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

48 results

Time (local)	Label
2021-11-10 09:37:06	ga_ls9c_ard_3-2-1_094071_2021-11-10_final.stac-item
2021-12-27 09:28:09	ga_ls9c_ard_3-2-1_092072_2021-12-26_final.stac-item
2022-01-01 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-01-01_final.stac-item
2022-01-15 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-01-15_final.stac-item
2022-03-01 09:29:05	ga_ls9c_ard_3-2-1_092075_2022-02-28_final.stac-item
2022-04-03 10:09:28	ga_ls9c_ard_3-2-1_099068_2022-04-03_final.stac-item
2022-04-05 11:37:35	ga_ls9c_ard_3-2-1_113072_2022-04-05_final.stac-item
2022-06-12 09:39:12	ga_ls9c_ard_3-2-1_093086_2022-06-12_final.stac-item
2022-07-26 09:57:09	ga_ls9c_ard_3-2-1_097068_2022-07-26_final.stac-item
2022-08-24 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-08-23_final.stac-item
2022-10-11 09:33:27	ga_ls9c_ard_3-2-1_092085_2022-10-11_final.stac-item
2022-10-27 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-10-26_final.stac-item
2022-11-15 11:38:07	ga_ls9c_ard_3-2-1_113072_2022-11-15_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-12-21 11:18:08	ga_ls9c_ard_3-2-1_109084_2022-12-21_final.stac-item
2023-01-17 10:54:20	ga_ls9c_ard_3-2-1_106071_2023-01-17_final.stac-item
2023-01-20 11:25:34	ga_ls9c_ard_3-2-1_111072_2023-01-20_final.stac-item
2023-01-23 10:17:38	ga_ls9c_ard_3-2-1_100072_2023-01-23_final.stac-item
2023-01-24 11:02:07	ga_ls9c_ard_3-2-1_107075_2023-01-24_final.stac-item
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-20 09:06:42	ga_ls9c_ard_3-2-1_088080_2023-02-19_final.stac-item
2023-03-18 11:20:03	ga_ls9c_ard_3-2-1_110074_2023-03-18_final.stac-item
2023-04-05 11:07:54	ga_ls9c_ard_3-2-1_108075_2023-04-05_final.stac-item
2023-05-02 09:10:13	ga_ls9c_ard_3-2-1_089075_2023-05-01_final.stac-item
2023-05-09 09:16:45	ga_ls9c_ard_3-2-1_090076_2023-05-08_final.stac-item
2023-05-16 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-05-15_final.stac-item
2023-05-22 10:27:24	ga_ls9c_ard_3-2-1_101083_2023-05-22_final.stac-item
2023-06-03 10:48:28	ga_ls9c_ard_3-2-1_105074_2023-06-03_final.stac-item
2023-06-08 09:32:28	ga_ls9c_ard_3-2-1_092085_2023-06-08_final.stac-item
2023-06-18 11:46:21	ga_ls9c_ard_3-2-1_114080_2023-06-18_final.stac-item
2023-06-24 09:27:59	ga_ls9c_ard_3-2-1_092074_2023-06-23_final.stac-item
2023-08-12 10:15:17	ga_ls9c_ard_3-2-1_099083_2023-08-12_final.stac-item
2023-08-23 11:32:07	ga_ls9c_ard_3-2-1_112074_2023-08-23_final.stac-item
2023-09-19 11:13:48	ga_ls9c_ard_3-2-1_109074_2023-09-19_final.stac-item
2023-10-27 10:36:04	ga_ls9c_ard_3-2-1_103072_2023-10-27_final.stac-item
2023-10-31 10:10:53	ga_ls9c_ard_3-2-1_099071_2023-10-31_final.stac-item
2023-11-08 09:23:51	ga_ls9c_ard_3-2-1_091077_2023-11-07_final.stac-item
2023-11-29 09:40:32	ga_ls9c_ard_3-2-1_094072_2023-11-29_final.stac-item
2023-12-09 10:19:32	ga_ls9c_ard_3-2-1_100077_2023-12-09_final.stac-item
2023-12-19 10:55:55	ga_ls9c_ard_3-2-1_106075_2023-12-19_final.stac-item
2023-12-24 09:34:47	ga_ls9c_ard_3-2-1_093073_2023-12-24_final.stac-item
2023-12-31 11:18:37	ga_ls9c_ard_3-2-1_110070_2023-12-31_final.stac-item
2024-02-02 10:27:47	ga_ls9c_ard_3-2-1_101082_2024-02-02_final.stac-item
2024-02-06 09:58:41	ga_ls9c_ard_3-2-1_097071_2024-02-06_final.stac-item
2024-02-21 10:53:18	ga_ls9c_ard_3-2-1_106069_2024-02-21_final.stac-item
2024-03-24 09:17:12	ga_ls9c_ard_3-2-1_090076_2024-03-23_final.stac-item
2024-04-28 11:25:43	ga_ls9c_ard_3-2-1_111074_2024-04-28_final.stac-item
2024-05-21 09:56:26	ga_ls9c_ard_3-2-1_096083_2024-05-21_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