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

61 results

Time (local)	Label
2021-11-08 09:59:50	ga_ls9c_ard_3-2-1_097081_2021-11-08_final.stac-item
2021-12-10 10:27:49	ga_ls9c_ard_3-2-1_101082_2021-12-10_final.stac-item
2022-01-14 10:53:25	ga_ls9c_ard_3-2-1_106069_2022-01-14_final.stac-item
2022-01-21 11:05:13	ga_ls9c_ard_3-2-1_107083_2022-01-21_final.stac-item
2022-01-28 09:33:20	ga_ls9c_ard_3-2-1_092085_2022-01-28_final.stac-item
2022-02-05 10:17:10	ga_ls9c_ard_3-2-1_100071_2022-02-05_final.stac-item
2022-02-24 10:49:06	ga_ls9c_ard_3-2-1_105074_2022-02-24_final.stac-item
2022-04-12 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-04-12_final.stac-item
2022-05-13 09:22:06	ga_ls9c_ard_3-2-1_091074_2022-05-12_final.stac-item
2022-05-13 09:22:30	ga_ls9c_ard_3-2-1_091075_2022-05-12_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-07-23 11:07:53	ga_ls9c_ard_3-2-1_108075_2022-07-23_final.stac-item
2022-07-25 09:16:40	ga_ls9c_ard_3-2-1_090075_2022-07-24_final.stac-item
2022-08-02 10:03:02	ga_ls9c_ard_3-2-1_098067_2022-08-02_final.stac-item
2022-08-25 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-08-25_final.stac-item
2022-09-10 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-09-10_final.stac-item
2022-09-12 10:04:13	ga_ls9c_ard_3-2-1_097085_2022-09-12_final.stac-item
2022-09-19 11:46:33	ga_ls9c_ard_3-2-1_114078_2022-09-19_final.stac-item
2022-09-30 11:25:39	ga_ls9c_ard_3-2-1_111072_2022-09-30_final.stac-item
2022-10-06 10:50:09	ga_ls9c_ard_3-2-1_105076_2022-10-06_final.stac-item
2022-11-05 11:02:11	ga_ls9c_ard_3-2-1_107075_2022-11-05_final.stac-item
2022-11-06 11:47:51	ga_ls9c_ard_3-2-1_114081_2022-11-06_final.stac-item
2022-11-07 09:15:21	ga_ls9c_ard_3-2-1_089086_2022-11-06_final.stac-item
2022-11-13 10:16:47	ga_ls9c_ard_3-2-1_099085_2022-11-13_final.stac-item
2022-11-20 10:18:58	ga_ls9c_ard_3-2-1_100075_2022-11-20_final.stac-item
2022-11-22 10:03:25	ga_ls9c_ard_3-2-1_098067_2022-11-22_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_final.stac-item
2023-01-07 10:19:45	ga_ls9c_ard_3-2-1_100077_2023-01-07_final.stac-item
2023-01-16 11:53:10	ga_ls9c_ard_3-2-1_115079_2023-01-16_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-01-28 10:37:04	ga_ls9c_ard_3-2-1_103074_2023-01-28_final.stac-item
2023-02-02 10:53:16	ga_ls9c_ard_3-2-1_106068_2023-02-02_final.stac-item
2023-02-09 09:23:47	ga_ls9c_ard_3-2-1_091076_2023-02-08_final.stac-item
2023-02-26 11:47:41	ga_ls9c_ard_3-2-1_114081_2023-02-26_final.stac-item
2023-03-23 09:59:15	ga_ls9c_ard_3-2-1_097073_2023-03-23_final.stac-item
2023-04-10 09:45:55	ga_ls9c_ard_3-2-1_095071_2023-04-10_final.stac-item
2023-04-23 12:31:07	ga_ls9c_ard_3-2-1_122067_2023-04-23_final.stac-item
2023-05-11 10:42:04	ga_ls9c_ard_3-2-1_104073_2023-05-11_final.stac-item
2023-05-21 09:44:57	ga_ls9c_ard_3-2-1_094085_2023-05-21_final.stac-item
2023-06-20 11:32:23	ga_ls9c_ard_3-2-1_112076_2023-06-20_final.stac-item
2023-06-29 09:48:13	ga_ls9c_ard_3-2-1_095078_2023-06-29_final.stac-item
2023-07-03 09:27:34	ga_ls9c_ard_3-2-1_091088_2023-07-02_final.stac-item
2023-07-04 10:04:04	ga_ls9c_ard_3-2-1_098071_2023-07-04_final.stac-item
2023-07-05 09:14:02	ga_ls9c_ard_3-2-1_089085_2023-07-04_final.stac-item
2023-07-06 09:51:19	ga_ls9c_ard_3-2-1_096070_2023-07-06_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_final.stac-item
2023-08-21 10:07:33	ga_ls9c_ard_3-2-1_098079_2023-08-21_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-09-16 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-09-16_final.stac-item
2023-10-08 10:03:05	ga_ls9c_ard_3-2-1_098067_2023-10-08_final.stac-item
2023-10-26 09:58:00	ga_ls9c_ard_3-2-1_096085_2023-10-26_final.stac-item
2023-11-25 10:03:15	ga_ls9c_ard_3-2-1_098067_2023-11-25_final.stac-item
2023-12-16 10:25:48	ga_ls9c_ard_3-2-1_101077_2023-12-16_final.stac-item
2023-12-31 09:40:31	ga_ls9c_ard_3-2-1_094072_2023-12-31_final.stac-item
2024-01-03 10:09:00	ga_ls9c_ard_3-2-1_099066_2024-01-03_final.stac-item
2024-01-04 09:17:45	ga_ls9c_ard_3-2-1_090077_2024-01-03_final.stac-item
2024-01-07 09:46:14	ga_ls9c_ard_3-2-1_095071_2024-01-07_final.stac-item
2024-01-11 09:29:08	ga_ls9c_ard_3-2-1_091090_2024-01-10_final.stac-item
2024-02-04 10:09:02	ga_ls9c_ard_3-2-1_099066_2024-02-04_final.stac-item
2024-02-28 12:37:36	ga_ls9c_ard_3-2-1_123067_2024-02-28_final.stac-item
2024-03-06 09:32:02	ga_ls9c_ard_3-2-1_092082_2024-03-06_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