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

First 100 results (query limit)

Time (local)	Label
2023-09-04 10:18:28	ga_ls9c_ard_3-2-1_100075_2023-09-04_final.stac-item
2023-09-04 10:18:52	ga_ls9c_ard_3-2-1_100076_2023-09-04_final.stac-item
2023-09-04 10:19:16	ga_ls9c_ard_3-2-1_100077_2023-09-04_final.stac-item
2023-09-04 10:19:40	ga_ls9c_ard_3-2-1_100078_2023-09-04_final.stac-item
2023-09-04 10:20:04	ga_ls9c_ard_3-2-1_100079_2023-09-04_final.stac-item
2023-09-04 10:20:28	ga_ls9c_ard_3-2-1_100080_2023-09-04_final.stac-item
2023-09-04 10:20:52	ga_ls9c_ard_3-2-1_100081_2023-09-04_final.stac-item
2023-09-04 10:21:16	ga_ls9c_ard_3-2-1_100082_2023-09-04_final.stac-item
2023-09-04 10:21:40	ga_ls9c_ard_3-2-1_100083_2023-09-04_final.stac-item
2023-09-04 10:22:04	ga_ls9c_ard_3-2-1_100084_2023-09-04_final.stac-item
2023-09-06 10:09:20	ga_ls9c_ard_3-2-1_098083_2023-09-06_final.stac-item
2023-09-06 10:09:44	ga_ls9c_ard_3-2-1_098084_2023-09-06_final.stac-item
2023-09-06 10:10:08	ga_ls9c_ard_3-2-1_098085_2023-09-06_final.stac-item
2023-09-07 10:46:13	ga_ls9c_ard_3-2-1_105067_2023-09-07_final.stac-item
2023-09-07 10:46:37	ga_ls9c_ard_3-2-1_105068_2023-09-07_final.stac-item
2023-09-09 10:34:17	ga_ls9c_ard_3-2-1_103068_2023-09-09_final.stac-item
2023-09-09 10:34:41	ga_ls9c_ard_3-2-1_103069_2023-09-09_final.stac-item
2023-09-09 10:35:05	ga_ls9c_ard_3-2-1_103070_2023-09-09_final.stac-item
2023-09-09 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-09_final.stac-item
2023-09-09 10:35:53	ga_ls9c_ard_3-2-1_103072_2023-09-09_final.stac-item
2023-09-09 10:36:17	ga_ls9c_ard_3-2-1_103073_2023-09-09_final.stac-item
2023-09-09 10:36:41	ga_ls9c_ard_3-2-1_103074_2023-09-09_final.stac-item
2023-09-09 10:37:05	ga_ls9c_ard_3-2-1_103075_2023-09-09_final.stac-item
2023-09-09 10:37:29	ga_ls9c_ard_3-2-1_103076_2023-09-09_final.stac-item
2023-09-09 10:37:53	ga_ls9c_ard_3-2-1_103077_2023-09-09_final.stac-item
2023-09-11 10:22:45	ga_ls9c_ard_3-2-1_101070_2023-09-11_final.stac-item
2023-09-11 10:23:08	ga_ls9c_ard_3-2-1_101071_2023-09-11_final.stac-item
2023-09-11 10:23:32	ga_ls9c_ard_3-2-1_101072_2023-09-11_final.stac-item
2023-09-11 10:23:56	ga_ls9c_ard_3-2-1_101073_2023-09-11_final.stac-item
2023-09-11 10:24:20	ga_ls9c_ard_3-2-1_101074_2023-09-11_final.stac-item
2023-09-11 10:24:44	ga_ls9c_ard_3-2-1_101075_2023-09-11_final.stac-item
2023-09-11 10:25:08	ga_ls9c_ard_3-2-1_101076_2023-09-11_final.stac-item
2023-09-11 10:25:32	ga_ls9c_ard_3-2-1_101077_2023-09-11_final.stac-item
2023-09-11 10:25:56	ga_ls9c_ard_3-2-1_101078_2023-09-11_final.stac-item
2023-09-11 10:26:20	ga_ls9c_ard_3-2-1_101079_2023-09-11_final.stac-item
2023-09-11 10:26:44	ga_ls9c_ard_3-2-1_101080_2023-09-11_final.stac-item
2023-09-11 10:27:08	ga_ls9c_ard_3-2-1_101081_2023-09-11_final.stac-item
2023-09-11 10:27:32	ga_ls9c_ard_3-2-1_101082_2023-09-11_final.stac-item
2023-09-11 10:27:56	ga_ls9c_ard_3-2-1_101083_2023-09-11_final.stac-item
2023-09-13 10:13:59	ga_ls9c_ard_3-2-1_099079_2023-09-13_final.stac-item
2023-09-13 10:14:23	ga_ls9c_ard_3-2-1_099080_2023-09-13_final.stac-item
2023-09-13 10:14:47	ga_ls9c_ard_3-2-1_099081_2023-09-13_final.stac-item
2023-09-13 10:15:11	ga_ls9c_ard_3-2-1_099082_2023-09-13_final.stac-item
2023-09-13 10:15:35	ga_ls9c_ard_3-2-1_099083_2023-09-13_final.stac-item
2023-09-13 10:15:59	ga_ls9c_ard_3-2-1_099084_2023-09-13_final.stac-item
2023-09-13 10:16:23	ga_ls9c_ard_3-2-1_099085_2023-09-13_final.stac-item
2023-09-16 10:40:31	ga_ls9c_ard_3-2-1_104068_2023-09-16_final.stac-item
2023-09-16 10:40:55	ga_ls9c_ard_3-2-1_104069_2023-09-16_final.stac-item
2023-09-16 10:41:18	ga_ls9c_ard_3-2-1_104070_2023-09-16_final.stac-item
2023-09-16 10:41:42	ga_ls9c_ard_3-2-1_104071_2023-09-16_final.stac-item
2023-09-16 10:42:06	ga_ls9c_ard_3-2-1_104072_2023-09-16_final.stac-item
2023-09-16 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-09-16_final.stac-item
2023-09-18 10:28:09	ga_ls9c_ard_3-2-1_102068_2023-09-18_final.stac-item
2023-09-18 10:28:33	ga_ls9c_ard_3-2-1_102069_2023-09-18_final.stac-item
2023-09-18 10:28:57	ga_ls9c_ard_3-2-1_102070_2023-09-18_final.stac-item
2023-09-18 10:29:21	ga_ls9c_ard_3-2-1_102071_2023-09-18_final.stac-item
2023-09-18 10:29:45	ga_ls9c_ard_3-2-1_102072_2023-09-18_final.stac-item
2023-09-18 10:30:09	ga_ls9c_ard_3-2-1_102073_2023-09-18_final.stac-item
2023-09-18 10:30:33	ga_ls9c_ard_3-2-1_102074_2023-09-18_final.stac-item
2023-09-18 10:30:57	ga_ls9c_ard_3-2-1_102075_2023-09-18_final.stac-item
2023-09-18 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-09-18_final.stac-item
2023-09-18 10:31:44	ga_ls9c_ard_3-2-1_102077_2023-09-18_final.stac-item
2023-09-18 10:32:08	ga_ls9c_ard_3-2-1_102078_2023-09-18_final.stac-item
2023-09-18 10:32:32	ga_ls9c_ard_3-2-1_102079_2023-09-18_final.stac-item
2023-09-18 10:32:56	ga_ls9c_ard_3-2-1_102080_2023-09-18_final.stac-item
2023-09-18 10:33:20	ga_ls9c_ard_3-2-1_102081_2023-09-18_final.stac-item
2023-09-18 10:33:44	ga_ls9c_ard_3-2-1_102082_2023-09-18_final.stac-item
2023-09-20 10:18:35	ga_ls9c_ard_3-2-1_100075_2023-09-20_final.stac-item
2023-09-20 10:18:59	ga_ls9c_ard_3-2-1_100076_2023-09-20_final.stac-item
2023-09-20 10:19:22	ga_ls9c_ard_3-2-1_100077_2023-09-20_final.stac-item
2023-09-20 10:19:46	ga_ls9c_ard_3-2-1_100078_2023-09-20_final.stac-item
2023-09-20 10:20:10	ga_ls9c_ard_3-2-1_100079_2023-09-20_final.stac-item
2023-09-20 10:20:34	ga_ls9c_ard_3-2-1_100080_2023-09-20_final.stac-item
2023-09-20 10:20:58	ga_ls9c_ard_3-2-1_100081_2023-09-20_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-09-22 10:09:24	ga_ls9c_ard_3-2-1_098083_2023-09-22_final.stac-item
2023-09-22 10:09:48	ga_ls9c_ard_3-2-1_098084_2023-09-22_final.stac-item
2023-09-22 10:10:12	ga_ls9c_ard_3-2-1_098085_2023-09-22_final.stac-item
2023-09-23 10:46:16	ga_ls9c_ard_3-2-1_105067_2023-09-23_final.stac-item
2023-09-23 10:46:40	ga_ls9c_ard_3-2-1_105068_2023-09-23_final.stac-item
2023-09-27 10:22:41	ga_ls9c_ard_3-2-1_101070_2023-09-27_final.stac-item
2023-09-27 10:23:05	ga_ls9c_ard_3-2-1_101071_2023-09-27_final.stac-item
2023-09-27 10:23:29	ga_ls9c_ard_3-2-1_101072_2023-09-27_final.stac-item
2023-09-27 10:23:53	ga_ls9c_ard_3-2-1_101073_2023-09-27_final.stac-item
2023-09-27 10:24:17	ga_ls9c_ard_3-2-1_101074_2023-09-27_final.stac-item
2023-09-27 10:24:41	ga_ls9c_ard_3-2-1_101075_2023-09-27_final.stac-item
2023-09-27 10:25:05	ga_ls9c_ard_3-2-1_101076_2023-09-27_final.stac-item
2023-09-27 10:25:29	ga_ls9c_ard_3-2-1_101077_2023-09-27_final.stac-item
2023-09-27 10:25:53	ga_ls9c_ard_3-2-1_101078_2023-09-27_final.stac-item
2023-09-27 10:26:17	ga_ls9c_ard_3-2-1_101079_2023-09-27_final.stac-item
2023-09-27 10:26:41	ga_ls9c_ard_3-2-1_101080_2023-09-27_final.stac-item
2023-09-27 10:27:05	ga_ls9c_ard_3-2-1_101081_2023-09-27_final.stac-item
2023-09-27 10:27:29	ga_ls9c_ard_3-2-1_101082_2023-09-27_final.stac-item
2023-09-27 10:27:53	ga_ls9c_ard_3-2-1_101083_2023-09-27_final.stac-item
2023-09-29 10:13:56	ga_ls9c_ard_3-2-1_099079_2023-09-29_final.stac-item
2023-09-29 10:14:20	ga_ls9c_ard_3-2-1_099080_2023-09-29_final.stac-item
2023-09-29 10:14:44	ga_ls9c_ard_3-2-1_099081_2023-09-29_final.stac-item
2023-09-29 10:15:08	ga_ls9c_ard_3-2-1_099082_2023-09-29_final.stac-item
2023-09-29 10:15:32	ga_ls9c_ard_3-2-1_099083_2023-09-29_final.stac-item
2023-09-29 10:15:56	ga_ls9c_ard_3-2-1_099084_2023-09-29_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