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
2021-11-03 09:58:56	ga_ls9c_ard_3-2-1_096085_2021-11-03_final.stac-item
2021-11-05 09:40:12	ga_ls9c_ard_3-2-1_093085_2021-11-05_final.stac-item
2021-11-10 09:42:40	ga_ls9c_ard_3-2-1_094085_2021-11-10_final.stac-item
2021-12-05 10:10:32	ga_ls9c_ard_3-2-1_098085_2021-12-05_final.stac-item
2021-12-07 09:58:09	ga_ls9c_ard_3-2-1_096085_2021-12-07_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-23 09:58:04	ga_ls9c_ard_3-2-1_096085_2021-12-23_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 11:24:35	ga_ls9c_ard_3-2-1_110085_2021-12-25_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-10 11:24:33	ga_ls9c_ard_3-2-1_110085_2022-01-10_final.stac-item
2022-01-17 09:51:50	ga_ls9c_ard_3-2-1_095085_2022-01-17_final.stac-item
2022-01-26 11:24:34	ga_ls9c_ard_3-2-1_110085_2022-01-26_final.stac-item
2022-03-02 10:16:20	ga_ls9c_ard_3-2-1_099085_2022-03-02_final.stac-item
2022-03-31 11:24:14	ga_ls9c_ard_3-2-1_110085_2022-03-31_final.stac-item
2022-04-09 09:39:08	ga_ls9c_ard_3-2-1_093085_2022-04-09_final.stac-item
2022-04-14 09:57:38	ga_ls9c_ard_3-2-1_096085_2022-04-14_final.stac-item
2022-05-30 10:09:39	ga_ls9c_ard_3-2-1_098085_2022-05-30_final.stac-item
2022-05-31 09:14:02	ga_ls9c_ard_3-2-1_089085_2022-05-30_final.stac-item
2022-06-01 09:57:18	ga_ls9c_ard_3-2-1_096085_2022-06-01_final.stac-item
2022-06-03 09:44:57	ga_ls9c_ard_3-2-1_094085_2022-06-03_final.stac-item
2022-06-03 11:23:50	ga_ls9c_ard_3-2-1_110085_2022-06-03_final.stac-item
2022-06-06 10:15:51	ga_ls9c_ard_3-2-1_099085_2022-06-06_final.stac-item
2022-06-10 09:51:08	ga_ls9c_ard_3-2-1_095085_2022-06-10_final.stac-item
2022-06-15 10:09:45	ga_ls9c_ard_3-2-1_098085_2022-06-15_final.stac-item
2022-06-17 09:57:25	ga_ls9c_ard_3-2-1_096085_2022-06-17_final.stac-item
2022-06-19 11:23:59	ga_ls9c_ard_3-2-1_110085_2022-06-19_final.stac-item
2022-06-22 10:16:07	ga_ls9c_ard_3-2-1_099085_2022-06-22_final.stac-item
2022-07-01 10:10:00	ga_ls9c_ard_3-2-1_098085_2022-07-01_final.stac-item
2022-07-02 09:14:23	ga_ls9c_ard_3-2-1_089085_2022-07-01_final.stac-item
2022-07-03 09:57:38	ga_ls9c_ard_3-2-1_096085_2022-07-03_final.stac-item
2022-07-05 11:24:09	ga_ls9c_ard_3-2-1_110085_2022-07-05_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-07-21 09:45:19	ga_ls9c_ard_3-2-1_094085_2022-07-21_final.stac-item
2022-07-21 11:24:12	ga_ls9c_ard_3-2-1_110085_2022-07-21_final.stac-item
2022-07-28 09:51:36	ga_ls9c_ard_3-2-1_095085_2022-07-28_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-08-02 10:10:12	ga_ls9c_ard_3-2-1_098085_2022-08-02_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-06 09:45:32	ga_ls9c_ard_3-2-1_094085_2022-08-06_final.stac-item
2022-08-06 11:24:25	ga_ls9c_ard_3-2-1_110085_2022-08-06_final.stac-item
2022-08-13 09:51:46	ga_ls9c_ard_3-2-1_095085_2022-08-13_final.stac-item
2022-08-18 10:10:21	ga_ls9c_ard_3-2-1_098085_2022-08-18_final.stac-item
2022-08-19 09:14:44	ga_ls9c_ard_3-2-1_089085_2022-08-18_final.stac-item
2022-08-20 09:57:59	ga_ls9c_ard_3-2-1_096085_2022-08-20_final.stac-item
2022-08-22 11:24:31	ga_ls9c_ard_3-2-1_110085_2022-08-22_final.stac-item
2022-08-25 10:16:33	ga_ls9c_ard_3-2-1_099085_2022-08-25_final.stac-item
2022-08-31 09:39:28	ga_ls9c_ard_3-2-1_093085_2022-08-31_final.stac-item
2022-09-03 10:10:22	ga_ls9c_ard_3-2-1_098085_2022-09-03_final.stac-item
2022-09-04 09:14:45	ga_ls9c_ard_3-2-1_089085_2022-09-03_final.stac-item
2022-09-05 09:58:00	ga_ls9c_ard_3-2-1_096085_2022-09-05_final.stac-item
2022-09-07 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-09-07_final.stac-item
2022-09-07 11:24:31	ga_ls9c_ard_3-2-1_110085_2022-09-07_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-09-14 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-09-14_final.stac-item
2022-09-16 09:39:32	ga_ls9c_ard_3-2-1_093085_2022-09-16_final.stac-item
2022-09-19 10:10:27	ga_ls9c_ard_3-2-1_098085_2022-09-19_final.stac-item
2022-09-21 09:58:06	ga_ls9c_ard_3-2-1_096085_2022-09-21_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-23 11:24:38	ga_ls9c_ard_3-2-1_110085_2022-09-23_final.stac-item
2022-09-25 09:33:24	ga_ls9c_ard_3-2-1_092085_2022-09-25_final.stac-item
2022-09-30 09:51:57	ga_ls9c_ard_3-2-1_095085_2022-09-30_final.stac-item
2022-10-07 09:58:07	ga_ls9c_ard_3-2-1_096085_2022-10-07_final.stac-item
2022-10-09 09:45:47	ga_ls9c_ard_3-2-1_094085_2022-10-09_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-21 10:10:35	ga_ls9c_ard_3-2-1_098085_2022-10-21_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-10-28 10:16:46	ga_ls9c_ard_3-2-1_099085_2022-10-28_final.stac-item
2022-11-07 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-11-06_final.stac-item
2022-11-08 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-11-08_final.stac-item
2022-11-10 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-11-10_final.stac-item
2022-11-13 10:16:47	ga_ls9c_ard_3-2-1_099085_2022-11-13_final.stac-item
2022-11-26 11:24:44	ga_ls9c_ard_3-2-1_110085_2022-11-26_final.stac-item
2023-01-16 10:16:41	ga_ls9c_ard_3-2-1_099085_2023-01-16_final.stac-item
2023-01-27 09:58:10	ga_ls9c_ard_3-2-1_096085_2023-01-27_final.stac-item
2023-01-29 11:24:44	ga_ls9c_ard_3-2-1_110085_2023-01-29_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-02-14 11:24:46	ga_ls9c_ard_3-2-1_110085_2023-02-14_final.stac-item
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final.stac-item
2023-05-24 10:15:48	ga_ls9c_ard_3-2-1_099085_2023-05-24_final.stac-item
2023-06-18 10:09:27	ga_ls9c_ard_3-2-1_098085_2023-06-18_final.stac-item
2023-06-19 09:13:50	ga_ls9c_ard_3-2-1_089085_2023-06-18_final.stac-item
2023-06-20 09:57:06	ga_ls9c_ard_3-2-1_096085_2023-06-20_final.stac-item
2023-06-22 11:23:37	ga_ls9c_ard_3-2-1_110085_2023-06-22_final.stac-item
2023-06-25 10:15:38	ga_ls9c_ard_3-2-1_099085_2023-06-25_final.stac-item
2023-07-04 10:09:39	ga_ls9c_ard_3-2-1_098085_2023-07-04_final.stac-item
2023-07-06 09:57:19	ga_ls9c_ard_3-2-1_096085_2023-07-06_final.stac-item
2023-07-08 11:23:51	ga_ls9c_ard_3-2-1_110085_2023-07-08_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_2023-07-20_final.stac-item
2023-08-06 09:14:16	ga_ls9c_ard_3-2-1_089085_2023-08-05_final.stac-item
2023-08-09 11:24:04	ga_ls9c_ard_3-2-1_110085_2023-08-09_final.stac-item
2023-08-25 11:24:10	ga_ls9c_ard_3-2-1_110085_2023-08-25_final.stac-item
2023-09-10 11:24:20	ga_ls9c_ard_3-2-1_110085_2023-09-10_final.stac-item
2023-10-12 11:24:29	ga_ls9c_ard_3-2-1_110085_2023-10-12_final.stac-item
2023-10-28 11:24:30	ga_ls9c_ard_3-2-1_110085_2023-10-28_final.stac-item
2023-11-29 11:24:36	ga_ls9c_ard_3-2-1_110085_2023-11-29_final.stac-item
2023-12-15 11:24:36	ga_ls9c_ard_3-2-1_110085_2023-12-15_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