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

78 results

Time (local)	Label
2023-03-12 10:20:15	ga_ls9c_ard_3-2-1_100079_2023-03-12_final.stac-item
2023-03-13 09:26:37	ga_ls9c_ard_3-2-1_091084_2023-03-12_final.stac-item
2023-03-13 09:27:01	ga_ls9c_ard_3-2-1_091085_2023-03-12_final.stac-item
2023-03-13 11:02:19	ga_ls9c_ard_3-2-1_107076_2023-03-13_final.stac-item
2023-03-16 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-03-16_final.stac-item
2023-03-17 10:35:35	ga_ls9c_ard_3-2-1_103071_2023-03-17_final.stac-item
2023-03-18 09:40:46	ga_ls9c_ard_3-2-1_094073_2023-03-18_final.stac-item
2023-03-18 09:45:57	ga_ls9c_ard_3-2-1_094086_2023-03-18_final.stac-item
2023-03-18 11:19:15	ga_ls9c_ard_3-2-1_110072_2023-03-18_final.stac-item
2023-03-18 11:20:51	ga_ls9c_ard_3-2-1_110076_2023-03-18_final.stac-item
2023-03-19 10:24:49	ga_ls9c_ard_3-2-1_101075_2023-03-19_final.stac-item
2023-03-19 10:26:25	ga_ls9c_ard_3-2-1_101079_2023-03-19_final.stac-item
2023-03-19 10:26:49	ga_ls9c_ard_3-2-1_101080_2023-03-19_final.stac-item
2023-03-20 09:30:23	ga_ls9c_ard_3-2-1_092078_2023-03-20_final.stac-item
2023-03-20 09:32:47	ga_ls9c_ard_3-2-1_092084_2023-03-20_final.stac-item
2023-03-20 11:06:52	ga_ls9c_ard_3-2-1_108072_2023-03-20_final.stac-item
2023-03-20 11:09:16	ga_ls9c_ard_3-2-1_108078_2023-03-20_final.stac-item
2023-03-20 11:11:16	ga_ls9c_ard_3-2-1_108083_2023-03-20_final.stac-item
2023-03-21 10:11:14	ga_ls9c_ard_3-2-1_099072_2023-03-21_final.stac-item
2023-03-21 10:12:02	ga_ls9c_ard_3-2-1_099074_2023-03-21_final.stac-item
2023-03-21 10:12:26	ga_ls9c_ard_3-2-1_099075_2023-03-21_final.stac-item
2023-03-21 10:12:50	ga_ls9c_ard_3-2-1_099076_2023-03-21_final.stac-item
2023-03-21 10:14:02	ga_ls9c_ard_3-2-1_099079_2023-03-21_final.stac-item
2023-03-21 11:51:19	ga_ls9c_ard_3-2-1_115075_2023-03-21_final.stac-item
2023-03-21 11:52:07	ga_ls9c_ard_3-2-1_115077_2023-03-21_final.stac-item
2023-03-21 11:52:55	ga_ls9c_ard_3-2-1_115079_2023-03-21_final.stac-item
2023-03-22 09:17:36	ga_ls9c_ard_3-2-1_090077_2023-03-21_final.stac-item
2023-03-22 09:21:35	ga_ls9c_ard_3-2-1_090087_2023-03-21_final.stac-item
2023-03-22 10:52:54	ga_ls9c_ard_3-2-1_106068_2023-03-22_final.stac-item
2023-03-22 10:56:05	ga_ls9c_ard_3-2-1_106076_2023-03-22_final.stac-item
2023-03-22 10:56:29	ga_ls9c_ard_3-2-1_106077_2023-03-22_final.stac-item
2023-03-22 10:57:41	ga_ls9c_ard_3-2-1_106080_2023-03-22_final.stac-item
2023-03-22 10:58:05	ga_ls9c_ard_3-2-1_106081_2023-03-22_final.stac-item
2023-03-23 09:59:15	ga_ls9c_ard_3-2-1_097073_2023-03-23_final.stac-item
2023-03-23 09:59:39	ga_ls9c_ard_3-2-1_097074_2023-03-23_final.stac-item
2023-03-23 11:38:56	ga_ls9c_ard_3-2-1_113075_2023-03-23_final.stac-item
2023-03-24 09:06:25	ga_ls9c_ard_3-2-1_088080_2023-03-23_final.stac-item
2023-03-24 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-03-23_final.stac-item
2023-03-24 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-03-23_final.stac-item
2023-03-24 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-03-24_final.stac-item
2023-03-24 10:42:54	ga_ls9c_ard_3-2-1_104074_2023-03-24_final.stac-item
2023-03-24 10:45:17	ga_ls9c_ard_3-2-1_104080_2023-03-24_final.stac-item
2023-03-24 10:46:05	ga_ls9c_ard_3-2-1_104082_2023-03-24_final.stac-item
2023-04-18 10:34:30	ga_ls9c_ard_3-2-1_103069_2023-04-18_final.stac-item
2023-04-19 09:39:41	ga_ls9c_ard_3-2-1_094071_2023-04-19_final.stac-item
2023-04-19 09:40:05	ga_ls9c_ard_3-2-1_094072_2023-04-19_final.stac-item
2023-04-19 09:40:29	ga_ls9c_ard_3-2-1_094073_2023-04-19_final.stac-item
2023-04-19 09:40:52	ga_ls9c_ard_3-2-1_094074_2023-04-19_final.stac-item
2023-04-19 09:41:16	ga_ls9c_ard_3-2-1_094075_2023-04-19_final.stac-item
2023-04-19 09:41:40	ga_ls9c_ard_3-2-1_094076_2023-04-19_final.stac-item
2023-04-19 09:42:04	ga_ls9c_ard_3-2-1_094077_2023-04-19_final.stac-item
2023-04-19 09:42:28	ga_ls9c_ard_3-2-1_094078_2023-04-19_final.stac-item
2023-04-19 09:42:52	ga_ls9c_ard_3-2-1_094079_2023-04-19_final.stac-item
2023-04-19 09:43:16	ga_ls9c_ard_3-2-1_094080_2023-04-19_final.stac-item
2023-04-19 09:43:40	ga_ls9c_ard_3-2-1_094081_2023-04-19_final.stac-item
2023-04-19 09:44:04	ga_ls9c_ard_3-2-1_094082_2023-04-19_final.stac-item
2023-04-19 09:44:52	ga_ls9c_ard_3-2-1_094084_2023-04-19_final.stac-item
2023-04-19 09:45:16	ga_ls9c_ard_3-2-1_094085_2023-04-19_final.stac-item
2023-04-19 09:45:40	ga_ls9c_ard_3-2-1_094086_2023-04-19_final.stac-item
2023-04-19 09:46:04	ga_ls9c_ard_3-2-1_094087_2023-04-19_final.stac-item
2023-04-19 11:17:46	ga_ls9c_ard_3-2-1_110069_2023-04-19_final.stac-item
2023-04-19 11:18:10	ga_ls9c_ard_3-2-1_110070_2023-04-19_final.stac-item
2023-04-19 11:18:34	ga_ls9c_ard_3-2-1_110071_2023-04-19_final.stac-item
2023-04-19 11:19:22	ga_ls9c_ard_3-2-1_110073_2023-04-19_final.stac-item
2023-04-19 11:19:45	ga_ls9c_ard_3-2-1_110074_2023-04-19_final.stac-item
2023-04-19 11:20:09	ga_ls9c_ard_3-2-1_110075_2023-04-19_final.stac-item
2023-04-19 11:20:57	ga_ls9c_ard_3-2-1_110077_2023-04-19_final.stac-item
2023-04-19 11:21:21	ga_ls9c_ard_3-2-1_110078_2023-04-19_final.stac-item
2023-04-19 11:22:09	ga_ls9c_ard_3-2-1_110080_2023-04-19_final.stac-item
2023-04-19 11:22:33	ga_ls9c_ard_3-2-1_110081_2023-04-19_final.stac-item
2023-04-19 11:22:57	ga_ls9c_ard_3-2-1_110082_2023-04-19_final.stac-item
2023-04-19 11:23:21	ga_ls9c_ard_3-2-1_110083_2023-04-19_final.stac-item
2023-04-19 11:23:45	ga_ls9c_ard_3-2-1_110084_2023-04-19_final.stac-item
2023-04-19 11:24:09	ga_ls9c_ard_3-2-1_110085_2023-04-19_final.stac-item
2023-04-20 10:24:32	ga_ls9c_ard_3-2-1_101075_2023-04-20_final.stac-item
2023-04-20 10:25:20	ga_ls9c_ard_3-2-1_101077_2023-04-20_final.stac-item
2023-04-20 10:26:08	ga_ls9c_ard_3-2-1_101079_2023-04-20_final.stac-item
2023-04-21 09:28:54	ga_ls9c_ard_3-2-1_092075_2023-04-20_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