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 09:56:57	ga_ls9c_ard_3-2-1_096080_2021-11-03_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-12-11 09:30:59	ga_ls9c_ard_3-2-1_092079_2021-12-11_final.stac-item
2021-12-13 10:57:53	ga_ls9c_ard_3-2-1_106080_2021-12-13_final.stac-item
2021-12-17 10:33:07	ga_ls9c_ard_3-2-1_102080_2021-12-17_final.stac-item
2021-12-20 09:24:45	ga_ls9c_ard_3-2-1_091079_2021-12-19_final.stac-item
2021-12-30 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-30_final.stac-item
2022-01-05 09:24:45	ga_ls9c_ard_3-2-1_091079_2022-01-04_final.stac-item
2022-01-21 09:24:44	ga_ls9c_ard_3-2-1_091079_2022-01-20_final.stac-item
2022-02-06 09:24:44	ga_ls9c_ard_3-2-1_091079_2022-02-05_final.stac-item
2022-02-15 10:57:47	ga_ls9c_ard_3-2-1_106080_2022-02-15_final.stac-item
2022-02-22 09:24:36	ga_ls9c_ard_3-2-1_091079_2022-02-21_final.stac-item
2022-03-10 09:24:30	ga_ls9c_ard_3-2-1_091079_2022-03-09_final.stac-item
2022-03-26 09:24:25	ga_ls9c_ard_3-2-1_091079_2022-03-25_final.stac-item
2022-04-11 09:24:22	ga_ls9c_ard_3-2-1_091079_2022-04-10_final.stac-item
2022-04-18 09:30:28	ga_ls9c_ard_3-2-1_092079_2022-04-18_final.stac-item
2022-04-27 09:24:14	ga_ls9c_ard_3-2-1_091079_2022-04-26_final.stac-item
2022-05-13 09:24:06	ga_ls9c_ard_3-2-1_091079_2022-05-12_final.stac-item
2022-06-05 09:30:11	ga_ls9c_ard_3-2-1_092079_2022-06-05_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-10 09:49:08	ga_ls9c_ard_3-2-1_095080_2022-06-10_final.stac-item
2022-06-14 09:24:05	ga_ls9c_ard_3-2-1_091079_2022-06-13_final.stac-item
2022-06-14 11:03:22	ga_ls9c_ard_3-2-1_107080_2022-06-14_final.stac-item
2022-06-19 11:22:00	ga_ls9c_ard_3-2-1_110080_2022-06-19_final.stac-item
2022-06-26 09:49:29	ga_ls9c_ard_3-2-1_095080_2022-06-26_final.stac-item
2022-06-28 11:16:00	ga_ls9c_ard_3-2-1_109080_2022-06-28_final.stac-item
2022-06-30 11:03:38	ga_ls9c_ard_3-2-1_107080_2022-06-30_final.stac-item
2022-07-03 09:55:39	ga_ls9c_ard_3-2-1_096080_2022-07-03_final.stac-item
2022-07-05 11:22:09	ga_ls9c_ard_3-2-1_110080_2022-07-05_final.stac-item
2022-07-07 09:30:30	ga_ls9c_ard_3-2-1_092079_2022-07-07_final.stac-item
2022-07-16 09:24:17	ga_ls9c_ard_3-2-1_091079_2022-07-15_final.stac-item
2022-07-16 11:03:34	ga_ls9c_ard_3-2-1_107080_2022-07-16_final.stac-item
2022-07-21 11:22:13	ga_ls9c_ard_3-2-1_110080_2022-07-21_final.stac-item
2022-07-28 09:49:36	ga_ls9c_ard_3-2-1_095080_2022-07-28_final.stac-item
2022-08-01 09:24:32	ga_ls9c_ard_3-2-1_091079_2022-07-31_final.stac-item
2022-08-06 11:22:25	ga_ls9c_ard_3-2-1_110080_2022-08-06_final.stac-item
2022-08-10 10:57:44	ga_ls9c_ard_3-2-1_106080_2022-08-10_final.stac-item
2022-08-11 11:40:37	ga_ls9c_ard_3-2-1_113079_2022-08-11_final.stac-item
2022-08-13 09:49:47	ga_ls9c_ard_3-2-1_095080_2022-08-13_final.stac-item
2022-08-17 09:24:41	ga_ls9c_ard_3-2-1_091079_2022-08-16_final.stac-item
2022-08-17 11:03:58	ga_ls9c_ard_3-2-1_107080_2022-08-17_final.stac-item
2022-09-02 09:24:43	ga_ls9c_ard_3-2-1_091079_2022-09-01_final.stac-item
2022-09-18 09:24:47	ga_ls9c_ard_3-2-1_091079_2022-09-17_final.stac-item
2022-09-23 11:22:39	ga_ls9c_ard_3-2-1_110080_2022-09-23_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-09-30 09:49:57	ga_ls9c_ard_3-2-1_095080_2022-09-30_final.stac-item
2022-10-04 09:24:50	ga_ls9c_ard_3-2-1_091079_2022-10-03_final.stac-item
2022-10-13 10:58:00	ga_ls9c_ard_3-2-1_106080_2022-10-13_final.stac-item
2022-10-16 09:50:02	ga_ls9c_ard_3-2-1_095080_2022-10-16_final.stac-item
2022-10-18 11:16:34	ga_ls9c_ard_3-2-1_109080_2022-10-18_final.stac-item
2022-10-20 09:24:56	ga_ls9c_ard_3-2-1_091079_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
2022-11-05 09:24:53	ga_ls9c_ard_3-2-1_091079_2022-11-04_final.stac-item
2022-11-19 11:16:11	ga_ls9c_ard_3-2-1_109079_2022-11-19_final.stac-item
2022-11-21 09:24:57	ga_ls9c_ard_3-2-1_091079_2022-11-20_final.stac-item
2022-11-28 09:31:05	ga_ls9c_ard_3-2-1_092079_2022-11-28_final.stac-item
2022-11-30 10:58:00	ga_ls9c_ard_3-2-1_106080_2022-11-30_final.stac-item
2022-12-07 09:24:55	ga_ls9c_ard_3-2-1_091079_2022-12-06_final.stac-item
2022-12-14 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-14_final.stac-item
2022-12-23 09:24:52	ga_ls9c_ard_3-2-1_091079_2022-12-22_final.stac-item
2023-01-08 09:24:55	ga_ls9c_ard_3-2-1_091079_2023-01-07_final.stac-item
2023-01-15 09:31:03	ga_ls9c_ard_3-2-1_092079_2023-01-15_final.stac-item
2023-01-24 09:24:50	ga_ls9c_ard_3-2-1_091079_2023-01-23_final.stac-item
2023-01-31 09:31:07	ga_ls9c_ard_3-2-1_092079_2023-01-31_final.stac-item
2023-02-09 09:24:59	ga_ls9c_ard_3-2-1_091079_2023-02-08_final.stac-item
2023-02-25 09:24:44	ga_ls9c_ard_3-2-1_091079_2023-02-24_final.stac-item
2023-03-13 09:24:37	ga_ls9c_ard_3-2-1_091079_2023-03-12_final.stac-item
2023-03-20 09:30:47	ga_ls9c_ard_3-2-1_092079_2023-03-20_final.stac-item
2023-03-23 11:40:32	ga_ls9c_ard_3-2-1_113079_2023-03-23_final.stac-item
2023-03-29 09:24:26	ga_ls9c_ard_3-2-1_091079_2023-03-28_final.stac-item
2023-04-08 11:40:22	ga_ls9c_ard_3-2-1_113079_2023-04-08_final.stac-item
2023-04-14 09:24:20	ga_ls9c_ard_3-2-1_091079_2023-04-13_final.stac-item
2023-04-17 11:34:07	ga_ls9c_ard_3-2-1_112079_2023-04-17_final.stac-item
2023-04-24 11:40:16	ga_ls9c_ard_3-2-1_113079_2023-04-24_final.stac-item
2023-04-30 09:24:13	ga_ls9c_ard_3-2-1_091079_2023-04-29_final.stac-item
2023-05-03 11:33:56	ga_ls9c_ard_3-2-1_112079_2023-05-03_final.stac-item
2023-05-10 11:40:05	ga_ls9c_ard_3-2-1_113079_2023-05-10_final.stac-item
2023-05-16 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-05-15_final.stac-item
2023-05-19 11:33:50	ga_ls9c_ard_3-2-1_112079_2023-05-19_final.stac-item
2023-05-26 11:39:55	ga_ls9c_ard_3-2-1_113079_2023-05-26_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-06-17 09:23:48	ga_ls9c_ard_3-2-1_091079_2023-06-16_final.stac-item
2023-06-20 11:33:35	ga_ls9c_ard_3-2-1_112079_2023-06-20_final.stac-item
2023-06-22 11:21:37	ga_ls9c_ard_3-2-1_110080_2023-06-22_final.stac-item
2023-06-27 11:39:48	ga_ls9c_ard_3-2-1_113079_2023-06-27_final.stac-item
2023-07-03 09:23:59	ga_ls9c_ard_3-2-1_091079_2023-07-02_final.stac-item
2023-07-06 11:33:48	ga_ls9c_ard_3-2-1_112079_2023-07-06_final.stac-item
2023-07-17 11:15:44	ga_ls9c_ard_3-2-1_109080_2023-07-17_final.stac-item
2023-08-02 11:15:50	ga_ls9c_ard_3-2-1_109080_2023-08-02_final.stac-item
2023-10-30 09:30:50	ga_ls9c_ard_3-2-1_092079_2023-10-30_final.stac-item
2023-11-08 09:24:39	ga_ls9c_ard_3-2-1_091079_2023-11-07_final.stac-item
2023-12-01 09:30:58	ga_ls9c_ard_3-2-1_092079_2023-12-01_final.stac-item
2023-12-10 09:24:43	ga_ls9c_ard_3-2-1_091079_2023-12-09_final.stac-item
2023-12-17 09:30:59	ga_ls9c_ard_3-2-1_092079_2023-12-17_final.stac-item
2023-12-26 09:24:49	ga_ls9c_ard_3-2-1_091079_2023-12-25_final.stac-item
2024-02-19 09:30:49	ga_ls9c_ard_3-2-1_092079_2024-02-19_final.stac-item
2024-02-28 09:24:37	ga_ls9c_ard_3-2-1_091079_2024-02-27_final.stac-item
2024-04-23 09:30:18	ga_ls9c_ard_3-2-1_092079_2024-04-23_final.stac-item
2024-05-02 09:24:04	ga_ls9c_ard_3-2-1_091079_2024-05-01_final.stac-item
2024-05-09 09:30:16	ga_ls9c_ard_3-2-1_092079_2024-05-09_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