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
2021-11-11 10:21:02	ga_ls9c_ard_3-2-1_100081_2021-11-11_final.stac-item
2021-12-10 10:27:25	ga_ls9c_ard_3-2-1_101081_2021-12-10_final.stac-item
2021-12-19 10:21:10	ga_ls9c_ard_3-2-1_100081_2021-12-19_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2022-01-04 10:21:10	ga_ls9c_ard_3-2-1_100081_2022-01-04_final.stac-item
2022-01-11 10:26:55	ga_ls9c_ard_3-2-1_101080_2022-01-11_final.stac-item
2022-01-11 10:27:19	ga_ls9c_ard_3-2-1_101081_2022-01-11_final.stac-item
2022-01-18 10:30:43	ga_ls9c_ard_3-2-1_102074_2022-01-18_final.stac-item
2022-01-20 10:21:09	ga_ls9c_ard_3-2-1_100081_2022-01-20_final.stac-item
2022-01-27 10:26:57	ga_ls9c_ard_3-2-1_101080_2022-01-27_final.stac-item
2022-02-03 10:30:44	ga_ls9c_ard_3-2-1_102074_2022-02-03_final.stac-item
2022-02-05 10:21:10	ga_ls9c_ard_3-2-1_100081_2022-02-05_final.stac-item
2022-02-12 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-02-12_final.stac-item
2022-02-21 10:21:02	ga_ls9c_ard_3-2-1_100081_2022-02-21_final.stac-item
2022-02-28 10:27:07	ga_ls9c_ard_3-2-1_101081_2022-02-28_final.stac-item
2022-03-07 10:30:29	ga_ls9c_ard_3-2-1_102074_2022-03-07_final.stac-item
2022-03-23 10:30:26	ga_ls9c_ard_3-2-1_102074_2022-03-23_final.stac-item
2022-03-25 10:20:51	ga_ls9c_ard_3-2-1_100081_2022-03-25_final.stac-item
2022-04-24 10:30:13	ga_ls9c_ard_3-2-1_102074_2022-04-24_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-05-03 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-05-03_final.stac-item
2022-05-10 10:30:07	ga_ls9c_ard_3-2-1_102074_2022-05-10_final.stac-item
2022-05-12 10:20:56	ga_ls9c_ard_3-2-1_100082_2022-05-12_final.stac-item
2022-05-19 10:26:36	ga_ls9c_ard_3-2-1_101081_2022-05-19_final.stac-item
2022-06-20 10:26:48	ga_ls9c_ard_3-2-1_101081_2022-06-20_final.stac-item
2022-06-29 10:20:47	ga_ls9c_ard_3-2-1_100081_2022-06-29_final.stac-item
2022-07-06 10:26:56	ga_ls9c_ard_3-2-1_101081_2022-07-06_final.stac-item
2022-07-13 10:30:16	ga_ls9c_ard_3-2-1_102074_2022-07-13_final.stac-item
2022-07-15 10:20:41	ga_ls9c_ard_3-2-1_100081_2022-07-15_final.stac-item
2022-07-31 10:20:57	ga_ls9c_ard_3-2-1_100081_2022-07-31_final.stac-item
2022-08-07 10:27:12	ga_ls9c_ard_3-2-1_101081_2022-08-07_final.stac-item
2022-08-14 10:30:39	ga_ls9c_ard_3-2-1_102074_2022-08-14_final.stac-item
2022-08-16 10:21:06	ga_ls9c_ard_3-2-1_100081_2022-08-16_final.stac-item
2022-09-01 10:21:08	ga_ls9c_ard_3-2-1_100081_2022-09-01_final.stac-item
2022-09-15 10:30:45	ga_ls9c_ard_3-2-1_102074_2022-09-15_final.stac-item
2022-09-17 10:21:12	ga_ls9c_ard_3-2-1_100081_2022-09-17_final.stac-item
2022-09-24 10:27:25	ga_ls9c_ard_3-2-1_101081_2022-09-24_final.stac-item
2022-10-03 10:21:15	ga_ls9c_ard_3-2-1_100081_2022-10-03_final.stac-item
2022-10-10 10:27:04	ga_ls9c_ard_3-2-1_101080_2022-10-10_final.stac-item
2022-10-19 10:21:21	ga_ls9c_ard_3-2-1_100081_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
2022-11-04 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-11-04_final.stac-item
2022-11-20 10:21:22	ga_ls9c_ard_3-2-1_100081_2022-11-20_final.stac-item
2022-12-04 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-04_final.stac-item
2022-12-06 10:21:20	ga_ls9c_ard_3-2-1_100081_2022-12-06_final.stac-item
2022-12-20 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-20_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2023-01-07 10:21:21	ga_ls9c_ard_3-2-1_100081_2023-01-07_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-23 10:21:14	ga_ls9c_ard_3-2-1_100081_2023-01-23_final.stac-item
2023-01-30 10:27:07	ga_ls9c_ard_3-2-1_101080_2023-01-30_final.stac-item
2023-02-06 10:30:58	ga_ls9c_ard_3-2-1_102074_2023-02-06_final.stac-item
2023-02-08 10:21:24	ga_ls9c_ard_3-2-1_100081_2023-02-08_final.stac-item
2023-02-22 10:29:35	ga_ls9c_ard_3-2-1_102071_2023-02-22_final.stac-item
2023-03-03 10:27:19	ga_ls9c_ard_3-2-1_101081_2023-03-03_final.stac-item
2023-03-10 10:29:24	ga_ls9c_ard_3-2-1_102071_2023-03-10_final.stac-item
2023-03-10 10:30:36	ga_ls9c_ard_3-2-1_102074_2023-03-10_final.stac-item
2023-03-12 10:21:02	ga_ls9c_ard_3-2-1_100081_2023-03-12_final.stac-item
2023-03-26 10:30:30	ga_ls9c_ard_3-2-1_102074_2023-03-26_final.stac-item
2023-04-02 10:35:24	ga_ls9c_ard_3-2-1_103071_2023-04-02_final.stac-item
2023-04-11 10:30:22	ga_ls9c_ard_3-2-1_102074_2023-04-11_final.stac-item
2023-04-13 10:20:46	ga_ls9c_ard_3-2-1_100081_2023-04-13_final.stac-item
2023-04-20 10:26:32	ga_ls9c_ard_3-2-1_101080_2023-04-20_final.stac-item
2023-04-29 10:20:39	ga_ls9c_ard_3-2-1_100081_2023-04-29_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-15 10:20:31	ga_ls9c_ard_3-2-1_100081_2023-05-15_final.stac-item
2023-05-29 10:29:56	ga_ls9c_ard_3-2-1_102074_2023-05-29_final.stac-item
2023-05-31 10:20:22	ga_ls9c_ard_3-2-1_100081_2023-05-31_final.stac-item
2023-05-31 10:20:46	ga_ls9c_ard_3-2-1_100082_2023-05-31_final.stac-item
2023-06-07 10:26:30	ga_ls9c_ard_3-2-1_101081_2023-06-07_final.stac-item
2023-06-30 10:29:55	ga_ls9c_ard_3-2-1_102074_2023-06-30_final.stac-item
2023-07-02 10:20:23	ga_ls9c_ard_3-2-1_100081_2023-07-02_final.stac-item
2023-07-16 10:28:52	ga_ls9c_ard_3-2-1_102071_2023-07-16_final.stac-item
2023-07-18 10:20:30	ga_ls9c_ard_3-2-1_100081_2023-07-18_final.stac-item
2023-07-18 10:20:54	ga_ls9c_ard_3-2-1_100082_2023-07-18_final.stac-item
2023-07-23 10:35:02	ga_ls9c_ard_3-2-1_103071_2023-07-23_final.stac-item
2023-08-01 10:28:58	ga_ls9c_ard_3-2-1_102071_2023-08-01_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-08 10:35:13	ga_ls9c_ard_3-2-1_103071_2023-08-08_final.stac-item
2023-08-17 10:29:02	ga_ls9c_ard_3-2-1_102071_2023-08-17_final.stac-item
2023-08-24 10:35:19	ga_ls9c_ard_3-2-1_103071_2023-08-24_final.stac-item
2023-09-02 10:29:13	ga_ls9c_ard_3-2-1_102071_2023-09-02_final.stac-item
2023-09-09 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-09_final.stac-item
2023-09-18 10:29:21	ga_ls9c_ard_3-2-1_102071_2023-09-18_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-09-25 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-25_final.stac-item
2023-10-04 10:29:22	ga_ls9c_ard_3-2-1_102071_2023-10-04_final.stac-item
2023-10-06 10:21:01	ga_ls9c_ard_3-2-1_100081_2023-10-06_final.stac-item
2023-10-06 10:21:25	ga_ls9c_ard_3-2-1_100082_2023-10-06_final.stac-item
2023-10-11 10:35:37	ga_ls9c_ard_3-2-1_103071_2023-10-11_final.stac-item
2023-10-20 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-10-20_final.stac-item
2023-10-27 10:35:40	ga_ls9c_ard_3-2-1_103071_2023-10-27_final.stac-item
2023-11-05 10:29:25	ga_ls9c_ard_3-2-1_102071_2023-11-05_final.stac-item
2023-11-12 10:35:37	ga_ls9c_ard_3-2-1_103071_2023-11-12_final.stac-item
2023-11-21 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-11-21_final.stac-item
2023-11-23 10:21:35	ga_ls9c_ard_3-2-1_100082_2023-11-23_final.stac-item
2023-11-28 10:35:46	ga_ls9c_ard_3-2-1_103071_2023-11-28_final.stac-item
2023-12-07 10:29:30	ga_ls9c_ard_3-2-1_102071_2023-12-07_final.stac-item
2023-12-14 10:35:45	ga_ls9c_ard_3-2-1_103071_2023-12-14_final.stac-item
2023-12-23 10:29:37	ga_ls9c_ard_3-2-1_102071_2023-12-23_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