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

57 results

Time (local)	Label
2021-11-09 10:37:48	ga_ls9c_ard_3-2-1_103076_2021-11-09_final.stac-item
2021-11-17 09:21:17	ga_ls9c_ard_3-2-1_091072_2021-11-16_final.stac-item
2021-12-04 09:29:17	ga_ls9c_ard_3-2-1_091090_2021-12-03_final.stac-item
2022-02-07 10:08:00	ga_ls9c_ard_3-2-1_098079_2022-02-07_final.stac-item
2022-02-15 10:53:47	ga_ls9c_ard_3-2-1_106070_2022-02-15_final.stac-item
2022-03-10 11:05:23	ga_ls9c_ard_3-2-1_107084_2022-03-10_final.stac-item
2022-04-09 09:38:21	ga_ls9c_ard_3-2-1_093083_2022-04-09_final.stac-item
2022-04-26 10:20:39	ga_ls9c_ard_3-2-1_100081_2022-04-26_final.stac-item
2022-06-10 11:25:38	ga_ls9c_ard_3-2-1_111074_2022-06-10_final.stac-item
2022-07-15 10:17:54	ga_ls9c_ard_3-2-1_100074_2022-07-15_final.stac-item
2022-08-04 11:35:57	ga_ls9c_ard_3-2-1_112083_2022-08-04_final.stac-item
2022-08-08 11:05:41	ga_ls9c_ard_3-2-1_108069_2022-08-08_final.stac-item
2022-09-14 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-09-14_final.stac-item
2022-10-14 09:57:12	ga_ls9c_ard_3-2-1_097067_2022-10-14_final.stac-item
2022-11-02 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-11-02_final.stac-item
2022-12-19 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-12-19_final.stac-item
2023-01-08 09:27:19	ga_ls9c_ard_3-2-1_091085_2023-01-07_final.stac-item
2023-01-10 09:13:21	ga_ls9c_ard_3-2-1_089081_2023-01-09_final.stac-item
2023-01-19 09:07:27	ga_ls9c_ard_3-2-1_088082_2023-01-18_final.stac-item
2023-02-26 11:46:29	ga_ls9c_ard_3-2-1_114078_2023-02-26_final.stac-item
2023-04-23 10:53:25	ga_ls9c_ard_3-2-1_106070_2023-04-23_final.stac-item
2023-05-16 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-05-15_final.stac-item
2023-05-17 10:04:56	ga_ls9c_ard_3-2-1_098073_2023-05-17_final.stac-item
2023-05-17 10:06:56	ga_ls9c_ard_3-2-1_098078_2023-05-17_final.stac-item
2023-05-29 10:29:32	ga_ls9c_ard_3-2-1_102073_2023-05-29_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-18 10:02:40	ga_ls9c_ard_3-2-1_098068_2023-06-18_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-14 10:42:01	ga_ls9c_ard_3-2-1_104073_2023-07-14_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-27 11:50:25	ga_ls9c_ard_3-2-1_115074_2023-07-27_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_2023-07-27_final.stac-item
2023-07-29 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-07-29_final.stac-item
2023-08-04 09:26:36	ga_ls9c_ard_3-2-1_091085_2023-08-03_final.stac-item
2023-08-05 10:02:42	ga_ls9c_ard_3-2-1_098067_2023-08-05_final.stac-item
2023-08-05 10:09:53	ga_ls9c_ard_3-2-1_098085_2023-08-05_final.stac-item
2023-08-13 09:21:40	ga_ls9c_ard_3-2-1_090088_2023-08-12_final.stac-item
2023-08-13 10:55:21	ga_ls9c_ard_3-2-1_106075_2023-08-13_final.stac-item
2023-08-29 10:55:30	ga_ls9c_ard_3-2-1_106075_2023-08-29_final.stac-item
2023-09-11 10:27:56	ga_ls9c_ard_3-2-1_101083_2023-09-11_final.stac-item
2023-09-19 09:39:43	ga_ls9c_ard_3-2-1_093086_2023-09-19_final.stac-item
2023-09-21 09:23:21	ga_ls9c_ard_3-2-1_091076_2023-09-20_interim.stac-item
2023-10-07 11:00:17	ga_ls9c_ard_3-2-1_107071_2023-10-07_final.stac-item
2023-10-08 10:07:28	ga_ls9c_ard_3-2-1_098078_2023-10-08_final.stac-item
2023-10-12 11:19:42	ga_ls9c_ard_3-2-1_110073_2023-10-12_final.stac-item
2023-11-28 10:40:09	ga_ls9c_ard_3-2-1_103082_2023-11-28_final.stac-item
2023-12-06 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-12-06_final.stac-item
2023-12-06 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-12-06_final.stac-item
2023-12-12 09:14:47	ga_ls9c_ard_3-2-1_089085_2023-12-11_final.stac-item
2024-01-01 10:24:10	ga_ls9c_ard_3-2-1_101073_2024-01-01_final.stac-item
2024-01-02 09:29:44	ga_ls9c_ard_3-2-1_092076_2024-01-01_final.stac-item
2024-01-02 09:34:08	ga_ls9c_ard_3-2-1_092087_2024-01-02_final.stac-item
2024-01-03 10:09:24	ga_ls9c_ard_3-2-1_099067_2024-01-03_final.stac-item
2024-02-06 09:58:41	ga_ls9c_ard_3-2-1_097071_2024-02-06_final.stac-item
2024-02-19 11:07:19	ga_ls9c_ard_3-2-1_108073_2024-02-19_final.stac-item
2024-02-26 09:39:21	ga_ls9c_ard_3-2-1_093085_2024-02-26_final.stac-item
2024-04-03 11:35:28	ga_ls9c_ard_3-2-1_112082_2024-04-03_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