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

71 results

Time (local)	Label
2021-12-16 11:26:22	ga_ls9c_ard_3-2-1_111074_2021-12-16_final.stac-item
2022-01-29 10:14:36	ga_ls9c_ard_3-2-1_099080_2022-01-29_final.stac-item
2022-02-14 11:51:25	ga_ls9c_ard_3-2-1_115075_2022-02-14_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-03-11 11:47:03	ga_ls9c_ard_3-2-1_114080_2022-03-11_final.stac-item
2022-03-24 09:40:00	ga_ls9c_ard_3-2-1_093087_2022-03-24_final.stac-item
2022-03-27 10:07:17	ga_ls9c_ard_3-2-1_098078_2022-03-27_final.stac-item
2022-03-31 09:40:10	ga_ls9c_ard_3-2-1_094072_2022-03-31_final.stac-item
2022-03-31 11:23:03	ga_ls9c_ard_3-2-1_110082_2022-03-31_final.stac-item
2022-04-04 10:52:44	ga_ls9c_ard_3-2-1_106068_2022-04-04_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-21 09:58:07	ga_ls9c_ard_3-2-1_097071_2022-04-21_final.stac-item
2022-04-27 09:27:49	ga_ls9c_ard_3-2-1_091088_2022-04-26_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-06 10:58:29	ga_ls9c_ard_3-2-1_106083_2022-05-06_final.stac-item
2022-05-14 11:46:38	ga_ls9c_ard_3-2-1_114080_2022-05-14_final.stac-item
2022-05-15 10:49:00	ga_ls9c_ard_3-2-1_105075_2022-05-15_final.stac-item
2022-07-16 11:04:46	ga_ls9c_ard_3-2-1_107083_2022-07-16_final.stac-item
2022-07-26 09:57:09	ga_ls9c_ard_3-2-1_097068_2022-07-26_final.stac-item
2022-07-30 09:40:04	ga_ls9c_ard_3-2-1_093087_2022-07-30_final.stac-item
2022-08-01 09:28:08	ga_ls9c_ard_3-2-1_091088_2022-07-31_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-09-25 09:29:25	ga_ls9c_ard_3-2-1_092075_2022-09-24_final.stac-item
2022-10-16 11:24:32	ga_ls9c_ard_3-2-1_111069_2022-10-16_final.stac-item
2022-10-25 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-10-25_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-11-13 10:11:12	ga_ls9c_ard_3-2-1_099071_2022-11-13_final.stac-item
2022-11-23 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-11-22_final.stac-item
2022-11-30 10:53:36	ga_ls9c_ard_3-2-1_106069_2022-11-30_final.stac-item
2022-12-15 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-12-15_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-10 09:10:57	ga_ls9c_ard_3-2-1_089075_2023-01-09_final.stac-item
2023-01-11 11:32:42	ga_ls9c_ard_3-2-1_112074_2023-01-11_final.stac-item
2023-01-13 11:20:19	ga_ls9c_ard_3-2-1_110074_2023-01-13_final.stac-item
2023-01-15 09:28:15	ga_ls9c_ard_3-2-1_092072_2023-01-14_final.stac-item
2023-01-19 10:46:20	ga_ls9c_ard_3-2-1_104082_2023-01-19_final.stac-item
2023-02-07 11:18:13	ga_ls9c_ard_3-2-1_109084_2023-02-07_final.stac-item
2023-02-16 11:08:23	ga_ls9c_ard_3-2-1_108075_2023-02-16_final.stac-item
2023-02-18 09:21:30	ga_ls9c_ard_3-2-1_090086_2023-02-17_final.stac-item
2023-02-21 09:47:32	ga_ls9c_ard_3-2-1_095074_2023-02-21_final.stac-item
2023-03-14 10:09:29	ga_ls9c_ard_3-2-1_098083_2023-03-14_final.stac-item
2023-03-23 11:38:32	ga_ls9c_ard_3-2-1_113074_2023-03-23_final.stac-item
2023-04-19 11:19:45	ga_ls9c_ard_3-2-1_110074_2023-04-19_final.stac-item
2023-04-22 10:10:10	ga_ls9c_ard_3-2-1_099070_2023-04-22_final.stac-item
2023-05-19 11:31:02	ga_ls9c_ard_3-2-1_112072_2023-05-19_final.stac-item
2023-06-01 09:27:32	ga_ls9c_ard_3-2-1_091088_2023-05-31_final.stac-item
2023-06-09 10:08:32	ga_ls9c_ard_3-2-1_099067_2023-06-09_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-06-26 10:54:07	ga_ls9c_ard_3-2-1_106073_2023-06-26_final.stac-item
2023-08-13 09:19:40	ga_ls9c_ard_3-2-1_090083_2023-08-12_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-09-23 10:46:40	ga_ls9c_ard_3-2-1_105068_2023-09-23_final.stac-item
2023-10-26 09:57:36	ga_ls9c_ard_3-2-1_096084_2023-10-26_final.stac-item
2023-11-15 09:31:13	ga_ls9c_ard_3-2-1_092080_2023-11-15_final.stac-item
2023-11-20 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-11-20_final.stac-item
2023-11-25 10:07:38	ga_ls9c_ard_3-2-1_098078_2023-11-25_final.stac-item
2023-12-04 11:38:43	ga_ls9c_ard_3-2-1_113074_2023-12-04_final.stac-item
2023-12-11 10:05:12	ga_ls9c_ard_3-2-1_098072_2023-12-11_final.stac-item
2023-12-12 10:50:05	ga_ls9c_ard_3-2-1_105076_2023-12-12_final.stac-item
2024-01-07 11:26:19	ga_ls9c_ard_3-2-1_111074_2024-01-07_final.stac-item
2024-01-13 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-12_final.stac-item
2024-01-20 09:17:45	ga_ls9c_ard_3-2-1_090077_2024-01-19_final.stac-item
2024-01-21 09:57:01	ga_ls9c_ard_3-2-1_097067_2024-01-21_final.stac-item
2024-01-23 09:46:13	ga_ls9c_ard_3-2-1_095071_2024-01-23_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_2024-02-11_final.stac-item
2024-02-14 09:16:22	ga_ls9c_ard_3-2-1_089089_2024-02-13_final.stac-item
2024-03-08 10:56:10	ga_ls9c_ard_3-2-1_106076_2024-03-08_final.stac-item
2024-03-22 11:07:41	ga_ls9c_ard_3-2-1_108074_2024-03-22_final.stac-item
2024-05-08 10:27:05	ga_ls9c_ard_3-2-1_101082_2024-05-08_final.stac-item
2024-05-14 09:45:33	ga_ls9c_ard_3-2-1_095071_2024-05-14_interim.stac-item
2024-05-18 09:21:09	ga_ls9c_ard_3-2-1_091072_2024-05-17_nrt.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