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

68 results

Time (local)	Label
2022-01-15 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-01-15_final.stac-item
2022-02-01 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-02-01_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-09 11:32:07	ga_ls9c_ard_3-2-1_112073_2022-02-09_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_2022-03-09_final.stac-item
2022-05-04 11:11:15	ga_ls9c_ard_3-2-1_108084_2022-05-04_final.stac-item
2022-05-18 11:23:02	ga_ls9c_ard_3-2-1_110083_2022-05-18_final.stac-item
2022-05-25 11:24:00	ga_ls9c_ard_3-2-1_111070_2022-05-25_final.stac-item
2022-05-31 09:11:38	ga_ls9c_ard_3-2-1_089079_2022-05-30_final.stac-item
2022-06-06 10:09:28	ga_ls9c_ard_3-2-1_099069_2022-06-06_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-08-18 10:04:21	ga_ls9c_ard_3-2-1_098070_2022-08-18_final.stac-item
2022-09-27 09:22:15	ga_ls9c_ard_3-2-1_090088_2022-09-26_final.stac-item
2022-09-27 10:53:09	ga_ls9c_ard_3-2-1_106068_2022-09-27_final.stac-item
2022-09-29 09:07:06	ga_ls9c_ard_3-2-1_088081_2022-09-28_final.stac-item
2022-10-04 09:26:50	ga_ls9c_ard_3-2-1_091084_2022-10-03_final.stac-item
2022-10-25 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-10-25_final.stac-item
2022-11-15 09:58:02	ga_ls9c_ard_3-2-1_097069_2022-11-15_final.stac-item
2022-11-23 09:12:11	ga_ls9c_ard_3-2-1_089078_2022-11-22_final.stac-item
2022-11-23 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-11-23_final.stac-item
2022-11-29 10:13:33	ga_ls9c_ard_3-2-1_099077_2022-11-29_final.stac-item
2022-11-29 10:13:57	ga_ls9c_ard_3-2-1_099078_2022-11-29_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2023-01-01 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-12-31_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-20 11:25:58	ga_ls9c_ard_3-2-1_111073_2023-01-20_final.stac-item
2023-03-13 09:22:14	ga_ls9c_ard_3-2-1_091073_2023-03-12_final.stac-item
2023-03-28 10:19:17	ga_ls9c_ard_3-2-1_100077_2023-03-28_final.stac-item
2023-03-30 11:45:22	ga_ls9c_ard_3-2-1_114076_2023-03-30_final.stac-item
2023-04-28 09:33:25	ga_ls9c_ard_3-2-1_093071_2023-04-28_final.stac-item
2023-05-17 10:03:44	ga_ls9c_ard_3-2-1_098070_2023-05-17_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-07-05 09:11:38	ga_ls9c_ard_3-2-1_089079_2023-07-04_final.stac-item
2023-07-14 09:06:44	ga_ls9c_ard_3-2-1_088082_2023-07-13_final.stac-item
2023-07-18 10:19:42	ga_ls9c_ard_3-2-1_100079_2023-07-18_final.stac-item
2023-07-19 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-07-18_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-03 10:19:25	ga_ls9c_ard_3-2-1_100078_2023-08-03_final.stac-item
2023-08-04 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-08-04_final.stac-item
2023-08-21 10:02:46	ga_ls9c_ard_3-2-1_098067_2023-08-21_final.stac-item
2023-08-22 09:11:09	ga_ls9c_ard_3-2-1_089077_2023-08-21_final.stac-item
2023-08-27 09:28:34	ga_ls9c_ard_3-2-1_092074_2023-08-26_final.stac-item
2023-08-30 09:57:06	ga_ls9c_ard_3-2-1_097068_2023-08-30_final.stac-item
2023-08-31 09:06:40	ga_ls9c_ard_3-2-1_088081_2023-08-30_final.stac-item
2023-09-06 10:04:09	ga_ls9c_ard_3-2-1_098070_2023-09-06_final.stac-item
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-09-13 10:10:24	ga_ls9c_ard_3-2-1_099070_2023-09-13_final.stac-item
2023-09-14 09:22:46	ga_ls9c_ard_3-2-1_090090_2023-09-13_final.stac-item
2023-09-16 09:06:49	ga_ls9c_ard_3-2-1_088081_2023-09-15_final.stac-item
2023-09-22 10:03:49	ga_ls9c_ard_3-2-1_098069_2023-09-22_final.stac-item
2023-09-29 10:10:20	ga_ls9c_ard_3-2-1_099070_2023-09-29_final.stac-item
2023-10-02 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-10-01_final.stac-item
2023-10-03 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-10-03_final.stac-item
2023-10-06 11:57:30	ga_ls9c_ard_3-2-1_116075_2023-10-06_final.stac-item
2023-10-06 11:57:54	ga_ls9c_ard_3-2-1_116076_2023-10-06_final.stac-item
2023-10-09 09:10:15	ga_ls9c_ard_3-2-1_089074_2023-10-08_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-11-19 09:06:57	ga_ls9c_ard_3-2-1_088081_2023-11-18_final.stac-item
2023-11-26 10:52:30	ga_ls9c_ard_3-2-1_105082_2023-11-26_final.stac-item
2024-01-28 10:04:24	ga_ls9c_ard_3-2-1_098070_2024-01-28_final.stac-item
2024-02-06 09:57:53	ga_ls9c_ard_3-2-1_097069_2024-02-06_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-02-20 10:13:16	ga_ls9c_ard_3-2-1_099077_2024-02-20_final.stac-item
2024-02-26 09:34:33	ga_ls9c_ard_3-2-1_093073_2024-02-26_final.stac-item
2024-03-13 11:12:17	ga_ls9c_ard_3-2-1_109070_2024-03-13_final.stac-item
2024-03-25 09:57:16	ga_ls9c_ard_3-2-1_097068_2024-03-25_final.stac-item
2024-04-26 09:57:12	ga_ls9c_ard_3-2-1_097069_2024-04-26_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