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
2021-11-08 09:58:38	ga_ls9c_ard_3-2-1_097078_2021-11-08_final.stac-item
2021-12-05 10:06:56	ga_ls9c_ard_3-2-1_098076_2021-12-05_final.stac-item
2021-12-05 10:07:44	ga_ls9c_ard_3-2-1_098078_2021-12-05_final.stac-item
2021-12-07 09:57:21	ga_ls9c_ard_3-2-1_096083_2021-12-07_final.stac-item
2021-12-14 10:01:03	ga_ls9c_ard_3-2-1_097077_2021-12-14_final.stac-item
2021-12-21 10:07:37	ga_ls9c_ard_3-2-1_098078_2021-12-21_final.stac-item
2021-12-23 09:57:16	ga_ls9c_ard_3-2-1_096083_2021-12-23_final.stac-item
2021-12-30 10:01:03	ga_ls9c_ard_3-2-1_097077_2021-12-30_final.stac-item
2022-01-15 10:01:24	ga_ls9c_ard_3-2-1_097078_2022-01-15_final.stac-item
2022-01-31 10:01:26	ga_ls9c_ard_3-2-1_097078_2022-01-31_final.stac-item
2022-02-16 10:01:21	ga_ls9c_ard_3-2-1_097078_2022-02-16_final.stac-item
2022-02-23 10:07:27	ga_ls9c_ard_3-2-1_098078_2022-02-23_final.stac-item
2022-03-04 10:00:47	ga_ls9c_ard_3-2-1_097077_2022-03-04_final.stac-item
2022-03-11 10:07:22	ga_ls9c_ard_3-2-1_098078_2022-03-11_final.stac-item
2022-03-20 10:00:45	ga_ls9c_ard_3-2-1_097077_2022-03-20_final.stac-item
2022-03-27 10:07:17	ga_ls9c_ard_3-2-1_098078_2022-03-27_final.stac-item
2022-04-12 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-04-12_final.stac-item
2022-04-21 10:00:31	ga_ls9c_ard_3-2-1_097077_2022-04-21_final.stac-item
2022-05-14 10:06:09	ga_ls9c_ard_3-2-1_098076_2022-05-14_final.stac-item
2022-05-14 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-05-14_final.stac-item
2022-05-14 10:06:57	ga_ls9c_ard_3-2-1_098078_2022-05-14_final.stac-item
2022-05-16 09:56:33	ga_ls9c_ard_3-2-1_096083_2022-05-16_final.stac-item
2022-05-23 10:00:16	ga_ls9c_ard_3-2-1_097077_2022-05-23_final.stac-item
2022-05-23 10:00:40	ga_ls9c_ard_3-2-1_097078_2022-05-23_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-05-30 10:06:51	ga_ls9c_ard_3-2-1_098078_2022-05-30_final.stac-item
2022-06-08 10:00:18	ga_ls9c_ard_3-2-1_097077_2022-06-08_final.stac-item
2022-06-15 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-06-15_final.stac-item
2022-06-17 09:56:37	ga_ls9c_ard_3-2-1_096083_2022-06-17_final.stac-item
2022-07-01 10:06:49	ga_ls9c_ard_3-2-1_098077_2022-07-01_final.stac-item
2022-07-10 10:00:59	ga_ls9c_ard_3-2-1_097078_2022-07-10_final.stac-item
2022-07-17 10:06:23	ga_ls9c_ard_3-2-1_098076_2022-07-17_final.stac-item
2022-07-19 09:56:51	ga_ls9c_ard_3-2-1_096083_2022-07-19_final.stac-item
2022-07-26 10:01:09	ga_ls9c_ard_3-2-1_097078_2022-07-26_final.stac-item
2022-08-11 10:01:19	ga_ls9c_ard_3-2-1_097078_2022-08-11_final.stac-item
2022-08-18 10:06:45	ga_ls9c_ard_3-2-1_098076_2022-08-18_final.stac-item
2022-08-18 10:07:09	ga_ls9c_ard_3-2-1_098077_2022-08-18_final.stac-item
2022-08-18 10:07:33	ga_ls9c_ard_3-2-1_098078_2022-08-18_final.stac-item
2022-08-20 09:57:12	ga_ls9c_ard_3-2-1_096083_2022-08-20_final.stac-item
2022-08-27 10:01:00	ga_ls9c_ard_3-2-1_097077_2022-08-27_final.stac-item
2022-09-12 10:01:25	ga_ls9c_ard_3-2-1_097078_2022-09-12_final.stac-item
2022-09-19 10:07:16	ga_ls9c_ard_3-2-1_098077_2022-09-19_final.stac-item
2022-09-21 09:57:18	ga_ls9c_ard_3-2-1_096083_2022-09-21_final.stac-item
2022-09-28 10:01:31	ga_ls9c_ard_3-2-1_097078_2022-09-28_final.stac-item
2022-10-05 10:06:53	ga_ls9c_ard_3-2-1_098076_2022-10-05_final.stac-item
2022-10-05 10:07:17	ga_ls9c_ard_3-2-1_098077_2022-10-05_final.stac-item
2022-10-07 09:57:19	ga_ls9c_ard_3-2-1_096083_2022-10-07_final.stac-item
2022-10-14 10:01:35	ga_ls9c_ard_3-2-1_097078_2022-10-14_final.stac-item
2022-10-21 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-10-21_final.stac-item
2022-10-21 10:07:24	ga_ls9c_ard_3-2-1_098077_2022-10-21_final.stac-item
2022-10-30 10:01:12	ga_ls9c_ard_3-2-1_097077_2022-10-30_final.stac-item
2022-10-30 10:01:36	ga_ls9c_ard_3-2-1_097078_2022-10-30_final.stac-item
2022-11-06 10:06:58	ga_ls9c_ard_3-2-1_098076_2022-11-06_final.stac-item
2022-11-06 10:06:58	ga_ls9c_ard_3-2-1_098076_2022-11-06_nrt.stac-item
2022-11-06 10:07:22	ga_ls9c_ard_3-2-1_098077_2022-11-06_nrt.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-08 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-11-08_final.stac-item
2022-11-22 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-11-22_final.stac-item
2022-11-22 10:07:24	ga_ls9c_ard_3-2-1_098077_2022-11-22_final.stac-item
2022-11-24 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-11-24_final.stac-item
2022-12-08 10:07:23	ga_ls9c_ard_3-2-1_098077_2022-12-08_final.stac-item
2022-12-08 10:07:47	ga_ls9c_ard_3-2-1_098078_2022-12-08_final.stac-item
2022-12-10 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-12-10_final.stac-item
2022-12-17 10:01:36	ga_ls9c_ard_3-2-1_097078_2022-12-17_final.stac-item
2022-12-24 10:06:56	ga_ls9c_ard_3-2-1_098076_2022-12-24_final.stac-item
2022-12-24 10:07:44	ga_ls9c_ard_3-2-1_098078_2022-12-24_final.stac-item
2023-01-02 10:01:13	ga_ls9c_ard_3-2-1_097077_2023-01-02_final.stac-item
2023-01-09 10:07:23	ga_ls9c_ard_3-2-1_098077_2023-01-09_final.stac-item
2023-01-09 10:07:47	ga_ls9c_ard_3-2-1_098078_2023-01-09_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-18 10:01:05	ga_ls9c_ard_3-2-1_097077_2023-01-18_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-02-03 10:01:15	ga_ls9c_ard_3-2-1_097077_2023-02-03_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-10 10:07:03	ga_ls9c_ard_3-2-1_098076_2023-02-10_final.stac-item
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final.stac-item
2023-02-19 10:01:33	ga_ls9c_ard_3-2-1_097078_2023-02-19_final.stac-item
2023-02-26 10:06:48	ga_ls9c_ard_3-2-1_098076_2023-02-26_final.stac-item
2023-02-26 10:07:12	ga_ls9c_ard_3-2-1_098077_2023-02-26_final.stac-item
2023-03-07 10:00:57	ga_ls9c_ard_3-2-1_097077_2023-03-07_final.stac-item
2023-03-07 10:01:21	ga_ls9c_ard_3-2-1_097078_2023-03-07_final.stac-item
2023-03-14 10:06:41	ga_ls9c_ard_3-2-1_098076_2023-03-14_final.stac-item
2023-03-16 09:57:07	ga_ls9c_ard_3-2-1_096083_2023-03-16_final.stac-item
2023-03-23 10:00:51	ga_ls9c_ard_3-2-1_097077_2023-03-23_final.stac-item
2023-03-23 10:01:15	ga_ls9c_ard_3-2-1_097078_2023-03-23_final.stac-item
2023-04-01 09:56:56	ga_ls9c_ard_3-2-1_096083_2023-04-01_final.stac-item
2023-04-15 10:06:23	ga_ls9c_ard_3-2-1_098076_2023-04-15_final.stac-item
2023-05-17 10:06:08	ga_ls9c_ard_3-2-1_098076_2023-05-17_final.stac-item
2023-06-02 10:06:00	ga_ls9c_ard_3-2-1_098076_2023-06-02_final.stac-item
2023-06-04 09:56:26	ga_ls9c_ard_3-2-1_096083_2023-06-04_final.stac-item
2023-06-18 10:05:52	ga_ls9c_ard_3-2-1_098076_2023-06-18_final.stac-item
2023-06-27 10:00:07	ga_ls9c_ard_3-2-1_097077_2023-06-27_final.stac-item
2023-09-08 09:57:00	ga_ls9c_ard_3-2-1_096083_2023-09-08_final.stac-item
2023-09-24 09:57:01	ga_ls9c_ard_3-2-1_096083_2023-09-24_final.stac-item
2023-10-10 09:57:08	ga_ls9c_ard_3-2-1_096083_2023-10-10_final.stac-item
2023-10-26 09:57:12	ga_ls9c_ard_3-2-1_096083_2023-10-26_final.stac-item
2023-11-11 09:57:09	ga_ls9c_ard_3-2-1_096083_2023-11-11_final.stac-item
2023-11-27 09:57:17	ga_ls9c_ard_3-2-1_096083_2023-11-27_final.stac-item
2023-12-13 09:57:16	ga_ls9c_ard_3-2-1_096083_2023-12-13_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