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
2023-07-08 09:39:23	ga_ls9c_ard_3-2-1_094071_2023-07-08_final.stac-item
2023-07-08 09:39:47	ga_ls9c_ard_3-2-1_094072_2023-07-08_final.stac-item
2023-07-08 09:40:11	ga_ls9c_ard_3-2-1_094073_2023-07-08_final.stac-item
2023-07-08 09:40:35	ga_ls9c_ard_3-2-1_094074_2023-07-08_final.stac-item
2023-07-08 09:41:23	ga_ls9c_ard_3-2-1_094076_2023-07-08_final.stac-item
2023-07-08 09:41:47	ga_ls9c_ard_3-2-1_094077_2023-07-08_final.stac-item
2023-07-08 09:42:11	ga_ls9c_ard_3-2-1_094078_2023-07-08_final.stac-item
2023-07-08 09:42:58	ga_ls9c_ard_3-2-1_094080_2023-07-08_final.stac-item
2023-07-08 09:43:22	ga_ls9c_ard_3-2-1_094081_2023-07-08_final.stac-item
2023-07-08 09:43:46	ga_ls9c_ard_3-2-1_094082_2023-07-08_final.stac-item
2023-07-08 09:44:10	ga_ls9c_ard_3-2-1_094083_2023-07-08_final.stac-item
2023-07-08 09:44:34	ga_ls9c_ard_3-2-1_094084_2023-07-08_final.stac-item
2023-07-08 09:44:58	ga_ls9c_ard_3-2-1_094085_2023-07-08_final.stac-item
2023-07-08 09:45:22	ga_ls9c_ard_3-2-1_094086_2023-07-08_final.stac-item
2023-07-08 11:17:28	ga_ls9c_ard_3-2-1_110069_2023-07-08_final.stac-item
2023-07-08 11:17:52	ga_ls9c_ard_3-2-1_110070_2023-07-08_final.stac-item
2023-07-08 11:18:16	ga_ls9c_ard_3-2-1_110071_2023-07-08_final.stac-item
2023-07-08 11:18:40	ga_ls9c_ard_3-2-1_110072_2023-07-08_final.stac-item
2023-07-08 11:19:04	ga_ls9c_ard_3-2-1_110073_2023-07-08_final.stac-item
2023-07-08 11:19:28	ga_ls9c_ard_3-2-1_110074_2023-07-08_final.stac-item
2023-07-08 11:19:52	ga_ls9c_ard_3-2-1_110075_2023-07-08_final.stac-item
2023-07-08 11:20:16	ga_ls9c_ard_3-2-1_110076_2023-07-08_final.stac-item
2023-07-08 11:20:40	ga_ls9c_ard_3-2-1_110077_2023-07-08_final.stac-item
2023-07-08 11:21:52	ga_ls9c_ard_3-2-1_110080_2023-07-08_final.stac-item
2023-07-08 11:22:15	ga_ls9c_ard_3-2-1_110081_2023-07-08_final.stac-item
2023-07-08 11:22:39	ga_ls9c_ard_3-2-1_110082_2023-07-08_final.stac-item
2023-07-08 11:23:03	ga_ls9c_ard_3-2-1_110083_2023-07-08_final.stac-item
2023-07-08 11:23:51	ga_ls9c_ard_3-2-1_110085_2023-07-08_final.stac-item
2023-07-09 10:22:15	ga_ls9c_ard_3-2-1_101070_2023-07-09_final.stac-item
2023-07-09 10:22:39	ga_ls9c_ard_3-2-1_101071_2023-07-09_final.stac-item
2023-07-09 10:23:03	ga_ls9c_ard_3-2-1_101072_2023-07-09_final.stac-item
2023-07-09 10:23:51	ga_ls9c_ard_3-2-1_101074_2023-07-09_final.stac-item
2023-07-09 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-09_final.stac-item
2023-07-09 10:24:39	ga_ls9c_ard_3-2-1_101076_2023-07-09_final.stac-item
2023-07-09 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-09_final.stac-item
2023-07-09 10:26:15	ga_ls9c_ard_3-2-1_101080_2023-07-09_final.stac-item
2023-07-10 09:27:02	ga_ls9c_ard_3-2-1_092071_2023-07-09_final.stac-item
2023-07-10 09:27:26	ga_ls9c_ard_3-2-1_092072_2023-07-09_final.stac-item
2023-07-10 09:27:50	ga_ls9c_ard_3-2-1_092073_2023-07-09_final.stac-item
2023-07-10 09:28:14	ga_ls9c_ard_3-2-1_092074_2023-07-09_final.stac-item
2023-07-10 09:28:38	ga_ls9c_ard_3-2-1_092075_2023-07-09_final.stac-item
2023-07-10 09:29:02	ga_ls9c_ard_3-2-1_092076_2023-07-09_final.stac-item
2023-07-10 09:29:26	ga_ls9c_ard_3-2-1_092077_2023-07-09_final.stac-item
2023-07-10 09:29:50	ga_ls9c_ard_3-2-1_092078_2023-07-09_final.stac-item
2023-07-10 09:30:14	ga_ls9c_ard_3-2-1_092079_2023-07-10_final.stac-item
2023-07-10 09:30:38	ga_ls9c_ard_3-2-1_092080_2023-07-10_final.stac-item
2023-07-10 09:31:26	ga_ls9c_ard_3-2-1_092082_2023-07-10_final.stac-item
2023-07-10 09:31:50	ga_ls9c_ard_3-2-1_092083_2023-07-10_final.stac-item
2023-07-10 09:32:14	ga_ls9c_ard_3-2-1_092084_2023-07-10_final.stac-item
2023-07-10 09:32:38	ga_ls9c_ard_3-2-1_092085_2023-07-10_final.stac-item
2023-07-10 09:33:02	ga_ls9c_ard_3-2-1_092086_2023-07-10_final.stac-item
2023-07-10 09:33:50	ga_ls9c_ard_3-2-1_092088_2023-07-10_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-10 09:34:37	ga_ls9c_ard_3-2-1_092090_2023-07-10_final.stac-item
2023-07-10 11:05:08	ga_ls9c_ard_3-2-1_108069_2023-07-10_final.stac-item
2023-07-10 11:05:32	ga_ls9c_ard_3-2-1_108070_2023-07-10_final.stac-item
2023-07-10 11:06:19	ga_ls9c_ard_3-2-1_108072_2023-07-10_final.stac-item
2023-07-10 11:07:07	ga_ls9c_ard_3-2-1_108074_2023-07-10_final.stac-item
2023-07-10 11:07:31	ga_ls9c_ard_3-2-1_108075_2023-07-10_final.stac-item
2023-07-10 11:07:55	ga_ls9c_ard_3-2-1_108076_2023-07-10_final.stac-item
2023-07-10 11:08:19	ga_ls9c_ard_3-2-1_108077_2023-07-10_final.stac-item
2023-07-10 11:08:43	ga_ls9c_ard_3-2-1_108078_2023-07-10_final.stac-item
2023-07-10 11:09:07	ga_ls9c_ard_3-2-1_108079_2023-07-10_final.stac-item
2023-07-10 11:09:55	ga_ls9c_ard_3-2-1_108081_2023-07-10_final.stac-item
2023-07-10 11:10:19	ga_ls9c_ard_3-2-1_108082_2023-07-10_final.stac-item
2023-07-10 11:10:43	ga_ls9c_ard_3-2-1_108083_2023-07-10_final.stac-item
2023-07-10 11:11:07	ga_ls9c_ard_3-2-1_108084_2023-07-10_final.stac-item
2023-07-11 10:08:43	ga_ls9c_ard_3-2-1_099067_2023-07-11_final.stac-item
2023-07-11 10:09:07	ga_ls9c_ard_3-2-1_099068_2023-07-11_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-07-11 10:10:19	ga_ls9c_ard_3-2-1_099071_2023-07-11_final.stac-item
2023-07-11 10:11:06	ga_ls9c_ard_3-2-1_099073_2023-07-11_final.stac-item
2023-07-11 10:11:30	ga_ls9c_ard_3-2-1_099074_2023-07-11_final.stac-item
2023-07-11 10:12:42	ga_ls9c_ard_3-2-1_099077_2023-07-11_final.stac-item
2023-07-11 10:13:30	ga_ls9c_ard_3-2-1_099079_2023-07-11_final.stac-item
2023-07-11 10:13:54	ga_ls9c_ard_3-2-1_099080_2023-07-11_final.stac-item
2023-07-11 10:14:18	ga_ls9c_ard_3-2-1_099081_2023-07-11_final.stac-item
2023-07-11 10:14:42	ga_ls9c_ard_3-2-1_099082_2023-07-11_final.stac-item
2023-07-11 10:15:06	ga_ls9c_ard_3-2-1_099083_2023-07-11_final.stac-item
2023-07-11 10:15:30	ga_ls9c_ard_3-2-1_099084_2023-07-11_final.stac-item
2023-07-11 11:50:23	ga_ls9c_ard_3-2-1_115074_2023-07-11_final.stac-item
2023-07-11 11:50:47	ga_ls9c_ard_3-2-1_115075_2023-07-11_final.stac-item
2023-07-11 11:51:11	ga_ls9c_ard_3-2-1_115076_2023-07-11_final.stac-item
2023-07-11 11:51:35	ga_ls9c_ard_3-2-1_115077_2023-07-11_final.stac-item
2023-07-11 11:52:47	ga_ls9c_ard_3-2-1_115080_2023-07-11_final.stac-item
2023-07-12 09:15:53	ga_ls9c_ard_3-2-1_090074_2023-07-11_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-12 09:16:41	ga_ls9c_ard_3-2-1_090076_2023-07-11_final.stac-item
2023-07-12 09:17:29	ga_ls9c_ard_3-2-1_090078_2023-07-11_final.stac-item
2023-07-12 09:17:53	ga_ls9c_ard_3-2-1_090079_2023-07-11_final.stac-item
2023-07-12 09:18:17	ga_ls9c_ard_3-2-1_090080_2023-07-11_final.stac-item
2023-07-12 09:18:41	ga_ls9c_ard_3-2-1_090081_2023-07-11_final.stac-item
2023-07-12 09:19:05	ga_ls9c_ard_3-2-1_090082_2023-07-11_final.stac-item
2023-07-12 09:19:29	ga_ls9c_ard_3-2-1_090083_2023-07-11_final.stac-item
2023-07-12 09:19:53	ga_ls9c_ard_3-2-1_090084_2023-07-11_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-07-12 09:20:41	ga_ls9c_ard_3-2-1_090086_2023-07-11_final.stac-item
2023-07-12 09:21:05	ga_ls9c_ard_3-2-1_090087_2023-07-11_final.stac-item
2023-07-12 09:21:29	ga_ls9c_ard_3-2-1_090088_2023-07-11_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_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