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
2021-11-15 09:43:33	ga_ls9c_ard_3-2-1_094081_2021-11-15_final.stac-item
2021-11-15 09:43:57	ga_ls9c_ard_3-2-1_094082_2021-11-15_final.stac-item
2021-11-15 09:44:21	ga_ls9c_ard_3-2-1_094083_2021-11-15_final.stac-item
2021-12-09 09:43:46	ga_ls9c_ard_3-2-1_094080_2021-12-09_final.stac-item
2021-12-09 09:44:10	ga_ls9c_ard_3-2-1_094081_2021-12-09_final.stac-item
2021-12-09 09:44:34	ga_ls9c_ard_3-2-1_094082_2021-12-09_final.stac-item
2021-12-09 09:44:58	ga_ls9c_ard_3-2-1_094083_2021-12-09_final.stac-item
2021-12-09 09:45:22	ga_ls9c_ard_3-2-1_094084_2021-12-09_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-09 09:46:10	ga_ls9c_ard_3-2-1_094086_2021-12-09_final.stac-item
2021-12-25 09:43:42	ga_ls9c_ard_3-2-1_094080_2021-12-25_final.stac-item
2021-12-25 09:44:06	ga_ls9c_ard_3-2-1_094081_2021-12-25_final.stac-item
2021-12-25 09:44:30	ga_ls9c_ard_3-2-1_094082_2021-12-25_final.stac-item
2021-12-25 09:44:54	ga_ls9c_ard_3-2-1_094083_2021-12-25_final.stac-item
2021-12-25 09:45:18	ga_ls9c_ard_3-2-1_094084_2021-12-25_final.stac-item
2021-12-25 09:45:42	ga_ls9c_ard_3-2-1_094085_2021-12-25_final.stac-item
2021-12-25 09:46:06	ga_ls9c_ard_3-2-1_094086_2021-12-25_final.stac-item
2022-01-03 09:39:07	ga_ls9c_ard_3-2-1_093084_2022-01-03_final.stac-item
2022-01-03 09:39:31	ga_ls9c_ard_3-2-1_093085_2022-01-03_final.stac-item
2022-01-03 09:39:55	ga_ls9c_ard_3-2-1_093086_2022-01-03_final.stac-item
2022-01-03 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-01-03_final.stac-item
2022-01-03 09:40:42	ga_ls9c_ard_3-2-1_093088_2022-01-03_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-01-24 09:53:15	ga_ls9c_ard_3-2-1_096073_2022-01-24_final.stac-item
2022-01-24 09:53:39	ga_ls9c_ard_3-2-1_096074_2022-01-24_final.stac-item
2022-01-24 09:54:03	ga_ls9c_ard_3-2-1_096075_2022-01-24_final.stac-item
2022-01-24 09:54:27	ga_ls9c_ard_3-2-1_096076_2022-01-24_final.stac-item
2022-01-24 09:54:51	ga_ls9c_ard_3-2-1_096077_2022-01-24_final.stac-item
2022-02-09 09:52:50	ga_ls9c_ard_3-2-1_096072_2022-02-09_final.stac-item
2022-02-09 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-02-09_final.stac-item
2022-02-09 09:53:38	ga_ls9c_ard_3-2-1_096074_2022-02-09_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-02-09 09:54:25	ga_ls9c_ard_3-2-1_096076_2022-02-09_final.stac-item
2022-02-09 09:54:49	ga_ls9c_ard_3-2-1_096077_2022-02-09_final.stac-item
2022-05-25 09:47:30	ga_ls9c_ard_3-2-1_095076_2022-05-25_final.stac-item
2022-05-25 09:47:54	ga_ls9c_ard_3-2-1_095077_2022-05-25_final.stac-item
2022-05-25 09:48:18	ga_ls9c_ard_3-2-1_095078_2022-05-25_final.stac-item
2022-05-25 09:48:42	ga_ls9c_ard_3-2-1_095079_2022-05-25_final.stac-item
2022-05-25 09:49:06	ga_ls9c_ard_3-2-1_095080_2022-05-25_final.stac-item
2022-05-25 09:49:30	ga_ls9c_ard_3-2-1_095081_2022-05-25_final.stac-item
2022-05-25 09:49:54	ga_ls9c_ard_3-2-1_095082_2022-05-25_final.stac-item
2022-06-10 09:47:33	ga_ls9c_ard_3-2-1_095076_2022-06-10_final.stac-item
2022-06-10 09:47:57	ga_ls9c_ard_3-2-1_095077_2022-06-10_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-10 09:49:08	ga_ls9c_ard_3-2-1_095080_2022-06-10_final.stac-item
2022-06-10 09:49:32	ga_ls9c_ard_3-2-1_095081_2022-06-10_final.stac-item
2022-06-10 09:49:56	ga_ls9c_ard_3-2-1_095082_2022-06-10_final.stac-item
2022-07-05 09:43:16	ga_ls9c_ard_3-2-1_094080_2022-07-05_final.stac-item
2022-07-05 09:43:40	ga_ls9c_ard_3-2-1_094081_2022-07-05_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-05 09:44:28	ga_ls9c_ard_3-2-1_094083_2022-07-05_final.stac-item
2022-07-05 09:44:52	ga_ls9c_ard_3-2-1_094084_2022-07-05_final.stac-item
2022-07-05 09:45:16	ga_ls9c_ard_3-2-1_094085_2022-07-05_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-12 09:47:49	ga_ls9c_ard_3-2-1_095076_2022-07-12_final.stac-item
2022-07-12 09:48:13	ga_ls9c_ard_3-2-1_095077_2022-07-12_final.stac-item
2022-07-12 09:48:37	ga_ls9c_ard_3-2-1_095078_2022-07-12_final.stac-item
2022-07-12 09:49:01	ga_ls9c_ard_3-2-1_095079_2022-07-12_final.stac-item
2022-07-12 09:49:25	ga_ls9c_ard_3-2-1_095080_2022-07-12_final.stac-item
2022-07-12 09:49:49	ga_ls9c_ard_3-2-1_095081_2022-07-12_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-30 09:38:52	ga_ls9c_ard_3-2-1_093084_2022-07-30_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-07-30 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-07-30_final.stac-item
2022-07-30 09:40:04	ga_ls9c_ard_3-2-1_093087_2022-07-30_final.stac-item
2022-07-30 09:40:28	ga_ls9c_ard_3-2-1_093088_2022-07-30_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-08-15 09:39:26	ga_ls9c_ard_3-2-1_093085_2022-08-15_final.stac-item
2022-08-15 09:39:50	ga_ls9c_ard_3-2-1_093086_2022-08-15_final.stac-item
2022-08-15 09:40:13	ga_ls9c_ard_3-2-1_093087_2022-08-15_final.stac-item
2022-08-15 09:40:37	ga_ls9c_ard_3-2-1_093088_2022-08-15_final.stac-item
2022-08-22 09:43:38	ga_ls9c_ard_3-2-1_094080_2022-08-22_final.stac-item
2022-08-22 09:44:02	ga_ls9c_ard_3-2-1_094081_2022-08-22_final.stac-item
2022-08-22 09:44:26	ga_ls9c_ard_3-2-1_094082_2022-08-22_final.stac-item
2022-08-22 09:44:50	ga_ls9c_ard_3-2-1_094083_2022-08-22_final.stac-item
2022-08-22 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-08-22_final.stac-item
2022-08-22 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-08-22_final.stac-item
2022-08-22 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-08-22_final.stac-item
2022-08-29 09:48:14	ga_ls9c_ard_3-2-1_095076_2022-08-29_final.stac-item
2022-08-29 09:48:38	ga_ls9c_ard_3-2-1_095077_2022-08-29_final.stac-item
2022-08-29 09:49:02	ga_ls9c_ard_3-2-1_095078_2022-08-29_final.stac-item
2022-08-29 09:49:26	ga_ls9c_ard_3-2-1_095079_2022-08-29_final.stac-item
2022-08-29 09:49:50	ga_ls9c_ard_3-2-1_095080_2022-08-29_final.stac-item
2022-08-29 09:50:14	ga_ls9c_ard_3-2-1_095081_2022-08-29_final.stac-item
2022-08-29 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-08-29_final.stac-item
2022-09-05 09:52:49	ga_ls9c_ard_3-2-1_096072_2022-09-05_final.stac-item
2022-09-05 09:53:13	ga_ls9c_ard_3-2-1_096073_2022-09-05_final.stac-item
2022-09-05 09:53:37	ga_ls9c_ard_3-2-1_096074_2022-09-05_final.stac-item
2022-09-05 09:54:01	ga_ls9c_ard_3-2-1_096075_2022-09-05_final.stac-item
2022-09-05 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-09-05_final.stac-item
2022-09-05 09:54:48	ga_ls9c_ard_3-2-1_096077_2022-09-05_final.stac-item
2022-09-12 09:57:02	ga_ls9c_ard_3-2-1_097067_2022-09-12_final.stac-item
2022-09-12 09:57:26	ga_ls9c_ard_3-2-1_097068_2022-09-12_final.stac-item
2022-09-12 09:57:49	ga_ls9c_ard_3-2-1_097069_2022-09-12_final.stac-item
2022-09-12 09:58:13	ga_ls9c_ard_3-2-1_097070_2022-09-12_final.stac-item
2022-09-12 09:58:37	ga_ls9c_ard_3-2-1_097071_2022-09-12_final.stac-item
2022-09-12 09:59:01	ga_ls9c_ard_3-2-1_097072_2022-09-12_final.stac-item
2022-09-12 09:59:25	ga_ls9c_ard_3-2-1_097073_2022-09-12_final.stac-item
2022-09-21 09:52:55	ga_ls9c_ard_3-2-1_096072_2022-09-21_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