
2023-03-29 11:04:55	ga_ls9c_ard_3-2-1_107083_2023-03-29_final.stac-item
2023-04-12 09:39:55	ga_ls9c_ard_3-2-1_093087_2023-04-12_final.stac-item
2023-04-26 11:26:17	ga_ls9c_ard_3-2-1_111075_2023-04-26_final.stac-item
2023-05-01 10:07:27	ga_ls9c_ard_3-2-1_098079_2023-05-01_final.stac-item
2023-05-24 10:09:48	ga_ls9c_ard_3-2-1_099070_2023-05-24_final.stac-item
2023-05-24 10:10:12	ga_ls9c_ard_3-2-1_099071_2023-05-24_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-08-05 10:03:05	ga_ls9c_ard_3-2-1_098068_2023-08-05_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-14 10:00:56	ga_ls9c_ard_3-2-1_097078_2023-08-14_final.stac-item
2023-08-23 09:58:01	ga_ls9c_ard_3-2-1_096086_2023-08-23_final.stac-item
2023-09-05 09:22:28	ga_ls9c_ard_3-2-1_091074_2023-09-04_final.stac-item
2023-09-28 09:33:02	ga_ls9c_ard_3-2-1_092085_2023-09-28_final.stac-item
2023-10-07 09:22:36	ga_ls9c_ard_3-2-1_091074_2023-10-06_final.stac-item
2023-10-13 10:25:17	ga_ls9c_ard_3-2-1_101076_2023-10-13_final.stac-item
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final.stac-item
2023-11-15 09:28:02	ga_ls9c_ard_3-2-1_092072_2023-11-14_final.stac-item
2023-11-16 10:11:18	ga_ls9c_ard_3-2-1_099072_2023-11-16_final.stac-item
2023-11-17 09:21:17	ga_ls9c_ard_3-2-1_090086_2023-11-16_final.stac-item
2024-01-09 11:17:10	ga_ls9c_ard_3-2-1_109082_2024-01-09_final.stac-item
2024-02-20 10:10:52	ga_ls9c_ard_3-2-1_099071_2024-02-20_final.stac-item
2024-02-26 09:35:21	ga_ls9c_ard_3-2-1_093075_2024-02-26_final.stac-item
2024-03-11 09:52:34	ga_ls9c_ard_3-2-1_095087_2024-03-11_final.stac-item
2024-03-26 10:40:30	ga_ls9c_ard_3-2-1_104068_2024-03-26_final.stac-item
2024-03-30 10:21:18	ga_ls9c_ard_3-2-1_100082_2024-03-30_final.stac-item
2024-04-07 11:06:44	ga_ls9c_ard_3-2-1_108072_2024-04-07_final.stac-item
2024-04-21 11:18:50	ga_ls9c_ard_3-2-1_110072_2024-04-21_final.stac-item
2024-05-01 10:21:18	ga_ls9c_ard_3-2-1_100083_2024-05-01_final.stac-item
2024-05-20 09:10:47	ga_ls9c_ard_3-2-1_089077_2024-05-19_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