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

46 results

Time (local)	Label
2021-12-06 10:52:59	ga_ls9c_ard_3-2-1_105083_2021-12-06_final.stac-item
2021-12-15 10:44:18	ga_ls9c_ard_3-2-1_104077_2021-12-15_final.stac-item
2022-01-13 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-01-13_final.stac-item
2022-01-13 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-01-13_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_2022-03-09_final.stac-item
2022-04-13 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-04-12_final.stac-item
2022-05-06 09:16:24	ga_ls9c_ard_3-2-1_090075_2022-05-05_final.stac-item
2022-05-09 11:23:46	ga_ls9c_ard_3-2-1_111069_2022-05-09_final.stac-item
2022-05-13 09:22:30	ga_ls9c_ard_3-2-1_091075_2022-05-12_final.stac-item
2022-05-23 09:57:29	ga_ls9c_ard_3-2-1_097070_2022-05-23_final.stac-item
2022-05-29 09:22:00	ga_ls9c_ard_3-2-1_091074_2022-05-28_final.stac-item
2022-06-04 10:26:37	ga_ls9c_ard_3-2-1_101081_2022-06-04_final.stac-item
2022-06-14 09:27:40	ga_ls9c_ard_3-2-1_091088_2022-06-13_final.stac-item
2022-06-25 09:07:25	ga_ls9c_ard_3-2-1_088083_2022-06-24_final.stac-item
2022-06-26 11:24:22	ga_ls9c_ard_3-2-1_111070_2022-06-26_final.stac-item
2022-07-07 09:34:30	ga_ls9c_ard_3-2-1_092089_2022-07-07_final.stac-item
2022-08-13 11:24:16	ga_ls9c_ard_3-2-1_111069_2022-08-13_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-10-18 09:34:30	ga_ls9c_ard_3-2-1_093072_2022-10-18_final.stac-item
2022-11-06 10:03:22	ga_ls9c_ard_3-2-1_098067_2022-11-06_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 10:10:45	ga_ls9c_ard_3-2-1_099070_2022-11-29_final.stac-item
2022-12-25 10:47:25	ga_ls9c_ard_3-2-1_105069_2022-12-25_final.stac-item
2022-12-30 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-12-30_final.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-13 10:35:08	ga_ls9c_ard_3-2-1_103069_2023-02-13_final.stac-item
2023-03-05 10:14:08	ga_ls9c_ard_3-2-1_099079_2023-03-05_final.stac-item
2023-04-24 11:38:16	ga_ls9c_ard_3-2-1_113074_2023-04-24_final.stac-item
2023-05-16 09:22:29	ga_ls9c_ard_3-2-1_091075_2023-05-15_final.stac-item
2023-06-19 10:51:31	ga_ls9c_ard_3-2-1_105082_2023-06-19_final.stac-item
2023-06-28 09:06:31	ga_ls9c_ard_3-2-1_088082_2023-06-27_final.stac-item
2023-07-08 11:17:52	ga_ls9c_ard_3-2-1_110070_2023-07-08_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_final.stac-item
2023-07-19 09:28:28	ga_ls9c_ard_3-2-1_091090_2023-07-18_final.stac-item
2023-08-03 10:19:25	ga_ls9c_ard_3-2-1_100078_2023-08-03_final.stac-item
2023-09-19 09:34:31	ga_ls9c_ard_3-2-1_093073_2023-09-19_final.stac-item
2023-09-24 11:31:55	ga_ls9c_ard_3-2-1_112073_2023-09-24_final.stac-item
2023-10-31 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-10-31_final.stac-item
2023-11-20 11:24:20	ga_ls9c_ard_3-2-1_111069_2023-11-20_final.stac-item
2023-12-02 10:10:13	ga_ls9c_ard_3-2-1_099069_2023-12-02_final.stac-item
2023-12-05 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-12-04_final.stac-item
2023-12-26 09:22:01	ga_ls9c_ard_3-2-1_091072_2023-12-25_final.stac-item
2024-03-01 09:16:40	ga_ls9c_ard_3-2-1_089090_2024-02-29_final.stac-item
2024-03-01 10:47:10	ga_ls9c_ard_3-2-1_105069_2024-03-01_final.stac-item
2024-03-18 11:31:37	ga_ls9c_ard_3-2-1_112072_2024-03-18_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