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

76 results

Time (local)	Label
2023-02-11 10:47:55	ga_ls9c_ard_3-2-1_105070_2023-02-11_final.stac-item
2023-02-12 09:52:17	ga_ls9c_ard_3-2-1_096070_2023-02-12_final.stac-item
2023-02-12 09:53:05	ga_ls9c_ard_3-2-1_096072_2023-02-12_final.stac-item
2023-02-12 09:55:52	ga_ls9c_ard_3-2-1_096079_2023-02-12_final.stac-item
2023-02-12 09:56:16	ga_ls9c_ard_3-2-1_096080_2023-02-12_final.stac-item
2023-02-12 11:32:46	ga_ls9c_ard_3-2-1_112074_2023-02-12_final.stac-item
2023-02-12 11:35:09	ga_ls9c_ard_3-2-1_112080_2023-02-12_final.stac-item
2023-02-12 11:36:21	ga_ls9c_ard_3-2-1_112083_2023-02-12_final.stac-item
2023-02-12 11:36:45	ga_ls9c_ard_3-2-1_112084_2023-02-12_final.stac-item
2023-02-13 10:35:32	ga_ls9c_ard_3-2-1_103070_2023-02-13_final.stac-item
2023-02-13 10:39:31	ga_ls9c_ard_3-2-1_103080_2023-02-13_final.stac-item
2023-02-14 09:41:54	ga_ls9c_ard_3-2-1_094075_2023-02-14_final.stac-item
2023-02-14 09:45:29	ga_ls9c_ard_3-2-1_094084_2023-02-14_final.stac-item
2023-02-14 09:46:17	ga_ls9c_ard_3-2-1_094086_2023-02-14_final.stac-item
2023-02-14 11:19:59	ga_ls9c_ard_3-2-1_110073_2023-02-14_final.stac-item
2023-02-14 11:20:23	ga_ls9c_ard_3-2-1_110074_2023-02-14_final.stac-item
2023-02-14 11:21:35	ga_ls9c_ard_3-2-1_110077_2023-02-14_final.stac-item
2023-02-14 11:23:58	ga_ls9c_ard_3-2-1_110083_2023-02-14_final.stac-item
2023-02-15 10:23:09	ga_ls9c_ard_3-2-1_101070_2023-02-15_final.stac-item
2023-02-16 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-02-16_final.stac-item
2023-02-16 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-02-16_final.stac-item
2023-02-16 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-02-16_final.stac-item
2023-02-16 11:07:59	ga_ls9c_ard_3-2-1_108074_2023-02-16_final.stac-item
2023-02-16 11:08:23	ga_ls9c_ard_3-2-1_108075_2023-02-16_final.stac-item
2023-02-16 11:09:59	ga_ls9c_ard_3-2-1_108079_2023-02-16_final.stac-item
2023-02-16 11:10:23	ga_ls9c_ard_3-2-1_108080_2023-02-16_final.stac-item
2023-02-16 11:10:47	ga_ls9c_ard_3-2-1_108081_2023-02-16_final.stac-item
2023-02-16 11:11:11	ga_ls9c_ard_3-2-1_108082_2023-02-16_final.stac-item
2023-02-16 11:11:59	ga_ls9c_ard_3-2-1_108084_2023-02-16_final.stac-item
2023-02-17 10:11:09	ga_ls9c_ard_3-2-1_099071_2023-02-17_final.stac-item
2023-02-17 10:12:21	ga_ls9c_ard_3-2-1_099074_2023-02-17_final.stac-item
2023-02-17 10:13:33	ga_ls9c_ard_3-2-1_099077_2023-02-17_final.stac-item
2023-02-17 10:13:57	ga_ls9c_ard_3-2-1_099078_2023-02-17_final.stac-item
2023-02-17 10:14:45	ga_ls9c_ard_3-2-1_099080_2023-02-17_final.stac-item
2023-02-17 11:52:02	ga_ls9c_ard_3-2-1_115076_2023-02-17_final.stac-item
2023-02-17 11:52:26	ga_ls9c_ard_3-2-1_115077_2023-02-17_final.stac-item
2023-02-17 11:52:50	ga_ls9c_ard_3-2-1_115078_2023-02-17_final.stac-item
2023-02-17 11:53:38	ga_ls9c_ard_3-2-1_115080_2023-02-17_final.stac-item
2023-02-18 09:18:18	ga_ls9c_ard_3-2-1_090078_2023-02-17_final.stac-item
2023-02-18 09:20:42	ga_ls9c_ard_3-2-1_090084_2023-02-17_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-02-18 09:21:54	ga_ls9c_ard_3-2-1_090087_2023-02-17_final.stac-item
2023-02-18 09:23:06	ga_ls9c_ard_3-2-1_090090_2023-02-17_final.stac-item
2023-02-18 10:54:00	ga_ls9c_ard_3-2-1_106070_2023-02-18_final.stac-item
2023-02-18 10:54:48	ga_ls9c_ard_3-2-1_106072_2023-02-18_final.stac-item
2023-02-18 10:56:47	ga_ls9c_ard_3-2-1_106077_2023-02-18_final.stac-item
2023-02-18 10:57:59	ga_ls9c_ard_3-2-1_106080_2023-02-18_final.stac-item
2023-02-18 10:58:23	ga_ls9c_ard_3-2-1_106081_2023-02-18_final.stac-item
2023-02-18 10:58:47	ga_ls9c_ard_3-2-1_106082_2023-02-18_final.stac-item
2023-02-19 09:57:09	ga_ls9c_ard_3-2-1_097067_2023-02-19_final.stac-item
2023-02-19 09:58:45	ga_ls9c_ard_3-2-1_097071_2023-02-19_final.stac-item
2023-02-19 09:59:57	ga_ls9c_ard_3-2-1_097074_2023-02-19_final.stac-item
2023-02-19 10:00:21	ga_ls9c_ard_3-2-1_097075_2023-02-19_final.stac-item
2023-02-19 10:01:33	ga_ls9c_ard_3-2-1_097078_2023-02-19_final.stac-item
2023-02-19 10:02:44	ga_ls9c_ard_3-2-1_097081_2023-02-19_final.stac-item
2023-02-19 10:03:08	ga_ls9c_ard_3-2-1_097082_2023-02-19_final.stac-item
2023-02-19 11:38:02	ga_ls9c_ard_3-2-1_113072_2023-02-19_final.stac-item
2023-02-19 11:40:49	ga_ls9c_ard_3-2-1_113079_2023-02-19_final.stac-item
2023-02-19 11:41:37	ga_ls9c_ard_3-2-1_113081_2023-02-19_final.stac-item
2023-02-20 09:07:54	ga_ls9c_ard_3-2-1_088083_2023-02-19_final.stac-item
2023-02-20 10:40:47	ga_ls9c_ard_3-2-1_104068_2023-02-20_final.stac-item
2023-02-20 10:41:59	ga_ls9c_ard_3-2-1_104071_2023-02-20_final.stac-item
2023-02-20 10:43:11	ga_ls9c_ard_3-2-1_104074_2023-02-20_final.stac-item
2023-02-20 10:44:47	ga_ls9c_ard_3-2-1_104078_2023-02-20_final.stac-item
2023-02-20 10:45:35	ga_ls9c_ard_3-2-1_104080_2023-02-20_final.stac-item
2023-02-21 09:50:20	ga_ls9c_ard_3-2-1_095081_2023-02-21_final.stac-item
2023-02-21 09:52:20	ga_ls9c_ard_3-2-1_095086_2023-02-21_final.stac-item
2023-02-21 11:26:49	ga_ls9c_ard_3-2-1_111075_2023-02-21_final.stac-item
2023-02-21 11:28:25	ga_ls9c_ard_3-2-1_111079_2023-02-21_final.stac-item
2023-02-21 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-02-21_final.stac-item
2023-02-21 11:30:01	ga_ls9c_ard_3-2-1_111083_2023-02-21_final.stac-item
2023-02-22 10:28:23	ga_ls9c_ard_3-2-1_102068_2023-02-22_final.stac-item
2023-02-22 10:29:11	ga_ls9c_ard_3-2-1_102070_2023-02-22_final.stac-item
2023-02-22 10:31:10	ga_ls9c_ard_3-2-1_102075_2023-02-22_final.stac-item
2023-02-22 10:33:10	ga_ls9c_ard_3-2-1_102080_2023-02-22_final.stac-item
2023-02-22 10:33:58	ga_ls9c_ard_3-2-1_102082_2023-02-22_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