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

45 results

Time (local)	Label
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2021-12-22 09:13:12	ga_ls9c_ard_3-2-1_089081_2021-12-21_final.stac-item
2022-01-07 10:47:16	ga_ls9c_ard_3-2-1_105069_2022-01-07_final.stac-item
2022-01-21 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-01-21_final.stac-item
2022-01-22 10:04:01	ga_ls9c_ard_3-2-1_098069_2022-01-22_final.stac-item
2022-03-12 10:47:02	ga_ls9c_ard_3-2-1_105069_2022-03-12_final.stac-item
2022-04-09 09:33:57	ga_ls9c_ard_3-2-1_093072_2022-04-09_final.stac-item
2022-04-19 11:51:24	ga_ls9c_ard_3-2-1_115076_2022-04-19_final.stac-item
2022-06-06 10:12:39	ga_ls9c_ard_3-2-1_099077_2022-06-06_final.stac-item
2022-06-25 09:07:25	ga_ls9c_ard_3-2-1_088083_2022-06-24_final.stac-item
2022-06-27 10:33:32	ga_ls9c_ard_3-2-1_102082_2022-06-27_final.stac-item
2022-08-19 09:10:44	ga_ls9c_ard_3-2-1_089075_2022-08-18_final.stac-item
2022-08-30 10:29:30	ga_ls9c_ard_3-2-1_102071_2022-08-30_final.stac-item
2022-09-20 10:47:20	ga_ls9c_ard_3-2-1_105069_2022-09-20_final.stac-item
2022-10-22 10:51:51	ga_ls9c_ard_3-2-1_105080_2022-10-22_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-12-03 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-12-03_final.stac-item
2022-12-05 09:34:52	ga_ls9c_ard_3-2-1_093073_2022-12-05_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2023-03-11 09:34:35	ga_ls9c_ard_3-2-1_093073_2023-03-11_final.stac-item
2023-03-31 09:13:16	ga_ls9c_ard_3-2-1_089082_2023-03-30_final.stac-item
2023-04-02 10:34:36	ga_ls9c_ard_3-2-1_103069_2023-04-02_final.stac-item
2023-05-30 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-05-30_final.stac-item
2023-05-30 11:14:00	ga_ls9c_ard_3-2-1_109076_2023-05-30_final.stac-item
2023-06-09 10:14:55	ga_ls9c_ard_3-2-1_099083_2023-06-09_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-08-27 09:32:57	ga_ls9c_ard_3-2-1_092085_2023-08-27_final.stac-item
2023-09-08 11:31:30	ga_ls9c_ard_3-2-1_112072_2023-09-08_final.stac-item
2023-10-19 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-10-19_final.stac-item
2023-10-19 11:30:20	ga_ls9c_ard_3-2-1_111084_2023-10-19_final.stac-item
2023-11-01 10:56:08	ga_ls9c_ard_3-2-1_106076_2023-11-01_final.stac-item
2023-11-17 09:16:53	ga_ls9c_ard_3-2-1_090075_2023-11-16_final.stac-item
2023-12-11 10:08:24	ga_ls9c_ard_3-2-1_098080_2023-12-11_final.stac-item
2023-12-14 10:34:33	ga_ls9c_ard_3-2-1_103068_2023-12-14_final.stac-item
2024-01-22 09:06:58	ga_ls9c_ard_3-2-1_088081_2024-01-21_final.stac-item
2024-02-03 09:28:10	ga_ls9c_ard_3-2-1_092072_2024-02-02_final.stac-item
2024-02-05 09:17:25	ga_ls9c_ard_3-2-1_090076_2024-02-04_final.stac-item
2024-02-10 09:34:45	ga_ls9c_ard_3-2-1_093073_2024-02-10_final.stac-item
2024-02-24 11:25:46	ga_ls9c_ard_3-2-1_111073_2024-02-24_final.stac-item
2024-02-25 10:28:58	ga_ls9c_ard_3-2-1_102070_2024-02-25_final.stac-item
2024-03-24 09:22:24	ga_ls9c_ard_3-2-1_090089_2024-03-23_final.stac-item
2024-04-04 10:34:15	ga_ls9c_ard_3-2-1_103068_2024-04-04_final.stac-item
2024-04-05 09:43:01	ga_ls9c_ard_3-2-1_094079_2024-04-05_final.stac-item
2024-04-25 09:21:31	ga_ls9c_ard_3-2-1_090088_2024-04-24_final.stac-item
2024-05-19 10:09:36	ga_ls9c_ard_3-2-1_098085_2024-05-19_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