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
2021-11-07 09:21:28	ga_ls9c_ard_3-2-1_090085_2021-11-06_final.stac-item
2021-11-12 09:23:56	ga_ls9c_ard_3-2-1_091085_2021-11-11_final.stac-item
2021-11-18 10:06:21	ga_ls9c_ard_3-2-1_097085_2021-11-18_final.stac-item
2021-12-09 09:46:10	ga_ls9c_ard_3-2-1_094086_2021-12-09_final.stac-item
2021-12-25 09:46:06	ga_ls9c_ard_3-2-1_094086_2021-12-25_final.stac-item
2021-12-30 10:04:14	ga_ls9c_ard_3-2-1_097085_2021-12-30_final.stac-item
2022-01-10 09:46:04	ga_ls9c_ard_3-2-1_094086_2022-01-10_final.stac-item
2022-01-26 09:46:05	ga_ls9c_ard_3-2-1_094086_2022-01-26_final.stac-item
2022-02-11 09:46:03	ga_ls9c_ard_3-2-1_094086_2022-02-11_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-31 09:45:45	ga_ls9c_ard_3-2-1_094086_2022-03-31_final.stac-item
2022-04-16 09:45:39	ga_ls9c_ard_3-2-1_094086_2022-04-16_final.stac-item
2022-04-30 09:57:55	ga_ls9c_ard_3-2-1_096086_2022-04-30_final.stac-item
2022-05-02 09:45:33	ga_ls9c_ard_3-2-1_094086_2022-05-02_final.stac-item
2022-05-04 09:33:10	ga_ls9c_ard_3-2-1_092086_2022-05-04_final.stac-item
2022-05-11 09:39:17	ga_ls9c_ard_3-2-1_093086_2022-05-11_final.stac-item
2022-05-18 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-05-18_final.stac-item
2022-05-20 09:32:57	ga_ls9c_ard_3-2-1_092086_2022-05-20_final.stac-item
2022-05-25 09:51:30	ga_ls9c_ard_3-2-1_095086_2022-05-25_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-06-03_final.stac-item
2022-06-07 09:20:14	ga_ls9c_ard_3-2-1_090085_2022-06-06_final.stac-item
2022-06-19 09:45:30	ga_ls9c_ard_3-2-1_094086_2022-06-19_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 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-10 10:03:47	ga_ls9c_ard_3-2-1_097085_2022-07-10_final.stac-item
2022-07-21 09:45:43	ga_ls9c_ard_3-2-1_094086_2022-07-21_final.stac-item
2022-07-26 10:03:56	ga_ls9c_ard_3-2-1_097085_2022-07-26_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 09:45:56	ga_ls9c_ard_3-2-1_094086_2022-08-06_final.stac-item
2022-08-10 09:20:51	ga_ls9c_ard_3-2-1_090085_2022-08-09_final.stac-item
2022-08-11 10:04:07	ga_ls9c_ard_3-2-1_097085_2022-08-11_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 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-08-22_final.stac-item
2022-08-26 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-08-25_final.stac-item
2022-08-27 10:04:11	ga_ls9c_ard_3-2-1_097085_2022-08-27_final.stac-item
2022-09-07 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-09-07_final.stac-item
2022-09-11 09:20:56	ga_ls9c_ard_3-2-1_090085_2022-09-10_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 09:46:09	ga_ls9c_ard_3-2-1_094086_2022-09-23_final.stac-item
2022-09-27 09:21:03	ga_ls9c_ard_3-2-1_090085_2022-09-26_final.stac-item
2022-09-28 10:04:19	ga_ls9c_ard_3-2-1_097085_2022-09-28_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 09:46:11	ga_ls9c_ard_3-2-1_094086_2022-10-09_final.stac-item
2022-10-14 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-10-14_final.stac-item
2022-10-25 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-10-25_final.stac-item
2022-10-30 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-10-30_final.stac-item
2022-11-10 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-11-10_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-11-26 09:46:15	ga_ls9c_ard_3-2-1_094086_2022-11-26_final.stac-item
2022-12-12 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-12-12_final.stac-item
2022-12-21 09:40:03	ga_ls9c_ard_3-2-1_093086_2022-12-21_final.stac-item
2022-12-28 09:46:14	ga_ls9c_ard_3-2-1_094086_2022-12-28_final.stac-item
2023-01-02 10:04:24	ga_ls9c_ard_3-2-1_097085_2023-01-02_final.stac-item
2023-01-04 09:52:27	ga_ls9c_ard_3-2-1_095086_2023-01-04_final.stac-item
2023-01-13 09:46:13	ga_ls9c_ard_3-2-1_094086_2023-01-13_final.stac-item
2023-01-17 09:21:03	ga_ls9c_ard_3-2-1_090085_2023-01-16_final.stac-item
2023-01-29 09:46:14	ga_ls9c_ard_3-2-1_094086_2023-01-29_final.stac-item
2023-02-14 09:46:17	ga_ls9c_ard_3-2-1_094086_2023-02-14_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-02-23 09:39:55	ga_ls9c_ard_3-2-1_093086_2023-02-23_final.stac-item
2023-03-02 09:46:04	ga_ls9c_ard_3-2-1_094086_2023-03-02_final.stac-item
2023-03-11 09:39:46	ga_ls9c_ard_3-2-1_093086_2023-03-11_final.stac-item
2023-03-18 09:45:57	ga_ls9c_ard_3-2-1_094086_2023-03-18_final.stac-item
2023-03-20 09:33:34	ga_ls9c_ard_3-2-1_092086_2023-03-20_final.stac-item
2023-04-03 09:45:46	ga_ls9c_ard_3-2-1_094086_2023-04-03_final.stac-item
2023-04-10 09:51:54	ga_ls9c_ard_3-2-1_095086_2023-04-10_final.stac-item
2023-04-12 09:39:31	ga_ls9c_ard_3-2-1_093086_2023-04-12_final.stac-item
2023-04-19 09:45:40	ga_ls9c_ard_3-2-1_094086_2023-04-19_final.stac-item
2023-04-21 09:33:18	ga_ls9c_ard_3-2-1_092086_2023-04-21_final.stac-item
2023-04-26 09:51:48	ga_ls9c_ard_3-2-1_095086_2023-04-26_final.stac-item
2023-05-05 09:45:27	ga_ls9c_ard_3-2-1_094086_2023-05-05_final.stac-item
2023-05-19 09:57:44	ga_ls9c_ard_3-2-1_096086_2023-05-19_final.stac-item
2023-05-21 09:45:21	ga_ls9c_ard_3-2-1_094086_2023-05-21_final.stac-item
2023-05-28 09:51:28	ga_ls9c_ard_3-2-1_095086_2023-05-28_final.stac-item
2023-06-06 09:45:15	ga_ls9c_ard_3-2-1_094086_2023-06-06_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 09:45:08	ga_ls9c_ard_3-2-1_094086_2023-06-22_final.stac-item
2023-06-27 10:03:18	ga_ls9c_ard_3-2-1_097085_2023-06-27_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 09:45:22	ga_ls9c_ard_3-2-1_094086_2023-07-08_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-07-24 09:45:23	ga_ls9c_ard_3-2-1_094086_2023-07-24_final.stac-item
2023-08-09 09:45:35	ga_ls9c_ard_3-2-1_094086_2023-08-09_final.stac-item
2023-08-25 09:45:41	ga_ls9c_ard_3-2-1_094086_2023-08-25_final.stac-item
2023-09-10 09:45:51	ga_ls9c_ard_3-2-1_094086_2023-09-10_final.stac-item
2023-09-26 09:45:50	ga_ls9c_ard_3-2-1_094086_2023-09-26_final.stac-item
2023-10-12 09:46:00	ga_ls9c_ard_3-2-1_094086_2023-10-12_final.stac-item
2023-10-28 09:46:01	ga_ls9c_ard_3-2-1_094086_2023-10-28_final.stac-item
2023-11-13 09:45:59	ga_ls9c_ard_3-2-1_094086_2023-11-13_final.stac-item
2023-11-29 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-11-29_final.stac-item
2023-12-15 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-12-15_final.stac-item
2023-12-31 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-12-31_final.stac-item
2024-01-16 09:46:05	ga_ls9c_ard_3-2-1_094086_2024-01-16_final.stac-item
2024-02-01 09:46:06	ga_ls9c_ard_3-2-1_094086_2024-02-01_final.stac-item
2024-02-17 09:46:01	ga_ls9c_ard_3-2-1_094086_2024-02-17_final.stac-item
2024-03-04 09:45:59	ga_ls9c_ard_3-2-1_094086_2024-03-04_final.stac-item
2024-03-20 09:45:57	ga_ls9c_ard_3-2-1_094086_2024-03-20_final.stac-item
2024-04-05 09:45:49	ga_ls9c_ard_3-2-1_094086_2024-04-05_final.stac-item
2024-04-21 09:45:33	ga_ls9c_ard_3-2-1_094086_2024-04-21_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