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
2023-09-05 09:21:40	ga_ls9c_ard_3-2-1_091072_2023-09-04_final.stac-item
2023-09-05 09:22:04	ga_ls9c_ard_3-2-1_091073_2023-09-04_final.stac-item
2023-09-05 09:22:28	ga_ls9c_ard_3-2-1_091074_2023-09-04_final.stac-item
2023-09-05 09:22:52	ga_ls9c_ard_3-2-1_091075_2023-09-04_final.stac-item
2023-09-05 09:23:16	ga_ls9c_ard_3-2-1_091076_2023-09-04_final.stac-item
2023-09-05 09:23:40	ga_ls9c_ard_3-2-1_091077_2023-09-04_final.stac-item
2023-09-05 09:24:04	ga_ls9c_ard_3-2-1_091078_2023-09-04_final.stac-item
2023-09-05 09:24:28	ga_ls9c_ard_3-2-1_091079_2023-09-04_final.stac-item
2023-09-07 09:10:08	ga_ls9c_ard_3-2-1_089074_2023-09-06_final.stac-item
2023-09-07 09:10:32	ga_ls9c_ard_3-2-1_089075_2023-09-06_final.stac-item
2023-09-07 09:10:56	ga_ls9c_ard_3-2-1_089076_2023-09-06_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-09-07 09:11:44	ga_ls9c_ard_3-2-1_089078_2023-09-06_final.stac-item
2023-09-07 09:12:08	ga_ls9c_ard_3-2-1_089079_2023-09-06_final.stac-item
2023-09-07 09:12:32	ga_ls9c_ard_3-2-1_089080_2023-09-06_final.stac-item
2023-09-07 09:12:55	ga_ls9c_ard_3-2-1_089081_2023-09-06_final.stac-item
2023-09-07 09:13:19	ga_ls9c_ard_3-2-1_089082_2023-09-06_final.stac-item
2023-09-07 09:13:43	ga_ls9c_ard_3-2-1_089083_2023-09-06_final.stac-item
2023-09-07 09:14:07	ga_ls9c_ard_3-2-1_089084_2023-09-06_final.stac-item
2023-09-07 09:14:31	ga_ls9c_ard_3-2-1_089085_2023-09-06_final.stac-item
2023-09-07 09:14:55	ga_ls9c_ard_3-2-1_089086_2023-09-06_final.stac-item
2023-09-12 09:27:32	ga_ls9c_ard_3-2-1_092071_2023-09-11_final.stac-item
2023-09-12 09:27:56	ga_ls9c_ard_3-2-1_092072_2023-09-11_final.stac-item
2023-09-12 09:28:19	ga_ls9c_ard_3-2-1_092073_2023-09-11_final.stac-item
2023-09-12 09:28:43	ga_ls9c_ard_3-2-1_092074_2023-09-11_final.stac-item
2023-09-12 09:29:07	ga_ls9c_ard_3-2-1_092075_2023-09-11_final.stac-item
2023-09-14 09:16:22	ga_ls9c_ard_3-2-1_090074_2023-09-13_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-09-14 09:17:10	ga_ls9c_ard_3-2-1_090076_2023-09-13_final.stac-item
2023-09-14 09:17:34	ga_ls9c_ard_3-2-1_090077_2023-09-13_final.stac-item
2023-09-14 09:17:58	ga_ls9c_ard_3-2-1_090078_2023-09-13_final.stac-item
2023-09-14 09:18:22	ga_ls9c_ard_3-2-1_090079_2023-09-13_final.stac-item
2023-09-14 09:18:46	ga_ls9c_ard_3-2-1_090080_2023-09-13_final.stac-item
2023-09-14 09:19:10	ga_ls9c_ard_3-2-1_090081_2023-09-13_final.stac-item
2023-09-14 09:19:34	ga_ls9c_ard_3-2-1_090082_2023-09-13_final.stac-item
2023-09-14 09:19:58	ga_ls9c_ard_3-2-1_090083_2023-09-13_final.stac-item
2023-09-16 09:06:25	ga_ls9c_ard_3-2-1_088080_2023-09-15_final.stac-item
2023-09-16 09:06:49	ga_ls9c_ard_3-2-1_088081_2023-09-15_final.stac-item
2023-09-16 09:07:13	ga_ls9c_ard_3-2-1_088082_2023-09-15_final.stac-item
2023-09-16 09:07:37	ga_ls9c_ard_3-2-1_088083_2023-09-15_final.stac-item
2023-09-21 09:21:45	ga_ls9c_ard_3-2-1_091072_2023-09-20_final.stac-item
2023-09-21 09:22:09	ga_ls9c_ard_3-2-1_091073_2023-09-20_final.stac-item
2023-09-21 09:22:33	ga_ls9c_ard_3-2-1_091074_2023-09-20_final.stac-item
2023-09-21 09:22:57	ga_ls9c_ard_3-2-1_091075_2023-09-20_final.stac-item
2023-09-21 09:23:21	ga_ls9c_ard_3-2-1_091076_2023-09-20_final.stac-item
2023-09-21 09:23:45	ga_ls9c_ard_3-2-1_091077_2023-09-20_final.stac-item
2023-09-21 09:24:09	ga_ls9c_ard_3-2-1_091078_2023-09-20_final.stac-item
2023-09-21 09:24:33	ga_ls9c_ard_3-2-1_091079_2023-09-20_final.stac-item
2023-09-23 09:10:10	ga_ls9c_ard_3-2-1_089074_2023-09-22_final.stac-item
2023-09-23 09:10:34	ga_ls9c_ard_3-2-1_089075_2023-09-22_final.stac-item
2023-09-23 09:10:58	ga_ls9c_ard_3-2-1_089076_2023-09-22_final.stac-item
2023-09-23 09:11:22	ga_ls9c_ard_3-2-1_089077_2023-09-22_final.stac-item
2023-09-23 09:11:46	ga_ls9c_ard_3-2-1_089078_2023-09-22_final.stac-item
2023-09-23 09:12:10	ga_ls9c_ard_3-2-1_089079_2023-09-22_final.stac-item
2023-09-23 09:12:34	ga_ls9c_ard_3-2-1_089080_2023-09-22_final.stac-item
2023-09-23 09:12:58	ga_ls9c_ard_3-2-1_089081_2023-09-22_final.stac-item
2023-09-23 09:13:22	ga_ls9c_ard_3-2-1_089082_2023-09-22_final.stac-item
2023-09-23 09:13:46	ga_ls9c_ard_3-2-1_089083_2023-09-22_final.stac-item
2023-09-23 09:14:10	ga_ls9c_ard_3-2-1_089084_2023-09-22_final.stac-item
2023-09-23 09:14:34	ga_ls9c_ard_3-2-1_089085_2023-09-22_final.stac-item
2023-09-23 09:14:58	ga_ls9c_ard_3-2-1_089086_2023-09-22_final.stac-item
2023-09-28 09:27:27	ga_ls9c_ard_3-2-1_092071_2023-09-27_final.stac-item
2023-09-28 09:27:51	ga_ls9c_ard_3-2-1_092072_2023-09-27_final.stac-item
2023-09-28 09:28:15	ga_ls9c_ard_3-2-1_092073_2023-09-27_final.stac-item
2023-09-28 09:28:39	ga_ls9c_ard_3-2-1_092074_2023-09-27_final.stac-item
2023-09-28 09:29:03	ga_ls9c_ard_3-2-1_092075_2023-09-27_final.stac-item
2023-09-30 09:16:20	ga_ls9c_ard_3-2-1_090074_2023-09-29_final.stac-item
2023-09-30 09:16:44	ga_ls9c_ard_3-2-1_090075_2023-09-29_final.stac-item
2023-09-30 09:17:08	ga_ls9c_ard_3-2-1_090076_2023-09-29_final.stac-item
2023-09-30 09:17:32	ga_ls9c_ard_3-2-1_090077_2023-09-29_final.stac-item
2023-09-30 09:17:56	ga_ls9c_ard_3-2-1_090078_2023-09-29_final.stac-item
2023-09-30 09:18:20	ga_ls9c_ard_3-2-1_090079_2023-09-29_final.stac-item
2023-09-30 09:18:44	ga_ls9c_ard_3-2-1_090080_2023-09-29_final.stac-item
2023-09-30 09:19:08	ga_ls9c_ard_3-2-1_090081_2023-09-29_final.stac-item
2023-09-30 09:19:31	ga_ls9c_ard_3-2-1_090082_2023-09-29_final.stac-item
2023-09-30 09:19:55	ga_ls9c_ard_3-2-1_090083_2023-09-29_final.stac-item
2023-10-02 09:06:24	ga_ls9c_ard_3-2-1_088080_2023-10-01_final.stac-item
2023-10-02 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-10-01_final.stac-item
2023-10-02 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-10-01_final.stac-item
2023-10-02 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-10-01_final.stac-item
2023-10-07 09:21:48	ga_ls9c_ard_3-2-1_091072_2023-10-06_final.stac-item
2023-10-07 09:22:12	ga_ls9c_ard_3-2-1_091073_2023-10-06_final.stac-item
2023-10-07 09:22:36	ga_ls9c_ard_3-2-1_091074_2023-10-06_final.stac-item
2023-10-07 09:23:00	ga_ls9c_ard_3-2-1_091075_2023-10-06_final.stac-item
2023-10-07 09:23:24	ga_ls9c_ard_3-2-1_091076_2023-10-06_final.stac-item
2023-10-07 09:23:48	ga_ls9c_ard_3-2-1_091077_2023-10-06_final.stac-item
2023-10-07 09:24:12	ga_ls9c_ard_3-2-1_091078_2023-10-06_final.stac-item
2023-10-07 09:24:36	ga_ls9c_ard_3-2-1_091079_2023-10-06_final.stac-item
2023-10-09 09:10:15	ga_ls9c_ard_3-2-1_089074_2023-10-08_final.stac-item
2023-10-09 09:10:39	ga_ls9c_ard_3-2-1_089075_2023-10-08_final.stac-item
2023-10-09 09:11:03	ga_ls9c_ard_3-2-1_089076_2023-10-08_final.stac-item
2023-10-09 09:11:27	ga_ls9c_ard_3-2-1_089077_2023-10-08_final.stac-item
2023-10-09 09:11:51	ga_ls9c_ard_3-2-1_089078_2023-10-08_final.stac-item
2023-10-09 09:12:15	ga_ls9c_ard_3-2-1_089079_2023-10-08_final.stac-item
2023-10-09 09:12:39	ga_ls9c_ard_3-2-1_089080_2023-10-08_final.stac-item
2023-10-09 09:13:03	ga_ls9c_ard_3-2-1_089081_2023-10-08_final.stac-item
2023-10-09 09:13:27	ga_ls9c_ard_3-2-1_089082_2023-10-08_final.stac-item
2023-10-09 09:13:51	ga_ls9c_ard_3-2-1_089083_2023-10-08_final.stac-item
2023-10-09 09:14:15	ga_ls9c_ard_3-2-1_089084_2023-10-08_final.stac-item
2023-10-09 09:14:39	ga_ls9c_ard_3-2-1_089085_2023-10-08_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