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 09:56:57	ga_ls9c_ard_3-2-1_096080_2021-11-03_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2021-12-07 09:56:09	ga_ls9c_ard_3-2-1_096080_2021-12-07_final.stac-item
2021-12-09 11:22:39	ga_ls9c_ard_3-2-1_110080_2021-12-09_final.stac-item
2021-12-14 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-14_final.stac-item
2021-12-17 10:33:07	ga_ls9c_ard_3-2-1_102080_2021-12-17_final.stac-item
2021-12-18 11:16:23	ga_ls9c_ard_3-2-1_109080_2021-12-18_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2021-12-30 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-30_final.stac-item
2021-12-31 09:06:37	ga_ls9c_ard_3-2-1_088080_2021-12-30_final.stac-item
2022-01-02 10:33:08	ga_ls9c_ard_3-2-1_102080_2022-01-02_final.stac-item
2022-01-08 09:56:02	ga_ls9c_ard_3-2-1_096080_2022-01-08_final.stac-item
2022-01-11 10:26:55	ga_ls9c_ard_3-2-1_101080_2022-01-11_final.stac-item
2022-01-15 10:02:12	ga_ls9c_ard_3-2-1_097080_2022-01-15_final.stac-item
2022-01-18 10:33:07	ga_ls9c_ard_3-2-1_102080_2022-01-18_final.stac-item
2022-01-19 11:16:22	ga_ls9c_ard_3-2-1_109080_2022-01-19_final.stac-item
2022-01-23 09:12:47	ga_ls9c_ard_3-2-1_089080_2022-01-22_final.stac-item
2022-01-27 10:26:57	ga_ls9c_ard_3-2-1_101080_2022-01-27_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-03 10:33:08	ga_ls9c_ard_3-2-1_102080_2022-02-03_final.stac-item
2022-02-16 10:02:09	ga_ls9c_ard_3-2-1_097080_2022-02-16_final.stac-item
2022-02-19 10:33:01	ga_ls9c_ard_3-2-1_102080_2022-02-19_final.stac-item
2022-02-25 09:55:52	ga_ls9c_ard_3-2-1_096080_2022-02-25_final.stac-item
2022-03-24 11:16:05	ga_ls9c_ard_3-2-1_109080_2022-03-24_final.stac-item
2022-04-07 09:49:31	ga_ls9c_ard_3-2-1_095080_2022-04-07_final.stac-item
2022-04-21 10:01:43	ga_ls9c_ard_3-2-1_097080_2022-04-21_final.stac-item
2022-05-03 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-05-03_final.stac-item
2022-05-07 10:01:39	ga_ls9c_ard_3-2-1_097080_2022-05-07_final.stac-item
2022-05-10 10:32:31	ga_ls9c_ard_3-2-1_102080_2022-05-10_final.stac-item
2022-05-27 11:15:37	ga_ls9c_ard_3-2-1_109080_2022-05-27_final.stac-item
2022-05-31 09:12:02	ga_ls9c_ard_3-2-1_089080_2022-05-30_final.stac-item
2022-06-01 09:55:18	ga_ls9c_ard_3-2-1_096080_2022-06-01_final.stac-item
2022-06-03 11:21:50	ga_ls9c_ard_3-2-1_110080_2022-06-03_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-10 09:49:08	ga_ls9c_ard_3-2-1_095080_2022-06-10_final.stac-item
2022-06-12 11:15:42	ga_ls9c_ard_3-2-1_109080_2022-06-12_final.stac-item
2022-06-17 09:55:25	ga_ls9c_ard_3-2-1_096080_2022-06-17_final.stac-item
2022-06-19 11:22:00	ga_ls9c_ard_3-2-1_110080_2022-06-19_final.stac-item
2022-06-26 09:49:29	ga_ls9c_ard_3-2-1_095080_2022-06-26_final.stac-item
2022-06-28 11:16:00	ga_ls9c_ard_3-2-1_109080_2022-06-28_final.stac-item
2022-07-03 09:55:39	ga_ls9c_ard_3-2-1_096080_2022-07-03_final.stac-item
2022-07-05 11:22:09	ga_ls9c_ard_3-2-1_110080_2022-07-05_final.stac-item
2022-07-06 10:26:32	ga_ls9c_ard_3-2-1_101080_2022-07-06_final.stac-item
2022-07-14 11:15:55	ga_ls9c_ard_3-2-1_109080_2022-07-14_final.stac-item
2022-07-21 11:22:13	ga_ls9c_ard_3-2-1_110080_2022-07-21_final.stac-item
2022-07-27 09:06:20	ga_ls9c_ard_3-2-1_088080_2022-07-26_final.stac-item
2022-08-06 11:22:25	ga_ls9c_ard_3-2-1_110080_2022-08-06_final.stac-item
2022-08-12 09:06:31	ga_ls9c_ard_3-2-1_088080_2022-08-11_final.stac-item
2022-08-15 11:16:19	ga_ls9c_ard_3-2-1_109080_2022-08-15_final.stac-item
2022-08-19 09:12:44	ga_ls9c_ard_3-2-1_089080_2022-08-18_final.stac-item
2022-08-22 11:22:31	ga_ls9c_ard_3-2-1_110080_2022-08-22_final.stac-item
2022-08-28 09:06:34	ga_ls9c_ard_3-2-1_088080_2022-08-27_final.stac-item
2022-08-31 11:16:21	ga_ls9c_ard_3-2-1_109080_2022-08-31_final.stac-item
2022-09-04 09:12:45	ga_ls9c_ard_3-2-1_089080_2022-09-03_final.stac-item
2022-09-17 10:20:48	ga_ls9c_ard_3-2-1_100080_2022-09-17_final.stac-item
2022-09-19 10:08:27	ga_ls9c_ard_3-2-1_098080_2022-09-19_final.stac-item
2022-09-21 09:56:07	ga_ls9c_ard_3-2-1_096080_2022-09-21_final.stac-item
2022-09-23 11:22:39	ga_ls9c_ard_3-2-1_110080_2022-09-23_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-10-09 11:22:41	ga_ls9c_ard_3-2-1_110080_2022-10-09_final.stac-item
2022-10-10 10:27:04	ga_ls9c_ard_3-2-1_101080_2022-10-10_final.stac-item
2022-10-14 10:02:23	ga_ls9c_ard_3-2-1_097080_2022-10-14_final.stac-item
2022-10-16 09:50:02	ga_ls9c_ard_3-2-1_095080_2022-10-16_final.stac-item
2022-10-18 11:16:34	ga_ls9c_ard_3-2-1_109080_2022-10-18_final.stac-item
2022-10-19 10:20:57	ga_ls9c_ard_3-2-1_100080_2022-10-19_final.stac-item
2022-10-26 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-10-26_final.stac-item
2022-10-28 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-10-28_final.stac-item
2022-11-06 10:08:34	ga_ls9c_ard_3-2-1_098080_2022-11-06_final.stac-item
2022-11-09 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-11-09_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-18 10:33:20	ga_ls9c_ard_3-2-1_102080_2022-11-18_final.stac-item
2022-11-19 11:16:35	ga_ls9c_ard_3-2-1_109080_2022-11-19_final.stac-item
2022-12-04 10:33:17	ga_ls9c_ard_3-2-1_102080_2022-12-04_final.stac-item
2022-12-08 10:08:35	ga_ls9c_ard_3-2-1_098080_2022-12-08_final.stac-item
2022-12-12 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-12-12_final.stac-item
2022-12-20 10:33:17	ga_ls9c_ard_3-2-1_102080_2022-12-20_final.stac-item
2022-12-21 11:16:32	ga_ls9c_ard_3-2-1_109080_2022-12-21_final.stac-item
2023-01-05 10:33:19	ga_ls9c_ard_3-2-1_102080_2023-01-05_final.stac-item
2023-01-06 11:16:34	ga_ls9c_ard_3-2-1_109080_2023-01-06_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-21 10:33:09	ga_ls9c_ard_3-2-1_102080_2023-01-21_final.stac-item
2023-01-30 10:27:07	ga_ls9c_ard_3-2-1_101080_2023-01-30_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-03-27 11:16:08	ga_ls9c_ard_3-2-1_109080_2023-03-27_final.stac-item
2023-04-11 10:32:45	ga_ls9c_ard_3-2-1_102080_2023-04-11_final.stac-item
2023-06-22 11:21:37	ga_ls9c_ard_3-2-1_110080_2023-06-22_final.stac-item
2023-07-01 11:15:35	ga_ls9c_ard_3-2-1_109080_2023-07-01_final.stac-item
2023-07-08 11:21:52	ga_ls9c_ard_3-2-1_110080_2023-07-08_final.stac-item
2023-07-17 11:15:44	ga_ls9c_ard_3-2-1_109080_2023-07-17_final.stac-item
2023-08-02 11:15:50	ga_ls9c_ard_3-2-1_109080_2023-08-02_final.stac-item
2023-08-09 11:22:04	ga_ls9c_ard_3-2-1_110080_2023-08-09_final.stac-item
2023-08-18 11:15:53	ga_ls9c_ard_3-2-1_109080_2023-08-18_final.stac-item
2023-08-25 11:22:11	ga_ls9c_ard_3-2-1_110080_2023-08-25_final.stac-item
2023-10-28 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-11-06 11:16:17	ga_ls9c_ard_3-2-1_109080_2023-11-06_final.stac-item
2023-12-08 11:16:20	ga_ls9c_ard_3-2-1_109080_2023-12-08_final.stac-item
2024-01-16 11:22:35	ga_ls9c_ard_3-2-1_110080_2024-01-16_final.stac-item
2024-01-25 11:16:20	ga_ls9c_ard_3-2-1_109080_2024-01-25_final.stac-item
2024-02-17 11:22:30	ga_ls9c_ard_3-2-1_110080_2024-02-17_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