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 10:16:52	ga_ls9c_ard_3-2-1_100071_2023-09-04_final.stac-item
2023-09-04 10:17:16	ga_ls9c_ard_3-2-1_100072_2023-09-04_final.stac-item
2023-09-04 10:17:40	ga_ls9c_ard_3-2-1_100073_2023-09-04_final.stac-item
2023-09-04 10:18:04	ga_ls9c_ard_3-2-1_100074_2023-09-04_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-06 10:03:21	ga_ls9c_ard_3-2-1_098068_2023-09-06_final.stac-item
2023-09-06 10:03:45	ga_ls9c_ard_3-2-1_098069_2023-09-06_final.stac-item
2023-09-06 10:04:09	ga_ls9c_ard_3-2-1_098070_2023-09-06_final.stac-item
2023-09-06 10:04:33	ga_ls9c_ard_3-2-1_098071_2023-09-06_final.stac-item
2023-09-06 10:04:56	ga_ls9c_ard_3-2-1_098072_2023-09-06_final.stac-item
2023-09-06 10:05:20	ga_ls9c_ard_3-2-1_098073_2023-09-06_final.stac-item
2023-09-06 10:05:44	ga_ls9c_ard_3-2-1_098074_2023-09-06_final.stac-item
2023-09-06 10:06:08	ga_ls9c_ard_3-2-1_098075_2023-09-06_final.stac-item
2023-09-06 10:06:32	ga_ls9c_ard_3-2-1_098076_2023-09-06_final.stac-item
2023-09-06 10:06:56	ga_ls9c_ard_3-2-1_098077_2023-09-06_final.stac-item
2023-09-06 10:07:20	ga_ls9c_ard_3-2-1_098078_2023-09-06_final.stac-item
2023-09-06 10:07:44	ga_ls9c_ard_3-2-1_098079_2023-09-06_final.stac-item
2023-09-06 10:08:08	ga_ls9c_ard_3-2-1_098080_2023-09-06_final.stac-item
2023-09-06 10:08:32	ga_ls9c_ard_3-2-1_098081_2023-09-06_final.stac-item
2023-09-06 10:08:56	ga_ls9c_ard_3-2-1_098082_2023-09-06_final.stac-item
2023-09-08 09:53:48	ga_ls9c_ard_3-2-1_096075_2023-09-08_final.stac-item
2023-09-08 09:54:12	ga_ls9c_ard_3-2-1_096076_2023-09-08_final.stac-item
2023-09-08 09:54:36	ga_ls9c_ard_3-2-1_096077_2023-09-08_final.stac-item
2023-09-08 09:55:00	ga_ls9c_ard_3-2-1_096078_2023-09-08_final.stac-item
2023-09-08 09:55:24	ga_ls9c_ard_3-2-1_096079_2023-09-08_final.stac-item
2023-09-08 09:55:48	ga_ls9c_ard_3-2-1_096080_2023-09-08_final.stac-item
2023-09-08 09:56:12	ga_ls9c_ard_3-2-1_096081_2023-09-08_final.stac-item
2023-09-08 09:56:36	ga_ls9c_ard_3-2-1_096082_2023-09-08_final.stac-item
2023-09-08 09:57:00	ga_ls9c_ard_3-2-1_096083_2023-09-08_final.stac-item
2023-09-08 09:57:24	ga_ls9c_ard_3-2-1_096084_2023-09-08_final.stac-item
2023-09-08 09:57:48	ga_ls9c_ard_3-2-1_096085_2023-09-08_final.stac-item
2023-09-08 09:58:12	ga_ls9c_ard_3-2-1_096086_2023-09-08_final.stac-item
2023-09-10 09:45:03	ga_ls9c_ard_3-2-1_094084_2023-09-10_final.stac-item
2023-09-10 09:45:27	ga_ls9c_ard_3-2-1_094085_2023-09-10_final.stac-item
2023-09-10 09:45:51	ga_ls9c_ard_3-2-1_094086_2023-09-10_final.stac-item
2023-09-10 09:46:15	ga_ls9c_ard_3-2-1_094087_2023-09-10_final.stac-item
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-09-13 10:09:36	ga_ls9c_ard_3-2-1_099068_2023-09-13_final.stac-item
2023-09-13 10:10:00	ga_ls9c_ard_3-2-1_099069_2023-09-13_final.stac-item
2023-09-13 10:10:24	ga_ls9c_ard_3-2-1_099070_2023-09-13_final.stac-item
2023-09-13 10:10:48	ga_ls9c_ard_3-2-1_099071_2023-09-13_final.stac-item
2023-09-13 10:11:12	ga_ls9c_ard_3-2-1_099072_2023-09-13_final.stac-item
2023-09-13 10:11:36	ga_ls9c_ard_3-2-1_099073_2023-09-13_final.stac-item
2023-09-13 10:12:00	ga_ls9c_ard_3-2-1_099074_2023-09-13_final.stac-item
2023-09-13 10:12:23	ga_ls9c_ard_3-2-1_099075_2023-09-13_final.stac-item
2023-09-13 10:12:47	ga_ls9c_ard_3-2-1_099076_2023-09-13_final.stac-item
2023-09-13 10:13:11	ga_ls9c_ard_3-2-1_099077_2023-09-13_final.stac-item
2023-09-13 10:13:35	ga_ls9c_ard_3-2-1_099078_2023-09-13_final.stac-item
2023-09-17 09:49:41	ga_ls9c_ard_3-2-1_095080_2023-09-17_final.stac-item
2023-09-17 09:50:05	ga_ls9c_ard_3-2-1_095081_2023-09-17_final.stac-item
2023-09-17 09:50:29	ga_ls9c_ard_3-2-1_095082_2023-09-17_final.stac-item
2023-09-17 09:50:52	ga_ls9c_ard_3-2-1_095083_2023-09-17_final.stac-item
2023-09-17 09:51:16	ga_ls9c_ard_3-2-1_095084_2023-09-17_final.stac-item
2023-09-17 09:51:40	ga_ls9c_ard_3-2-1_095085_2023-09-17_final.stac-item
2023-09-17 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-09-17_final.stac-item
2023-09-17 09:52:28	ga_ls9c_ard_3-2-1_095087_2023-09-17_final.stac-item
2023-09-22 10:03:01	ga_ls9c_ard_3-2-1_098067_2023-09-22_final.stac-item
2023-09-22 10:03:25	ga_ls9c_ard_3-2-1_098068_2023-09-22_final.stac-item
2023-09-22 10:03:49	ga_ls9c_ard_3-2-1_098069_2023-09-22_final.stac-item
2023-09-22 10:04:12	ga_ls9c_ard_3-2-1_098070_2023-09-22_final.stac-item
2023-09-22 10:04:36	ga_ls9c_ard_3-2-1_098071_2023-09-22_final.stac-item
2023-09-22 10:05:00	ga_ls9c_ard_3-2-1_098072_2023-09-22_final.stac-item
2023-09-22 10:05:24	ga_ls9c_ard_3-2-1_098073_2023-09-22_final.stac-item
2023-09-22 10:05:48	ga_ls9c_ard_3-2-1_098074_2023-09-22_final.stac-item
2023-09-22 10:06:12	ga_ls9c_ard_3-2-1_098075_2023-09-22_final.stac-item
2023-09-22 10:06:36	ga_ls9c_ard_3-2-1_098076_2023-09-22_final.stac-item
2023-09-22 10:07:00	ga_ls9c_ard_3-2-1_098077_2023-09-22_final.stac-item
2023-09-22 10:07:24	ga_ls9c_ard_3-2-1_098078_2023-09-22_final.stac-item
2023-09-22 10:07:48	ga_ls9c_ard_3-2-1_098079_2023-09-22_final.stac-item
2023-09-22 10:08:12	ga_ls9c_ard_3-2-1_098080_2023-09-22_final.stac-item
2023-09-22 10:08:36	ga_ls9c_ard_3-2-1_098081_2023-09-22_final.stac-item
2023-09-22 10:09:00	ga_ls9c_ard_3-2-1_098082_2023-09-22_final.stac-item
2023-09-26 09:45:02	ga_ls9c_ard_3-2-1_094084_2023-09-26_final.stac-item
2023-09-26 09:45:26	ga_ls9c_ard_3-2-1_094085_2023-09-26_final.stac-item
2023-09-26 09:45:50	ga_ls9c_ard_3-2-1_094086_2023-09-26_final.stac-item
2023-09-26 09:46:14	ga_ls9c_ard_3-2-1_094087_2023-09-26_final.stac-item
2023-09-29 10:11:08	ga_ls9c_ard_3-2-1_099072_2023-09-29_final.stac-item
2023-09-29 10:11:32	ga_ls9c_ard_3-2-1_099073_2023-09-29_final.stac-item
2023-09-29 10:11:56	ga_ls9c_ard_3-2-1_099074_2023-09-29_final.stac-item
2023-09-29 10:13:08	ga_ls9c_ard_3-2-1_099077_2023-09-29_final.stac-item
2023-09-29 10:13:32	ga_ls9c_ard_3-2-1_099078_2023-09-29_final.stac-item
2023-10-01 09:58:01	ga_ls9c_ard_3-2-1_097070_2023-10-01_final.stac-item
2023-10-01 09:58:25	ga_ls9c_ard_3-2-1_097071_2023-10-01_final.stac-item
2023-10-01 09:58:49	ga_ls9c_ard_3-2-1_097072_2023-10-01_final.stac-item
2023-10-01 09:59:13	ga_ls9c_ard_3-2-1_097073_2023-10-01_final.stac-item
2023-10-01 09:59:37	ga_ls9c_ard_3-2-1_097074_2023-10-01_final.stac-item
2023-10-01 10:00:01	ga_ls9c_ard_3-2-1_097075_2023-10-01_final.stac-item
2023-10-01 10:00:25	ga_ls9c_ard_3-2-1_097076_2023-10-01_final.stac-item
2023-10-01 10:00:49	ga_ls9c_ard_3-2-1_097077_2023-10-01_final.stac-item
2023-10-01 10:01:13	ga_ls9c_ard_3-2-1_097078_2023-10-01_final.stac-item
2023-10-01 10:01:36	ga_ls9c_ard_3-2-1_097079_2023-10-01_final.stac-item
2023-10-01 10:02:00	ga_ls9c_ard_3-2-1_097080_2023-10-01_final.stac-item
2023-10-01 10:03:12	ga_ls9c_ard_3-2-1_097083_2023-10-01_final.stac-item
2023-10-03 09:49:41	ga_ls9c_ard_3-2-1_095080_2023-10-03_final.stac-item
2023-10-03 09:50:05	ga_ls9c_ard_3-2-1_095081_2023-10-03_final.stac-item
2023-10-03 09:50:29	ga_ls9c_ard_3-2-1_095082_2023-10-03_final.stac-item
2023-10-03 09:50:53	ga_ls9c_ard_3-2-1_095083_2023-10-03_final.stac-item
2023-10-03 09:51:17	ga_ls9c_ard_3-2-1_095084_2023-10-03_final.stac-item
2023-10-03 09:51:40	ga_ls9c_ard_3-2-1_095085_2023-10-03_final.stac-item
2023-10-03 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-10-03_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