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 09:55:45	ga_ls9c_ard_3-2-1_096077_2021-11-03_final.stac-item
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-10 09:39:05	ga_ls9c_ard_3-2-1_094076_2021-11-10_final.stac-item
2021-11-10 09:39:29	ga_ls9c_ard_3-2-1_094077_2021-11-10_final.stac-item
2021-11-22 09:25:40	ga_ls9c_ard_3-2-1_091077_2021-11-21_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-19 10:19:11	ga_ls9c_ard_3-2-1_100076_2021-12-19_final.stac-item
2021-12-28 10:13:01	ga_ls9c_ard_3-2-1_099076_2021-12-28_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-03-08 09:35:40	ga_ls9c_ard_3-2-1_093076_2022-03-08_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-04-03 10:12:40	ga_ls9c_ard_3-2-1_099076_2022-04-03_final.stac-item
2022-04-10 10:18:48	ga_ls9c_ard_3-2-1_100076_2022-04-10_final.stac-item
2022-04-17 10:24:54	ga_ls9c_ard_3-2-1_101076_2022-04-17_final.stac-item
2022-04-25 09:35:24	ga_ls9c_ard_3-2-1_093076_2022-04-25_final.stac-item
2022-05-03 10:24:48	ga_ls9c_ard_3-2-1_101076_2022-05-03_final.stac-item
2022-05-14 10:06:09	ga_ls9c_ard_3-2-1_098076_2022-05-14_final.stac-item
2022-05-19 10:24:36	ga_ls9c_ard_3-2-1_101076_2022-05-19_final.stac-item
2022-05-27 09:35:09	ga_ls9c_ard_3-2-1_093076_2022-05-27_final.stac-item
2022-06-06 10:12:15	ga_ls9c_ard_3-2-1_099076_2022-06-06_final.stac-item
2022-06-12 09:35:13	ga_ls9c_ard_3-2-1_093076_2022-06-12_final.stac-item
2022-06-20 10:24:49	ga_ls9c_ard_3-2-1_101076_2022-06-20_final.stac-item
2022-06-24 10:00:13	ga_ls9c_ard_3-2-1_097076_2022-06-24_final.stac-item
2022-06-28 09:35:31	ga_ls9c_ard_3-2-1_093076_2022-06-28_final.stac-item
2022-07-17 10:06:23	ga_ls9c_ard_3-2-1_098076_2022-07-17_final.stac-item
2022-07-30 09:35:41	ga_ls9c_ard_3-2-1_093076_2022-07-30_final.stac-item
2022-08-15 09:35:50	ga_ls9c_ard_3-2-1_093076_2022-08-15_final.stac-item
2022-08-31 09:35:53	ga_ls9c_ard_3-2-1_093076_2022-08-31_final.stac-item
2022-09-10 10:12:57	ga_ls9c_ard_3-2-1_099076_2022-09-10_final.stac-item
2022-09-12 10:00:37	ga_ls9c_ard_3-2-1_097076_2022-09-12_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-17 10:19:12	ga_ls9c_ard_3-2-1_100076_2022-09-17_final.stac-item
2022-09-26 10:13:05	ga_ls9c_ard_3-2-1_099076_2022-09-26_final.stac-item
2022-10-02 09:36:00	ga_ls9c_ard_3-2-1_093076_2022-10-02_final.stac-item
2022-10-05 10:06:53	ga_ls9c_ard_3-2-1_098076_2022-10-05_final.stac-item
2022-10-12 10:13:08	ga_ls9c_ard_3-2-1_099076_2022-10-12_final.stac-item
2022-10-14 10:00:47	ga_ls9c_ard_3-2-1_097076_2022-10-14_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-19 10:19:21	ga_ls9c_ard_3-2-1_100076_2022-10-19_final.stac-item
2022-10-21 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-10-21_final.stac-item
2022-10-26 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-10-26_final.stac-item
2022-11-03 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-11-03_final.stac-item
2022-11-04 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-11-04_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
2022-11-15 10:00:50	ga_ls9c_ard_3-2-1_097076_2022-11-15_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2022-11-22 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-11-22_final.stac-item
2022-11-29 10:13:09	ga_ls9c_ard_3-2-1_099076_2022-11-29_final.stac-item
2022-12-05 09:36:04	ga_ls9c_ard_3-2-1_093076_2022-12-05_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_nrt.stac-item
2022-12-13 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-12-13_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-21 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-12-21_final.stac-item
2022-12-22 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-12-22_final.stac-item
2022-12-24 10:06:56	ga_ls9c_ard_3-2-1_098076_2022-12-24_final.stac-item
2023-01-06 09:36:06	ga_ls9c_ard_3-2-1_093076_2023-01-06_final.stac-item
2023-01-07 10:19:21	ga_ls9c_ard_3-2-1_100076_2023-01-07_final.stac-item
2023-01-16 10:13:05	ga_ls9c_ard_3-2-1_099076_2023-01-16_final.stac-item
2023-01-18 10:00:41	ga_ls9c_ard_3-2-1_097076_2023-01-18_final.stac-item
2023-01-22 09:35:57	ga_ls9c_ard_3-2-1_093076_2023-01-22_final.stac-item
2023-01-23 10:19:14	ga_ls9c_ard_3-2-1_100076_2023-01-23_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-03 10:00:51	ga_ls9c_ard_3-2-1_097076_2023-02-03_final.stac-item
2023-02-07 09:36:09	ga_ls9c_ard_3-2-1_093076_2023-02-07_final.stac-item
2023-02-10 10:07:03	ga_ls9c_ard_3-2-1_098076_2023-02-10_final.stac-item
2023-02-17 10:13:09	ga_ls9c_ard_3-2-1_099076_2023-02-17_final.stac-item
2023-02-23 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-02-23_final.stac-item
2023-02-26 10:06:48	ga_ls9c_ard_3-2-1_098076_2023-02-26_final.stac-item
2023-03-11 09:35:47	ga_ls9c_ard_3-2-1_093076_2023-03-11_final.stac-item
2023-03-12 10:19:03	ga_ls9c_ard_3-2-1_100076_2023-03-12_final.stac-item
2023-03-19 10:25:13	ga_ls9c_ard_3-2-1_101076_2023-03-19_final.stac-item
2023-03-21 10:12:50	ga_ls9c_ard_3-2-1_099076_2023-03-21_final.stac-item
2023-04-08 10:00:17	ga_ls9c_ard_3-2-1_097076_2023-04-08_final.stac-item
2023-04-12 09:35:31	ga_ls9c_ard_3-2-1_093076_2023-04-12_final.stac-item
2023-04-15 10:06:23	ga_ls9c_ard_3-2-1_098076_2023-04-15_final.stac-item
2023-04-20 10:24:56	ga_ls9c_ard_3-2-1_101076_2023-04-20_final.stac-item
2023-04-22 10:12:34	ga_ls9c_ard_3-2-1_099076_2023-04-22_final.stac-item
2023-04-28 09:35:25	ga_ls9c_ard_3-2-1_093076_2023-04-28_final.stac-item
2023-05-06 10:24:44	ga_ls9c_ard_3-2-1_101076_2023-05-06_final.stac-item
2023-05-08 10:12:22	ga_ls9c_ard_3-2-1_099076_2023-05-08_final.stac-item
2023-05-10 10:00:00	ga_ls9c_ard_3-2-1_097076_2023-05-10_final.stac-item
2023-05-14 09:35:16	ga_ls9c_ard_3-2-1_093076_2023-05-14_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-17 10:06:08	ga_ls9c_ard_3-2-1_098076_2023-05-17_final.stac-item
2023-05-22 10:24:36	ga_ls9c_ard_3-2-1_101076_2023-05-22_final.stac-item
2023-05-24 10:12:12	ga_ls9c_ard_3-2-1_099076_2023-05-24_final.stac-item
2023-05-30 09:35:07	ga_ls9c_ard_3-2-1_093076_2023-05-30_final.stac-item
2023-06-02 10:06:00	ga_ls9c_ard_3-2-1_098076_2023-06-02_final.stac-item
2023-06-15 09:34:58	ga_ls9c_ard_3-2-1_093076_2023-06-15_final.stac-item
2023-06-18 10:05:52	ga_ls9c_ard_3-2-1_098076_2023-06-18_final.stac-item
2023-06-23 10:24:24	ga_ls9c_ard_3-2-1_101076_2023-06-23_final.stac-item
2023-06-25 10:12:02	ga_ls9c_ard_3-2-1_099076_2023-06-25_final.stac-item
2023-06-27 09:59:43	ga_ls9c_ard_3-2-1_097076_2023-06-27_final.stac-item
2023-07-01 09:35:07	ga_ls9c_ard_3-2-1_093076_2023-07-01_final.stac-item
2023-07-03 09:23:11	ga_ls9c_ard_3-2-1_091077_2023-07-02_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