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
2021-11-07 09:17:29	ga_ls9c_ard_3-2-1_090075_2021-11-06_final.stac-item
2021-11-12 09:18:45	ga_ls9c_ard_3-2-1_091072_2021-11-11_final.stac-item
2021-11-12 09:19:09	ga_ls9c_ard_3-2-1_091073_2021-11-11_final.stac-item
2021-11-12 09:19:57	ga_ls9c_ard_3-2-1_091075_2021-11-11_final.stac-item
2021-11-12 09:20:21	ga_ls9c_ard_3-2-1_091076_2021-11-11_final.stac-item
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final.stac-item
2021-12-04 09:22:06	ga_ls9c_ard_3-2-1_091072_2021-12-03_final.stac-item
2021-12-20 09:22:22	ga_ls9c_ard_3-2-1_091073_2021-12-19_final.stac-item
2021-12-29 09:16:59	ga_ls9c_ard_3-2-1_090075_2021-12-28_final.stac-item
2022-01-14 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-01-13_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-01-30 09:16:58	ga_ls9c_ard_3-2-1_090075_2022-01-29_final.stac-item
2022-02-15 09:16:54	ga_ls9c_ard_3-2-1_090075_2022-02-14_final.stac-item
2022-03-03 09:16:43	ga_ls9c_ard_3-2-1_090075_2022-03-02_final.stac-item
2022-03-10 09:21:43	ga_ls9c_ard_3-2-1_091072_2022-03-09_final.stac-item
2022-03-10 09:22:07	ga_ls9c_ard_3-2-1_091073_2022-03-09_final.stac-item
2022-03-26 09:21:38	ga_ls9c_ard_3-2-1_091072_2022-03-25_final.stac-item
2022-03-26 09:22:02	ga_ls9c_ard_3-2-1_091073_2022-03-25_final.stac-item
2022-04-04 09:16:38	ga_ls9c_ard_3-2-1_090075_2022-04-03_final.stac-item
2022-04-20 09:16:29	ga_ls9c_ard_3-2-1_090075_2022-04-19_final.stac-item
2022-05-06 09:16:24	ga_ls9c_ard_3-2-1_090075_2022-05-05_final.stac-item
2022-05-22 09:16:13	ga_ls9c_ard_3-2-1_090075_2022-05-21_final.stac-item
2022-06-07 09:16:14	ga_ls9c_ard_3-2-1_090075_2022-06-06_final.stac-item
2022-06-14 09:21:17	ga_ls9c_ard_3-2-1_091072_2022-06-13_final.stac-item
2022-06-23 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-06-22_final.stac-item
2022-07-09 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-07-08_final.stac-item
2022-07-16 09:21:30	ga_ls9c_ard_3-2-1_091072_2022-07-15_final.stac-item
2022-07-25 09:16:40	ga_ls9c_ard_3-2-1_090075_2022-07-24_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-10 09:16:51	ga_ls9c_ard_3-2-1_090075_2022-08-09_final.stac-item
2022-08-17 09:21:53	ga_ls9c_ard_3-2-1_091072_2022-08-16_final.stac-item
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final.stac-item
2022-09-11 09:16:57	ga_ls9c_ard_3-2-1_090075_2022-09-10_final.stac-item
2022-09-18 09:22:00	ga_ls9c_ard_3-2-1_091072_2022-09-17_final.stac-item
2022-09-27 09:17:03	ga_ls9c_ard_3-2-1_090075_2022-09-26_final.stac-item
2022-10-13 09:17:07	ga_ls9c_ard_3-2-1_090075_2022-10-12_final.stac-item
2022-10-29 09:17:08	ga_ls9c_ard_3-2-1_090075_2022-10-28_final.stac-item
2022-11-14 09:17:10	ga_ls9c_ard_3-2-1_090075_2022-11-13_final.stac-item
2022-11-30 09:17:07	ga_ls9c_ard_3-2-1_090075_2022-11-29_final.stac-item
2022-12-16 09:17:09	ga_ls9c_ard_3-2-1_090075_2022-12-15_final.stac-item
2023-01-01 09:17:09	ga_ls9c_ard_3-2-1_090075_2022-12-31_final.stac-item
2023-01-17 09:17:03	ga_ls9c_ard_3-2-1_090075_2023-01-16_final.stac-item
2023-02-02 09:17:10	ga_ls9c_ard_3-2-1_090075_2023-02-01_final.stac-item
2023-02-18 09:17:06	ga_ls9c_ard_3-2-1_090075_2023-02-17_final.stac-item
2023-02-25 09:22:21	ga_ls9c_ard_3-2-1_091073_2023-02-24_final.stac-item
2023-03-06 09:16:54	ga_ls9c_ard_3-2-1_090075_2023-03-05_final.stac-item
2023-03-13 09:21:50	ga_ls9c_ard_3-2-1_091072_2023-03-12_final.stac-item
2023-03-13 09:22:14	ga_ls9c_ard_3-2-1_091073_2023-03-12_final.stac-item
2023-03-22 09:16:48	ga_ls9c_ard_3-2-1_090075_2023-03-21_final.stac-item
2023-03-24 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-03-23_final.stac-item
2023-04-07 09:16:38	ga_ls9c_ard_3-2-1_090075_2023-04-06_final.stac-item
2023-04-23 09:16:32	ga_ls9c_ard_3-2-1_090075_2023-04-22_final.stac-item
2023-05-09 09:16:21	ga_ls9c_ard_3-2-1_090075_2023-05-08_final.stac-item
2023-05-25 09:16:10	ga_ls9c_ard_3-2-1_090075_2023-05-24_final.stac-item
2023-06-10 09:16:06	ga_ls9c_ard_3-2-1_090075_2023-06-09_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-19 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-07-18_final.stac-item
2023-07-19 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-07-18_final.stac-item
2023-07-28 09:16:20	ga_ls9c_ard_3-2-1_090075_2023-07-27_final.stac-item
2023-08-04 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-08-03_final.stac-item
2023-08-04 09:21:49	ga_ls9c_ard_3-2-1_091073_2023-08-03_final.stac-item
2023-08-13 09:16:28	ga_ls9c_ard_3-2-1_090075_2023-08-12_final.stac-item
2023-08-20 09:21:29	ga_ls9c_ard_3-2-1_091072_2023-08-19_final.stac-item
2023-08-20 09:21:53	ga_ls9c_ard_3-2-1_091073_2023-08-19_final.stac-item
2023-08-29 09:16:37	ga_ls9c_ard_3-2-1_090075_2023-08-28_final.stac-item
2023-09-05 09:21:40	ga_ls9c_ard_3-2-1_091072_2023-09-04_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-09-21 09:21:45	ga_ls9c_ard_3-2-1_091072_2023-09-20_final.stac-item
2023-09-30 09:16:44	ga_ls9c_ard_3-2-1_090075_2023-09-29_final.stac-item
2023-10-07 09:21:48	ga_ls9c_ard_3-2-1_091072_2023-10-06_final.stac-item
2023-10-07 09:22:12	ga_ls9c_ard_3-2-1_091073_2023-10-06_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-10-23 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-10-22_final.stac-item
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-11-17 09:16:53	ga_ls9c_ard_3-2-1_090075_2023-11-16_final.stac-item
2023-11-24 09:21:59	ga_ls9c_ard_3-2-1_091072_2023-11-23_final.stac-item
2023-12-03 09:16:59	ga_ls9c_ard_3-2-1_090075_2023-12-02_final.stac-item
2023-12-10 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-12-09_final.stac-item
2023-12-10 09:22:20	ga_ls9c_ard_3-2-1_091073_2023-12-09_final.stac-item
2023-12-19 09:17:02	ga_ls9c_ard_3-2-1_090075_2023-12-18_final.stac-item
2023-12-26 09:22:01	ga_ls9c_ard_3-2-1_091072_2023-12-25_final.stac-item
2023-12-26 09:22:25	ga_ls9c_ard_3-2-1_091073_2023-12-25_final.stac-item
2024-01-04 09:16:57	ga_ls9c_ard_3-2-1_090075_2024-01-03_final.stac-item
2024-01-11 09:21:57	ga_ls9c_ard_3-2-1_091072_2024-01-10_final.stac-item
2024-01-20 09:16:57	ga_ls9c_ard_3-2-1_090075_2024-01-19_final.stac-item
2024-01-27 09:21:56	ga_ls9c_ard_3-2-1_091072_2024-01-26_final.stac-item
2024-02-05 09:17:01	ga_ls9c_ard_3-2-1_090075_2024-02-04_final.stac-item
2024-02-12 09:21:58	ga_ls9c_ard_3-2-1_091072_2024-02-11_final.stac-item
2024-02-21 09:16:49	ga_ls9c_ard_3-2-1_090075_2024-02-20_final.stac-item
2024-02-28 09:21:49	ga_ls9c_ard_3-2-1_091072_2024-02-27_final.stac-item
2024-03-08 09:16:53	ga_ls9c_ard_3-2-1_090075_2024-03-07_final.stac-item
2024-03-15 09:21:50	ga_ls9c_ard_3-2-1_091072_2024-03-14_final.stac-item
2024-03-15 09:22:14	ga_ls9c_ard_3-2-1_091073_2024-03-14_final.stac-item
2024-03-24 09:16:49	ga_ls9c_ard_3-2-1_090075_2024-03-23_final.stac-item
2024-03-31 09:21:42	ga_ls9c_ard_3-2-1_091072_2024-03-30_final.stac-item
2024-03-31 09:22:06	ga_ls9c_ard_3-2-1_091073_2024-03-30_final.stac-item
2024-04-09 09:16:40	ga_ls9c_ard_3-2-1_090075_2024-04-08_final.stac-item
2024-04-16 09:21:33	ga_ls9c_ard_3-2-1_091072_2024-04-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years