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

77 results

Time (local)	Label
2021-11-16 10:21:55	ga_ls9c_ard_3-2-1_100077_2021-11-16_final.stac-item
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2022-01-07 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-07_final.stac-item
2022-01-23 10:46:53	ga_ls9c_ard_3-2-1_105068_2022-01-23_final.stac-item
2022-01-28 09:28:56	ga_ls9c_ard_3-2-1_092074_2022-01-27_final.stac-item
2022-02-15 09:18:06	ga_ls9c_ard_3-2-1_090078_2022-02-14_final.stac-item
2022-02-24 10:49:30	ga_ls9c_ard_3-2-1_105075_2022-02-24_final.stac-item
2022-03-11 10:03:47	ga_ls9c_ard_3-2-1_098069_2022-03-11_final.stac-item
2022-03-22 11:25:40	ga_ls9c_ard_3-2-1_111073_2022-03-22_final.stac-item
2022-04-04 10:55:55	ga_ls9c_ard_3-2-1_106076_2022-04-04_final.stac-item
2022-04-21 09:56:32	ga_ls9c_ard_3-2-1_097067_2022-04-21_final.stac-item
2022-04-24 10:28:13	ga_ls9c_ard_3-2-1_102069_2022-04-24_final.stac-item
2022-05-05 10:13:14	ga_ls9c_ard_3-2-1_099078_2022-05-05_final.stac-item
2022-05-10 10:33:19	ga_ls9c_ard_3-2-1_102082_2022-05-10_final.stac-item
2022-05-13 09:22:30	ga_ls9c_ard_3-2-1_091075_2022-05-12_final.stac-item
2022-05-23 11:40:21	ga_ls9c_ard_3-2-1_113080_2022-05-23_final.stac-item
2022-07-14 11:17:07	ga_ls9c_ard_3-2-1_109083_2022-07-14_final.stac-item
2022-07-16 09:22:42	ga_ls9c_ard_3-2-1_091075_2022-07-15_final.stac-item
2022-07-30 09:33:41	ga_ls9c_ard_3-2-1_093071_2022-07-30_final.stac-item
2022-08-04 11:32:22	ga_ls9c_ard_3-2-1_112074_2022-08-04_final.stac-item
2022-09-13 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-09-12_final.stac-item
2022-09-19 10:10:03	ga_ls9c_ard_3-2-1_098084_2022-09-19_final.stac-item
2022-10-04 09:22:50	ga_ls9c_ard_3-2-1_091074_2022-10-03_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-16 10:40:54	ga_ls9c_ard_3-2-1_104068_2022-11-16_final.stac-item
2022-11-16 10:42:06	ga_ls9c_ard_3-2-1_104071_2022-11-16_final.stac-item
2022-12-07 09:22:55	ga_ls9c_ard_3-2-1_091074_2022-12-06_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_nrt.stac-item
2022-12-21 11:16:56	ga_ls9c_ard_3-2-1_109081_2022-12-21_final.stac-item
2023-01-15 11:05:56	ga_ls9c_ard_3-2-1_108069_2023-01-15_final.stac-item
2023-01-22 09:33:57	ga_ls9c_ard_3-2-1_093071_2023-01-22_final.stac-item
2023-01-29 09:41:27	ga_ls9c_ard_3-2-1_094074_2023-01-29_final.stac-item
2023-02-03 09:58:27	ga_ls9c_ard_3-2-1_097070_2023-02-03_final.stac-item
2023-02-24 10:19:34	ga_ls9c_ard_3-2-1_100077_2023-02-24_final.stac-item
2023-03-06 09:17:42	ga_ls9c_ard_3-2-1_090077_2023-03-05_final.stac-item
2023-03-25 09:46:27	ga_ls9c_ard_3-2-1_095072_2023-03-25_final.stac-item
2023-03-25 11:24:33	ga_ls9c_ard_3-2-1_111070_2023-03-25_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-03-29 11:04:55	ga_ls9c_ard_3-2-1_107083_2023-03-29_final.stac-item
2023-04-11 10:28:46	ga_ls9c_ard_3-2-1_102070_2023-04-11_final.stac-item
2023-04-13 10:19:34	ga_ls9c_ard_3-2-1_100078_2023-04-13_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-04-14 09:22:20	ga_ls9c_ard_3-2-1_091074_2023-04-13_final.stac-item
2023-05-07 09:33:06	ga_ls9c_ard_3-2-1_092086_2023-05-07_final.stac-item
2023-05-12 11:24:08	ga_ls9c_ard_3-2-1_111070_2023-05-12_final.stac-item
2023-05-23 11:07:03	ga_ls9c_ard_3-2-1_108074_2023-05-23_final.stac-item
2023-05-25 09:16:58	ga_ls9c_ard_3-2-1_090077_2023-05-24_final.stac-item
2023-06-05 10:35:18	ga_ls9c_ard_3-2-1_103072_2023-06-05_final.stac-item
2023-06-06 09:45:39	ga_ls9c_ard_3-2-1_094087_2023-06-06_final.stac-item
2023-06-06 11:19:45	ga_ls9c_ard_3-2-1_110075_2023-06-06_final.stac-item
2023-06-12 10:41:48	ga_ls9c_ard_3-2-1_104073_2023-06-12_final.stac-item
2023-06-20 09:57:30	ga_ls9c_ard_3-2-1_096086_2023-06-20_final.stac-item
2023-07-09 10:24:39	ga_ls9c_ard_3-2-1_101076_2023-07-09_final.stac-item
2023-07-15 11:25:17	ga_ls9c_ard_3-2-1_111073_2023-07-15_final.stac-item
2023-08-18 09:34:12	ga_ls9c_ard_3-2-1_093073_2023-08-18_final.stac-item
2023-08-23 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-08-23_final.stac-item
2023-08-29 09:16:37	ga_ls9c_ard_3-2-1_090075_2023-08-28_final.stac-item
2023-09-03 09:34:00	ga_ls9c_ard_3-2-1_093072_2023-09-03_final.stac-item
2023-09-06 10:06:56	ga_ls9c_ard_3-2-1_098077_2023-09-06_final.stac-item
2023-09-10 11:20:21	ga_ls9c_ard_3-2-1_110075_2023-09-10_final.stac-item
2023-09-13 10:10:48	ga_ls9c_ard_3-2-1_099071_2023-09-13_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-10-31 10:10:05	ga_ls9c_ard_3-2-1_099069_2023-10-31_final.stac-item
2023-11-12 10:35:14	ga_ls9c_ard_3-2-1_103070_2023-11-12_final.stac-item
2023-11-24 09:27:58	ga_ls9c_ard_3-2-1_091087_2023-11-23_final.stac-item
2024-01-13 09:16:23	ga_ls9c_ard_3-2-1_089089_2024-01-12_final.stac-item
2024-01-16 11:18:59	ga_ls9c_ard_3-2-1_110071_2024-01-16_final.stac-item
2024-01-16 11:20:35	ga_ls9c_ard_3-2-1_110075_2024-01-16_final.stac-item
2024-01-20 09:20:57	ga_ls9c_ard_3-2-1_090085_2024-01-19_final.stac-item
2024-01-31 10:34:32	ga_ls9c_ard_3-2-1_103068_2024-01-31_final.stac-item
2024-02-04 10:10:38	ga_ls9c_ard_3-2-1_099070_2024-02-04_final.stac-item
2024-02-08 09:47:07	ga_ls9c_ard_3-2-1_095073_2024-02-08_final.stac-item
2024-03-20 11:18:27	ga_ls9c_ard_3-2-1_110070_2024-03-20_final.stac-item
2024-04-27 09:07:09	ga_ls9c_ard_3-2-1_088083_2024-04-26_final.stac-item
2024-05-03 10:06:56	ga_ls9c_ard_3-2-1_098078_2024-05-03_final.stac-item
2024-05-05 09:57:46	ga_ls9c_ard_3-2-1_096086_2024-05-05_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