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
2021-11-18 10:05:09	ga_ls9c_ard_3-2-1_097082_2021-11-18_final.stac-item
2021-11-23 10:08:48	ga_ls9c_ard_3-2-1_098085_2021-11-23_final.stac-item
2021-12-10 10:23:26	ga_ls9c_ard_3-2-1_101071_2021-12-10_final.stac-item
2021-12-26 10:23:23	ga_ls9c_ard_3-2-1_101071_2021-12-26_final.stac-item
2022-01-06 10:09:12	ga_ls9c_ard_3-2-1_098082_2022-01-06_final.stac-item
2022-01-13 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-01-13_final.stac-item
2022-01-29 10:14:12	ga_ls9c_ard_3-2-1_099079_2022-01-29_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-02-21 10:17:26	ga_ls9c_ard_3-2-1_100072_2022-02-21_final.stac-item
2022-04-17 10:22:54	ga_ls9c_ard_3-2-1_101071_2022-04-17_final.stac-item
2022-04-26 10:17:04	ga_ls9c_ard_3-2-1_100072_2022-04-26_final.stac-item
2022-05-03 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-05-03_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-12 10:16:56	ga_ls9c_ard_3-2-1_100072_2022-05-12_final.stac-item
2022-05-19 10:22:37	ga_ls9c_ard_3-2-1_101071_2022-05-19_final.stac-item
2022-05-19 10:23:01	ga_ls9c_ard_3-2-1_101072_2022-05-19_final.stac-item
2022-05-21 10:13:26	ga_ls9c_ard_3-2-1_099079_2022-05-21_final.stac-item
2022-05-30 10:08:27	ga_ls9c_ard_3-2-1_098082_2022-05-30_final.stac-item
2022-06-04 10:22:37	ga_ls9c_ard_3-2-1_101071_2022-06-04_final.stac-item
2022-06-20 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-06-20_final.stac-item
2022-07-01 10:08:49	ga_ls9c_ard_3-2-1_098082_2022-07-01_final.stac-item
2022-07-06 10:22:56	ga_ls9c_ard_3-2-1_101071_2022-07-06_final.stac-item
2022-07-08 10:13:46	ga_ls9c_ard_3-2-1_099079_2022-07-08_final.stac-item
2022-07-22 10:23:01	ga_ls9c_ard_3-2-1_101071_2022-07-22_final.stac-item
2022-08-02 10:09:01	ga_ls9c_ard_3-2-1_098082_2022-08-02_final.stac-item
2022-08-07 10:23:13	ga_ls9c_ard_3-2-1_101071_2022-08-07_final.stac-item
2022-08-07 10:23:37	ga_ls9c_ard_3-2-1_101072_2022-08-07_final.stac-item
2022-08-09 10:14:04	ga_ls9c_ard_3-2-1_099079_2022-08-09_final.stac-item
2022-08-18 10:09:09	ga_ls9c_ard_3-2-1_098082_2022-08-18_final.stac-item
2022-08-23 10:23:19	ga_ls9c_ard_3-2-1_101071_2022-08-23_final.stac-item
2022-08-23 10:23:43	ga_ls9c_ard_3-2-1_101072_2022-08-23_final.stac-item
2022-09-08 10:23:18	ga_ls9c_ard_3-2-1_101071_2022-09-08_final.stac-item
2022-09-10 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-09-10_final.stac-item
2022-09-17 10:17:37	ga_ls9c_ard_3-2-1_100072_2022-09-17_final.stac-item
2022-09-24 10:23:26	ga_ls9c_ard_3-2-1_101071_2022-09-24_final.stac-item
2022-09-24 10:23:50	ga_ls9c_ard_3-2-1_101072_2022-09-24_final.stac-item
2022-09-26 10:14:16	ga_ls9c_ard_3-2-1_099079_2022-09-26_final.stac-item
2022-10-05 10:09:17	ga_ls9c_ard_3-2-1_098082_2022-10-05_final.stac-item
2022-10-10 10:23:29	ga_ls9c_ard_3-2-1_101071_2022-10-10_final.stac-item
2022-10-10 10:23:52	ga_ls9c_ard_3-2-1_101072_2022-10-10_final.stac-item
2022-10-19 10:17:45	ga_ls9c_ard_3-2-1_100072_2022-10-19_final.stac-item
2022-10-21 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-10-21_final.stac-item
2022-10-26 10:23:32	ga_ls9c_ard_3-2-1_101071_2022-10-26_final.stac-item
2022-10-28 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-10-28_final.stac-item
2022-11-04 10:17:42	ga_ls9c_ard_3-2-1_100072_2022-11-04_final.stac-item
2022-11-06 10:09:21	ga_ls9c_ard_3-2-1_098082_2022-11-06_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-27 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-11-27_final.stac-item
2022-11-29 10:14:20	ga_ls9c_ard_3-2-1_099079_2022-11-29_final.stac-item
2022-12-13 10:23:32	ga_ls9c_ard_3-2-1_101071_2022-12-13_final.stac-item
2022-12-22 10:17:42	ga_ls9c_ard_3-2-1_100072_2022-12-22_final.stac-item
2022-12-29 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-12-29_final.stac-item
2022-12-29 10:23:55	ga_ls9c_ard_3-2-1_101072_2022-12-29_final.stac-item
2023-01-07 10:17:45	ga_ls9c_ard_3-2-1_100072_2023-01-07_final.stac-item
2023-01-14 10:23:29	ga_ls9c_ard_3-2-1_101071_2023-01-14_final.stac-item
2023-01-14 10:23:53	ga_ls9c_ard_3-2-1_101072_2023-01-14_final.stac-item
2023-01-23 10:17:38	ga_ls9c_ard_3-2-1_100072_2023-01-23_final.stac-item
2023-01-25 10:09:18	ga_ls9c_ard_3-2-1_098082_2023-01-25_final.stac-item
2023-01-30 10:23:32	ga_ls9c_ard_3-2-1_101071_2023-01-30_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-02-08 10:17:49	ga_ls9c_ard_3-2-1_100072_2023-02-08_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-15 10:23:57	ga_ls9c_ard_3-2-1_101072_2023-02-15_final.stac-item
2023-03-03 10:23:44	ga_ls9c_ard_3-2-1_101072_2023-03-03_final.stac-item
2023-03-12 10:17:27	ga_ls9c_ard_3-2-1_100072_2023-03-12_final.stac-item
2023-03-14 10:09:05	ga_ls9c_ard_3-2-1_098082_2023-03-14_final.stac-item
2023-03-19 10:23:13	ga_ls9c_ard_3-2-1_101071_2023-03-19_final.stac-item
2023-03-19 10:23:37	ga_ls9c_ard_3-2-1_101072_2023-03-19_final.stac-item
2023-04-04 10:23:02	ga_ls9c_ard_3-2-1_101071_2023-04-04_final.stac-item
2023-04-13 10:17:10	ga_ls9c_ard_3-2-1_100072_2023-04-13_final.stac-item
2023-04-20 10:22:56	ga_ls9c_ard_3-2-1_101071_2023-04-20_final.stac-item
2023-04-20 10:23:20	ga_ls9c_ard_3-2-1_101072_2023-04-20_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-05-06 10:22:44	ga_ls9c_ard_3-2-1_101071_2023-05-06_final.stac-item
2023-05-06 10:23:08	ga_ls9c_ard_3-2-1_101072_2023-05-06_final.stac-item
2023-05-15 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-05-15_final.stac-item
2023-05-22 10:22:36	ga_ls9c_ard_3-2-1_101071_2023-05-22_final.stac-item
2023-05-22 10:23:00	ga_ls9c_ard_3-2-1_101072_2023-05-22_final.stac-item
2023-05-31 10:16:47	ga_ls9c_ard_3-2-1_100072_2023-05-31_final.stac-item
2023-06-07 10:22:31	ga_ls9c_ard_3-2-1_101071_2023-06-07_final.stac-item
2023-06-07 10:22:55	ga_ls9c_ard_3-2-1_101072_2023-06-07_final.stac-item
2023-06-23 10:22:25	ga_ls9c_ard_3-2-1_101071_2023-06-23_final.stac-item
2023-06-23 10:22:48	ga_ls9c_ard_3-2-1_101072_2023-06-23_final.stac-item
2023-07-02 10:16:47	ga_ls9c_ard_3-2-1_100072_2023-07-02_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
2023-08-05 10:08:41	ga_ls9c_ard_3-2-1_098082_2023-08-05_final.stac-item
2023-08-21 10:08:45	ga_ls9c_ard_3-2-1_098082_2023-08-21_final.stac-item
2023-09-06 10:08:56	ga_ls9c_ard_3-2-1_098082_2023-09-06_final.stac-item
2023-10-24 10:09:10	ga_ls9c_ard_3-2-1_098082_2023-10-24_final.stac-item
2023-12-27 10:09:16	ga_ls9c_ard_3-2-1_098082_2023-12-27_final.stac-item
2024-01-28 10:09:12	ga_ls9c_ard_3-2-1_098082_2024-01-28_final.stac-item
2024-02-13 10:09:13	ga_ls9c_ard_3-2-1_098082_2024-02-13_final.stac-item
2024-02-29 10:09:05	ga_ls9c_ard_3-2-1_098082_2024-02-29_final.stac-item
2024-03-16 10:09:05	ga_ls9c_ard_3-2-1_098082_2024-03-16_final.stac-item
2024-04-01 10:08:57	ga_ls9c_ard_3-2-1_098082_2024-04-01_final.stac-item
2024-04-17 10:08:47	ga_ls9c_ard_3-2-1_098082_2024-04-17_final.stac-item
2024-05-03 10:08:32	ga_ls9c_ard_3-2-1_098082_2024-05-03_final.stac-item
2024-05-08 10:22:42	ga_ls9c_ard_3-2-1_101071_2024-05-08_final.stac-item
2024-05-19 10:08:24	ga_ls9c_ard_3-2-1_098082_2024-05-19_nrt.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