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 09:58:32	ga_ls9c_ard_3-2-1_096084_2021-11-03_final.stac-item
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
2021-11-18 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-12-05 10:10:32	ga_ls9c_ard_3-2-1_098085_2021-12-05_final.stac-item
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_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 11:24:11	ga_ls9c_ard_3-2-1_110084_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
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-31 10:03:50	ga_ls9c_ard_3-2-1_097084_2022-01-31_final.stac-item
2022-02-11 11:24:08	ga_ls9c_ard_3-2-1_110084_2022-02-11_final.stac-item
2022-04-16 11:23:44	ga_ls9c_ard_3-2-1_110084_2022-04-16_final.stac-item
2022-05-07 10:03:15	ga_ls9c_ard_3-2-1_097084_2022-05-07_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
2022-06-08 10:03:05	ga_ls9c_ard_3-2-1_097084_2022-06-08_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
2022-06-22 10:16:07	ga_ls9c_ard_3-2-1_099085_2022-06-22_final.stac-item
2022-06-24 10:03:25	ga_ls9c_ard_3-2-1_097084_2022-06-24_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
2022-07-05 11:24:09	ga_ls9c_ard_3-2-1_110085_2022-07-05_final.stac-item
2022-07-10 10:03:23	ga_ls9c_ard_3-2-1_097084_2022-07-10_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 11:24:12	ga_ls9c_ard_3-2-1_110085_2022-07-21_final.stac-item
2022-07-26 10:03:32	ga_ls9c_ard_3-2-1_097084_2022-07-26_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
2022-08-06 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
2022-08-11 10:03:43	ga_ls9c_ard_3-2-1_097084_2022-08-11_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
2022-08-22 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
2022-08-27 10:03:47	ga_ls9c_ard_3-2-1_097084_2022-08-27_final.stac-item
2022-08-31 09:39:28	ga_ls9c_ard_3-2-1_093085_2022-08-31_final.stac-item
2022-09-05 09:58:00	ga_ls9c_ard_3-2-1_096085_2022-09-05_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-09-12 10:03:49	ga_ls9c_ard_3-2-1_097084_2022-09-12_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
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_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
2022-09-28 10:03:55	ga_ls9c_ard_3-2-1_097084_2022-09-28_final.stac-item
2022-09-30 09:51:57	ga_ls9c_ard_3-2-1_095085_2022-09-30_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
2022-10-14 10:03:59	ga_ls9c_ard_3-2-1_097084_2022-10-14_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
2022-10-30 10:03:59	ga_ls9c_ard_3-2-1_097084_2022-10-30_final.stac-item
2022-11-08 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-11-08_final.stac-item
2022-11-15 10:04:01	ga_ls9c_ard_3-2-1_097084_2022-11-15_final.stac-item
2022-11-26 11:24:44	ga_ls9c_ard_3-2-1_110085_2022-11-26_final.stac-item
2022-12-12 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-12-12_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2023-01-02 10:04:00	ga_ls9c_ard_3-2-1_097084_2023-01-02_final.stac-item
2023-01-16 10:16:41	ga_ls9c_ard_3-2-1_099085_2023-01-16_final.stac-item
2023-02-03 10:04:02	ga_ls9c_ard_3-2-1_097084_2023-02-03_final.stac-item
2023-04-28 11:17:29	ga_ls9c_ard_3-2-1_109084_2023-04-28_final.stac-item
2023-06-11 10:02:56	ga_ls9c_ard_3-2-1_097084_2023-06-11_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
2023-06-27 10:02:55	ga_ls9c_ard_3-2-1_097084_2023-06-27_final.stac-item
2023-07-01 11:17:11	ga_ls9c_ard_3-2-1_109084_2023-07-01_final.stac-item
2023-07-04 10:09:39	ga_ls9c_ard_3-2-1_098085_2023-07-04_final.stac-item
2023-07-08 11:23:51	ga_ls9c_ard_3-2-1_110085_2023-07-08_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
2023-08-14 10:03:19	ga_ls9c_ard_3-2-1_097084_2023-08-14_final.stac-item
2023-08-22 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-08-21_final.stac-item
2023-08-25 11:24:10	ga_ls9c_ard_3-2-1_110085_2023-08-25_final.stac-item
2023-08-30 10:03:29	ga_ls9c_ard_3-2-1_097084_2023-08-30_final.stac-item
2023-09-10 11:24:20	ga_ls9c_ard_3-2-1_110085_2023-09-10_final.stac-item
2023-10-01 10:03:36	ga_ls9c_ard_3-2-1_097084_2023-10-01_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
2023-12-20 10:03:53	ga_ls9c_ard_3-2-1_097084_2023-12-20_final.stac-item
2024-02-06 10:03:52	ga_ls9c_ard_3-2-1_097084_2024-02-06_final.stac-item
2024-03-09 10:03:44	ga_ls9c_ard_3-2-1_097084_2024-03-09_final.stac-item
2024-04-10 10:03:31	ga_ls9c_ard_3-2-1_097084_2024-04-10_final.stac-item
2024-05-12 10:03:08	ga_ls9c_ard_3-2-1_097084_2024-05-12_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